1
|
Secara MT, Oliver LD, Gallucci J, Dickie EW, Foussias G, Gold J, Malhotra AK, Buchanan RW, Voineskos AN, Hawco C. Heterogeneity in functional connectivity: Dimensional predictors of individual variability during rest and task fMRI in psychosis. Prog Neuropsychopharmacol Biol Psychiatry 2024; 132:110991. [PMID: 38484928 PMCID: PMC11034852 DOI: 10.1016/j.pnpbp.2024.110991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 02/27/2024] [Accepted: 03/07/2024] [Indexed: 03/21/2024]
Abstract
BACKGROUND Individuals with schizophrenia spectrum disorders (SSD) often demonstrate cognitive impairments, associated with poor functional outcomes. While neurobiological heterogeneity has posed challenges when examining social cognition in SSD, it provides a unique opportunity to explore brain-behavior relationships. The aim of this study was to investigate the relationship between individual variability in functional connectivity during resting state and the performance of a social task and social and non-social cognition in a large sample of controls and individuals diagnosed with SSD. METHODS Neuroimaging and behavioral data were analyzed for 193 individuals with SSD and 155 controls (total n = 348). Individual variability was quantified through mean correlational distance (MCD) of functional connectivity between participants; MCD was defined as a global 'variability score'. Pairwise correlational distance was calculated as 1 - the correlation coefficient between a given pair of participants, and averaging distance from one participant to all other participants provided the mean correlational distance metric. Hierarchical regressions were performed on variability scores derived from resting state and Empathic Accuracy (EA) task functional connectivity data to determine potential predictors (e.g., age, sex, neurocognitive and social cognitive scores) of individual variability. RESULTS Group comparison between SSD and controls showed greater SSD MCD during rest (p = 0.00038), while no diagnostic differences were observed during task (p = 0.063). Hierarchical regression analyses demonstrated the persistence of a significant diagnostic effect during rest (p = 0.008), contrasting with its non-significance during the task (p = 0.50), after social cognition was added to the model. Notably, social cognition exhibited significance in both resting state and task conditions (both p = 0.01). CONCLUSIONS Diagnostic differences were more prevalent during unconstrained resting scans, whereas the task pushed participants into a more common pattern which better emphasized transdiagnostic differences in cognitive abilities. Focusing on variability may provide new opportunities for interventions targeting specific cognitive impairments to improve functional outcomes.
Collapse
Affiliation(s)
- Maria T Secara
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Lindsay D Oliver
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Julia Gallucci
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Erin W Dickie
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - George Foussias
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - James Gold
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Anil K Malhotra
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, USA
| | - Robert W Buchanan
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Aristotle N Voineskos
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Colin Hawco
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
| |
Collapse
|
2
|
Tan V, Downar J, Nestor S, Vila-Rodriguez F, Daskalakis ZJ, Blumberger DM, Hawco C. Effects of repetitive transcranial magnetic stimulation on individual variability of resting-state functional connectivity in major depressive disorder. J Psychiatry Neurosci 2024; 49:E172-E181. [PMID: 38729664 PMCID: PMC11090631 DOI: 10.1503/jpn.230135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 01/30/2024] [Accepted: 03/16/2024] [Indexed: 05/12/2024] Open
Abstract
BACKGROUND Repetitive transcranial magnetic stimulation (rTMS) is an effective treatment for major depressive disorder (MDD), but substantial heterogeneity in outcomes remains. We examined a potential mechanism of action of rTMS to normalize individual variability in resting-state functional connectivity (rs-fc) before and after a course of treatment. METHODS Variability in rs-fc was examined in healthy controls (baseline) and individuals with MDD (baseline and after 4-6 weeks of rTMS). Seed-based connectivity was calculated to 4 regions associated with MDD: left dorsolateral prefrontal cortex (DLPFC), right subgenual anterior cingulate cortex (sgACC), bilateral insula, and bilateral precuneus. Individual variability was quantified for each region by calculating the mean correlational distance of connectivity maps relative to the healthy controls; a higher variability score indicated a more atypical/idiosyncratic connectivity pattern. RESULTS We included data from 66 healthy controls and 252 individuals with MDD in our analyses. Patients with MDD did not show significant differences in baseline variability of rs-fc compared with controls. Treatment with rTMS increased rs-fc variability from the right sgACC and precuneus, but the increased variability was not associated with clinical outcomes. Interestingly, higher baseline variability of the right sgACC was significantly associated with less clinical improvement (p = 0.037, uncorrected; did not survive false discovery rate correction).Limitations: The linear model was constructed separately for each region of interest. CONCLUSION This was, to our knowledge, the first study to examine individual variability of rs-fc related to rTMS in individuals with MDD. In contrast to our hypotheses, we found that rTMS increased the individual variability of rs-fc. Our results suggest that individual variability of the right sgACC and bilateral precuneus connectivity may be a potential mechanism of rTMS.
Collapse
Affiliation(s)
- Vinh Tan
- From the Campbell Family Research Centre, Centre for Addiction and Mental Health, Toronto, Ont. (Tan, Blumberger, Hawco); the Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ont. (Downar, Nestor); the Harquail Centre for Neuromodulation, Department of Psychiatry, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ont. (Nestor, Blumberger, Hawco); the Non-Invasive Neurostimulation Therapies Laboratory, Department of Psychiatry, University of British Columbia, Vancouver, BC (Vila-Rodriguez); the Department of Psychiatry, University of California, San Diego (Daskalakis); the Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, Ont. (Blumberger)
| | - Jonathan Downar
- From the Campbell Family Research Centre, Centre for Addiction and Mental Health, Toronto, Ont. (Tan, Blumberger, Hawco); the Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ont. (Downar, Nestor); the Harquail Centre for Neuromodulation, Department of Psychiatry, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ont. (Nestor, Blumberger, Hawco); the Non-Invasive Neurostimulation Therapies Laboratory, Department of Psychiatry, University of British Columbia, Vancouver, BC (Vila-Rodriguez); the Department of Psychiatry, University of California, San Diego (Daskalakis); the Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, Ont. (Blumberger)
| | - Sean Nestor
- From the Campbell Family Research Centre, Centre for Addiction and Mental Health, Toronto, Ont. (Tan, Blumberger, Hawco); the Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ont. (Downar, Nestor); the Harquail Centre for Neuromodulation, Department of Psychiatry, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ont. (Nestor, Blumberger, Hawco); the Non-Invasive Neurostimulation Therapies Laboratory, Department of Psychiatry, University of British Columbia, Vancouver, BC (Vila-Rodriguez); the Department of Psychiatry, University of California, San Diego (Daskalakis); the Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, Ont. (Blumberger)
| | - Fidel Vila-Rodriguez
- From the Campbell Family Research Centre, Centre for Addiction and Mental Health, Toronto, Ont. (Tan, Blumberger, Hawco); the Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ont. (Downar, Nestor); the Harquail Centre for Neuromodulation, Department of Psychiatry, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ont. (Nestor, Blumberger, Hawco); the Non-Invasive Neurostimulation Therapies Laboratory, Department of Psychiatry, University of British Columbia, Vancouver, BC (Vila-Rodriguez); the Department of Psychiatry, University of California, San Diego (Daskalakis); the Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, Ont. (Blumberger)
| | - Zafiris J Daskalakis
- From the Campbell Family Research Centre, Centre for Addiction and Mental Health, Toronto, Ont. (Tan, Blumberger, Hawco); the Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ont. (Downar, Nestor); the Harquail Centre for Neuromodulation, Department of Psychiatry, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ont. (Nestor, Blumberger, Hawco); the Non-Invasive Neurostimulation Therapies Laboratory, Department of Psychiatry, University of British Columbia, Vancouver, BC (Vila-Rodriguez); the Department of Psychiatry, University of California, San Diego (Daskalakis); the Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, Ont. (Blumberger)
| | - Daniel M Blumberger
- From the Campbell Family Research Centre, Centre for Addiction and Mental Health, Toronto, Ont. (Tan, Blumberger, Hawco); the Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ont. (Downar, Nestor); the Harquail Centre for Neuromodulation, Department of Psychiatry, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ont. (Nestor, Blumberger, Hawco); the Non-Invasive Neurostimulation Therapies Laboratory, Department of Psychiatry, University of British Columbia, Vancouver, BC (Vila-Rodriguez); the Department of Psychiatry, University of California, San Diego (Daskalakis); the Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, Ont. (Blumberger)
| | - Colin Hawco
- From the Campbell Family Research Centre, Centre for Addiction and Mental Health, Toronto, Ont. (Tan, Blumberger, Hawco); the Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ont. (Downar, Nestor); the Harquail Centre for Neuromodulation, Department of Psychiatry, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ont. (Nestor, Blumberger, Hawco); the Non-Invasive Neurostimulation Therapies Laboratory, Department of Psychiatry, University of British Columbia, Vancouver, BC (Vila-Rodriguez); the Department of Psychiatry, University of California, San Diego (Daskalakis); the Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, Ont. (Blumberger)
| |
Collapse
|
3
|
Oliver LD, Jeyachandra J, Dickie EW, Hawco C, Mansour S, Hare SM, Buchanan RW, Malhotra AK, Blumberger DM, Deng ZD, Voineskos AN. Bayesian Optimization of Neurostimulation (BOONStim). bioRxiv 2024:2024.03.08.584169. [PMID: 38559269 PMCID: PMC10979934 DOI: 10.1101/2024.03.08.584169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
BACKGROUND Transcranial magnetic stimulation (TMS) treatment response is influenced by individual variability in brain structure and function. Sophisticated, user-friendly approaches, incorporating both established functional magnetic resonance imaging (fMRI) and TMS simulation tools, to identify TMS targets are needed. OBJECTIVE The current study presents the development and validation of the Bayesian Optimization of Neuro-Stimulation (BOONStim) pipeline. METHODS BOONStim uses Bayesian optimization for individualized TMS targeting, automating interoperability between surface-based fMRI analytic tools and TMS electric field modeling. Bayesian optimization performance was evaluated in a sample dataset (N=10) using standard circular and functional connectivity-defined targets, and compared to grid optimization. RESULTS Bayesian optimization converged to similar levels of total electric field stimulation across targets in under 30 iterations, converging within a 5% error of the maxima detected by grid optimization, and requiring less time. CONCLUSIONS BOONStim is a scalable and configurable user-friendly pipeline for individualized TMS targeting with quick turnaround.
Collapse
|
4
|
Wainberg M, Forde NJ, Mansour S, Kerrebijn I, Medland SE, Hawco C, Tripathy SJ. Genetic architecture of the structural connectome. Nat Commun 2024; 15:1962. [PMID: 38438384 PMCID: PMC10912129 DOI: 10.1038/s41467-024-46023-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 02/12/2024] [Indexed: 03/06/2024] Open
Abstract
Myelinated axons form long-range connections that enable rapid communication between distant brain regions, but how genetics governs the strength and organization of these connections remains unclear. We perform genome-wide association studies of 206 structural connectivity measures derived from diffusion magnetic resonance imaging tractography of 26,333 UK Biobank participants, each representing the density of myelinated connections within or between a pair of cortical networks, subcortical structures or cortical hemispheres. We identify 30 independent genome-wide significant variants after Bonferroni correction for the number of measures studied (126 variants at nominal genome-wide significance) implicating genes involved in myelination (SEMA3A), neurite elongation and guidance (NUAK1, STRN, DPYSL2, EPHA3, SEMA3A, HGF, SHTN1), neural cell proliferation and differentiation (GMNC, CELF4, HGF), neuronal migration (CCDC88C), cytoskeletal organization (CTTNBP2, MAPT, DAAM1, MYO16, PLEC), and brain metal transport (SLC39A8). These variants have four broad patterns of spatial association with structural connectivity: some have disproportionately strong associations with corticothalamic connectivity, interhemispheric connectivity, or both, while others are more spatially diffuse. Structural connectivity measures are highly polygenic, with a median of 9.1 percent of common variants estimated to have non-zero effects on each measure, and exhibited signatures of negative selection. Structural connectivity measures have significant genetic correlations with a variety of neuropsychiatric and cognitive traits, indicating that connectivity-altering variants tend to influence brain health and cognitive function. Heritability is enriched in regions with increased chromatin accessibility in adult oligodendrocytes (as well as microglia, inhibitory neurons and astrocytes) and multiple fetal cell types, suggesting that genetic control of structural connectivity is partially mediated by effects on myelination and early brain development. Our results indicate pervasive, pleiotropic, and spatially structured genetic control of white-matter structural connectivity via diverse neurodevelopmental pathways, and support the relevance of this genetic control to healthy brain function.
Collapse
Affiliation(s)
- Michael Wainberg
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada.
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada.
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
- Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada.
| | - Natalie J Forde
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
| | - Salim Mansour
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Isabel Kerrebijn
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Psychology, University of Queensland, Brisbane, QLD, Australia
- Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
| | - Colin Hawco
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
- Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada.
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada.
| | - Shreejoy J Tripathy
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada.
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
- Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada.
- Department of Physiology, University of Toronto, Toronto, ON, Canada.
| |
Collapse
|
5
|
Voineskos AN, Hawco C, Neufeld NH, Turner JA, Ameis SH, Anticevic A, Buchanan RW, Cadenhead K, Dazzan P, Dickie EW, Gallucci J, Lahti AC, Malhotra AK, Öngür D, Lencz T, Sarpal DK, Oliver LD. Functional magnetic resonance imaging in schizophrenia: current evidence, methodological advances, limitations and future directions. World Psychiatry 2024; 23:26-51. [PMID: 38214624 PMCID: PMC10786022 DOI: 10.1002/wps.21159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/13/2024] Open
Abstract
Functional neuroimaging emerged with great promise and has provided fundamental insights into the neurobiology of schizophrenia. However, it has faced challenges and criticisms, most notably a lack of clinical translation. This paper provides a comprehensive review and critical summary of the literature on functional neuroimaging, in particular functional magnetic resonance imaging (fMRI), in schizophrenia. We begin by reviewing research on fMRI biomarkers in schizophrenia and the clinical high risk phase through a historical lens, moving from case-control regional brain activation to global connectivity and advanced analytical approaches, and more recent machine learning algorithms to identify predictive neuroimaging features. Findings from fMRI studies of negative symptoms as well as of neurocognitive and social cognitive deficits are then reviewed. Functional neural markers of these symptoms and deficits may represent promising treatment targets in schizophrenia. Next, we summarize fMRI research related to antipsychotic medication, psychotherapy and psychosocial interventions, and neurostimulation, including treatment response and resistance, therapeutic mechanisms, and treatment targeting. We also review the utility of fMRI and data-driven approaches to dissect the heterogeneity of schizophrenia, moving beyond case-control comparisons, as well as methodological considerations and advances, including consortia and precision fMRI. Lastly, limitations and future directions of research in the field are discussed. Our comprehensive review suggests that, in order for fMRI to be clinically useful in the care of patients with schizophrenia, research should address potentially actionable clinical decisions that are routine in schizophrenia treatment, such as which antipsychotic should be prescribed or whether a given patient is likely to have persistent functional impairment. The potential clinical utility of fMRI is influenced by and must be weighed against cost and accessibility factors. Future evaluations of the utility of fMRI in prognostic and treatment response studies may consider including a health economics analysis.
Collapse
Affiliation(s)
- Aristotle N Voineskos
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Colin Hawco
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Nicholas H Neufeld
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Jessica A Turner
- Department of Psychiatry and Behavioral Health, Wexner Medical Center, Ohio State University, Columbus, OH, USA
| | - Stephanie H Ameis
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- Cundill Centre for Child and Youth Depression and McCain Centre for Child, Youth and Family Mental Health, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Alan Anticevic
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA
- Department of Psychiatry, Yale University, New Haven, CT, USA
| | - Robert W Buchanan
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Kristin Cadenhead
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Paola Dazzan
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Erin W Dickie
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Julia Gallucci
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Adrienne C Lahti
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Anil K Malhotra
- Institute for Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Psychiatry, Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, USA
| | - Dost Öngür
- McLean Hospital/Harvard Medical School, Belmont, MA, USA
| | - Todd Lencz
- Institute for Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Psychiatry, Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, USA
| | - Deepak K Sarpal
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Lindsay D Oliver
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| |
Collapse
|
6
|
Calarco N, Oliver LD, Joseph M, Hawco C, Dickie EW, DeRosse P, Gold JM, Foussias G, Argyelan M, Malhotra AK, Buchanan RW, Voineskos AN. Multivariate Associations Among White Matter, Neurocognition, and Social Cognition Across Individuals With Schizophrenia Spectrum Disorders and Healthy Controls. Schizophr Bull 2023; 49:1518-1529. [PMID: 36869812 PMCID: PMC10686342 DOI: 10.1093/schbul/sbac216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/05/2023]
Abstract
BACKGROUND AND HYPOTHESIS Neurocognitive and social cognitive abilities are important contributors to functional outcomes in schizophrenia spectrum disorders (SSDs). An unanswered question of considerable interest is whether neurocognitive and social cognitive deficits arise from overlapping or distinct white matter impairment(s). STUDY DESIGN We sought to fill this gap, by harnessing a large sample of individuals from the multi-center Social Processes Initiative in the Neurobiology of the Schizophrenia(s) (SPINS) dataset, unique in its collection of advanced diffusion imaging and an extensive battery of cognitive assessments. We applied canonical correlation analysis to estimates of white matter microstructure, and cognitive performance, across people with and without an SSD. STUDY RESULTS Our results established that white matter circuitry is dimensionally and strongly related to both neurocognition and social cognition, and that microstructure of the uncinate fasciculus and the rostral body of the corpus callosum may assume a "privileged role" subserving both. Further, we found that participant-wise estimates of white matter microstructure, weighted by cognitive performance, were largely consistent with participants' categorical diagnosis, and predictive of (cross-sectional) functional outcomes. CONCLUSIONS The demonstrated strength of the relationship between white matter circuitry and neurocognition and social cognition underscores the potential for using relationships among these variables to identify biomarkers of functioning, with potential prognostic and therapeutic implications.
Collapse
Affiliation(s)
- Navona Calarco
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Lindsay D Oliver
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Michael Joseph
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Colin Hawco
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Erin W Dickie
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Pamela DeRosse
- Division of Psychiatry Research, Division of Northwell Health, The Zucker Hillside Hospital, Glen Oaks, NY, USA
- Department of Psychiatry, The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Center for Psychiatric Neuroscience, The Feinstein Institute for Medical Research, Manhasset, NY, USA
| | - James M Gold
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, USA
| | - George Foussias
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Miklos Argyelan
- Division of Psychiatry Research, Division of Northwell Health, The Zucker Hillside Hospital, Glen Oaks, NY, USA
- Department of Psychiatry, The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Center for Psychiatric Neuroscience, The Feinstein Institute for Medical Research, Manhasset, NY, USA
| | - Anil K Malhotra
- Division of Psychiatry Research, Division of Northwell Health, The Zucker Hillside Hospital, Glen Oaks, NY, USA
- Department of Psychiatry, The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Center for Psychiatric Neuroscience, The Feinstein Institute for Medical Research, Manhasset, NY, USA
| | - Robert W Buchanan
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Aristotle N Voineskos
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| |
Collapse
|
7
|
Dickie EW, Shahab S, Hawco C, Miranda D, Herman G, Argyelan M, Ji JL, Jeyachandra J, Anticevic A, Malhotra AK, Voineskos AN. Robust hierarchically organized whole-brain patterns of dysconnectivity in schizophrenia spectrum disorders observed after personalized intrinsic network topography. Hum Brain Mapp 2023; 44:5153-5166. [PMID: 37605827 PMCID: PMC10502662 DOI: 10.1002/hbm.26453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 07/05/2023] [Accepted: 08/01/2023] [Indexed: 08/23/2023] Open
Abstract
BACKGROUND Spatial patterns of brain functional connectivity can vary substantially at the individual level. Applying cortical surface-based approaches with individualized rather than group templates may accelerate the discovery of biological markers related to psychiatric disorders. We investigated cortico-subcortical networks from multi-cohort data in people with schizophrenia spectrum disorders (SSDs) and healthy controls (HC) using individualized connectivity profiles. METHODS We utilized resting-state and anatomical MRI data from n = 406 participants (n = 203 SSD, n = 203 HC) from four cohorts. Functional timeseries were extracted from previously defined intrinsic network subregions of the striatum, thalamus, and cerebellum as well as 80 cortical regions of interest, representing six intrinsic networks using (1) volume-based approaches, (2) a surface-based group atlas approaches, and (3) Personalized Intrinsic Network Topography (PINT). RESULTS The correlations between all cortical networks and the expected subregions of the striatum, cerebellum, and thalamus were increased using a surface-based approach (Cohen's D volume vs. surface 0.27-1.00, all p < 10-6 ) and further increased after PINT (Cohen's D surface vs. PINT 0.18-0.96, all p < 10-4 ). In SSD versus HC comparisons, we observed robust patterns of dysconnectivity that were strengthened using a surface-based approach and PINT (Number of differing pairwise-correlations: volume: 404, surface: 570, PINT: 628, FDR corrected). CONCLUSION Surface-based and individualized approaches can more sensitively delineate cortical network dysconnectivity differences in people with SSDs. These robust patterns of dysconnectivity were visibly organized in accordance with the cortical hierarchy, as predicted by computational models.
Collapse
Affiliation(s)
- Erin W. Dickie
- Center for Addiction and Mental HealthCampbell Family Mental Health ResearchTorontoOntarioCanada
- Department of PsychiatryUniversity of TorontoTorontoOntarioUSA
| | - Saba Shahab
- Department of MedicineUniversity of OttawaOttawaOntarioCanada
| | - Colin Hawco
- Center for Addiction and Mental HealthCampbell Family Mental Health ResearchTorontoOntarioCanada
- Department of PsychiatryUniversity of TorontoTorontoOntarioUSA
| | - Dayton Miranda
- Center for Addiction and Mental HealthCampbell Family Mental Health ResearchTorontoOntarioCanada
| | - Gabrielle Herman
- Center for Addiction and Mental HealthCampbell Family Mental Health ResearchTorontoOntarioCanada
| | - Miklos Argyelan
- Psychiatry Research, The Zucker Hillside HospitalGlen CoveNew YorkUSA
- Institute of Behavioral Science, Feinstein Institutes for Medical ResearchManhassetNew YorkUSA
- Donald and Barbara Zucker School of Medicine at Hofstra/NorthwellHempsteadNew YorkUSA
| | - Jie Lisa Ji
- Department of PsychiatryYale UniversityNew HavenConnecticutUSA
| | - Jerrold Jeyachandra
- Center for Addiction and Mental HealthCampbell Family Mental Health ResearchTorontoOntarioCanada
| | - Alan Anticevic
- Department of PsychiatryYale UniversityNew HavenConnecticutUSA
| | - Anil K. Malhotra
- Psychiatry Research, The Zucker Hillside HospitalGlen CoveNew YorkUSA
- Institute of Behavioral Science, Feinstein Institutes for Medical ResearchManhassetNew YorkUSA
- Donald and Barbara Zucker School of Medicine at Hofstra/NorthwellHempsteadNew YorkUSA
| | - Aristotle N. Voineskos
- Center for Addiction and Mental HealthCampbell Family Mental Health ResearchTorontoOntarioCanada
- Department of PsychiatryUniversity of TorontoTorontoOntarioUSA
| |
Collapse
|
8
|
Jones BDM, Zhukovsky P, Hawco C, Ortiz A, Cipriani A, Voineskos AN, Mulsant BH, Husain MI. Protocol for a systematic review and meta-analysis of coordinate-based network mapping of brain structure in bipolar disorder across the lifespan. BJPsych Open 2023; 9:e178. [PMID: 37811544 PMCID: PMC10594157 DOI: 10.1192/bjo.2023.569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 08/03/2023] [Accepted: 08/22/2023] [Indexed: 10/10/2023] Open
Abstract
BACKGROUND Studies about brain structure in bipolar disorder have reported conflicting findings. These findings may be explained by the high degree of heterogeneity within bipolar disorder, especially if structural differences are mapped to single brain regions rather than networks. AIMS We aim to complete a systematic review and meta-analysis to identify brain networks underlying structural abnormalities observed on T1-weighted magnetic resonance imaging scans in bipolar disorder across the lifespan. We also aim to explore how these brain networks are affected by sociodemographic and clinical heterogeneity in bipolar disorder. METHOD We will include case-control studies that focus on whole-brain analyses of structural differences between participants of any age with a standardised diagnosis of bipolar disorder and controls. The electronic databases Medline, PsycINFO and Web of Science will be searched. We will complete an activation likelihood estimation analysis and a novel coordinate-based network mapping approach to identify specific brain regions and brain circuits affected in bipolar disorder or relevant subgroups. Meta-regressions will examine the effect of sociodemographic and clinical variables on identified brain circuits. CONCLUSIONS Findings from this systematic review and meta-analysis will enhance understanding of the pathophysiology of bipolar disorder. The results will identify brain circuitry implicated in bipolar disorder, and how they may relate to relevant sociodemographic and clinical variables across the lifespan.
Collapse
Affiliation(s)
- Brett D. M. Jones
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Canada; and Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Canada
| | - Peter Zhukovsky
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Canada; and Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Canada
| | - Colin Hawco
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Canada; and Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Canada
| | - Abigail Ortiz
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Canada; and Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Canada
| | - Andrea Cipriani
- Department of Psychiatry, University of Oxford, UK; Oxford Health NHS Foundation Trust, Warneford Hospital, Oxford, UK; and Oxford Precision Psychiatry Laboratory, NIHR Oxford Health Biomedical Research Centre, UK
| | - Aristotle N. Voineskos
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Canada; and Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Canada
| | - Benoit H. Mulsant
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Canada; and Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Canada
| | - Muhammad Ishrat Husain
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Canada; and Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Canada
| |
Collapse
|
9
|
Pan R, Dickie EW, Hawco C, Reid N, Voineskos AN, Park JY. Spatial-extent inference for testing variance components in reliability and heritability studies. bioRxiv 2023:2023.04.19.537270. [PMID: 37131799 PMCID: PMC10153210 DOI: 10.1101/2023.04.19.537270] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Clusterwise inference is a popular approach in neuroimaging to increase sensitivity, but most existing methods are currently restricted to the General Linear Model (GLM) for testing mean parameters. Statistical methods for testing variance components, which are critical in neuroimaging studies that involve estimation of narrow-sense heritability or test-retest reliability, are underdeveloped due to methodological and computational challenges, which would potentially lead to low power. We propose a fast and powerful test for variance components called CLEAN-V (CLEAN for testing Variance components). CLEAN-V models the global spatial dependence structure of imaging data and computes a locally powerful variance component test statistic by data-adaptively pooling neighborhood information. Correction for multiple comparisons is achieved by permutations to control family-wise error rate (FWER). Through analysis of task-fMRI data from the Human Connectome Project across five tasks and comprehensive data-driven simulations, we show that CLEAN-V outperforms existing methods in detecting test-retest reliability and narrow-sense heritability with significantly improved power, with the detected areas aligning with activation maps. The computational efficiency of CLEAN-V also speaks of its practical utility, and it is available as an R package.
Collapse
Affiliation(s)
- Ruyi Pan
- Department of Statistical Sciences, University of Toronto, Toronto, ON, M5G 1Z5, Canada
- The Centre for Addiction and Mental Health, Toronto, ON, M5T 1R8, Canada
| | - Erin W. Dickie
- The Centre for Addiction and Mental Health, Toronto, ON, M5T 1R8, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, M5T 1R8, Canada
| | - Colin Hawco
- The Centre for Addiction and Mental Health, Toronto, ON, M5T 1R8, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, M5T 1R8, Canada
| | - Nancy Reid
- Department of Statistical Sciences, University of Toronto, Toronto, ON, M5G 1Z5, Canada
| | - Aristotle N. Voineskos
- The Centre for Addiction and Mental Health, Toronto, ON, M5T 1R8, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, M5T 1R8, Canada
| | - Jun Young Park
- Department of Statistical Sciences, University of Toronto, Toronto, ON, M5G 1Z5, Canada
- Department of Psychology, University of Toronto, Toronto, ON, M5G 1Z5, Canada
| |
Collapse
|
10
|
Agarwal SM, Dissanayake J, Agid O, Bowie C, Brierley N, Chintoh A, De Luca V, Diaconescu A, Gerretsen P, Graff-Guerrero A, Hawco C, Herman Y, Hill S, Hum K, Husain MO, Kennedy JL, Kiang M, Kidd S, Kozloff N, Maslej M, Mueller DJ, Naeem F, Neufeld N, Remington G, Rotenberg M, Selby P, Siddiqui I, Szacun-Shimizu K, Tiwari AK, Thirunavukkarasu S, Wang W, Yu J, Zai CC, Zipursky R, Hahn M, Foussias G. Characterization and prediction of individual functional outcome trajectories in schizophrenia spectrum disorders (PREDICTS study): Study protocol. PLoS One 2023; 18:e0288354. [PMID: 37733693 PMCID: PMC10513234 DOI: 10.1371/journal.pone.0288354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 06/23/2023] [Indexed: 09/23/2023] Open
Abstract
Schizophrenia spectrum disorders (SSDs) are associated with significant functional impairments, disability, and low rates of personal recovery, along with tremendous economic costs linked primarily to lost productivity and premature mortality. Efforts to delineate the contributors to disability in SSDs have highlighted prominent roles for a diverse range of symptoms, physical health conditions, substance use disorders, neurobiological changes, and social factors. These findings have provided valuable advances in knowledge and helped define broad patterns of illness and outcomes across SSDs. Unsurprisingly, there have also been conflicting findings for many of these determinants that reflect the heterogeneous population of individuals with SSDs and the challenges of conceptualizing and treating SSDs as a unitary categorical construct. Presently it is not possible to identify the functional course on an individual level that would enable a personalized approach to treatment to alter the individual's functional trajectory and mitigate the ensuing disability they would otherwise experience. To address this ongoing challenge, this study aims to conduct a longitudinal multimodal investigation of a large cohort of individuals with SSDs in order to establish discrete trajectories of personal recovery, disability, and community functioning, as well as the antecedents and predictors of these trajectories. This investigation will also provide the foundation for the co-design and testing of personalized interventions that alter these functional trajectories and improve outcomes for people with SSDs.
Collapse
Affiliation(s)
- Sri Mahavir Agarwal
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
- Temerty Faculty Institute of Medical Science, University of Toronto, Toronto, Canada
- Department of Psychiatry, University of Toronto, Toronto, Canada
- Banting and Best Diabetes Centre (BBDC), University of Toronto, Toronto, Canada
| | - Joel Dissanayake
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Ofer Agid
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Christopher Bowie
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Noah Brierley
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Araba Chintoh
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Vincenzo De Luca
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Andreea Diaconescu
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Philip Gerretsen
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Ariel Graff-Guerrero
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Colin Hawco
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Yarissa Herman
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Sean Hill
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Kathryn Hum
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Muhammad Omair Husain
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - James L. Kennedy
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Michael Kiang
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Sean Kidd
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Nicole Kozloff
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Marta Maslej
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Daniel J. Mueller
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Farooq Naeem
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Nicholas Neufeld
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Gary Remington
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Martin Rotenberg
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Peter Selby
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Ishraq Siddiqui
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Kate Szacun-Shimizu
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Arun K. Tiwari
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | | | - Wei Wang
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Joanna Yu
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Clement C. Zai
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Robert Zipursky
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Margaret Hahn
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
- Temerty Faculty Institute of Medical Science, University of Toronto, Toronto, Canada
- Department of Psychiatry, University of Toronto, Toronto, Canada
- Banting and Best Diabetes Centre (BBDC), University of Toronto, Toronto, Canada
| | - George Foussias
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
- Temerty Faculty Institute of Medical Science, University of Toronto, Toronto, Canada
- Department of Psychiatry, University of Toronto, Toronto, Canada
| |
Collapse
|
11
|
Tan V, Jeyachandra J, Ge R, Dickie EW, Gregory E, Vanderwal T, Vila-Rodriguez F, Hawco C. Subgenual cingulate connectivity as a treatment predictor during low-frequency right dorsolateral prefrontal rTMS: A concurrent TMS-fMRI study. Brain Stimul 2023; 16:1165-1172. [PMID: 37543171 DOI: 10.1016/j.brs.2023.07.051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2023] [Revised: 07/19/2023] [Accepted: 07/25/2023] [Indexed: 08/07/2023] Open
Abstract
INTRODUCTION Repetitive transcranial magnetic stimulation (rTMS) to the dorsolateral prefrontal cortex (DLPFC) is effective in alleviating treatment-resistant depression (TRD). It has been proposed that regions within the left DLPFC that are anti-correlated with the right subgenual anterior cingulate cortex (sgACC) may represent optimal individualized target sites for high-frequency left rTMS (HFL). OBJECTIVE/HYPOTHESIS This study aimed to explore the effects of low-frequency right rTMS (LFR) on left sgACC connectivity during concurrent TMS-fMRI. METHODS 34 TRD patients underwent an imaging session that included both a resting-state fMRI run (rs-fMRI0) and a run during which LFR was applied to the right DLPFC (TMS-fMRI). Participants subsequently completed four weeks of LFR treatment. The left sgACC functional connectivity was compared between the rs-fMRI0 run and TMS-fMRI run. Personalized e-fields and a region-of-interest approach were used to calculate overlap of left sgACC functional connectivity at the TMS target and to assess for a relationship with treatment effects. RESULTS TMS-fMRI increased left sgACC functional connectivity to parietal regions within the ventral attention network; differences were not significantly associated with clinical improvements. Personalized e-fields were not significant in predicting treatment outcomes (p = 0.18). CONCLUSION This was the first study to examine left sgACC anti-correlation with the right DLPFC during an LFR rTMS protocol. In contrast to studies that targeted the left DLPFC, we did not find that higher anti-correlation was associated with clinical outcomes. Our results suggest that the antidepressant mechanism of action of LFR to the right DLPFC may be different than for HFL.
Collapse
Affiliation(s)
- Vinh Tan
- Kimel Family Translational Imaging Genetics Research Laboratory, Centre for Addiction and Mental Health, Toronto, Canada
| | - Jerrold Jeyachandra
- Kimel Family Translational Imaging Genetics Research Laboratory, Centre for Addiction and Mental Health, Toronto, Canada
| | - Ruiyang Ge
- Non-Invasive Neurostimulation Therapies Laboratory, Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada; Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada; Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
| | - Erin W Dickie
- Kimel Family Translational Imaging Genetics Research Laboratory, Centre for Addiction and Mental Health, Toronto, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Elizabeth Gregory
- Non-Invasive Neurostimulation Therapies Laboratory, Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Tamara Vanderwal
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada; Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
| | - Fidel Vila-Rodriguez
- Non-Invasive Neurostimulation Therapies Laboratory, Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Colin Hawco
- Kimel Family Translational Imaging Genetics Research Laboratory, Centre for Addiction and Mental Health, Toronto, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada.
| |
Collapse
|
12
|
Poorganji M, Zomorrodi R, Hawco C, Hill AT, Hadas I, Zrenner C, Rajji TK, Chen R, Voineskos D, Blumberger DM, Daskalakis ZJ. Isolating sensory artifacts in the suprathreshold TMS-EEG signal over DLPFC. Sci Rep 2023; 13:6796. [PMID: 37100795 PMCID: PMC10130812 DOI: 10.1038/s41598-023-29920-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Accepted: 02/13/2023] [Indexed: 04/28/2023] Open
Abstract
Combined transcranial magnetic stimulation and electroencephalography (TMS-EEG) is an effective way to evaluate neurophysiological processes at the level of the cortex. To further characterize the TMS-evoked potential (TEP) generated with TMS-EEG, beyond the motor cortex, we aimed to distinguish between cortical reactivity to TMS versus non-specific somatosensory and auditory co-activations using both single-pulse and paired-pulse protocols at suprathreshold stimulation intensities over the left dorsolateral prefrontal cortex (DLPFC). Fifteen right-handed healthy participants received six blocks of stimulation including single and paired TMS delivered as active-masked (i.e., TMS-EEG with auditory masking and foam spacing), active-unmasked (TMS-EEG without auditory masking and foam spacing) and sham (sham TMS coil). We evaluated cortical excitability following single-pulse TMS, and cortical inhibition following a paired-pulse paradigm (long-interval cortical inhibition (LICI)). Repeated measure ANOVAs revealed significant differences in mean cortical evoked activity (CEA) of active-masked, active-unmasked, and sham conditions for both the single-pulse (F(1.76, 24.63) = 21.88, p < 0.001, η2 = 0.61) and LICI (F(1.68, 23.49) = 10.09, p < 0.001, η2 = 0.42) protocols. Furthermore, global mean field amplitude (GMFA) differed significantly across the three conditions for both single-pulse (F(1.85, 25.89) = 24.68, p < 0.001, η2 = 0.64) and LICI (F(1.8, 25.16) = 14.29, p < 0.001, η2 = 0.5). Finally, only active LICI protocols but not sham stimulation ([active-masked (0.78 ± 0.16, P < 0.0001)], [active-unmasked (0.83 ± 0.25, P < 0.01)]) resulted in significant signal inhibition. While previous findings of a significant somatosensory and auditory contribution to the evoked EEG signal are replicated by our study, an artifact attenuated cortical reactivity can reliably be measured in the TMS-EEG signal with suprathreshold stimulation of DLPFC. Artifact attenuation can be accomplished using standard procedures, and even when masked, the level of cortical reactivity is still far above what is produced by sham stimulation. Our study illustrates that TMS-EEG of DLPFC remains a valid investigational tool.
Collapse
Affiliation(s)
- Mohsen Poorganji
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Reza Zomorrodi
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Colin Hawco
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Aron T Hill
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Melbourne, VIC, Australia
| | - Itay Hadas
- Department of Psychiatry, School of Medicine, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093-0603, USA
| | - Christoph Zrenner
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Department of Neurology and Stroke, and Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Tarek K Rajji
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Toronto Dementia Research Alliance, University of Toronto, Toronto, ON, Canada
| | - Robert Chen
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Krembil Research Institute, University Health Network, Toronto, ON, Canada
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Daphne Voineskos
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Daniel M Blumberger
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Zafiris J Daskalakis
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada.
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada.
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
- Department of Psychiatry, School of Medicine, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093-0603, USA.
| |
Collapse
|
13
|
Nakua H, Hawco C, Forde NJ, Joseph M, Grillet M, Johnson D, Jacobs GR, Hill S, Voineskos A, Wheeler AL, Lai MC, Szatmari P, Georgiades S, Nicolson R, Schachar R, Crosbie J, Anagnostou E, Lerch JP, Arnold PD, Ameis SH. Systematic comparisons of different quality control approaches applied to three large pediatric neuroimaging datasets. Neuroimage 2023; 274:120119. [PMID: 37068719 DOI: 10.1016/j.neuroimage.2023.120119] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 03/22/2023] [Accepted: 04/14/2023] [Indexed: 04/19/2023] Open
Abstract
INTRODUCTION Poor quality T1-weighted brain scans systematically affect the calculation of brain measures. Removing the influence of such scans requires identifying and excluding scans with noise and artefacts through a quality control (QC) procedure. While QC is critical for brain imaging analyses, it is not yet clear whether different QC approaches lead to the exclusion of the same participants. Further, the removal of poor-quality scans may unintentionally introduce a sampling bias by excluding the subset of participants who are younger and/or feature greater clinical impairment. This study had two aims: 1) examine whether different QC approaches applied to T1-weighted scans would exclude the same participants, and 2) examine how exclusion of poor-quality scans impacts specific demographic, clinical and brain measure characteristics between excluded and included participants in three large pediatric neuroimaging samples. METHODS We used T1-weighted, resting-state fMRI, demographic and clinical data from the Province of Ontario Neurodevelopmental Disorders network (Aim 1: n=553, Aim 2: n=465), the Healthy Brain Network (Aim 1: n=1051, Aim 2: n=558), and the Philadelphia Neurodevelopmental Cohort (Aim 1: n=1087; Aim 2: n=619). Four different QC approaches were applied to T1-weighted MRI (visual QC, metric QC, automated QC, fMRI-derived QC). We used tetrachoric correlation and inter-rater reliability analyses to examine whether different QC approaches excluded the same participants. We examined differences in age, mental health symptoms, everyday/adaptive functioning, IQ and structural MRI-derived brain indices between participants that were included versus excluded following each QC approach. RESULTS Dataset-specific findings revealed mixed results with respect to overlap of QC exclusion. However, in POND and HBN, we found a moderate level of overlap between visual and automated QC approaches (rtet=0.52-0.59). Implementation of QC excluded younger participants, and tended to exclude those with lower IQ, and lower everyday/adaptive functioning scores across several approaches in a dataset-specific manner. Across nearly all datasets and QC approaches examined, excluded participants had lower estimates of cortical thickness and subcortical volume, but this effect did not differ by QC approach. CONCLUSION The results of this study provide insight into the influence of QC decisions on structural pediatric imaging analyses. While different QC approaches exclude different subsets of participants, the variation of influence of different QC approaches on clinical and brain metrics is minimal in large datasets. Overall, implementation of QC tends to exclude participants who are younger, and those who have more cognitive and functional impairment. Given that automated QC is standardized and can reduce between-study differences, the results of this study support the potential to use automated QC for large pediatric neuroimaging datasets.
Collapse
Affiliation(s)
- Hajer Nakua
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Canada
| | - Colin Hawco
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Natalie J Forde
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Michael Joseph
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Maud Grillet
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Delaney Johnson
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Grace R Jacobs
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Canada
| | - Sean Hill
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Canada
| | - Aristotle Voineskos
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Anne L Wheeler
- Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada; Department of Physiology, University of Toronto, Toronto, Ontario, Canada
| | - Meng-Chuan Lai
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Peter Szatmari
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada
| | | | - Rob Nicolson
- Department of Psychiatry, University of Western Ontario, London, Ontario, Canada
| | - Russell Schachar
- Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada; Genetics & Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Jennifer Crosbie
- Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada; Genetics & Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Evdokia Anagnostou
- Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Ontario, Canada; Department of Pediatrics, University of Toronto, Toronto, Canada
| | - Jason P Lerch
- Mouse Imaging Centre, Hospital for Sick Children, Toronto, Ontario, Canada; Department of Medical Biophysics, Faculty of Medicine, University of Toronto, Toronto, Canada; Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Paul D Arnold
- The Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; Departments of Psychiatry and Medical Genetics, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Stephanie H Ameis
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada.
| |
Collapse
|
14
|
Nakua H, Yu JC, Abdi H, Hawco C, Voineskos A, Hill S, Lai MC, Wheeler AL, McIntosh AR, Ameis SH. Comparing the stability and reproducibility of brain-behaviour relationships found using Canonical Correlation Analysis and Partial Least Squares within the ABCD Sample. bioRxiv 2023:2023.03.08.531763. [PMID: 36945610 PMCID: PMC10028915 DOI: 10.1101/2023.03.08.531763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Introduction Canonical Correlation Analysis (CCA) and Partial Least Squares Correlation (PLS) detect associations between two data matrices based on computing a linear combination between the two matrices (called latent variables; LVs). These LVs maximize correlation (CCA) and covariance (PLS). These different maximization criteria may render one approach more stable and reproducible than the other when working with brain and behavioural data at the population-level. This study compared the LVs which emerged from CCA and PLS analyses of brain-behaviour relationships from the Adolescent Brain Cognitive Development (ABCD) dataset and examined their stability and reproducibility. Methods Structural T1-weighted imaging and behavioural data were accessed from the baseline Adolescent Brain Cognitive Development dataset (N > 9000, ages = 9-11 years). The brain matrix consisted of cortical thickness estimates in different cortical regions. The behavioural matrix consisted of 11 subscale scores from the parent-reported Child Behavioral Checklist (CBCL) or 7 cognitive performance measures from the NIH Toolbox. CCA and PLS models were separately applied to the brain-CBCL analysis and brain-cognition analysis. A permutation test was used to assess whether identified LVs were statistically significant. A series of resampling statistical methods were used to assess stability and reproducibility of the LVs. Results When examining the relationship between cortical thickness and CBCL scores, the first LV was found to be significant across both CCA and PLS models (singular value: CCA = .13, PLS = .39, p < .001). LV1 from the CCA model found that covariation of CBCL scores was linked to covariation of cortical thickness. LV1 from the PLS model identified decreased cortical thickness linked to lower CBCL scores. There was limited evidence of stability or reproducibility of LV1 for both CCA and PLS. When examining the relationship between cortical thickness and cognitive performance, there were 6 significant LVs for both CCA and PLS (p < .01). The first LV showed similar relationships between CCA and PLS and was found to be stable and reproducible (singular value: CCA = .21, PLS = .43, p < .001). Conclusion CCA and PLS identify different brain-behaviour relationships with limited stability and reproducibility when examining the relationship between cortical thickness and parent-reported behavioural measures. However, both methods identified relatively similar brain-behaviour relationships that were stable and reproducible when examining the relationship between cortical thickness and cognitive performance. The results of the current study suggest that stability and reproducibility of brain-behaviour relationships identified by CCA and PLS are influenced by characteristics of the analyzed sample and the included behavioural measurements when applied to a large pediatric dataset.
Collapse
Affiliation(s)
- Hajer Nakua
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Ju-Chi Yu
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Hervé Abdi
- The University of Texas at Dallas, Richardson, Texas, United States
| | - Colin Hawco
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Aristotle Voineskos
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Sean Hill
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Meng-Chuan Lai
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
- Program in Neurosciences and Mental Health, The Hospital for Sick Children, Ontario, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Anne L. Wheeler
- Program in Neurosciences and Mental Health, The Hospital for Sick Children, Ontario, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | | | - Stephanie H. Ameis
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| |
Collapse
|
15
|
Gill H, McIntyre RS, Hawco C, Rodrigues NB, Gill B, DiVincenzo JD, Lieberman JM, Marks CA, Cha DS, Lipsitz O, Nazal H, Jasrai A, Rosenblat JD, Mansur RB. Evaluating the neural substrates of effort-expenditure for reward in adults with major depressive disorder and obesity. Psychiatry Res Neuroimaging 2023; 329:111592. [PMID: 36708594 DOI: 10.1016/j.pscychresns.2023.111592] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 11/29/2022] [Accepted: 01/12/2023] [Indexed: 01/15/2023]
Abstract
Converging evidence has suggested that disturbances in monetary reward processing may subserve the shared biosignature between major depressive disorder (MDD) and obesity. However, there remains a paucity of studies that have evaluated the deficits in specific subcomponents of reward functioning in populations with MDD and obesity comorbidity. We evaluated the association between effort-expenditure for monetary reward and neural activation in regions associated with reward-based decision making (i.e., the caudate nucleus, anterior cingulate cortex (ACC) and hippocampus) in people with MDD and obesity comorbidity. We acquired structural and functional magnetic resonance imaging (fMRI) in 12 participants and performed a spherical region-of-interest analysis (ROI) using previously defined peak MNI coordinates. A one-sample t-test was employed to compare ROI-specific blood-oxygen-level-dependent (BOLD) signal change during the task choice selection window (i.e., high-effort vs. low-effort task) of the effort-expenditure for reward task (EEfRT). We observed no change in activation of the caudate nucleus, ACC or hippocampus in participants with increased BMI when contrasting the high effort > low effort reward magnitude condition for the EEfRT. The findings from our exploratory study evaluated the disturbances in fundamental reward processes, including cost-benefit decision making, in people MDD and obesity. Future studies should further investigate this relationship with a larger sample size.
Collapse
Affiliation(s)
- Hartej Gill
- Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Canadian Rapid Treatment Center of Excellence, Mississauga, ON, Canada; Brain and Cognition Discovery Foundation, Toronto, ON, Canada.
| | - Roger S McIntyre
- Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Canadian Rapid Treatment Center of Excellence, Mississauga, ON, Canada; Department of Pharmacology, University of Toronto, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Brain and Cognition Discovery Foundation, Toronto, ON, Canada
| | - Colin Hawco
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry & Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Nelson B Rodrigues
- Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada; Canadian Rapid Treatment Center of Excellence, Mississauga, ON, Canada
| | - Barjot Gill
- Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada
| | - Joshua D DiVincenzo
- Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada; Canadian Rapid Treatment Center of Excellence, Mississauga, ON, Canada; Department of Pharmacology, University of Toronto, Toronto, ON, Canada; Brain and Cognition Discovery Foundation, Toronto, ON, Canada
| | - Jonathan M Lieberman
- Royal Brisbane & Women's Hospital, Metro North Hospital and Health Service, Brisbane, QLD, Australia
| | - CéAnn A Marks
- Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada
| | - Danielle S Cha
- Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada; Canadian Rapid Treatment Center of Excellence, Mississauga, ON, Canada; Royal Brisbane & Women's Hospital, Metro North Hospital and Health Service, Brisbane, QLD, Australia
| | - Orly Lipsitz
- Canadian Rapid Treatment Center of Excellence, Mississauga, ON, Canada
| | - Hana Nazal
- Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada
| | - Ashitija Jasrai
- Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada
| | - Joshua D Rosenblat
- Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Canadian Rapid Treatment Center of Excellence, Mississauga, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Brain and Cognition Discovery Foundation, Toronto, ON, Canada
| | - Rodrigo B Mansur
- Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| |
Collapse
|
16
|
Poorganji M, Zomorrodi R, Zrenner C, Bansal A, Hawco C, Hill AT, Hadas I, Rajji TK, Chen R, Zrenner B, Voineskos D, Blumberger DM, Daskalakis ZJ. Pre-Stimulus Power but Not Phase Predicts Prefrontal Cortical Excitability in TMS-EEG. Biosensors (Basel) 2023; 13:220. [PMID: 36831986 PMCID: PMC9953459 DOI: 10.3390/bios13020220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 01/10/2023] [Accepted: 01/23/2023] [Indexed: 06/18/2023]
Abstract
The cortical response to transcranial magnetic stimulation (TMS) has notable inter-trial variability. One source of this variability can be the influence of the phase and power of pre-stimulus neuronal oscillations on single-trial TMS responses. Here, we investigate the effect of brain oscillatory activity on TMS response in 49 distinct healthy participants (64 datasets) who had received single-pulse TMS over the left dorsolateral prefrontal cortex. Across all frequency bands of theta (4-7 Hz), alpha (8-13 Hz), and beta (14-30 Hz), there was no significant effect of pre-TMS phase on single-trial cortical evoked activity. After high-powered oscillations, whether followed by a TMS pulse or not, the subsequent activity was larger than after low-powered oscillations. We further defined a measure, corrected_effect, to enable us to investigate brain responses to the TMS pulse disentangled from the power of ongoing (spontaneous) oscillations. The corrected_effect was significantly different from zero (meaningful added effect of TMS) only in theta and beta bands. Our results suggest that brain state prior to stimulation might play some role in shaping the subsequent TMS-EEG response. Specifically, our findings indicate that the power of ongoing oscillatory activity, but not phase, can influence brain responses to TMS. Aligning the TMS pulse with specific power thresholds of an EEG signal might therefore reduce variability in neurophysiological measurements and also has the potential to facilitate more robust therapeutic effects of stimulation.
Collapse
Affiliation(s)
- Mohsen Poorganji
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Reza Zomorrodi
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
| | - Christoph Zrenner
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
- Institute for Biomedical Engineering, University of Toronto, Toronto, ON M5S 3G9, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada
| | - Aiyush Bansal
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
| | - Colin Hawco
- Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada
| | - Aron T. Hill
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Melbourne, VIC 3125, Australia
| | - Itay Hadas
- Department of Psychiatry, School of Medicine, University of California San Diego, La Jolla, CA 92093-0603, USA
| | - Tarek K. Rajji
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON M5S 1A8, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada
- Toronto Dementia Research Alliance, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Robert Chen
- Institute of Medical Science, University of Toronto, Toronto, ON M5S 1A8, Canada
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON M5S 1A1, Canada
- Krembil Research Institute, University Health Network, Toronto, ON M5T 0S8, Canada
| | - Brigitte Zrenner
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada
| | - Daphne Voineskos
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON M5S 1A8, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada
- Krembil Research Institute, University Health Network, Toronto, ON M5T 0S8, Canada
| | - Daniel M. Blumberger
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON M5S 1A8, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada
| | - Zafiris J. Daskalakis
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON M5S 1A8, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada
- Department of Psychiatry, School of Medicine, University of California San Diego, La Jolla, CA 92093-0603, USA
| |
Collapse
|
17
|
Rashidi-Ranjbar N, Rajji TK, Hawco C, Kumar S, Herrmann N, Mah L, Flint AJ, Fischer CE, Butters MA, Pollock BG, Dickie EW, Bowie CR, Soffer M, Mulsant BH, Voineskos AN. Association of functional connectivity of the executive control network or default mode network with cognitive impairment in older adults with remitted major depressive disorder or mild cognitive impairment. Neuropsychopharmacology 2023; 48:468-477. [PMID: 35410366 PMCID: PMC9852291 DOI: 10.1038/s41386-022-01308-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 02/13/2022] [Accepted: 03/09/2022] [Indexed: 02/02/2023]
Abstract
Major depressive disorder (MDD) is associated with an increased risk of developing dementia. The present study aimed to better understand this risk by comparing resting state functional connectivity (rsFC) in the executive control network (ECN) and the default mode network (DMN) in older adults with MDD or mild cognitive impairment (MCI). Additionally, we examined the association between rsFC in the ECN or DMN and cognitive impairment transdiagnostically. We assessed rsFC alterations in ECN and DMN in 383 participants from five groups at-risk for dementia-remitted MDD with normal cognition (MDD-NC), non-amnestic mild cognitive impairment (naMCI), remitted MDD + naMCI, amnestic MCI (aMCI), and remitted MDD + aMCI-and from healthy controls (HC) or individuals with Alzheimer's dementia (AD). Subject-specific whole-brain functional connectivity maps were generated for each network and group differences in rsFC were calculated. We hypothesized that alteration of rsFC in the ECN and DMN would be progressively larger among our seven groups, ranked from low to high according to their risk for dementia as HC, MDD-NC, naMCI, MDD + naMCI, aMCI, MDD + aMCI, and AD. We also regressed scores of six cognitive domains (executive functioning, processing speed, language, visuospatial memory, verbal memory, and working memory) on the ECN and DMN connectivity maps. We found a significant alteration in the rsFC of the ECN, with post hoc testing showing differences between the AD group and the HC, MDD-NC, or naMCI groups, but no significant alterations in rsFC of the DMN. Alterations in rsFC of the ECN and DMN were significantly associated with several cognitive domain scores transdiagnostically. Our findings suggest that a diagnosis of remitted MDD may not confer functional brain risk for dementia. However, given the association of rs-FC with cognitive performance (i.e., transdiagnostically), rs-FC may help in stratifying this risk among people with MDD and varying degrees of cognitive impairment.
Collapse
Affiliation(s)
- Neda Rashidi-Ranjbar
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Tarek K Rajji
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Toronto Dementia Research Alliance, University of Toronto, Toronto, Canada
| | - Colin Hawco
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Sanjeev Kumar
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Nathan Herrmann
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Sunnybrook Health Sciences Centre, Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Linda Mah
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Baycrest Health Sciences, Rotman Research Institute, Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Alastair J Flint
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Centre for Mental Health, University Health Network, Toronto, ON, Canada
| | - Corinne E Fischer
- Keenan Research Centre for Biomedical Science, St. Michael's Hospital, Toronto, ON, Canada
| | - Meryl A Butters
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Bruce G Pollock
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Erin W Dickie
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Christopher R Bowie
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Departments of Psychology and Psychiatry (CRB), Queen's University, Kingston, ON, Canada
| | - Matan Soffer
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Benoit H Mulsant
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Aristotle N Voineskos
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada.
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
| |
Collapse
|
18
|
Hawco C, Steeves JKE, Voineskos AN, Blumberger DM, Daskalakis ZJ. Within-subject reliability of concurrent TMS-fMRI during a single session. Psychophysiology 2023:e14252. [PMID: 36694109 DOI: 10.1111/psyp.14252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 11/03/2022] [Accepted: 12/06/2022] [Indexed: 01/26/2023]
Abstract
Concurrent transcranial magnetic stimulation with functional MRI (concurrent TMS-fMRI) allows real-time causative probing of brain connectivity. However, technical challenges, safety, and tolerability may limit the number of trials employed during a concurrent TMS-fMRI experiment. We leveraged an existing data set with 100 trials of active TMS compared to a sub-threshold control condition to assess the reliability of the evoked BOLD response during concurrent TMS-fMRI. This data will permit an analysis of the minimum number of trials that should be employed in a concurrent TMS-fMRI protocol in order to achieve reliable spatial changes in activity. Single-subject maps of brain activity were created by splitting the trials within the same experimental session into groups of 50, 40, 30, 25, 20, 15, or 10 trials, correlations (R) between t-maps derived from paired subsets of trials within the same individual were calculated as reliability. R was moderate-high for 50 trials (mean R = .695) and decreased as the number of trials decreased. Consistent with previous findings of high individual variability in the spatial patterns of evoked neuronal changes following a TMS pulse, the spatial pattern of Rs differed across participants, but regional R was correlated with the magnitude of TMS-evoked activity. These results demonstrate concurrent TMS-fMRI produces a reliable pattern of activity at the individual level at higher trial numbers, particularly within localized regions. The spatial pattern of reliability is individually idiosyncratic and related to the individual pattern of evoked changes.
Collapse
Affiliation(s)
- Colin Hawco
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Jennifer K E Steeves
- Centre for Vision Research and Department of Psychology, York University, Toronto, Ontario, Canada
| | - Aristotle N Voineskos
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Daniel M Blumberger
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.,Temerty Centre for Therapeutic Brain Intervention, Toronto, Ontario, Canada
| | - Zafiris J Daskalakis
- Temerty Centre for Therapeutic Brain Intervention, Toronto, Ontario, Canada.,Department of Psychiatry, University of California, San Diego, California, USA
| |
Collapse
|
19
|
Abstract
BACKGROUND Our understanding of major depression is complicated by substantial heterogeneity in disease presentation, which can be disentangled by data-driven analyses of depressive symptom dimensions. We aimed to determine the clinical portrait of such symptom dimensions among individuals in the community. METHODS This cross-sectional study consisted of 25 261 self-reported White UK Biobank participants with major depression. Nine questions from the UK Biobank Mental Health Questionnaire encompassing depressive symptoms were decomposed into underlying factors or 'symptom dimensions' via factor analysis, which were then tested for association with psychiatric diagnoses and polygenic risk scores for major depressive disorder (MDD), bipolar disorder and schizophrenia. Replication was performed among 655 self-reported non-White participants, across sexes, and among 7190 individuals with an ICD-10 code for MDD from linked inpatient or primary care records. RESULTS Four broad symptom dimensions were identified, encompassing negative cognition, functional impairment, insomnia and atypical symptoms. These dimensions replicated across ancestries, sexes and individuals with inpatient or primary care MDD diagnoses, and were also consistent among 43 090 self-reported White participants with undiagnosed self-reported depression. Every dimension was associated with increased risk of nearly every psychiatric diagnosis and polygenic risk score. However, while certain psychiatric diagnoses were disproportionately associated with specific symptom dimensions, the three polygenic risk scores did not show the same specificity of associations. CONCLUSIONS An analysis of questionnaire data from a large community-based cohort reveals four replicable symptom dimensions of depression with distinct clinical, but not genetic, correlates.
Collapse
Affiliation(s)
- Michael Wainberg
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Peter Zhukovsky
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Sean L Hill
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, Canada
- Department of Physiology, University of Toronto, Toronto, Canada
| | - Daniel Felsky
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, Canada
| | - Aristotle Voineskos
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, Canada
| | - Sidney Kennedy
- Department of Psychiatry, University of Toronto, Toronto, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, Canada
- Krembil Research Institute, University Health Network, Toronto, Canada
- Li Ka Shing Knowledge Institute, Saint Michael's Hospital, Toronto, Canada
| | - Colin Hawco
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, Canada
| | - Shreejoy J Tripathy
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, Canada
- Department of Physiology, University of Toronto, Toronto, Canada
| |
Collapse
|
20
|
Gallucci J, Pomarol-Clotet E, Voineskos AN, Guerrero-Pedraza A, Alonso-Lana S, Vieta E, Salvador R, Hawco C. Longer illness duration is associated with greater individual variability in functional brain activity in Schizophrenia, but not bipolar disorder. Neuroimage Clin 2022; 36:103269. [PMID: 36451371 PMCID: PMC9723315 DOI: 10.1016/j.nicl.2022.103269] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 10/24/2022] [Accepted: 11/14/2022] [Indexed: 11/16/2022]
Abstract
BACKGROUND Individuals with schizophrenia exhibit greater inter-patient variability in functional brain activity during neurocognitive task performance. Some studies have shown associations of age and illness duration with brain function; however, the association of these variables with variability in brain function activity is not known. In order to better understand the progressive effects of age and illness duration across disorders, we examined the relationship with individual variability in brain activity. METHODS Neuroimaging and behavioural data were extracted from harmonized datasets collectively including 212 control participants, 107 individuals with bipolar disorder, and 232 individuals with schizophrenia (total n = 551). Functional activity in response to an N-back working memory task (2-back vs 1-back) was examined. Individual variability was quantified via the correlational distance of fMRI activity between participants; mean correlational distance of one participant in relation to all others was defined as a 'variability score'. RESULTS Greater individual variability was found in the schizophrenia group compared to the bipolar disorder and control groups (p = 1.52e-09). Individual variability was significantly associated with aging (p = 0.027), however, this relationship was not different across diagnostic groups. In contrast, in the schizophrenia sample only, a longer illness duration was associated with increased variability (p = 0.027). CONCLUSION An increase in variability was observed in the schizophrenia group related to illness duration, beyond the effects of normal aging, implying illness-related deterioration of cognitive networks. This has clinical implications for considering long-term trajectories in schizophrenia and progressive neural and cognitive decline which may be amiable to novel treatments.
Collapse
Affiliation(s)
- Julia Gallucci
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada,Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Catalonia, Spain,Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Catalonia, Spain
| | - Aristotle N. Voineskos
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Amalia Guerrero-Pedraza
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Catalonia, Spain,Benito Menni Complex Assistencial en Salut Mental, Barcelona, Catalonia, Spain
| | - Silvia Alonso-Lana
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Catalonia, Spain,Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Catalonia, Spain,Research Centre and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades – Universitat Internacional de Catalunya (UIC), Barcelona, Spain
| | - Eduard Vieta
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Catalonia, Spain,Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Hospital Clinic, University of Barcelona, IDIBAPS, Barcelona, Catalonia, Spain
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Catalonia, Spain,Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Catalonia, Spain
| | - Colin Hawco
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada,Corresponding authors at: Centre for Addiction and Mental Health, 250 College Street, Toronto, ON, Spain.
| |
Collapse
|
21
|
Gallucci J, Tan T, Schifani C, Dickie EW, Voineskos AN, Hawco C. Greater individual variability in functional brain activity during working memory performance in Schizophrenia Spectrum Disorders (SSD). Schizophr Res 2022; 248:21-31. [PMID: 35908378 DOI: 10.1016/j.schres.2022.07.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 06/14/2022] [Accepted: 07/17/2022] [Indexed: 10/16/2022]
Abstract
Heterogeneity has been a persistent challenge in understanding Schizophrenia Spectrum Disorders (SSD). Traditional case-control comparisons often show variable results, and may not map well onto individuals. To better understand heterogeneity and group differences in SSD compared to typically developing controls (TDC), we examined variability in functional brain activity during a working memory (WM) task with known deficits in SSD. Neuroimaging and behavioural data were extracted from two datasets collectively providing 34 TDC and 56 individuals with SSD (n = 90). Functional activity in response to an N-Back WM task (3-Back vs 1-Back) was examined between and within groups. Individual variability was calculated via the correlational distance of fMRI activity maps between participants; mean correlational distance from one participant to all others was defined as a 'variability score'. Greater individual variability in functional activity was found in SSD compared to TDC (p = 0.00090). At the group level, a case-control comparison suggested SSD had reduced activity in task positive and task negative networks. However, when SSD were divided into high and low variability subgroups, the low variability groups showed no differences relative to TDC while the high variability group showed little activity at the group level. Our results imply prior case-control differences may be driven by a subgroup of SSD who do not show specific impairments but instead show more 'idiosyncratic' activity patterns. In SSD but not TDC, variability was also related to cognitive performance and age. This novel approach focusing on individual variability has important implications for understanding the neurobiology of SSD.
Collapse
Affiliation(s)
- Julia Gallucci
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Thomas Tan
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Christin Schifani
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Erin W Dickie
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Aristotle N Voineskos
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Colin Hawco
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
| |
Collapse
|
22
|
Calarco N, Cassidy CM, Selby B, Hawco C, Voineskos AN, Diniz BS, Nikolova YS. Associations between locus coeruleus integrity and diagnosis, age, and cognitive performance in older adults with and without late-life depression: An exploratory study. Neuroimage Clin 2022; 36:103182. [PMID: 36088841 PMCID: PMC9474922 DOI: 10.1016/j.nicl.2022.103182] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2022] [Revised: 08/31/2022] [Accepted: 09/01/2022] [Indexed: 12/14/2022]
Abstract
Late-life depression (LLD) is a risk factor for age-dependent cognitive deterioration. Norepinephrine-related degeneration in the locus coeruleus (LC) may explain this link. To examine the LC norepinephrine system in vivo, we acquired neuromelanin-sensitive MRI (NM-MRI) in a sample of 48 participants, including 25 with LLD (18 women, age 68.08 ± 5.41) and 23 never-depressed comparison participants (ND, 12 women, age 70 ± 8.02), matched on age and cognitive status. We employed a semi-automated procedure to segment the LC into three bilateral sections along its rostro-caudal extent, and calculated relative contrast as a proxy of integrity. Then, we examined associations between integrity and LLD diagnosis, age, and cognition, as measured via the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and the Delis-Kaplan Executive Function System (D-KEFS). We did not identify an effect of LLD diagnosis nor age on LC integrity, but exploratory canonical correlation analysis across the combined participant sample revealed a strong (Rc = 0.853) and significant multivariate relationship between integrity and cognition (Wilks' λ = 0.03, F(84, 162.44) = 1.66, p = <.01). The first and only significant variate explained 72.83% model variance, and linked better attention and delayed memory performance, faster processing speed, and lower verbal fluency performance with higher integrity in the right rostral but lower integrity in the left caudal LC. Our results complement prior evidence of LC involvement in cognition in healthy older adults, and extend this association to individuals with LLD.
Collapse
Affiliation(s)
- Navona Calarco
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
| | - Clifford M. Cassidy
- The University of Ottawa Institute of Mental Health Research at the Royal, Ottawa, ON, Canada
| | - Ben Selby
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
| | - Colin Hawco
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
| | - Aristotle N. Voineskos
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Breno S. Diniz
- UConn Center on Aging, University of Connecticut Health Center, Farmington, CT, USA,Department of Psychiatry, School of Medicine, University of Connecticut, Farmington, CT, USA
| | - Yuliya S. Nikolova
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada,Department of Psychiatry, University of Toronto, Toronto, ON, Canada,Corresponding author at: Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health (CAMH), 250 College Street, Toronto, ON M5T 1L8, Canada.
| |
Collapse
|
23
|
Hawco C, Dickie EW, Herman G, Turner JA, Argyelan M, Malhotra AK, Buchanan RW, Voineskos AN. A longitudinal multi-scanner multimodal human neuroimaging dataset. Sci Data 2022; 9:332. [PMID: 35701471 PMCID: PMC9198098 DOI: 10.1038/s41597-022-01386-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Accepted: 05/12/2022] [Indexed: 11/09/2022] Open
Abstract
Human neuroimaging has led to an overwhelming amount of research into brain function in healthy and clinical populations. However, a better appreciation of the limitations of small sample studies has led to an increased number of multi-site, multi-scanner protocols to understand human brain function. As part of a multi-site project examining social cognition in schizophrenia, a group of "travelling human phantoms" had structural T1, diffusion, and resting-state functional MRIs obtained annually at each of three sites. Scan protocols were carefully harmonized across sites prior to the study. Due to scanner upgrades at each site (all sites acquired PRISMA MRIs during the study) and one participant being replaced, the end result was 30 MRI scans across 4 people, 6 MRIs, and 4 years. This dataset includes multiple neuroimaging modalities and repeated scans across six MRIs. It can be used to evaluate differences across scanners, consistency of pipeline outputs, or test multi-scanner harmonization approaches.
Collapse
Affiliation(s)
- Colin Hawco
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada. .,Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
| | - Erin W Dickie
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Gabrielle Herman
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Jessica A Turner
- Department of Psychology & Neuroscience Institute, Georgia State University, Atlanta, GA, United States
| | - Miklos Argyelan
- The Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, United States
| | - Anil K Malhotra
- The Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, United States
| | - Robert W Buchanan
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Aristotle N Voineskos
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| |
Collapse
|
24
|
Nakua H, Hawco C, Forde NJ, Jacobs GR, Joseph M, Voineskos AN, Wheeler AL, Lai MC, Szatmari P, Kelley E, Liu X, Georgiades S, Nicolson R, Schachar R, Crosbie J, Anagnostou E, Lerch JP, Arnold PD, Ameis SH. Cortico-amygdalar connectivity and externalizing/internalizing behavior in children with neurodevelopmental disorders. Brain Struct Funct 2022; 227:1963-1979. [PMID: 35469103 PMCID: PMC9232404 DOI: 10.1007/s00429-022-02483-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Accepted: 03/15/2022] [Indexed: 12/31/2022]
Abstract
Background Externalizing and internalizing behaviors contribute to clinical impairment in children with neurodevelopmental disorders (NDDs). Although associations between externalizing or internalizing behaviors and cortico-amygdalar connectivity have been found in clinical and non-clinical pediatric samples, no previous study has examined whether similar shared associations are present across children with different NDDs. Methods Multi-modal neuroimaging and behavioral data from the Province of Ontario Neurodevelopmental Disorders (POND) Network were used. POND participants aged 6–18 years with a primary diagnosis of autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD) or obsessive–compulsive disorder (OCD), as well as typically developing children (TDC) with T1-weighted, resting-state fMRI or diffusion weighted imaging (DWI) and parent-report Child Behavioral Checklist (CBCL) data available, were analyzed (total n = 346). Associations between externalizing or internalizing behavior and cortico-amygdalar structural and functional connectivity indices were examined using linear regressions, controlling for age, gender, and image-modality specific covariates. Behavior-by-diagnosis interaction effects were also examined. Results No significant linear associations (or diagnosis-by-behavior interaction effects) were found between CBCL-measured externalizing or internalizing behaviors and any of the connectivity indices examined. Post-hoc bootstrapping analyses indicated stability and reliability of these null results. Conclusions The current study provides evidence towards an absence of a shared linear relationship between internalizing or externalizing behaviors and cortico-amygdalar connectivity properties across a transdiagnostic sample of children with different primary NDD diagnoses and TDC. Different methodological approaches, including incorporation of multi-dimensional behavioral data (e.g., task-based fMRI) or clustering approaches may be needed to clarify complex brain-behavior relationships relevant to externalizing/internalizing behaviors in heterogeneous clinical NDD populations. Supplementary Information The online version contains supplementary material available at 10.1007/s00429-022-02483-0.
Collapse
Affiliation(s)
- Hajer Nakua
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, 80 Workman Way, Toronto, ON, M6J 1H4, Canada
- Institute of Medical Science, University of Toronto, Toronto, Canada
| | - Colin Hawco
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, 80 Workman Way, Toronto, ON, M6J 1H4, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Natalie J Forde
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, 80 Workman Way, Toronto, ON, M6J 1H4, Canada
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Grace R Jacobs
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, 80 Workman Way, Toronto, ON, M6J 1H4, Canada
- Institute of Medical Science, University of Toronto, Toronto, Canada
| | - Michael Joseph
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, 80 Workman Way, Toronto, ON, M6J 1H4, Canada
| | - Aristotle N Voineskos
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, 80 Workman Way, Toronto, ON, M6J 1H4, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Anne L Wheeler
- Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Physiology, University of Toronto, Toronto, ON, Canada
| | - Meng-Chuan Lai
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, 80 Workman Way, Toronto, ON, M6J 1H4, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, ON, Canada
| | - Peter Szatmari
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, 80 Workman Way, Toronto, ON, M6J 1H4, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, ON, Canada
| | - Elizabeth Kelley
- Department of Psychology, Department of Psychiatry, Queens University, Kingston, ON, Canada
| | - Xudong Liu
- Department of Psychology, Department of Psychiatry, Queens University, Kingston, ON, Canada
| | | | - Rob Nicolson
- Department of Psychiatry, University of Western Ontario, London, ON, Canada
| | - Russell Schachar
- Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, ON, Canada
- Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada
| | - Jennifer Crosbie
- Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, ON, Canada
- Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada
| | - Evdokia Anagnostou
- Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON, Canada
- Department of Pediatrics, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Jason P Lerch
- Mouse Imaging Centre, Hospital for Sick Children, Toronto, ON, Canada
- Department of Medical Biophysics, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Paul D Arnold
- The Mathison Centre for Mental Health Research and Education, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Departments of Psychiatry and Medical Genetics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Stephanie H Ameis
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, 80 Workman Way, Toronto, ON, M6J 1H4, Canada.
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
- Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, ON, Canada.
| |
Collapse
|
25
|
Oliver LD, Hawco C, Viviano JD, Voineskos AN. From the Group to the Individual in Schizophrenia Spectrum Disorders: Biomarkers of Social Cognitive Impairments and Therapeutic Translation. Biol Psychiatry 2022; 91:699-708. [PMID: 34799097 DOI: 10.1016/j.biopsych.2021.09.007] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Revised: 08/11/2021] [Accepted: 09/11/2021] [Indexed: 12/23/2022]
Abstract
People with schizophrenia spectrum disorders (SSDs) often experience persistent social cognitive impairments, associated with poor functional outcome. There are currently no approved treatment options for these debilitating symptoms, highlighting the need for novel therapeutic strategies. Work to date has elucidated differential social processes and underlying neural circuitry affected in SSDs, which may be amenable to modulation using neurostimulation. Further, advances in functional connectivity mapping and electric field modeling may be used to identify individualized treatment targets to maximize the impact of brain stimulation on social cognitive networks. Here, we review literature supporting a roadmap for translating functional connectivity biomarker discovery to individualized treatment development for social cognitive impairments in SSDs. First, we outline the relevance of social cognitive impairments in SSDs. We review machine learning approaches for dimensional brain-behavior biomarker discovery, emphasizing the importance of individual differences. We synthesize research showing that brain stimulation techniques, such as repetitive transcranial magnetic stimulation, can be used to target relevant networks. Further, functional connectivity-based individualized targeting may enhance treatment response. We then outline recent approaches to account for neuroanatomical variability and optimize coil positioning to individually maximize target engagement. Overall, the synthesized literature provides support for the utility and feasibility of this translational approach to precision treatment. The proposed roadmap to translate biomarkers of social cognitive impairments to individualized treatment is currently under evaluation in precision-guided trials. Such a translational approach may also be applicable across conditions and generalizable for the development of individualized neurostimulation targeting other behavioral deficits.
Collapse
Affiliation(s)
- Lindsay D Oliver
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Colin Hawco
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Joseph D Viviano
- Mila-Quebec Artificial Intelligence Institute, Montreal, Quebec, Canada
| | - Aristotle N Voineskos
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.
| |
Collapse
|
26
|
Poorganji M, Zomorrodi R, Hawco C, Hill AT, Hadas I, Rajji TK, Chen R, Voineskos D, Daskalakis AA, Blumberger DM, Daskalakis ZJ. Differentiating transcranial magnetic stimulation cortical and auditory responses via single pulse and paired pulse protocols: A TMS-EEG study. Clin Neurophysiol 2021; 132:1850-1858. [PMID: 34147010 DOI: 10.1016/j.clinph.2021.05.009] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 04/26/2021] [Accepted: 05/04/2021] [Indexed: 01/08/2023]
Abstract
OBJECTIVE We measured the neurophysiological responses of both active and sham transcranial magnetic stimulation (TMS) for both single pulse (SP) and paired pulse (PP; long interval cortical inhibition (LICI)) paradigms using TMS-EEG (electroencephalography). METHODS Nineteen healthy subjects received active and sham (coil 90° tilted and touching the scalp) SP and PP TMS over the left dorsolateral prefrontal cortex (DLPFC). We measured excitability through SP TMS and inhibition (i.e., cortical inhibition (CI)) through PP TMS. RESULTS Cortical excitability indexed by area under the curve (AUC(25-275ms)) was significantly higher in the active compared to sham stimulation (F(1,18) = 43.737, p < 0.001, η2 = 0.708). Moreover, the amplitude of N100-P200 complex was significantly larger (F(1,18) = 9.118, p < 0.01, η2 = 0.336) with active stimulation (10.38 ± 9.576 µV) compared to sham (4.295 ± 2.323 µV). Significant interaction effects were also observed between active and sham stimulation for both the SP and PP (i.e., LICI) cortical responses. Finally, only active stimulation (CI = 0.64 ± 0.23, p < 0.001) resulted in significant cortical inhibition. CONCLUSION The significant differences between active and sham stimulation in both excitatory and inhibitory neurophysiological responses showed that active stimulation elicits responses from the cortex that are different from the non-specific effects of sham stimulation. SIGNIFICANCE Our study reaffirms that TMS-EEG represents an effective tool to evaluate cortical neurophysiology with high fidelity.
Collapse
Affiliation(s)
- Mohsen Poorganji
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Reza Zomorrodi
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Colin Hawco
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Aron T Hill
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada; Cognitive Neuroscience Unit, School of Psychology, Deakin University, Melbourne, Victoria, Australia
| | - Itay Hadas
- Department of Psychiatry, Faculty of Health, University of California San Diego, La Jolla, CA, USA
| | - Tarek K Rajji
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Robert Chen
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Krembil Neuroscience Centre, University Health Network, Toronto, Ontario, Canada; Division of Neurology, Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Daphne Voineskos
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Anastasios A Daskalakis
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Daniel M Blumberger
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Zafiris J Daskalakis
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Department of Psychiatry, Faculty of Health, University of California San Diego, La Jolla, CA, USA.
| |
Collapse
|
27
|
Mareckova K, Hawco C, Santos FCD, Bakht A, Calarco N, Miles AE, Voineskos AN, Sibille E, Hariri AR, Nikolova YS. Correction: Novel polygenic risk score as a translational tool linking depression-related changes in the corticolimbic transcriptome with neural face processing and anhedonic symptoms. Transl Psychiatry 2021; 11:152. [PMID: 33654052 PMCID: PMC7925572 DOI: 10.1038/s41398-021-01277-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
A Correction to this paper has been published: https://doi.org/10.1038/s41398-021-01277-y
Collapse
Affiliation(s)
- Klara Mareckova
- grid.155956.b0000 0000 8793 5925Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, ON Canada
| | - Colin Hawco
- grid.155956.b0000 0000 8793 5925Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, ON Canada
| | - Fernanda C. Dos Santos
- grid.155956.b0000 0000 8793 5925Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, ON Canada
| | - Arin Bakht
- grid.155956.b0000 0000 8793 5925Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, ON Canada
| | - Navona Calarco
- grid.155956.b0000 0000 8793 5925Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, ON Canada
| | - Amy E. Miles
- grid.155956.b0000 0000 8793 5925Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, ON Canada
| | - Aristotle N. Voineskos
- grid.155956.b0000 0000 8793 5925Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Psychiatry, University of Toronto, Toronto, ON Canada
| | - Etienne Sibille
- grid.155956.b0000 0000 8793 5925Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Psychiatry, University of Toronto, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON Canada
| | - Ahmad R. Hariri
- grid.26009.3d0000 0004 1936 7961Laboratory of NeuroGenetics, Department of Psychology and Neuroscience, Duke University, Durham, NC 27708 USA
| | - Yuliya S. Nikolova
- grid.155956.b0000 0000 8793 5925Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Psychiatry, University of Toronto, Toronto, ON Canada
| |
Collapse
|
28
|
Hawco C, Dickie EW, Jacobs G, Daskalakis ZJ, Voineskos AN. Moving beyond the mean: Subgroups and dimensions of brain activity and cognitive performance across domains. Neuroimage 2021; 231:117823. [PMID: 33549760 DOI: 10.1016/j.neuroimage.2021.117823] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Revised: 01/29/2021] [Accepted: 01/31/2021] [Indexed: 01/08/2023] Open
Abstract
Human neuroimaging during cognitive tasks has provided unique and important insights into the neurobiology of cognition. However, the vast majority of research relies on group aggregate or average statistical maps of activity, which do not fully capture the rich intersubject variability in brain function. In order to fully understand the neurobiology of cognitive processes, it is necessary to explore the range of variability in activation patterns across individuals. To better characterize individual variability, hierarchical clustering was performed separately on six fMRI tasks in 822 participants from the Human Connectome Project. Across all tasks, clusters ranged from a predominantly 'deactivating' pattern towards a more 'activating' pattern of brain activity, with significant differences in out-of-scanner cognitive test scores between clusters. Cluster stability was assessed via a resampling approach; a cluster probability matrix was generated, as the probability of any pair of participants clustering together when both were present in a random subsample. Rather than forming distinct clusters, participants fell along a spectrum or into pseudo-clusters without clear boundaries. A principal components analysis of the cluster probability matrix revealed three components explaining over 90% of the variance in clustering. Plotting participants in this lower-dimensional 'similarity space' revealed manifolds of variations along an S 'snake' shaped spectrum or a folded circle or 'tortilla' shape. The 'snake' shape was present in tasks where individual variability related to activity along covarying networks, while the 'tortilla' shape represented multiple networks which varied independently.
Collapse
Affiliation(s)
- Colin Hawco
- Centre for Addiction and Mental Health, Campbell Family Mental Health Institute, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
| | - Erin W Dickie
- Centre for Addiction and Mental Health, Campbell Family Mental Health Institute, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Grace Jacobs
- Centre for Addiction and Mental Health, Campbell Family Mental Health Institute, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, ON, Canada
| | - Zafiris J Daskalakis
- Centre for Addiction and Mental Health, Campbell Family Mental Health Institute, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Aristotle N Voineskos
- Centre for Addiction and Mental Health, Campbell Family Mental Health Institute, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
| |
Collapse
|
29
|
Kolla NJ, Smaragdi A, Gainham G, Karas KH, Hawco C, Haas J, Skilling TA, Walsh M, Augimeri L. Psychosocial Intervention for Youth With High Externalizing Behaviors and Aggression Is Associated With Improvement in Impulsivity and Brain Gray Matter Volume Changes. Front Psychiatry 2021; 12:788240. [PMID: 35087430 PMCID: PMC8788585 DOI: 10.3389/fpsyt.2021.788240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 11/24/2021] [Indexed: 11/19/2022] Open
Abstract
Background: Stop, Now And Plan (SNAP) is a cognitive behavioral-based psychosocial intervention that has a strong evidence base for treating youth with high aggression and externalizing behaviors, many of whom have disruptive behavior disorders. In a pre-post design, we tested whether SNAP could improve externalizing behaviors, assessed by the parent-rated Child Behavior Checklist (CBCL) and also improve behavioral measures of impulsivity in children with high aggression and impulsivity. We then investigated whether any improvement in externalizing behavior or impulsivity was associated with gray matter volume (GMV) changes assessed using structural magnetic resonance imaging (sMRI). We also recruited typically developing youth who were assessed twice without undergoing the SNAP intervention. Methods: Ten children who were participating in SNAP treatment completed the entire study protocol. CBCL measures, behavioral measures of impulsivity, and sMRI scanning was conducted pre-SNAP and then 13 weeks later post-SNAP. Twelve healthy controls also completed the study; they were rated on the CBCL, performed the same behavioral measure of impulsivity, and underwent sMRI twice, separated by 13 weeks. They did not receive the SNAP intervention. Result: At baseline, SNAP participants had higher CBCL scores and performed worse on the impulsivity task compared with the healthy controls. At the second visit, SNAP participants still had higher scores on the CBCL compared with normally-developing controls, but their performance on the impulsivity task had improved to the point where their results were indistinguishable from the healthy controls. Structural magnetic resonance imaging in the SNAP participants further revealed that improvements in impulsivity were associated with GMV changes in the frontotemporal region. Conclusion: These results suggest that SNAP led to improvement in behavioral measures of impulsivity in a cohort of boys with high externalizing behavior. Improvement in impulsivity was also associated with increased GMV changes. The mechanism behind these brain changes is unknown but could relate to cognitive behavioral therapy and contingency management interventions, important components of SNAP, that target frontotemporal brain regions. Clinically, this study offers new evidence for the potential targeting of brain regions by non-invasive modalities, such as repetitive transcranial magnetic stimulation, to improve externalizing behavior and impulsivity.
Collapse
Affiliation(s)
- Nathan J Kolla
- Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada.,Violence Prevention Neurobiological Research Unit, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Waypoint Centre for Mental Health Care, Penetanguishene, ON, Canada.,Waypoint/University of Toronto Chair in Forensic Mental Health Science, Penetanguishene, ON, Canada
| | | | | | | | - Colin Hawco
- Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | | | - Tracey A Skilling
- Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | | | | |
Collapse
|
30
|
Oliver LD, Hawco C, Homan P, Lee J, Green MF, Gold JM, DeRosse P, Argyelan M, Malhotra AK, Buchanan RW, Voineskos AN. Social Cognitive Networks and Social Cognitive Performance Across Individuals With Schizophrenia Spectrum Disorders and Healthy Control Participants. Biol Psychiatry Cogn Neurosci Neuroimaging 2020; 6:1202-1214. [PMID: 33579663 DOI: 10.1016/j.bpsc.2020.11.014] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 11/17/2020] [Accepted: 11/30/2020] [Indexed: 11/24/2022]
Abstract
BACKGROUND Schizophrenia spectrum disorders (SSDs) feature social cognitive deficits, although their neural basis remains unclear. Social cognitive performance may relate to neural circuit activation patterns more than to diagnosis, which would have important prognostic and therapeutic implications. The current study aimed to determine how functional connectivity within and between social cognitive networks relates to social cognitive performance across individuals with SSDs and healthy control participants. METHODS Participants with SSDs (n = 164) and healthy control participants (n = 117) completed the Empathic Accuracy task during functional magnetic resonance imaging as well as lower-level (e.g., emotion recognition) and higher-level (e.g., theory of mind) social cognitive measures outside the scanner. Functional connectivity during the Empathic Accuracy task was analyzed using background connectivity and graph theory. Data-driven social cognitive networks were identified across participants. Regression analyses were used to examine network connectivity-performance relationships across individuals. Positive and negative within- and between-network connectivity strengths were also compared in poor versus good social cognitive performers and in SSD versus control groups. RESULTS Three social cognitive networks were identified: motor resonance, affect sharing, and mentalizing. Regression and group-based analyses demonstrated reduced between-network negative connectivity, or segregation, and greater within- and between-network positive connectivity in worse social cognitive performers. There were no significant effects of diagnostic group on within- or between-network connectivity. CONCLUSIONS These findings suggest that the neural circuitry of social cognitive performance may exist dimensionally. Across participants, better social cognitive performance was associated with greater segregation between social cognitive networks, whereas poor versus good performers may compensate via hyperconnectivity within and between social cognitive networks.
Collapse
Affiliation(s)
- Lindsay D Oliver
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Colin Hawco
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Philipp Homan
- University Hospital of Psychiatry, University of Zurich, Zurich, Switzerland; Division of Psychiatry Research, Zucker Hillside Hospital, Division of Northwell Health, Glen Oaks, New York; Department of Psychiatry, The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York; Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, New York
| | - Junghee Lee
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles; Department of Veterans Affairs, Desert Pacific Mental Illness Research, Education, and Clinical Center, Los Angeles, California; Department of Psychiatry and Behavioral Neurobiology, School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
| | - Michael F Green
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles; Department of Veterans Affairs, Desert Pacific Mental Illness Research, Education, and Clinical Center, Los Angeles, California
| | - James M Gold
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Pamela DeRosse
- Division of Psychiatry Research, Zucker Hillside Hospital, Division of Northwell Health, Glen Oaks, New York; Department of Psychiatry, The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York; Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, New York
| | - Miklos Argyelan
- Division of Psychiatry Research, Zucker Hillside Hospital, Division of Northwell Health, Glen Oaks, New York; Department of Psychiatry, The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York; Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, New York
| | - Anil K Malhotra
- Division of Psychiatry Research, Zucker Hillside Hospital, Division of Northwell Health, Glen Oaks, New York; Department of Psychiatry, The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York; Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, New York
| | - Robert W Buchanan
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Aristotle N Voineskos
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.
| | | |
Collapse
|
31
|
Voineskos AN, Blumberger DM, Schifani C, Hawco C, Dickie EW, Rajji TK, Mulsant BH, Foussias G, Wang W, Daskalakis ZJ. Effects of Repetitive Transcranial Magnetic Stimulation on Working Memory Performance and Brain Structure in People With Schizophrenia Spectrum Disorders: A Double-Blind, Randomized, Sham-Controlled Trial. Biol Psychiatry Cogn Neurosci Neuroimaging 2020; 6:449-458. [PMID: 33551284 DOI: 10.1016/j.bpsc.2020.11.011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 11/09/2020] [Accepted: 11/23/2020] [Indexed: 01/04/2023]
Abstract
BACKGROUND There are currently no approved treatments for working memory deficits in schizophrenia spectrum disorders (SSDs). The objective of the present study was to assess whether repetitive transcranial magnetic stimulation (rTMS) to the bilateral dorsolateral prefrontal cortex (DLPFC) in people with SSDs 1) improves working memory deficits and 2) changes brain structure. METHODS We conducted a double-blind, parallel, randomized, sham-controlled study at the Centre for Addiction and Mental Health in Toronto, Canada. We randomized 83 participants with SSDs to receive either active 20 Hz rTMS applied to the bilateral DLPFC or sham rTMS for 4 weeks. The participants also completed pre/posttreatment magnetic resonance imaging. Clinical and cognitive assessments were performed at baseline, treatment end, and 1 month later. The primary outcome was change in verbal n-back working memory performance accuracy (d-prime). The secondary outcome measures were change in DLPFC thickness and fractional anisotropy of white matter tracts connecting to the DLPFC. Prespecified exploratory outcome measures were changes in general cognition; positive, negative, and depressive symptoms. RESULTS Compared with sham treatment, active rTMS did not lead to significant change in working memory performance; it was associated with an increase in right DLPFC thickness but not fractional anisotropy. Prespecified exploratory analysis showed a significant decrease in depressive symptoms in the active group; the decrease in depressive symptoms was correlated with an increase in right DLPFC thickness. CONCLUSIONS Although rTMS applied to the bilateral DLPFC was not efficacious in treating working memory deficits in SSDs, it did increase right DLPFC thickness and decrease depressive symptoms. These findings deserve further study given the lack of efficacy of antidepressant medications in SSDs.
Collapse
Affiliation(s)
- Aristotle N Voineskos
- Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.
| | - Daniel M Blumberger
- Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Christin Schifani
- Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Colin Hawco
- Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Erin W Dickie
- Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Tarek K Rajji
- Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Benoit H Mulsant
- Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - George Foussias
- Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Wei Wang
- Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Zafiris J Daskalakis
- Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Department of Psychiatry, University of California San Diego School of Medicine, La Jolla, California
| |
Collapse
|
32
|
Botvinik-Nezer R, Holzmeister F, Camerer CF, Dreber A, Huber J, Johannesson M, Kirchler M, Iwanir R, Mumford JA, Adcock RA, Avesani P, Baczkowski BM, Bajracharya A, Bakst L, Ball S, Barilari M, Bault N, Beaton D, Beitner J, Benoit RG, Berkers RMWJ, Bhanji JP, Biswal BB, Bobadilla-Suarez S, Bortolini T, Bottenhorn KL, Bowring A, Braem S, Brooks HR, Brudner EG, Calderon CB, Camilleri JA, Castrellon JJ, Cecchetti L, Cieslik EC, Cole ZJ, Collignon O, Cox RW, Cunningham WA, Czoschke S, Dadi K, Davis CP, Luca AD, Delgado MR, Demetriou L, Dennison JB, Di X, Dickie EW, Dobryakova E, Donnat CL, Dukart J, Duncan NW, Durnez J, Eed A, Eickhoff SB, Erhart A, Fontanesi L, Fricke GM, Fu S, Galván A, Gau R, Genon S, Glatard T, Glerean E, Goeman JJ, Golowin SAE, González-García C, Gorgolewski KJ, Grady CL, Green MA, Guassi Moreira JF, Guest O, Hakimi S, Hamilton JP, Hancock R, Handjaras G, Harry BB, Hawco C, Herholz P, Herman G, Heunis S, Hoffstaedter F, Hogeveen J, Holmes S, Hu CP, Huettel SA, Hughes ME, Iacovella V, Iordan AD, Isager PM, Isik AI, Jahn A, Johnson MR, Johnstone T, Joseph MJE, Juliano AC, Kable JW, Kassinopoulos M, Koba C, Kong XZ, Koscik TR, Kucukboyaci NE, Kuhl BA, Kupek S, Laird AR, Lamm C, Langner R, Lauharatanahirun N, Lee H, Lee S, Leemans A, Leo A, Lesage E, Li F, Li MYC, Lim PC, Lintz EN, Liphardt SW, Losecaat Vermeer AB, Love BC, Mack ML, Malpica N, Marins T, Maumet C, McDonald K, McGuire JT, Melero H, Méndez Leal AS, Meyer B, Meyer KN, Mihai G, Mitsis GD, Moll J, Nielson DM, Nilsonne G, Notter MP, Olivetti E, Onicas AI, Papale P, Patil KR, Peelle JE, Pérez A, Pischedda D, Poline JB, Prystauka Y, Ray S, Reuter-Lorenz PA, Reynolds RC, Ricciardi E, Rieck JR, Rodriguez-Thompson AM, Romyn A, Salo T, Samanez-Larkin GR, Sanz-Morales E, Schlichting ML, Schultz DH, Shen Q, Sheridan MA, Silvers JA, Skagerlund K, Smith A, Smith DV, Sokol-Hessner P, Steinkamp SR, Tashjian SM, Thirion B, Thorp JN, Tinghög G, Tisdall L, Tompson SH, Toro-Serey C, Torre Tresols JJ, Tozzi L, Truong V, Turella L, van 't Veer AE, Verguts T, Vettel JM, Vijayarajah S, Vo K, Wall MB, Weeda WD, Weis S, White DJ, Wisniewski D, Xifra-Porxas A, Yearling EA, Yoon S, Yuan R, Yuen KSL, Zhang L, Zhang X, Zosky JE, Nichols TE, Poldrack RA, Schonberg T. Variability in the analysis of a single neuroimaging dataset by many teams. Nature 2020; 582:84-88. [PMID: 32483374 PMCID: PMC7771346 DOI: 10.1038/s41586-020-2314-9] [Citation(s) in RCA: 423] [Impact Index Per Article: 105.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Accepted: 04/07/2020] [Indexed: 01/13/2023]
Abstract
Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses1. The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset2-5. Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed.
Collapse
Affiliation(s)
- Rotem Botvinik-Nezer
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
- Department of Neurobiology, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
| | - Felix Holzmeister
- Department of Banking and Finance, University of Innsbruck, Innsbruck, Austria
| | - Colin F Camerer
- HSS and CNS, California Institute of Technology, Pasadena, CA, USA
| | - Anna Dreber
- Department of Economics, Stockholm School of Economics, Stockholm, Sweden
- Department of Economics, University of Innsbruck, Innsbruck, Austria
| | - Juergen Huber
- Department of Banking and Finance, University of Innsbruck, Innsbruck, Austria
| | - Magnus Johannesson
- Department of Economics, Stockholm School of Economics, Stockholm, Sweden
| | - Michael Kirchler
- Department of Banking and Finance, University of Innsbruck, Innsbruck, Austria
| | - Roni Iwanir
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
- Department of Neurobiology, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Jeanette A Mumford
- Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI, USA
| | - R Alison Adcock
- Center for Cognitive Neuroscience, Duke University, Durham, NC, USA
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
| | - Paolo Avesani
- Neuroinformatics Laboratory, Fondazione Bruno Kessler, Trento, Italy
- Center for Mind/Brain Sciences - CIMeC, University of Trento, Rovereto, Italy
| | - Blazej M Baczkowski
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Aahana Bajracharya
- Department of Otolaryngology, Washington University in St. Louis, St. Louis, MO, USA
| | - Leah Bakst
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
- Center for Systems Neuroscience, Boston University, Boston, MA, USA
| | - Sheryl Ball
- Department of Economics, Virginia Tech, Blacksburg, VA, USA
- School of Neuroscience, Virginia Tech, Blacksburg, VA, USA
| | - Marco Barilari
- Crossmodal Perception and Plasticity Laboratory, Institutes for Research in Psychology (IPSY) and Neurosciences (IoNS), UCLouvain, Louvain-la-Neuve, Belgium
| | - Nadège Bault
- School of Psychology, University of Plymouth, Plymouth, UK
| | - Derek Beaton
- Rotman Research Institute, Baycrest Health Sciences Centre, Toronto, Ontario, Canada
| | - Julia Beitner
- Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands
- Department of Psychology, Goethe University, Frankfurt am Main, Germany
| | - Roland G Benoit
- Max Planck Research Group: Adaptive Memory, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Ruud M W J Berkers
- Max Planck Research Group: Adaptive Memory, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Jamil P Bhanji
- Department of Psychology, Rutgers University-Newark, Newark, NJ, USA
| | - Bharat B Biswal
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, USA
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | | | - Tiago Bortolini
- D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil
| | | | - Alexander Bowring
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Senne Braem
- Department of Experimental Psychology, Ghent University, Ghent, Belgium
- Department of Psychology, Vrije Universiteit Brussel, Brussels, Belgium
| | - Hayley R Brooks
- Department of Psychology, University of Denver, Denver, CO, USA
| | - Emily G Brudner
- Department of Psychology, Rutgers University-Newark, Newark, NJ, USA
| | | | - Julia A Camilleri
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Jaime J Castrellon
- Center for Cognitive Neuroscience, Duke University, Durham, NC, USA
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Luca Cecchetti
- MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Lucca, Italy
| | - Edna C Cieslik
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Zachary J Cole
- Department of Psychology, University of Nebraska-Lincoln, Lincoln, NE, USA
| | - Olivier Collignon
- Center for Mind/Brain Sciences - CIMeC, University of Trento, Rovereto, Italy
- Crossmodal Perception and Plasticity Laboratory, Institutes for Research in Psychology (IPSY) and Neurosciences (IoNS), UCLouvain, Louvain-la-Neuve, Belgium
| | - Robert W Cox
- National Institute of Mental Health (NIMH), National Institutes of Health, Bethesda, MD, USA
| | | | - Stefan Czoschke
- Institute of Medical Psychology, Goethe University, Frankfurt am Main, Germany
| | | | - Charles P Davis
- Department of Psychological Sciences, University of Connecticut, Storrs, CT, USA
- Brain Imaging Research Center, University of Connecticut, Storrs, CT, USA
- Connecticut Institute for the Brain and Cognitive Sciences, University of Connecticut, Storrs, CT, USA
| | - Alberto De Luca
- PROVIDI Lab, Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
| | | | - Lysia Demetriou
- Section of Endocrinology and Investigative Medicine, Faculty of Medicine, Imperial College London, London, UK
- Nuffield Department of Women's and Reproductive Health, University of Oxford, Oxford, UK
| | | | - Xin Di
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, USA
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Erin W Dickie
- Krembil Centre for Neuroinformatics, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Ekaterina Dobryakova
- Center for Traumatic Brain Injury Research, Kessler Foundation, East Hanover, NJ, USA
| | - Claire L Donnat
- Department of Statistics, Stanford University, Stanford, CA, USA
| | - Juergen Dukart
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Niall W Duncan
- Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University, Taipei, Taiwan
- Brain and Consciousness Research Centre, TMU-ShuangHo Hospital, New Taipei City, Taiwan
| | - Joke Durnez
- Department of Psychology and Stanford Center for Reproducible Neuroscience, Stanford University, Stanford, CA, USA
| | - Amr Eed
- Instituto de Neurociencias, CSIC-UMH, Alicante, Spain
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Andrew Erhart
- Department of Psychology, University of Denver, Denver, CO, USA
| | - Laura Fontanesi
- Faculty of Psychology, University of Basel, Basel, Switzerland
| | - G Matthew Fricke
- Computer Science Department, University of New Mexico, Albuquerque, NM, USA
| | - Shiguang Fu
- School of Management, Zhejiang University of Technology, Hangzhou, China
- Institute of Neuromanagement, Zhejiang University of Technology, Hangzhou, China
| | - Adriana Galván
- Department of Psychology, University of California Los Angeles, Los Angeles, CA, USA
| | - Remi Gau
- Crossmodal Perception and Plasticity Laboratory, Institutes for Research in Psychology (IPSY) and Neurosciences (IoNS), UCLouvain, Louvain-la-Neuve, Belgium
| | - Sarah Genon
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Tristan Glatard
- Department of Computer Science and Software Engineering, Concordia University, Montreal, Quebec, Canada
| | - Enrico Glerean
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
| | - Jelle J Goeman
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Sergej A E Golowin
- Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University, Taipei, Taiwan
| | | | | | - Cheryl L Grady
- Rotman Research Institute, Baycrest Health Sciences Centre, Toronto, Ontario, Canada
| | - Mikella A Green
- Center for Cognitive Neuroscience, Duke University, Durham, NC, USA
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - João F Guassi Moreira
- Department of Psychology, University of California Los Angeles, Los Angeles, CA, USA
| | - Olivia Guest
- Department of Experimental Psychology, University College London, London, UK
- Research Centre on Interactive Media, Smart Systems and Emerging Technologies - RISE, Nicosia, Cyprus
| | - Shabnam Hakimi
- Center for Cognitive Neuroscience, Duke University, Durham, NC, USA
| | - J Paul Hamilton
- Center for Social and Affective Neuroscience, Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
| | - Roeland Hancock
- Brain Imaging Research Center, University of Connecticut, Storrs, CT, USA
- Connecticut Institute for the Brain and Cognitive Sciences, University of Connecticut, Storrs, CT, USA
| | - Giacomo Handjaras
- MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Lucca, Italy
| | - Bronson B Harry
- The MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Sydney, New South Wales, Australia
| | - Colin Hawco
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Peer Herholz
- McConnell Brain Imaging Centre, The Neuro (Montreal Neurological Institute-Hospital), Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Gabrielle Herman
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Stephan Heunis
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
- Department of Research and Development, Epilepsy Centre Kempenhaeghe, Heeze, The Netherlands
| | - Felix Hoffstaedter
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Jeremy Hogeveen
- Department of Psychology, University of New Mexico, Albuquerque, NM, USA
- Psychology Clinical Neuroscience Center, University of New Mexico, Albuquerque, NM, USA
| | - Susan Holmes
- Department of Statistics, Stanford University, Stanford, CA, USA
| | - Chuan-Peng Hu
- Leibniz-Institut für Resilienzforschung (LIR), Mainz, Germany
| | - Scott A Huettel
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Matthew E Hughes
- School of Health Sciences, Swinburne University of Technology, Hawthorn, Victoria, Australia
| | - Vittorio Iacovella
- Center for Mind/Brain Sciences - CIMeC, University of Trento, Rovereto, Italy
| | | | - Peder M Isager
- Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Ayse I Isik
- Department of Neuroscience, Max Planck Institute for Empirical Aesthetics, Frankfurt am Main, Germany
| | - Andrew Jahn
- fMRI Laboratory, University of Michigan, Ann Arbor, MI, USA
| | - Matthew R Johnson
- Department of Psychology, University of Nebraska-Lincoln, Lincoln, NE, USA
- Center for Brain, Biology and Behavior, University of Nebraska-Lincoln, Lincoln, NE, USA
| | - Tom Johnstone
- School of Health Sciences, Swinburne University of Technology, Hawthorn, Victoria, Australia
| | - Michael J E Joseph
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Anthony C Juliano
- Center for Neuropsychology and Neuroscience Research, Kessler Foundation, East Hanover, NJ, USA
| | - Joseph W Kable
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
- MindCORE, University of Pennsylvania, Philadelphia, PA, USA
| | - Michalis Kassinopoulos
- Graduate Program in Biological and Biomedical Engineering, McGill University, Montreal, Quebec, Canada
| | - Cemal Koba
- MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Lucca, Italy
| | - Xiang-Zhen Kong
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Timothy R Koscik
- Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, IA, USA
| | - Nuri Erkut Kucukboyaci
- Center for Traumatic Brain Injury Research, Kessler Foundation, East Hanover, NJ, USA
- Department of Physical Medicine and Rehabilitation, Rutgers New Jersey Medical School, Newark, NJ, USA
| | - Brice A Kuhl
- Department of Psychology, University of Oregon, Eugene, OR, USA
| | - Sebastian Kupek
- Faculty of Economics and Statistics, University of Innsbruck, Innsbruck, Austria
| | - Angela R Laird
- Department of Physics, Florida International University, Miami, Florida, USA
| | - Claus Lamm
- Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
- Vienna Cognitive Science Hub, University of Vienna, Vienna, Austria
| | - Robert Langner
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Nina Lauharatanahirun
- US CCDC Army Research Laboratory, Human Research and Engineering Directorate, Aberdeen Proving Ground, MD, USA
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, PA, USA
| | - Hongmi Lee
- Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, USA
| | - Sangil Lee
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
| | - Alexander Leemans
- PROVIDI Lab, Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Andrea Leo
- MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Lucca, Italy
| | - Elise Lesage
- Department of Experimental Psychology, Ghent University, Ghent, Belgium
| | - Flora Li
- Fralin Biomedical Research Institute, Roanoke, VA, USA
- Economics Experimental Lab, Nanjing Audit University, Nanjing, China
| | - Monica Y C Li
- Department of Psychological Sciences, University of Connecticut, Storrs, CT, USA
- Brain Imaging Research Center, University of Connecticut, Storrs, CT, USA
- Connecticut Institute for the Brain and Cognitive Sciences, University of Connecticut, Storrs, CT, USA
- Haskins Laboratories, New Haven, CT, USA
| | - Phui Cheng Lim
- Department of Psychology, University of Nebraska-Lincoln, Lincoln, NE, USA
- Center for Brain, Biology and Behavior, University of Nebraska-Lincoln, Lincoln, NE, USA
| | - Evan N Lintz
- Department of Psychology, University of Nebraska-Lincoln, Lincoln, NE, USA
| | | | - Annabel B Losecaat Vermeer
- Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
| | - Bradley C Love
- Department of Experimental Psychology, University College London, London, UK
- The Alan Turing Institute, London, UK
| | - Michael L Mack
- Department of Psychology, University of Toronto, Toronto, Ontario, Canada
| | - Norberto Malpica
- Laboratorio de Análisis de Imagen Médica y Biometría (LAIMBIO), Universidad Rey Juan Carlos, Madrid, Spain
| | - Theo Marins
- D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil
| | - Camille Maumet
- Inria, Univ Rennes, CNRS, Inserm, IRISA UMR 6074, Empenn ERL U 1228, Rennes, France
| | - Kelsey McDonald
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Joseph T McGuire
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
- Center for Systems Neuroscience, Boston University, Boston, MA, USA
| | - Helena Melero
- Laboratorio de Análisis de Imagen Médica y Biometría (LAIMBIO), Universidad Rey Juan Carlos, Madrid, Spain
- Departamento de Psicobiología, División de Psicología, CES Cardenal Cisneros, Madrid, Spain
- Northeastern University Biomedical Imaging Center, Northeastern University, Boston, MA, USA
| | - Adriana S Méndez Leal
- Department of Psychology, University of California Los Angeles, Los Angeles, CA, USA
| | - Benjamin Meyer
- Leibniz-Institut für Resilienzforschung (LIR), Mainz, Germany
- Neuroimaging Center (NIC), Focus Program Translational Neurosciences (FTN), Johannes Gutenberg University Medical Center Mainz, Mainz, Germany
| | - Kristin N Meyer
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Glad Mihai
- Max Planck Research Group: Neural Mechanisms of Human Communication, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Chair of Cognitive and Clinical Neuroscience, Faculty of Psychology, Technische Universität Dresden, Dresden, Germany
| | - Georgios D Mitsis
- Department of Bioengineering, McGill University, Montreal, Quebec, Canada
| | - Jorge Moll
- D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil
- Department of Psychology, Stanford University, Stanford, CA, USA
| | - Dylan M Nielson
- Data Science and Sharing Team, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Gustav Nilsonne
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Psychology, Stockholm University, Stockholm, Sweden
| | - Michael P Notter
- The Laboratory for Investigative Neurophysiology (The LINE), Department of Radiology, University Hospital Center and University of Lausanne, Lausanne, Switzerland
| | - Emanuele Olivetti
- Neuroinformatics Laboratory, Fondazione Bruno Kessler, Trento, Italy
- Center for Mind/Brain Sciences - CIMeC, University of Trento, Rovereto, Italy
| | - Adrian I Onicas
- MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Lucca, Italy
| | - Paolo Papale
- MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Lucca, Italy
- Department of Vision and Cognition, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
| | - Kaustubh R Patil
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Jonathan E Peelle
- Department of Otolaryngology, Washington University in St. Louis, St. Louis, MO, USA
| | - Alexandre Pérez
- McConnell Brain Imaging Centre, The Neuro (Montreal Neurological Institute-Hospital), Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Doris Pischedda
- Bernstein Center for Computational Neuroscience and Berlin Center for Advanced Neuroimaging and Clinic for Neurology, Charité Universitätsmedizin, corporate member of Freie Universität Berlin, Humboldt Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- Cluster of Excellence Science of Intelligence, Technische Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
- NeuroMI - Milan Center for Neuroscience, Milan, Italy
| | - Jean-Baptiste Poline
- McConnell Brain Imaging Centre, The Neuro (Montreal Neurological Institute-Hospital), Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- Henry H. Wheeler, Jr. Brain Imaging Center, Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA
| | - Yanina Prystauka
- Department of Psychological Sciences, University of Connecticut, Storrs, CT, USA
- Brain Imaging Research Center, University of Connecticut, Storrs, CT, USA
- Connecticut Institute for the Brain and Cognitive Sciences, University of Connecticut, Storrs, CT, USA
| | - Shruti Ray
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, USA
| | | | - Richard C Reynolds
- Scientific and Statistical Computing Core, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Emiliano Ricciardi
- MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Lucca, Italy
| | - Jenny R Rieck
- Rotman Research Institute, Baycrest Health Sciences Centre, Toronto, Ontario, Canada
| | - Anais M Rodriguez-Thompson
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Anthony Romyn
- Department of Psychology, University of Toronto, Toronto, Ontario, Canada
| | - Taylor Salo
- Department of Psychology, Florida International University, Miami, FL, USA
| | - Gregory R Samanez-Larkin
- Center for Cognitive Neuroscience, Duke University, Durham, NC, USA
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Emilio Sanz-Morales
- Laboratorio de Análisis de Imagen Médica y Biometría (LAIMBIO), Universidad Rey Juan Carlos, Madrid, Spain
| | | | - Douglas H Schultz
- Department of Psychology, University of Nebraska-Lincoln, Lincoln, NE, USA
- Center for Brain, Biology and Behavior, University of Nebraska-Lincoln, Lincoln, NE, USA
| | - Qiang Shen
- School of Management, Zhejiang University of Technology, Hangzhou, China
- Institute of Neuromanagement, Zhejiang University of Technology, Hangzhou, China
| | - Margaret A Sheridan
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jennifer A Silvers
- Department of Psychology, University of California Los Angeles, Los Angeles, CA, USA
| | - Kenny Skagerlund
- Department of Behavioural Sciences and Learning, Linköping University, Linköping, Sweden
- Center for Social and Affective Neuroscience, Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden
| | - Alec Smith
- Department of Economics, Virginia Tech, Blacksburg, VA, USA
- School of Neuroscience, Virginia Tech, Blacksburg, VA, USA
| | - David V Smith
- Department of Psychology, Temple University, Philadelphia, PA, USA
| | | | - Simon R Steinkamp
- Institute of Neuroscience and Medicine, Cognitive Neuroscience (INM-3), Research Centre Jülich, Jülich, Germany
| | - Sarah M Tashjian
- Department of Psychology, University of California Los Angeles, Los Angeles, CA, USA
| | | | - John N Thorp
- Department of Psychology, Columbia University, New York, NY, USA
| | - Gustav Tinghög
- Department of Management and Engineering, Linköping University, Linköping, Sweden
- Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
| | - Loreen Tisdall
- Department of Psychology, Stanford University, Stanford, CA, USA
- Center for Cognitive and Decision Sciences, University of Basel, Basel, Switzerland
| | - Steven H Tompson
- US CCDC Army Research Laboratory, Human Research and Engineering Directorate, Aberdeen Proving Ground, MD, USA
| | - Claudio Toro-Serey
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
- Center for Systems Neuroscience, Boston University, Boston, MA, USA
| | | | - Leonardo Tozzi
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Vuong Truong
- Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University, Taipei, Taiwan
- Brain and Consciousness Research Centre, TMU-ShuangHo Hospital, New Taipei City, Taiwan
| | - Luca Turella
- Center for Mind/Brain Sciences - CIMeC, University of Trento, Rovereto, Italy
| | - Anna E van 't Veer
- Methodology and Statistics Unit, Institute of Psychology, Leiden University, Leiden, The Netherlands
| | - Tom Verguts
- Department of Experimental Psychology, Ghent University, Ghent, Belgium
| | - Jean M Vettel
- US Combat Capabilities Development Command Army Research Laboratory, Aberdeen, MD, USA
- University of California Santa Barbara, Santa Barbara, CA, USA
- University of Pennsylvania, Philadelphia, PA, USA
| | - Sagana Vijayarajah
- Department of Psychology, University of Toronto, Toronto, Ontario, Canada
| | - Khoi Vo
- Center for Cognitive Neuroscience, Duke University, Durham, NC, USA
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | - Matthew B Wall
- Invicro, London, UK
- Faculty of Medicine, Imperial College London, London, UK
- Clinical Psychopharmacology Unit, University College London, London, UK
| | - Wouter D Weeda
- Methodology and Statistics Unit, Institute of Psychology, Leiden University, Leiden, The Netherlands
| | - Susanne Weis
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - David J White
- Centre for Human Psychopharmacology, Swinburne University, Hawthorn, Victoria, Australia
| | - David Wisniewski
- Department of Experimental Psychology, Ghent University, Ghent, Belgium
| | - Alba Xifra-Porxas
- Graduate Program in Biological and Biomedical Engineering, McGill University, Montreal, Quebec, Canada
| | - Emily A Yearling
- Department of Psychological Sciences, University of Connecticut, Storrs, CT, USA
- Brain Imaging Research Center, University of Connecticut, Storrs, CT, USA
- Connecticut Institute for the Brain and Cognitive Sciences, University of Connecticut, Storrs, CT, USA
| | - Sangsuk Yoon
- Department of Management and Marketing, School of Business, University of Dayton, Dayton, OH, USA
| | - Rui Yuan
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Kenneth S L Yuen
- Leibniz-Institut für Resilienzforschung (LIR), Mainz, Germany
- Neuroimaging Center (NIC), Focus Program Translational Neurosciences (FTN), Johannes Gutenberg University Medical Center Mainz, Mainz, Germany
| | - Lei Zhang
- Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
| | - Xu Zhang
- Brain Imaging Research Center, University of Connecticut, Storrs, CT, USA
- Connecticut Institute for the Brain and Cognitive Sciences, University of Connecticut, Storrs, CT, USA
- Biomedical Engineering Department, University of Connecticut, Storrs, CT, USA
| | - Joshua E Zosky
- Department of Psychology, University of Nebraska-Lincoln, Lincoln, NE, USA
- Center for Brain, Biology and Behavior, University of Nebraska-Lincoln, Lincoln, NE, USA
| | - Thomas E Nichols
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
| | | | - Tom Schonberg
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.
- Department of Neurobiology, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel.
| |
Collapse
|
33
|
Hawco C, Yoganathan L, Voineskos AN, Lyon R, Tan T, Daskalakis ZJ, Blumberger DM, Croarkin PE, Lai MC, Szatmari P, Ameis SH. Greater Individual Variability in Functional Brain Activity during Working Memory Performance in young people with Autism and Executive Function Impairment. Neuroimage Clin 2020; 27:102260. [PMID: 32388347 PMCID: PMC7218076 DOI: 10.1016/j.nicl.2020.102260] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2019] [Revised: 03/12/2020] [Accepted: 04/02/2020] [Indexed: 12/11/2022]
Abstract
BACKGROUND Individuals with autism spectrum disorder (ASD) often present with executive functioning (EF) deficits, including spatial working memory (SWM) impairment, which impedes real-world functioning. The present study examined task-related brain activity, connectivity and individual variability in fMRI-measured neural response during an SWM task in older youth and young adults with autism and clinically significant EF impairment. METHODS Neuroimaging was analyzed in 29 individuals with ASD without intellectual disability who had clinically significant EF impairment on the Behavior Rating Inventory of Executive Function, and 20 typically developing controls (participant age range=16-34). An SWM N-Back task was performed during fMRI. SWM activity (2-Back vs. 0-Back) and task-related dorsolateral prefrontal cortex (DLPFC) connectivity was examined within and between groups. Variability of neural response during SWM was also examined. RESULTS During SWM performance both groups activated the expected networks, and no group differences in network activation or task-related DLPFC-connectivity were found. However, greater individual variability in the pattern of SWM activity was found in the ASD versus the typically developing control group. CONCLUSIONS While there were no group differences in SWM task-evoked activity or connectivity, fronto-parietal network engagement was found to be more variable/idiosyncratic in ASD. Our results suggest that the fronto-parietal network may be shifted or sub-optimally engaged during SWM performance in participants with ASD with clinically significant EF impairment, with implications for developing targeted interventions for this subgroup.
Collapse
Affiliation(s)
- Colin Hawco
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, 250 College St., Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Laagishan Yoganathan
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, 250 College St., Toronto, ON, Canada; Department of Psychology, Neuroscience & Behaviour, McMaster University, Hamilton, ON, Canada
| | - Aristotle N Voineskos
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, 250 College St., Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Rachael Lyon
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, 250 College St., Toronto, ON, Canada
| | - Thomas Tan
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, 250 College St., Toronto, ON, Canada
| | - Zafiris J Daskalakis
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, 250 College St., Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Daniel M Blumberger
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, 250 College St., Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Paul E Croarkin
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota, USA
| | - Meng-Chuan Lai
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, 250 College St., Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Department of Psychiatry, The Hospital for Sick Children, Toronto, ON, Canada; Margaret and Wallace McCain Centre for Child, Youth & Family Mental Health, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Peter Szatmari
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Department of Psychiatry, The Hospital for Sick Children, Toronto, ON, Canada; Margaret and Wallace McCain Centre for Child, Youth & Family Mental Health, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Stephanie H Ameis
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, 250 College St., Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Department of Psychiatry, The Hospital for Sick Children, Toronto, ON, Canada; Margaret and Wallace McCain Centre for Child, Youth & Family Mental Health, Centre for Addiction and Mental Health, Toronto, ON, Canada.
| |
Collapse
|
34
|
Mansur RB, Subramaniapillai M, Zuckerman H, Park C, Iacobucci M, Lee Y, Tuineag M, Hawco C, Frey BN, Rasgon N, Brietzke E, McIntyre RS. Effort-based decision-making is affected by overweight/obesity in major depressive disorder. J Affect Disord 2019; 256:221-227. [PMID: 31181378 DOI: 10.1016/j.jad.2019.06.002] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Revised: 04/09/2019] [Accepted: 06/02/2019] [Indexed: 01/04/2023]
Abstract
BACKGROUND Anhedonia and abnormalities in reward behavior are core features of major depressive disorder (MDD). Convergent evidence indicates that overweight/obesity (OW), a highly prevalent condition in MDD, is independently associated with reward disturbances. We therefore aimed to investigate the moderating effect of OW on the willingness to expend efforts for reward in individuals with MDD and healthy controls (HC). METHODS Forty-one adults (HC n = 20, MDD n = 21) completed the Effort Expenditure for Rewards Task (EEfRT), clinical and cognitive measures. Anthropometric parameters were assessed in all participants, and an additional evaluation of laboratorial parameters were conducted solely on those with MDD. Individuals with MDD were all on vortioxetine monotherapy (10-20 mg/day). RESULTS Interactions between reward magnitude, group and OW were observed (χ2 = 9.192, p = 0.010); the OW-MDD group chose the hard task significantly less than normal weight (NW)-HC (p = 0.033) and OW-HC (p = 0.034), whereas there were no differences between NW-MDD and HCs. Within individuals with MDD, the proportion of hard task choices was more strongly correlated with body mass index (BMI) (r = -0.456, p = 0.043) and insulin resistance (HOMA2-IR) (r = -0.467, p = 0.038), than with depressive symptoms (r = 0.290, p = 0.214). CONCLUSIONS OW significantly moderated the association between MDD and willingness to make efforts for rewards. These findings offer novel evidence on the potential role of metabolic factors on the basis of anhedonia, and for the heuristic models proposing a pathophysiological connection between mood and metabolic disorders.
Collapse
Affiliation(s)
- Rodrigo B Mansur
- Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, M5T 2S8, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, M5T 2S8, Canada.
| | - Mehala Subramaniapillai
- Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, M5T 2S8, Canada
| | - Hannah Zuckerman
- Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, M5T 2S8, Canada
| | - Caroline Park
- Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, M5T 2S8, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, M5T 2S8, Canada
| | - Michelle Iacobucci
- Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, M5T 2S8, Canada
| | - Yena Lee
- Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, M5T 2S8, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, M5T 2S8, Canada
| | - Maria Tuineag
- Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, M5T 2S8, Canada
| | - Colin Hawco
- Department of Psychiatry, University of Toronto, Toronto, ON, M5T 2S8, Canada; Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, 250 College St., Toronto, ON, Canada
| | - Benicio N Frey
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Ontario, Canada
| | - Natalie Rasgon
- Center for Neuroscience in Women's Health, Stanford University, Palo Alto, USA
| | - Elisa Brietzke
- Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, M5T 2S8, Canada; Department of Psychiatry, Queen's University, Kingston, ON, K7L 7X3, Canada; Research Group in Molecular and Behavioral Neurosciences of Mood Disorders, Department of Psychiatry, Universidade Federal de São Paulo, São Paulo, SP, 04038-000, Brazil
| | - Roger S McIntyre
- Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, M5T 2S8, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, M5T 2S8, Canada; Research Group in Molecular and Behavioral Neurosciences of Mood Disorders, Department of Psychiatry, Universidade Federal de São Paulo, São Paulo, SP, 04038-000, Brazil; Brain and Cognition Discovery Foundation, Mississauga, ON L5C 4E, Canada
| |
Collapse
|
35
|
Hawco C, Buchanan RW, Calarco N, Mulsant BH, Viviano JD, Dickie EW, Argyelan M, Gold JM, Iacoboni M, DeRosse P, Foussias G, Malhotra AK, Voineskos AN. Separable and Replicable Neural Strategies During Social Brain Function in People With and Without Severe Mental Illness. Am J Psychiatry 2019; 176:521-530. [PMID: 30606045 DOI: 10.1176/appi.ajp.2018.17091020] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
OBJECTIVE Case-control study design and disease heterogeneity may impede biomarker discovery in brain disorders, including serious mental illnesses. To identify biologically and/or behaviorally driven as opposed to diagnostically driven subgroups of individuals, the authors used hierarchical clustering to identify individuals with similar patterns of brain activity during a facial imitate/observe functional MRI task. METHODS Participants in the Social Processes Initiative in Neurobiology of the Schizophrenia(s) study (N=179; 109 with a schizophrenia spectrum disorder and 70 healthy control participants) underwent MRI scanning at three sites. Hierarchical clustering was used to identify new data-driven groups of participants; differences on social and neurocognitive tests completed outside the scanner were compared among the new groups. RESULTS Three clusters with distinct patterns of neural activity were found. Cluster membership was not related to diagnosis or scan site. The largest cluster consisted of "typical activators," with activity in the canonical "simulation" circuit. The other clusters represented a "hyperactivating" group and a "deactivating" group. Between-participants Euclidean distances were smaller within clusters than within site or diagnostics groups. The deactivating group had the highest social cognitive and neurocognitive test scores. The hierarchical clustering analysis was repeated on a replication sample (N=108; 32 schizophrenia spectrum disorder, 37 euthymic bipolar disorder, and 39 healthy control participants), which exhibited the same three cluster patterns. CONCLUSIONS The study findings demonstrate replicable differing patterns of neural activity among individuals during a socio-emotional task, independent of DSM diagnosis or scan site. The findings may provide objective neuroimaging endpoints (biomarkers) for subgroups of individuals in target engagement research aimed at enhancing cognitive performance independent of diagnostic category.
Collapse
Affiliation(s)
- Colin Hawco
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto (Hawco, Calarco, Mulsant, Viviano, Dickie, Foussias, Voineskos); the Department of Psychiatry, University of Toronto, Toronto (Hawco, Foussias, Mulsant, Voineskos); Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Md. (Buchanan, Gold); Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, N.Y. (Argyelan, DeRosse, Malhotra); Zucker School of Medicine at Hofstra/Northwell, Hempstead, N.Y. (Argyelan, DeRosse, Malhotra); the Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at the University of California, Los Angeles (Iacoboni)
| | - Robert W Buchanan
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto (Hawco, Calarco, Mulsant, Viviano, Dickie, Foussias, Voineskos); the Department of Psychiatry, University of Toronto, Toronto (Hawco, Foussias, Mulsant, Voineskos); Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Md. (Buchanan, Gold); Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, N.Y. (Argyelan, DeRosse, Malhotra); Zucker School of Medicine at Hofstra/Northwell, Hempstead, N.Y. (Argyelan, DeRosse, Malhotra); the Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at the University of California, Los Angeles (Iacoboni)
| | - Navona Calarco
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto (Hawco, Calarco, Mulsant, Viviano, Dickie, Foussias, Voineskos); the Department of Psychiatry, University of Toronto, Toronto (Hawco, Foussias, Mulsant, Voineskos); Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Md. (Buchanan, Gold); Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, N.Y. (Argyelan, DeRosse, Malhotra); Zucker School of Medicine at Hofstra/Northwell, Hempstead, N.Y. (Argyelan, DeRosse, Malhotra); the Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at the University of California, Los Angeles (Iacoboni)
| | - Benoit H Mulsant
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto (Hawco, Calarco, Mulsant, Viviano, Dickie, Foussias, Voineskos); the Department of Psychiatry, University of Toronto, Toronto (Hawco, Foussias, Mulsant, Voineskos); Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Md. (Buchanan, Gold); Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, N.Y. (Argyelan, DeRosse, Malhotra); Zucker School of Medicine at Hofstra/Northwell, Hempstead, N.Y. (Argyelan, DeRosse, Malhotra); the Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at the University of California, Los Angeles (Iacoboni)
| | - Joseph D Viviano
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto (Hawco, Calarco, Mulsant, Viviano, Dickie, Foussias, Voineskos); the Department of Psychiatry, University of Toronto, Toronto (Hawco, Foussias, Mulsant, Voineskos); Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Md. (Buchanan, Gold); Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, N.Y. (Argyelan, DeRosse, Malhotra); Zucker School of Medicine at Hofstra/Northwell, Hempstead, N.Y. (Argyelan, DeRosse, Malhotra); the Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at the University of California, Los Angeles (Iacoboni)
| | - Erin W Dickie
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto (Hawco, Calarco, Mulsant, Viviano, Dickie, Foussias, Voineskos); the Department of Psychiatry, University of Toronto, Toronto (Hawco, Foussias, Mulsant, Voineskos); Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Md. (Buchanan, Gold); Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, N.Y. (Argyelan, DeRosse, Malhotra); Zucker School of Medicine at Hofstra/Northwell, Hempstead, N.Y. (Argyelan, DeRosse, Malhotra); the Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at the University of California, Los Angeles (Iacoboni)
| | - Miklos Argyelan
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto (Hawco, Calarco, Mulsant, Viviano, Dickie, Foussias, Voineskos); the Department of Psychiatry, University of Toronto, Toronto (Hawco, Foussias, Mulsant, Voineskos); Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Md. (Buchanan, Gold); Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, N.Y. (Argyelan, DeRosse, Malhotra); Zucker School of Medicine at Hofstra/Northwell, Hempstead, N.Y. (Argyelan, DeRosse, Malhotra); the Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at the University of California, Los Angeles (Iacoboni)
| | - James M Gold
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto (Hawco, Calarco, Mulsant, Viviano, Dickie, Foussias, Voineskos); the Department of Psychiatry, University of Toronto, Toronto (Hawco, Foussias, Mulsant, Voineskos); Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Md. (Buchanan, Gold); Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, N.Y. (Argyelan, DeRosse, Malhotra); Zucker School of Medicine at Hofstra/Northwell, Hempstead, N.Y. (Argyelan, DeRosse, Malhotra); the Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at the University of California, Los Angeles (Iacoboni)
| | - Marco Iacoboni
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto (Hawco, Calarco, Mulsant, Viviano, Dickie, Foussias, Voineskos); the Department of Psychiatry, University of Toronto, Toronto (Hawco, Foussias, Mulsant, Voineskos); Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Md. (Buchanan, Gold); Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, N.Y. (Argyelan, DeRosse, Malhotra); Zucker School of Medicine at Hofstra/Northwell, Hempstead, N.Y. (Argyelan, DeRosse, Malhotra); the Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at the University of California, Los Angeles (Iacoboni)
| | - Pamela DeRosse
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto (Hawco, Calarco, Mulsant, Viviano, Dickie, Foussias, Voineskos); the Department of Psychiatry, University of Toronto, Toronto (Hawco, Foussias, Mulsant, Voineskos); Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Md. (Buchanan, Gold); Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, N.Y. (Argyelan, DeRosse, Malhotra); Zucker School of Medicine at Hofstra/Northwell, Hempstead, N.Y. (Argyelan, DeRosse, Malhotra); the Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at the University of California, Los Angeles (Iacoboni)
| | - George Foussias
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto (Hawco, Calarco, Mulsant, Viviano, Dickie, Foussias, Voineskos); the Department of Psychiatry, University of Toronto, Toronto (Hawco, Foussias, Mulsant, Voineskos); Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Md. (Buchanan, Gold); Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, N.Y. (Argyelan, DeRosse, Malhotra); Zucker School of Medicine at Hofstra/Northwell, Hempstead, N.Y. (Argyelan, DeRosse, Malhotra); the Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at the University of California, Los Angeles (Iacoboni)
| | - Anil K Malhotra
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto (Hawco, Calarco, Mulsant, Viviano, Dickie, Foussias, Voineskos); the Department of Psychiatry, University of Toronto, Toronto (Hawco, Foussias, Mulsant, Voineskos); Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Md. (Buchanan, Gold); Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, N.Y. (Argyelan, DeRosse, Malhotra); Zucker School of Medicine at Hofstra/Northwell, Hempstead, N.Y. (Argyelan, DeRosse, Malhotra); the Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at the University of California, Los Angeles (Iacoboni)
| | - Aristotle N Voineskos
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto (Hawco, Calarco, Mulsant, Viviano, Dickie, Foussias, Voineskos); the Department of Psychiatry, University of Toronto, Toronto (Hawco, Foussias, Mulsant, Voineskos); Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Md. (Buchanan, Gold); Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, N.Y. (Argyelan, DeRosse, Malhotra); Zucker School of Medicine at Hofstra/Northwell, Hempstead, N.Y. (Argyelan, DeRosse, Malhotra); the Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at the University of California, Los Angeles (Iacoboni)
| | -
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto (Hawco, Calarco, Mulsant, Viviano, Dickie, Foussias, Voineskos); the Department of Psychiatry, University of Toronto, Toronto (Hawco, Foussias, Mulsant, Voineskos); Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Md. (Buchanan, Gold); Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, N.Y. (Argyelan, DeRosse, Malhotra); Zucker School of Medicine at Hofstra/Northwell, Hempstead, N.Y. (Argyelan, DeRosse, Malhotra); the Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at the University of California, Los Angeles (Iacoboni)
| |
Collapse
|
36
|
Hawco C, Viviano JD, Chavez S, Dickie EW, Calarco N, Kochunov P, Argyelan M, Turner JA, Malhotra AK, Buchanan RW, Voineskos AN. A longitudinal human phantom reliability study of multi-center T1-weighted, DTI, and resting state fMRI data. Psychiatry Res Neuroimaging 2018; 282:134-142. [PMID: 29945740 PMCID: PMC6482446 DOI: 10.1016/j.pscychresns.2018.06.004] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/16/2017] [Revised: 06/06/2018] [Accepted: 06/06/2018] [Indexed: 12/31/2022]
Abstract
Multi-center MRI studies can enhance power, generalizability, and discovery for clinical neuroimaging research in brain disorders. Here, we sought to establish the utility of a clustering algorithm as an alternative to more traditional intra-class correlation coefficient approaches in a longitudinal multi-center human phantom study. We completed annual reliability scans on 'travelling human phantoms'. Acquisitions across sites were harmonized prospectively. Twenty-seven MRI sessions were available across four participants, scanned on five scanners, across three years. For each scan, three metrics were extracted: cortical thickness (CT), white matter fractional anisotropy (FA), and resting state functional connectivity (FC). For each metric, hierarchical clustering (Ward's method) was performed. The cluster solutions were compared to participant and scanner using the adjusted Rand index (ARI). For all metrics, data clustered by participant rather than by scanner (ARI > 0.8 comparing clusters to participants, ARI < 0.2 comparing clusters to scanners). These results demonstrate that hierarchical clustering can reliably identify structural and functional scans from different participants imaged on different scanners across time. With increasing interest in data-driven approaches in psychiatric and neurologic brain imaging studies, our findings provide a framework for multi-center analytic approaches aiming to identify subgroups of participants based on brain structure or function.
Collapse
Affiliation(s)
- Colin Hawco
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, 250 College St., Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Joseph D Viviano
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, 250 College St., Toronto, ON, Canada
| | - Sofia Chavez
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, 250 College St., Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Erin W Dickie
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, 250 College St., Toronto, ON, Canada
| | - Navona Calarco
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, 250 College St., Toronto, ON, Canada
| | - Peter Kochunov
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, P.O. Box 21247, Baltimore, MD, United States
| | - Miklos Argyelan
- Zucker Hillside Hospital, 75-59 263rd St, Glen Oaks, NY, United States
| | - Jessica A Turner
- Department of Psychology, Georgia State University, 33 Gilmer Street SE, Atlanta, GA, United States
| | - Anil K Malhotra
- Zucker Hillside Hospital, 75-59 263rd St, Glen Oaks, NY, United States; The Zucker School of Medicine at Hofstra/Northwell
| | - Robert W Buchanan
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, P.O. Box 21247, Baltimore, MD, United States
| | - Aristotle N Voineskos
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, 250 College St., Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
| |
Collapse
|
37
|
Viviano JD, Buchanan RW, Calarco N, Gold JM, Foussias G, Bhagwat N, Stefanik L, Hawco C, DeRosse P, Argyelan M, Turner J, Chavez S, Kochunov P, Kingsley P, Zhou X, Malhotra AK, Voineskos AN. Resting-State Connectivity Biomarkers of Cognitive Performance and Social Function in Individuals With Schizophrenia Spectrum Disorder and Healthy Control Subjects. Biol Psychiatry 2018; 84:665-674. [PMID: 29779671 PMCID: PMC6177285 DOI: 10.1016/j.biopsych.2018.03.013] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2017] [Revised: 03/12/2018] [Accepted: 03/31/2018] [Indexed: 12/17/2022]
Abstract
BACKGROUND Deficits in neurocognition and social cognition are drivers of reduced functioning in schizophrenia spectrum disorders, with potentially shared neurobiological underpinnings. Many studies have sought to identify brain-based biomarkers of these clinical variables using a priori dichotomies (e.g., good vs. poor cognition, deficit vs. nondeficit syndrome). METHODS We evaluated a fully data-driven approach to do the same by building and validating a brain connectivity-based biomarker of social cognitive and neurocognitive performance in a sample using resting-state and task-based functional magnetic resonance imaging (n = 74 healthy control participants, n = 114 persons with schizophrenia spectrum disorder, 188 total). We used canonical correlation analysis followed by clustering to identify a functional connectivity signature of normal and poor social cognitive and neurocognitive performance. RESULTS Persons with poor social cognitive and neurocognitive performance were differentiated from those with normal performance by greater resting-state connectivity in the mirror neuron and mentalizing systems. We validated our findings by showing that poor performers also scored lower on functional outcome measures not included in the original analysis and by demonstrating neuroanatomical differences between the normal and poorly performing groups. We used a support vector machine classifier to demonstrate that functional connectivity alone is enough to distinguish normal and poorly performing participants, and we replicated our findings in an independent sample (n = 75). CONCLUSIONS A brief functional magnetic resonance imaging scan may ultimately be useful in future studies aimed at characterizing long-term illness trajectories and treatments that target specific brain circuitry in those with impaired cognition and function.
Collapse
Affiliation(s)
- Joseph D Viviano
- Kimel Family Translational Imaging-Genetics Research Lab, Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario
| | - Robert W Buchanan
- Department of Psychiatry, Maryland Psychiatric Research Center, Catonsville, Maryland
| | - Navona Calarco
- Kimel Family Translational Imaging-Genetics Research Lab, Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario
| | - James M Gold
- Department of Psychiatry, Maryland Psychiatric Research Center, Catonsville, Maryland
| | - George Foussias
- Department of Psychiatry, University of Toronto, Toronto, Ontario
| | - Nikhil Bhagwat
- Kimel Family Translational Imaging-Genetics Research Lab, Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario; Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario; Computational Brain Anatomy Laboratory, Brain Imaging Center, Douglas Mental Health University Institute, Verdun, Quebec, Canada
| | - Laura Stefanik
- Kimel Family Translational Imaging-Genetics Research Lab, Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario
| | - Colin Hawco
- Kimel Family Translational Imaging-Genetics Research Lab, Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario; Department of Psychiatry, University of Toronto, Toronto, Ontario
| | - Pamela DeRosse
- Department of Psychiatry, The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hofstra University, Hempstead, Manhasset; Center for Psychiatric Neuroscience, The Feinstein Institute for Medical Research, Manhasset, New York; Division of Psychiatry Research, The Zucker Hillside Hospital, Division of Northwell Health, Glen Oaks, New York
| | - Miklos Argyelan
- Department of Psychiatry, The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hofstra University, Hempstead, Manhasset; Center for Psychiatric Neuroscience, The Feinstein Institute for Medical Research, Manhasset, New York; Division of Psychiatry Research, The Zucker Hillside Hospital, Division of Northwell Health, Glen Oaks, New York
| | - Jessica Turner
- Department of Psychology, Georgia State University, Atlanta, Georgia
| | - Sofia Chavez
- Department of Psychiatry, University of Toronto, Toronto, Ontario; MRI Unit, Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario
| | - Peter Kochunov
- Department of Psychiatry, Maryland Psychiatric Research Center, Catonsville, Maryland
| | - Peter Kingsley
- Department of Psychiatry, The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hofstra University, Hempstead, Manhasset; Center for Psychiatric Neuroscience, The Feinstein Institute for Medical Research, Manhasset, New York; Division of Psychiatry Research, The Zucker Hillside Hospital, Division of Northwell Health, Glen Oaks, New York
| | - Xiangzhi Zhou
- Department of Psychiatry, The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hofstra University, Hempstead, Manhasset; Center for Psychiatric Neuroscience, The Feinstein Institute for Medical Research, Manhasset, New York; Division of Psychiatry Research, The Zucker Hillside Hospital, Division of Northwell Health, Glen Oaks, New York
| | - Anil K Malhotra
- Department of Psychiatry, The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hofstra University, Hempstead, Manhasset; Center for Psychiatric Neuroscience, The Feinstein Institute for Medical Research, Manhasset, New York; Division of Psychiatry Research, The Zucker Hillside Hospital, Division of Northwell Health, Glen Oaks, New York
| | - Aristotle N Voineskos
- Kimel Family Translational Imaging-Genetics Research Lab, Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario; Department of Psychiatry, University of Toronto, Toronto, Ontario.
| |
Collapse
|
38
|
Hawco C, Voineskos AN, Radhu N, Rotenberg D, Ameis S, Backhouse FA, Semeralul M, Daskalakis ZJ. Age and gender interactions in white matter of schizophrenia and obsessive compulsive disorder compared to non-psychiatric controls: commonalities across disorders. Brain Imaging Behav 2018; 11:1836-1848. [PMID: 27915397 DOI: 10.1007/s11682-016-9657-8] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Schizophrenia (SCZ) and obsessive-compulsive disorder (OCD) are psychiatric disorders with abnormalities in white matter structure. These disorders share high comorbidity and family history of OCD is a risk factor for SCZ which suggests some shared neurobiology. White matter was examined using diffusion tensor imaging in relativity large samples of SCZ (N = 48), OCD (N = 38) and non-psychiatric controls (N = 45). Fractional anisotropy (FA) was calculated and tract based spatial statistics were used to compare groups. In a whole brain analysis, SCZ and OCD both showed small FA reductions relative to controls in the corpus callosum. Both SCZ and OCD showed accelerated reductions in FA with age; specifically in the left superior longitudinal fasciculus in OCD, while the SCZ group demonstrated a more widespread pattern of FA reduction. Patient groups did not differ from each other in total FA or age effects in any regions. A general linear model using 13 a-priori regions of interest showed marginal group, group*gender, and group*age interactions. When OCD and SCZ groups were analyzed together, these marginal effects became significant (p < 0.05), suggesting commonalities exist between these patient groups. Overall, our results demonstrate a similar pattern of accelerated white matter decline with age and greater white matter deficit in females in OCD and SCZ, with overlap in the spatial pattern of deficits. There was no evidence for statistical differences in overall white matter between OCD and SCZ. Taken together, the results support the notion of shared neurobiology in SCZ and OCD.
Collapse
Affiliation(s)
- Colin Hawco
- Centre for Addiction and Mental Health, Campbell Family Mental Health Research Institute, Unit 4-1, Office 125, 1001 Queen Street West, Toronto, ON, M6J 1H4, Canada. .,Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada.
| | - Aristotle N Voineskos
- Centre for Addiction and Mental Health, Campbell Family Mental Health Research Institute, Unit 4-1, Office 125, 1001 Queen Street West, Toronto, ON, M6J 1H4, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Natasha Radhu
- Centre for Addiction and Mental Health, Campbell Family Mental Health Research Institute, Unit 4-1, Office 125, 1001 Queen Street West, Toronto, ON, M6J 1H4, Canada.,Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - David Rotenberg
- Centre for Addiction and Mental Health, Campbell Family Mental Health Research Institute, Unit 4-1, Office 125, 1001 Queen Street West, Toronto, ON, M6J 1H4, Canada
| | - Stephanie Ameis
- Centre for Addiction and Mental Health, Campbell Family Mental Health Research Institute, Unit 4-1, Office 125, 1001 Queen Street West, Toronto, ON, M6J 1H4, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Felicity A Backhouse
- Centre for Addiction and Mental Health, Campbell Family Mental Health Research Institute, Unit 4-1, Office 125, 1001 Queen Street West, Toronto, ON, M6J 1H4, Canada.,Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Mawahib Semeralul
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Zafiris J Daskalakis
- Centre for Addiction and Mental Health, Campbell Family Mental Health Research Institute, Unit 4-1, Office 125, 1001 Queen Street West, Toronto, ON, M6J 1H4, Canada.,Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| |
Collapse
|
39
|
Crafa D, Hawco C, Brodeur MB. Heightened Responses of the Parahippocampal and Retrosplenial Cortices during Contextualized Recognition of Congruent Objects. Front Behav Neurosci 2017; 11:232. [PMID: 29311862 PMCID: PMC5735118 DOI: 10.3389/fnbeh.2017.00232] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2017] [Accepted: 11/08/2017] [Indexed: 12/21/2022] Open
Abstract
Context sometimes helps make objects more recognizable. Previous studies using functional magnetic resonance imaging (fMRI) have examined regional neural activity when objects have strong or weak associations with their contexts. Such studies have demonstrated that activity in the parahippocampal cortex (PHC) generally corresponds with strong associations between objects and their spatial contexts while retrosplenial cortex (RSC) activity is linked with episodic memory. However these studies investigated objects viewed in associated contexts, but the direct influence of scene on the perception of visual objects has not been widely investigated. We hypothesized that the PHC and RSC may only be engaged for congruent contexts in which the object could typically be found but not for neutral contexts. While in an fMRI scanner, 15 participants rated the recognizability of 152 photographic images of objects, presented within congruent and incongruent contexts. Regions of interest were created to examine PHC and RSC activity using a hypothesis-driven approach. Exploratory analyses were also performed to identify other regional activity. In line with previous studies, PHC and RSC activity emerged when objects were viewed in congruent contexts. Activity in the RSC, inferior parietal lobe (IPL) and fusiform gyrus also emerged. These findings indicate that different brain regions are employed when objects are meaningfully contextualized.
Collapse
Affiliation(s)
- Daina Crafa
- Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada
| | - Colin Hawco
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Mathieu B. Brodeur
- Department of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada
| |
Collapse
|
40
|
Hawco C, Armony JL, Daskalakis ZJ, Berlim MT, Chakravarty MM, Pike GB, Lepage M. Differing Time of Onset of Concurrent TMS-fMRI during Associative Memory Encoding: A Measure of Dynamic Connectivity. Front Hum Neurosci 2017; 11:404. [PMID: 28855865 PMCID: PMC5557775 DOI: 10.3389/fnhum.2017.00404] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2016] [Accepted: 07/21/2017] [Indexed: 02/02/2023] Open
Abstract
There has been a distinct shift in neuroimaging from localization of function into a more network based approach focused on connectivity. While fMRI has proven very fruitful for this, the hemodynamic signal is inherently slow which limits the temporal resolution of fMRI-only connectivity measures. The brain, however, works on a time scale of milliseconds. This study utilized concurrent transcranial magnetic stimulation (TMS)-fMRI in a novel way to obtain measures of dynamic connectivity by measuring changes in fMRI signal amplitude in regions distal to the site of stimulation following differing TMS onset times. Seventeen healthy subjects completed an associative memory encoding task known to involve the DLPFC, viewing pairs of objects which could be semantically related or unrelated. Three pulses of 10 Hz repetitive TMS were applied over the left DLPFC starting either at 200, 600, or 1000 ms after stimulus onset. Associations for related pairs were better remembered than unrelated pairs in a post-scan cued recall test. Differences in neural activity were assessed across different TMS onsets, separately for related and unrelated pairs. Time specific TMS effects were observed in several regions, including those associated with higher-level processing (lateral frontal, anterior cingulate), visual areas (occipital), and regions involved in semantic processing (e.g., left mid-temporal and medial frontal). Activity in the frontal cortex was decreased at 200 ms post-stimulus for unrelated pairs, and 1000 ms post-stimulus for related pairs. This suggests differences in the timing across conditions in which the DLFPC interacts with other PFC regions, consistent with the notion that the DLPFC is facilitating extended semantic processing for related items. This study demonstrates that time-varying TMS onset inside the MRI can be used to reliably measure fast dynamic connectivity with a temporal resolution in the hundreds of milliseconds.
Collapse
Affiliation(s)
- Colin Hawco
- Douglas Mental Health University Institute, McGill University, MontrealQC, Canada.,Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, TorontoON, Canada
| | - Jorge L Armony
- Douglas Mental Health University Institute, McGill University, MontrealQC, Canada
| | - Zafiris J Daskalakis
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, TorontoON, Canada
| | - Marcelo T Berlim
- Douglas Mental Health University Institute, McGill University, MontrealQC, Canada
| | - M Mallar Chakravarty
- Douglas Mental Health University Institute, McGill University, MontrealQC, Canada.,Departments of Psychiatry and Biological and Biomedical Engineering, McGill University, MontrealQC, Canada
| | - G Bruce Pike
- Department of Radiology, University of Calgary, CalgaryAB, Canada
| | - Martin Lepage
- Douglas Mental Health University Institute, McGill University, MontrealQC, Canada
| |
Collapse
|
41
|
Guimond S, Hawco C, Lepage M. Prefrontal activity and impaired memory encoding strategies in schizophrenia. J Psychiatr Res 2017; 91:64-73. [PMID: 28325680 DOI: 10.1016/j.jpsychires.2017.02.024] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2016] [Revised: 12/21/2016] [Accepted: 02/28/2017] [Indexed: 02/02/2023]
Abstract
Schizophrenia patients have significant memory difficulties that have far-reaching implications in their daily life. These impairments are partly attributed to an inability to self-initiate effective memory encoding strategies, but its core neurobiological correlates remain unknown. The current study addresses this critical gap in our knowledge of episodic memory impairments in schizophrenia. Schizophrenia patients (n = 35) and healthy controls (n = 23) underwent a Semantic Encoding Memory Task (SEMT) during an fMRI scan. Brain activity was examined for conditions where participants were a) prompted to use semantic encoding strategies, or b) not prompted but required to self-initiate such strategies. When prompted to use semantic encoding strategies, schizophrenia patients exhibited similar recognition performance and brain activity as healthy controls. However, when required to self-initiate these strategies, patients had significant reduced recognition performance and brain activity in the left dorsolateral prefrontal cortex, as well as in the left temporal gyrus, left superior parietal lobule, and cerebellum. When patients were divided based on performance on the SEMT, the subgroup with more severe deficits in self-initiation also showed greater reduction in left dorsolateral prefrontal activity. These results suggest that impaired self-initiation of elaborative encoding strategies is a driving feature of memory deficits in schizophrenia. We also identified the neural correlates of impaired self-initiation of semantic encoding strategies, in which a failure to activate the left dorsolateral prefrontal cortex plays a key role. These findings provide important new targets in the development of novel treatments aiming to improve memory and ultimately patients' outcome.
Collapse
Affiliation(s)
- Synthia Guimond
- Department of Psychology, McGill University, Montréal, Canada; Douglas Mental Health University Institute, Montréal, Canada; Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, USA
| | - Colin Hawco
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto, Canada
| | - Martin Lepage
- Douglas Mental Health University Institute, Montréal, Canada; Department of Psychiatry, McGill University, Montréal, Canada.
| |
Collapse
|
42
|
Guimond S, Lepage M, Benoit A, Charbonneau G, Hawco C, Malla AK, Joober R, Brodeur MB. Recollection rejection of new items in individuals with first-episode psychosis. Journal of Abnormal Psychology 2016; 125:104-113. [DOI: 10.1037/abn0000102] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
|
43
|
Affiliation(s)
- Martin Lepage
- Department of Psychiatry, McGill University, Montreal, Quebec, Canada2Department of Psychology, McGill University, Montreal, Quebec, Canada3Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - Colin Hawco
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Michael Bodnar
- Department of Psychology, McGill University, Montreal, Quebec, Canada3Douglas Mental Health University Institute, Montreal, Quebec, Canada
| |
Collapse
|
44
|
Buchy L, Hawco C, Joober R, Malla A, Lepage M. Cognitive insight in first-episode schizophrenia: further evidence for a role of the ventrolateral prefrontal cortex. Schizophr Res 2015; 166:65-8. [PMID: 26004692 DOI: 10.1016/j.schres.2015.05.009] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2015] [Revised: 05/01/2015] [Accepted: 05/04/2015] [Indexed: 01/31/2023]
Abstract
In people with psychoses, Self-Reflectiveness may rely on the right ventrolateral prefrontal cortex (VLPFC). We used functional magnetic resonance imaging (fMRI) and a novel virtual reality paradigm to evaluate the role of the VLPFC for Self-Reflectiveness in 25 first-episode of schizophrenia (FES) participants and 24 controls. Participants first viewed 20 characters each paired with a unique object/location, and later completed source memory judgements during fMRI scanning. Self-Reflectiveness, measured with the Beck Cognitive Insight Scale, was significantly and positively correlated to activation in bilateral VLPFC in FES, but not in controls, providing further evidence that the VLPFC supports Self-Reflectiveness in FES.
Collapse
Affiliation(s)
- Lisa Buchy
- Department of Psychiatry, University of Calgary, Alberta, Canada
| | - Colin Hawco
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Ontario, Canada
| | - Ridha Joober
- Prevention and Early Intervention Program for Psychoses, Douglas Mental Health University Institute, Verdun, Canada
| | - Ashok Malla
- Prevention and Early Intervention Program for Psychoses, Douglas Mental Health University Institute, Verdun, Canada
| | - Martin Lepage
- Prevention and Early Intervention Program for Psychoses, Douglas Mental Health University Institute, Verdun, Canada; Department of Psychiatry, McGill University, Montreal, Canada; Department of Neurology & Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Canada.
| |
Collapse
|
45
|
Abstract
When stimuli are presented multiple times, the neural response to repeated stimuli is reduced relative to novel stimuli (repetition suppression). Responses to different types of novelty were examined. Stimulus novelty was examined by contrasting first vs. second presentation of triads of objects during memory encoding. Semantic novelty was contrasted by comparing unrelated (semantically novel) triads of objects to triads in which all three objects were related (e.g., all objects were tools). In recognition, associative novelty was examined by contrasting rearranged triads (previously seen objects in a new association) with intact triads. Activity was observed in posterior regions (occipital and fusiform), with the largest extent of activity for stimulus novelty and smallest for associational novelty. Frontal activity was also observed in stimulus and semantic novelty. Additional analysis indicated that the hemodynamic response in voxels identified in the stimulus and semantic novelty contrasts was modulated by reaction time on a trial-by-trial basis. That is, the duration of the hemodynamic response was driven by reaction time. This was not the case for associative novelty. The high level of overlap across different forms of novelty suggests a similar mechanism for reduced neural activity, which may be related to reduced visual processing time. This is consistent with a facilitation model of repetition suppression, which posits a reduced peak and duration of neuronal firing for repeated stimuli.
Collapse
Affiliation(s)
- Colin Hawco
- Temerty Center for Therapeutic Brain Stimulation, Centre for Addiction and Mental Health, University of Toronto Toronto, ON, Canada
| | - Martin Lepage
- Douglas Mental Health University Institute, McGill University Montreal, QC, Canada
| |
Collapse
|
46
|
Buchy L, Hawco C, Bodnar M, Izadi S, Dell'Elce J, Messina K, Lepage M. Functional magnetic resonance imaging study of external source memory and its relation to cognitive insight in non-clinical subjects. Psychiatry Clin Neurosci 2014; 68:683-91. [PMID: 24612152 DOI: 10.1111/pcn.12177] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2013] [Revised: 02/04/2014] [Accepted: 02/18/2014] [Indexed: 12/19/2022]
Abstract
AIM Previous research has linked cognitive insight (a measure of self-reflectiveness and self-certainty) in psychosis with neurocognitive and neuroanatomical disturbances in the fronto-hippocampal neural network. The authors' goal was to use functional magnetic resonance imaging (fMRI) to investigate the neural correlates of cognitive insight during an external source memory paradigm in non-clinical subjects. METHODS At encoding, 24 non-clinical subjects travelled through a virtual city where they came across 20 separate people, each paired with a unique object in a distinct location. fMRI data were then acquired while participants viewed images of the city, and completed source recognition memory judgments of where and with whom objects were seen, which is known to involve prefrontal cortex. Cognitive insight was assessed with the Beck Cognitive Insight Scale. RESULTS External source memory was associated with neural activity in a widespread network consisting of frontal cortex, including ventrolateral prefrontal cortex (VLPFC), temporal and occipital cortices. Activation in VLPFC correlated with higher self-reflectiveness and activation in midbrain correlated with lower self-certainty during source memory attributions. Neither self-reflectiveness nor self-certainty significantly correlated with source memory accuracy. CONCLUSION By means of virtual reality and in the context of an external source memory paradigm, the study identified a preliminary functional neural basis for cognitive insight in the VLPFC in healthy people that accords with our fronto-hippocampal theoretical model as well as recent neuroimaging data in people with psychosis. The results may facilitate the understanding of the role of neural mechanisms in psychotic disorders associated with cognitive insight distortions.
Collapse
Affiliation(s)
- Lisa Buchy
- Department of Neurology & Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Canada
| | | | | | | | | | | | | |
Collapse
|
47
|
Hawco C, Berlim MT, Lepage M. The dorsolateral prefrontal cortex plays a role in self-initiated elaborative cognitive processing during episodic memory encoding: rTMS evidence. PLoS One 2013; 8:e73789. [PMID: 24040072 PMCID: PMC3764025 DOI: 10.1371/journal.pone.0073789] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2013] [Accepted: 07/31/2013] [Indexed: 01/18/2023] Open
Abstract
During episodic memory encoding, elaborative cognitive processing can improve later recall or recognition. While multiple studies examined the neural correlates of encoding strategies, few studies have explicitly focused on the self-initiation of elaborative encoding. Repetitive transcranial magnetic stimulation (rTMS), a method which can transiently disrupt neural activity, was administered during an associative encoding task. rTMS was either applied to the left dorsolateral prefrontal cortex (DLPFC) or to the vertex (a control region not involved in memory encoding) during presentation of pairs of words. Pairs could be semantically related or not related. Two encoding instructions were given, either cueing participants to analyze semantic relationships (cued condition), or to memorize the pair without any specific strategy cues (the self-initiated condition). Participants filled out a questionnaire regarding their use of memory strategies and performed a cued-recall task. We hypothesized that if the DLPFC plays a role in the self-initiation of elaborative encoding we would observe a reduction in memory performance in the self-initiated condition, particularly for related. We found a significant correlation between the effects of rTMS and strategy use, only in the self-initiated condition with related pairs. High strategy users showed reduced performance following DLPFC stimulation, while low strategy users tended to show increased recall following DLPFC stimulation during encoding. These results suggest the left DLPFC may be involved in the self-initiation of memory strategy use, and individuals may utilize different neural networks depending on their use of encoding strategies.
Collapse
Affiliation(s)
- Colin Hawco
- Department of Neurology and Neurosurgery, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada
| | - Marcelo T. Berlim
- Department of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada
| | - Martin Lepage
- Department of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada
- * E-mail:
| |
Collapse
|
48
|
Keough D, Hawco C, Jones JA. Auditory-motor adaptation to frequency-altered auditory feedback occurs when participants ignore feedback. BMC Neurosci 2013; 14:25. [PMID: 23497238 PMCID: PMC3602002 DOI: 10.1186/1471-2202-14-25] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2012] [Accepted: 02/27/2013] [Indexed: 11/10/2022] Open
Abstract
Background Auditory feedback is important for accurate control of voice fundamental frequency (F0). The purpose of this study was to address whether task instructions could influence the compensatory responding and sensorimotor adaptation that has been previously found when participants are presented with a series of frequency-altered feedback (FAF) trials. Trained singers and musically untrained participants (nonsingers) were informed that their auditory feedback would be manipulated in pitch while they sang the target vowel [/ɑ /]. Participants were instructed to either ‘compensate’ for, or ‘ignore’ the changes in auditory feedback. Whole utterance auditory feedback manipulations were either gradually presented (‘ramp’) in -2 cent increments down to -100 cents (1 semitone) or were suddenly (’constant‘) shifted down by 1 semitone. Results Results indicated that singers and nonsingers could not suppress their compensatory responses to FAF, nor could they reduce the sensorimotor adaptation observed during both the ramp and constant FAF trials. Conclusions Compared to previous research, these data suggest that musical training is effective in suppressing compensatory responses only when FAF occurs after vocal onset (500-2500 ms). Moreover, our data suggest that compensation and adaptation are automatic and are influenced little by conscious control.
Collapse
Affiliation(s)
- Dwayne Keough
- Psychology Department & Laurier Centre for Cognitive Neuroscience, Wilfrid Laurier University, Waterloo, ON N2L 3C5, Canada
| | | | | |
Collapse
|
49
|
Hawco C, Armony JL, Lepage M. Neural activity related to self-initiating elaborative semantic encoding in associative memory. Neuroimage 2013; 67:273-82. [DOI: 10.1016/j.neuroimage.2012.11.004] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2012] [Revised: 10/30/2012] [Accepted: 11/02/2012] [Indexed: 10/27/2022] Open
|
50
|
Jarick M, Hawco C, Ferretti T, Dixon M. Electrophysiological evidence of shifts in spatial attention corresponding to a synaesthetes mental calendar. J Vis 2010. [DOI: 10.1167/9.8.98] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
|