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Tansey R, Graff K, Rai S, Merrikh D, Godfrey KJ, Vanderwal T, Bray S. Development of human visual cortical function: A scoping review of task- and naturalistic-fMRI studies through the interactive specialization and maturational frameworks. Neurosci Biobehav Rev 2024; 162:105729. [PMID: 38763178 DOI: 10.1016/j.neubiorev.2024.105729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Revised: 05/12/2024] [Accepted: 05/14/2024] [Indexed: 05/21/2024]
Abstract
Overarching theories such as the interactive specialization and maturational frameworks have been proposed to describe human functional brain development. However, these frameworks have not yet been systematically examined across the fMRI literature. Visual processing is one of the most well-studied fields in neuroimaging, and research in this area has recently expanded to include naturalistic paradigms that facilitate study in younger age ranges, allowing for an in-depth critical appraisal of these frameworks across childhood. To this end, we conducted a scoping review of 94 developmental visual fMRI studies, including both traditional experimental task and naturalistic studies, across multiple sub-domains (early visual processing, category-specific higher order processing, naturalistic visual processing). We found that across domains, many studies reported progressive development, but few studies describe regressive or emergent changes necessary to fit the maturational or interactive specialization frameworks. Our findings suggest a need for the expansion of developmental frameworks and clearer reporting of both progressive and regressive changes, along with well-powered, longitudinal studies.
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Affiliation(s)
- Ryann Tansey
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.
| | - Kirk Graff
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
| | - Shefali Rai
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Daria Merrikh
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Kate J Godfrey
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Tamara Vanderwal
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada; BC Children's Hospital Research Institute, Vancouver, BC, Canada
| | - Signe Bray
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; Department of Pediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
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Taylor PA, Glen D, Chen G, Cox RW, Hanayik T, Rorden C, Nielson DM, Rajendra JK, Reynolds RC. A Set of FMRI Quality Control Tools in AFNI: Systematic, in-depth and interactive QC with afni_proc.py and more. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.27.586976. [PMID: 38585923 PMCID: PMC10996659 DOI: 10.1101/2024.03.27.586976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Quality control (QC) assessment is a vital part of FMRI processing and analysis, and a typically under-discussed aspect of reproducibility. This includes checking datasets at their very earliest stages (acquisition and conversion) through their processing steps (e.g., alignment and motion correction) to regression modeling (correct stimuli, no collinearity, valid fits, enough degrees of freedom, etc.) for each subject. There are a wide variety of features to verify throughout any single subject processing pipeline, both quantitatively and qualitatively. We present several FMRI preprocessing QC features available in the AFNI toolbox, many of which are automatically generated by the pipeline-creation tool, afni_proc.py. These items include: a modular HTML document that covers full single subject processing from the raw data through statistical modeling; several review scripts in the results directory of processed data; and command line tools for identifying subjects with one or more quantitative properties across a group (such as triaging warnings, making exclusion criteria or creating informational tables). The HTML itself contains several buttons that efficiently facilitate interactive investigations into the data, when deeper checks are needed beyond the systematic images. The pages are linkable, so that users can evaluate individual items across a group, for increased sensitivity to differences (e.g., in alignment or regression modeling images). Finally, the QC document contains rating buttons for each "QC block", as well as comment fields for each, to facilitate both saving and sharing the evaluations. This increases the specificity of QC, as well as its shareability, as these files can be shared with others and potentially uploaded into repositories, promoting transparency and open science. We describe the features and applications of these QC tools for FMRI.
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Sundermann B, Pfleiderer B, McLeod A, Mathys C. Seeing more than the Tip of the Iceberg: Approaches to Subthreshold Effects in Functional Magnetic Resonance Imaging of the Brain. Clin Neuroradiol 2024:10.1007/s00062-024-01422-2. [PMID: 38842737 DOI: 10.1007/s00062-024-01422-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 05/05/2024] [Indexed: 06/07/2024]
Abstract
Many functional magnetic resonance imaging (fMRI) studies and presurgical mapping applications rely on mass-univariate inference with subsequent multiple comparison correction. Statistical results are frequently visualized as thresholded statistical maps. This approach has inherent limitations including the risk of drawing overly-selective conclusions based only on selective results passing such thresholds. This article gives an overview of both established and newly emerging scientific approaches to supplement such conventional analyses by incorporating information about subthreshold effects with the aim to improve interpretation of findings or leverage a wider array of information. Topics covered include neuroimaging data visualization, p-value histogram analysis and the related Higher Criticism approach for detecting rare and weak effects. Further examples from multivariate analyses and dedicated Bayesian approaches are provided.
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Affiliation(s)
- Benedikt Sundermann
- Institute of Radiology and Neuroradiology, Evangelisches Krankenhaus Oldenburg, Universitätsmedizin Oldenburg, Steinweg 13-17, 26122, Oldenburg, Germany.
- Research Center Neurosensory Science, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany.
- Clinic of Radiology, Medical Faculty, University of Münster, Münster, Germany.
| | - Bettina Pfleiderer
- Clinic of Radiology, Medical Faculty, University of Münster, Münster, Germany
| | - Anke McLeod
- Institute of Radiology and Neuroradiology, Evangelisches Krankenhaus Oldenburg, Universitätsmedizin Oldenburg, Steinweg 13-17, 26122, Oldenburg, Germany
| | - Christian Mathys
- Institute of Radiology and Neuroradiology, Evangelisches Krankenhaus Oldenburg, Universitätsmedizin Oldenburg, Steinweg 13-17, 26122, Oldenburg, Germany
- Research Center Neurosensory Science, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany
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Beynel L, Gura H, Rezaee Z, Ekpo EC, Deng ZD, Joseph JO, Taylor P, Luber B, Lisanby SH. Lessons learned from an fMRI-guided rTMS study on performance in a numerical Stroop task. PLoS One 2024; 19:e0302660. [PMID: 38709724 PMCID: PMC11073721 DOI: 10.1371/journal.pone.0302660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Accepted: 04/04/2024] [Indexed: 05/08/2024] Open
Abstract
The Stroop task is a well-established tool to investigate the influence of competing visual categories on decision making. Neuroimaging as well as rTMS studies have demonstrated the involvement of parietal structures, particularly the intraparietal sulcus (IPS), in this task. Given its reliability, the numerical Stroop task was used to compare the effects of different TMS targeting approaches by Sack and colleagues (Sack AT 2009), who elegantly demonstrated the superiority of individualized fMRI targeting. We performed the present study to test whether fMRI-guided rTMS effects on numerical Stroop task performance could still be observed while using more advanced techniques that have emerged in the last decade (e.g., electrical sham, robotic coil holder system, etc.). To do so we used a traditional reaction time analysis and we performed, post-hoc, a more advanced comprehensive drift diffusion modeling approach. Fifteen participants performed the numerical Stroop task while active or sham 10 Hz rTMS was applied over the region of the right intraparietal sulcus (IPS) showing the strongest functional activation in the Incongruent > Congruent contrast. This target was determined based on individualized fMRI data collected during a separate session. Contrary to our assumption, the classical reaction time analysis did not show any superiority of active rTMS over sham, probably due to confounds such as potential cumulative rTMS effects, and the effect of practice. However, the modeling approach revealed a robust effect of rTMS on the drift rate variable, suggesting differential processing of congruent and incongruent properties in perceptual decision-making, and more generally, illustrating that more advanced computational analysis of performance can elucidate the effects of rTMS on the brain where simpler methods may not.
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Affiliation(s)
- Lysianne Beynel
- Noninvasive Neuromodulation Unit, Experimental Therapeutics Branch, Intramural Research Program, National Institute of Mental Health, Bethesda, Maryland, United States of America
| | - Hannah Gura
- Noninvasive Neuromodulation Unit, Experimental Therapeutics Branch, Intramural Research Program, National Institute of Mental Health, Bethesda, Maryland, United States of America
- Neuroscience Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States Of America
| | - Zeynab Rezaee
- Noninvasive Neuromodulation Unit, Experimental Therapeutics Branch, Intramural Research Program, National Institute of Mental Health, Bethesda, Maryland, United States of America
| | - Ekaete C. Ekpo
- Noninvasive Neuromodulation Unit, Experimental Therapeutics Branch, Intramural Research Program, National Institute of Mental Health, Bethesda, Maryland, United States of America
| | - Zhi-De Deng
- Noninvasive Neuromodulation Unit, Experimental Therapeutics Branch, Intramural Research Program, National Institute of Mental Health, Bethesda, Maryland, United States of America
| | - Janet O. Joseph
- Noninvasive Neuromodulation Unit, Experimental Therapeutics Branch, Intramural Research Program, National Institute of Mental Health, Bethesda, Maryland, United States of America
- Pathobiology Graduate Program, Division of Biology and Medicine, Brown University, Providence, Rhode Island, United States of America
| | - Paul Taylor
- Scientific and Statistical Computing Core, Intramural Research Program, National Institute of Mental Health, Bethesda, Maryland, United States of America
| | - Bruce Luber
- Noninvasive Neuromodulation Unit, Experimental Therapeutics Branch, Intramural Research Program, National Institute of Mental Health, Bethesda, Maryland, United States of America
| | - Sarah H. Lisanby
- Noninvasive Neuromodulation Unit, Experimental Therapeutics Branch, Intramural Research Program, National Institute of Mental Health, Bethesda, Maryland, United States of America
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Freund MC, Chen R, Chen G, Braver TS. Complementary benefits of multivariate and hierarchical models for identifying individual differences in cognitive control. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.24.591032. [PMID: 38712215 PMCID: PMC11071497 DOI: 10.1101/2024.04.24.591032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Understanding individual differences in cognitive control is a central goal in psychology and neuroscience. Reliably measuring these differences, however, has proven extremely challenging, at least when using standard measures in cognitive neuroscience such as response times or task-based fMRI activity. While prior work has pinpointed the source of the issue - the vast amount of cross-trial variability within these measures - no study has rigorously evaluated potential solutions. Here, we do so with one potential way forward: an analytic framework that combines hierarchical Bayesian modeling with multivariate decoding of trial-level fMRI data. Using this framework and longitudinal data from the Dual Mechanisms of Cognitive Control project, we estimated individuals' neural responses associated with cognitive control within a color-word Stroop task, then assessed the reliability of these individuals' responses across a time interval of several months. We show that in many prefrontal and parietal brain regions, test-retest reliability was near maximal, and that only hierarchical models were able to reveal this state of affairs. Further, when compared to traditional univariate contrasts, multivariate decoding enabled individual-level correlations to be estimated with significantly greater precision. We specifically link these improvements in precision to the optimized suppression of cross-trial variability in decoding. Together, these findings not only indicate that cognitive control-related neural responses individuate people in a highly stable manner across time, but also suggest that integrating hierarchical and multivariate models provides a powerful approach for investigating individual differences in cognitive control, one that can effectively address the issue of high-variability measures.
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Affiliation(s)
- Michael C. Freund
- Department of Cognitive, Linguistic, and Psychological Sciences, Brown University
- Department of Psychological & Brain Sciences, Washington University in St. Louis
| | - Ruiqi Chen
- Division of Biology and Biomedical Sciences, Washington University in St. Louis
| | - Gang Chen
- Scientific and Statistical Computing Core, NIMH, NIH, Bethesda, MD, USA
| | - Todd S. Braver
- Department of Cognitive, Linguistic, and Psychological Sciences, Brown University
- Department of Psychological & Brain Sciences, Washington University in St. Louis
- Department of Radiology, Washington University in St. Louis
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6
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Reddy NA, Clements RG, Brooks JCW, Bright MG. Simultaneous cortical, subcortical, and brainstem mapping of sensory activation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.11.589099. [PMID: 38659741 PMCID: PMC11042175 DOI: 10.1101/2024.04.11.589099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
Non-painful tactile sensory stimuli are processed in the cortex, subcortex, and brainstem. Recent functional magnetic resonance imaging (fMRI) studies have highlighted the value of whole-brain, systems-level investigation for examining pain processing. However, whole-brain fMRI studies are uncommon, in part due to challenges with signal to noise when studying the brainstem. Furthermore, the differentiation of small sensory brainstem structures such as the cuneate and gracile nuclei necessitates high resolution imaging. To address this gap in systems-level sensory investigation, we employed a whole-brain, multi-echo fMRI acquisition at 3T with multi-echo independent component analysis (ME-ICA) denoising and brainstem-specific modeling to enable detection of activation across the entire sensory system. In healthy participants, we examined patterns of activity in response to non-painful brushing of the right hand, left hand, and right foot, and found the expected lateralization, with distinct cortical and subcortical responses for upper and lower limb stimulation. At the brainstem level, we were able to differentiate the small, adjacent cuneate and gracile nuclei, corresponding to hand and foot stimulation respectively. Our findings demonstrate that simultaneous cortical, subcortical, and brainstem mapping at 3T could be a key tool to understand the sensory system in both healthy individuals and clinical cohorts with sensory deficits.
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Affiliation(s)
- Neha A. Reddy
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
- Department of Biomedical Engineering, McCormick School of Engineering and Applied Sciences, Northwestern University, Evanston, IL, United States
| | - Rebecca G. Clements
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
- Department of Biomedical Engineering, McCormick School of Engineering and Applied Sciences, Northwestern University, Evanston, IL, United States
| | | | - Molly G. Bright
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
- Department of Biomedical Engineering, McCormick School of Engineering and Applied Sciences, Northwestern University, Evanston, IL, United States
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7
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Vriend C, de Joode NT, Pouwels PJW, Liu F, Otaduy MCG, Pastorello B, Robertson FC, Ipser J, Lee S, Hezel DM, van Meter PE, Batistuzzo MC, Hoexter MQ, Sheshachala K, Narayanaswamy JC, Venkatasubramanian G, Lochner C, Miguel EC, Reddy YCJ, Shavitt RG, Stein DJ, Wall M, Simpson HB, van den Heuvel OA. Age of onset of obsessive-compulsive disorder differentially affects white matter microstructure. Mol Psychiatry 2024; 29:1033-1045. [PMID: 38228890 PMCID: PMC11176057 DOI: 10.1038/s41380-023-02390-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Revised: 12/04/2023] [Accepted: 12/15/2023] [Indexed: 01/18/2024]
Abstract
Previous diffusion MRI studies have reported mixed findings on white matter microstructure alterations in obsessive-compulsive disorder (OCD), likely due to variation in demographic and clinical characteristics, scanning methods, and underpowered samples. The OCD global study was created across five international sites to overcome these challenges by harmonizing data collection to identify consistent brain signatures of OCD that are reproducible and generalizable. Single-shell diffusion measures (e.g., fractional anisotropy), multi-shell Neurite Orientation Dispersion and Density Imaging (NODDI) and fixel-based measures, were extracted from skeletonized white matter tracts in 260 medication-free adults with OCD and 252 healthy controls. We additionally performed structural connectome analysis. We compared cases with controls and cases with early (<18) versus late (18+) OCD onset using mixed-model and Bayesian multilevel analysis. Compared with healthy controls, adult OCD individuals showed higher fiber density in the sagittal stratum (B[SE] = 0.10[0.05], P = 0.04) and credible evidence for higher fiber density in several other tracts. When comparing early (n = 145) and late-onset (n = 114) cases, converging evidence showed lower integrity of the posterior thalamic radiation -particularly radial diffusivity (B[SE] = 0.28[0.12], P = 0.03)-and lower global efficiency of the structural connectome (B[SE] = 15.3[6.6], P = 0.03) in late-onset cases. Post-hoc analyses indicated divergent direction of effects of the two OCD groups compared to healthy controls. Age of OCD onset differentially affects the integrity of thalamo-parietal/occipital tracts and the efficiency of the structural brain network. These results lend further support for the role of the thalamus and its afferent fibers and visual attentional processes in the pathophysiology of OCD.
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Affiliation(s)
- Chris Vriend
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Psychiatry, and Department of Anatomy and Neuroscience, de Boelelaan 1117, Amsterdam, the Netherlands.
- Compulsivity, Impulsivity and Attention, Amsterdam Neuroscience, de Boelelaan 1117, Amsterdam, the Netherlands.
| | - Niels T de Joode
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Psychiatry, and Department of Anatomy and Neuroscience, de Boelelaan 1117, Amsterdam, the Netherlands
- Compulsivity, Impulsivity and Attention, Amsterdam Neuroscience, de Boelelaan 1117, Amsterdam, the Netherlands
| | - Petra J W Pouwels
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, de Boelelaan 1117, Amsterdam, the Netherlands
- Brain Imaging, Amsterdam Neuroscience, de Boelelaan 1117, Amsterdam, the Netherlands
| | - Feng Liu
- Columbia University Irving Medical Center, Columbia University, New York, NY, 10032, USA
- The New York State Psychiatric Institute, New York, NY, 10032, USA
| | - Maria C G Otaduy
- LIM44, Hospital das Clinicas HCFMUSP, Instituto e Departamento de Radiologia da Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil
| | - Bruno Pastorello
- LIM44, Hospital das Clinicas HCFMUSP, Instituto e Departamento de Radiologia da Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil
| | - Frances C Robertson
- Cape Universities Body Imaging Centre, University of Cape Town, Cape Town, South Africa
| | - Jonathan Ipser
- SAMRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry & Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Seonjoo Lee
- Columbia University Irving Medical Center, Columbia University, New York, NY, 10032, USA
- The New York State Psychiatric Institute, New York, NY, 10032, USA
| | - Dianne M Hezel
- Columbia University Irving Medical Center, Columbia University, New York, NY, 10032, USA
- The New York State Psychiatric Institute, New York, NY, 10032, USA
| | - Page E van Meter
- Columbia University Irving Medical Center, Columbia University, New York, NY, 10032, USA
- The New York State Psychiatric Institute, New York, NY, 10032, USA
| | - Marcelo C Batistuzzo
- Obsessive-Compulsive Spectrum Disorders Program, LIM23, Hospital das Clinicas HCFMUSP, Instituto & Departamento de Psiquiatria da Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil
- Department of Methods and Techniques in Psychology, Pontifical Catholic University, Sao Paulo, SP, Brazil
| | - Marcelo Q Hoexter
- LIM44, Hospital das Clinicas HCFMUSP, Instituto e Departamento de Radiologia da Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil
| | - Karthik Sheshachala
- National Institute of Mental Health & Neurosciences (NIMHANS), Bangalore, India
| | | | | | - Christine Lochner
- SAMRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry, Stellenbosch University, Stellenbosch, South Africa
| | - Euripedes C Miguel
- Obsessive-Compulsive Spectrum Disorders Program, LIM23, Hospital das Clinicas HCFMUSP, Instituto & Departamento de Psiquiatria da Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil
| | - Y C Janardhan Reddy
- National Institute of Mental Health & Neurosciences (NIMHANS), Bangalore, India
| | - Roseli G Shavitt
- Obsessive-Compulsive Spectrum Disorders Program, LIM23, Hospital das Clinicas HCFMUSP, Instituto & Departamento de Psiquiatria da Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil
| | - Dan J Stein
- SAMRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry, Stellenbosch University, Stellenbosch, South Africa
| | - Melanie Wall
- Columbia University Irving Medical Center, Columbia University, New York, NY, 10032, USA
- The New York State Psychiatric Institute, New York, NY, 10032, USA
| | - Helen Blair Simpson
- Columbia University Irving Medical Center, Columbia University, New York, NY, 10032, USA
- The New York State Psychiatric Institute, New York, NY, 10032, USA
| | - Odile A van den Heuvel
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Psychiatry, and Department of Anatomy and Neuroscience, de Boelelaan 1117, Amsterdam, the Netherlands
- Compulsivity, Impulsivity and Attention, Amsterdam Neuroscience, de Boelelaan 1117, Amsterdam, the Netherlands
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Thye M, Hoffman P, Mirman D. The neural basis of naturalistic semantic and social cognition. Sci Rep 2024; 14:6796. [PMID: 38514738 PMCID: PMC10957894 DOI: 10.1038/s41598-024-56897-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Accepted: 03/11/2024] [Indexed: 03/23/2024] Open
Abstract
Decoding social environments and engaging meaningfully with other people are critical aspects of human cognition. Multiple cognitive systems, including social and semantic cognition, work alongside each other to support these processes. This study investigated shared processing between social and semantic systems using neuroimaging data collected during movie-viewing, which captures the multimodal environment in which social knowledge is exchanged. Semantic and social content from movie events (event-level) and movie transcripts (word-level) were used in parametric modulation analyses to test (1) the degree to which semantic and social information is processed within each respective network and (2) engagement of the same cross-network regions or the same domain-general hub located within the semantic network during semantic and social processing. Semantic word and event-level content engaged the same fronto-temporo-parietal network and a portion of the semantic hub in the anterior temporal lobe (ATL). Social word and event-level content engaged the supplementary motor area and right angular gyrus within the social network, but only social words engaged the domain-general semantic hub in left ATL. There was evidence of shared processing between the social and semantic systems in the dorsolateral portion of right ATL which was engaged by word and event-level semantic and social content. Overlap between the semantic and social word and event results was highly variable within and across participants, with the most consistent loci of overlap occurring in left inferior frontal, bilateral precentral and supramarginal gyri for social and semantic words and in bilateral superior temporal gyrus extending from ATL posteriorly into supramarginal gyri for social and semantic events. These results indicate a complex pattern of shared and distinct regions for social and semantic cognition during naturalistic processing. PROTOCOL REGISTRATION: The stage 1 protocol for this Registered Report was accepted in principle on October 11, 2022. The protocol, as accepted by the journal, can be found at: https://doi.org/10.17605/OSF.IO/ACWQY .
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Affiliation(s)
- Melissa Thye
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.
| | - Paul Hoffman
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Daniel Mirman
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
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Bishay S, Robb WH, Schwartz TM, Smith DS, Lee LH, Lynn CJ, Clark TL, Jefferson AL, Warner JL, Rosenthal EL, Murphy BA, Hohman TJ, Koran MEI. Frontal and anterior temporal hypometabolism post chemoradiation in head and neck cancer: A real-world PET study. J Neuroimaging 2024; 34:211-216. [PMID: 38148283 DOI: 10.1111/jon.13181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 11/20/2023] [Accepted: 12/11/2023] [Indexed: 12/28/2023] Open
Abstract
BACKGROUND AND PURPOSE Adverse neurological effects after cancer therapy are common, but biomarkers to diagnose, monitor, or risk stratify patients are still not validated or used clinically. An accessible imaging method, such as fluorodeoxyglucose positron emission tomography (FDG PET) of the brain, could meet this gap and serve as a biomarker for functional brain changes. We utilized FDG PET to evaluate which brain regions are most susceptible to altered glucose metabolism after chemoradiation in patients with head and neck cancer (HNCa). METHODS Real-world FDG PET images were acquired as standard of care before and after chemoradiation for HNCa in 68 patients. Linear mixed-effects voxelwise models assessed changes after chemoradiation in cerebral glucose metabolism quantified with standardized uptake value ratio (SUVR), covarying for follow-up time and patient demographics. RESULTS Voxelwise analysis revealed two large clusters of decreased glucose metabolism in the medial frontal and polar temporal cortices following chemoradiation, with decreases of approximately 5% SUVR after therapy. CONCLUSIONS These findings provide evidence that standard chemoradiation for HNCa can lead to decreased neuronal glucose metabolism, contributing to literature emphasizing the vulnerability of the frontal and anterior temporal lobes, especially in HNCa, where these areas may be particularly vulnerable to indirect radiation-induced injury. FDG PET shows promise as a sensitive biomarker for assessing these changes.
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Affiliation(s)
- Steven Bishay
- School of Medicine, Vanderbilt University, Nashville, Tennessee, USA
| | - W Hudson Robb
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Trent M Schwartz
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - David S Smith
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt University Institute of Imaging Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Lok Hin Lee
- School of Medicine, Vanderbilt University, Nashville, Tennessee, USA
| | - Cynthia J Lynn
- Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Tammy L Clark
- Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Angela L Jefferson
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Jeremy L Warner
- Department of Medicine, Brown University, Providence, Rhode Island, USA
- Lifespan Cancer Institute, Providence, Rhode Island, USA
| | - Eben L Rosenthal
- Department of Otolaryngology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Barbara A Murphy
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Timothy J Hohman
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Mary Ellen I Koran
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt University Institute of Imaging Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA
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10
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Kirk‐Provencher KT, Hakimi RH, Andereas K, Penner AE, Gowin JL. Neural response to threat and reward among young adults at risk for alcohol use disorder. Addict Biol 2024; 29:e13378. [PMID: 38334006 PMCID: PMC10898840 DOI: 10.1111/adb.13378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 01/15/2024] [Accepted: 01/20/2024] [Indexed: 02/10/2024]
Abstract
Alcohol use disorder (AUD) is heritable. Thus, young adults with positive family histories represent an at-risk group relative to those without a family history, and if studied at a time when both groups have similar levels of alcohol use, it provides an opportunity to identify neural processing patterns associated with risk for AUD. Previous studies have shown that diminished response to potential reward is associated with genetic risk for AUD, but it is unclear how threat may modulate this response. We used a modified Monetary Incentive Delay task during fMRI to examine neural correlates of the interaction between threat and reward anticipation in a sample of young adults with (n = 31) and without (n = 44) family histories of harmful alcohol use. We found an interaction (p = 0.048) between cue and group in the right nucleus accumbens where the family history positive group showed less differentiation to the anticipation of gaining $5 and losing $5 relative to gaining $0. The family history-positive group also reported less excitement for trials to gain $5 relative to gaining $0 (p < 0.001). Family history-positive individuals showed less activation in the left insula during both safe and threat blocks compared to family history-negative individuals (p = 0.005), but the groups did not differ as a function of threat (p > 0.70). Young adults with, relative to without, enriched risk for AUD may have diminished reward processing via both neural and behavioural markers to potential rewarding and negative consequences. Neural response to threat may not be a contributing factor to risk at this stage.
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Affiliation(s)
- Katelyn T. Kirk‐Provencher
- Department of Radiology, School of MedicineUniversity of Colorado Anschutz Medical CampusAuroraColoradoUSA
| | - Rosa H. Hakimi
- Department of Radiology, School of MedicineUniversity of Colorado Anschutz Medical CampusAuroraColoradoUSA
| | - Keinada Andereas
- Department of Radiology, School of MedicineUniversity of Colorado Anschutz Medical CampusAuroraColoradoUSA
| | - Anne E. Penner
- Department of Psychiatry, School of MedicineUniversity of Colorado Anschutz Medical CampusAuroraColoradoUSA
| | - Joshua L. Gowin
- Department of Radiology, School of MedicineUniversity of Colorado Anschutz Medical CampusAuroraColoradoUSA
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11
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Chen DY, Di X, Yu X, Biswal BB. The significance and limited influence of cerebrovascular reactivity on age and sex effects in task- and resting-state brain activity. Cereb Cortex 2024; 34:bhad448. [PMID: 38212284 PMCID: PMC10832986 DOI: 10.1093/cercor/bhad448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 10/31/2023] [Indexed: 01/13/2024] Open
Abstract
Functional MRI measures the blood-oxygen-level dependent signals, which provide an indirect measure of neural activity mediated by neurovascular responses. Cerebrovascular reactivity affects both task-induced and resting-state blood-oxygen-level dependent activity and may confound inter-individual effects, such as those related to aging and biological sex. We examined a large dataset containing breath-holding, checkerboard, and resting-state tasks. We used the breath-holding task to measure cerebrovascular reactivity, used the checkerboard task to obtain task-based activations, and quantified resting-state activity with amplitude of low-frequency fluctuations and regional homogeneity. We hypothesized that cerebrovascular reactivity would be correlated with blood-oxygen-level dependent measures and that accounting for these correlations would result in better estimates of age and sex effects. We found that cerebrovascular reactivity was correlated with checkerboard task activations in the visual cortex and with amplitude of low-frequency fluctuations and regional homogeneity in widespread fronto-parietal regions, as well as regions with large vessels. We also found significant age and sex effects in cerebrovascular reactivity, some of which overlapped with those observed in amplitude of low-frequency fluctuations and regional homogeneity. However, correcting for the effects of cerebrovascular reactivity had very limited influence on the estimates of age and sex. Our results highlight the limitations of accounting for cerebrovascular reactivity with the current breath-holding task.
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Affiliation(s)
- Donna Y Chen
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ 07102, United States
- Rutgers Biomedical and Health Sciences, Rutgers School of Graduate Studies, Newark, NJ 08901, United States
| | - Xin Di
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ 07102, United States
| | - Xin Yu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA 02114, United States
| | - Bharat B Biswal
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ 07102, United States
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12
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Ben-Zion Z, Korem N, Fine NB, Katz S, Siddhanta M, Funaro MC, Duek O, Spiller TR, Danböck SK, Levy I, Harpaz-Rotem I. Structural Neuroimaging of Hippocampus and Amygdala Subregions in Posttraumatic Stress Disorder: A Scoping Review. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2024; 4:120-134. [PMID: 38298789 PMCID: PMC10829655 DOI: 10.1016/j.bpsgos.2023.07.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 06/28/2023] [Accepted: 07/02/2023] [Indexed: 02/02/2024] Open
Abstract
Numerous studies have explored the relationship between posttraumatic stress disorder (PTSD) and the hippocampus and the amygdala because both regions are implicated in the disorder's pathogenesis and pathophysiology. Nevertheless, those key limbic regions consist of functionally and cytoarchitecturally distinct substructures that may play different roles in the etiology of PTSD. Spurred by the availability of automatic segmentation software, structural neuroimaging studies of human hippocampal and amygdala subregions have proliferated in recent years. Here, we present a preregistered scoping review of the existing structural neuroimaging studies of the hippocampus and amygdala subregions in adults diagnosed with PTSD. A total of 3513 studies assessing subregion volumes were identified, 1689 of which were screened, and 21 studies were eligible for this review (total N = 2876 individuals). Most studies examined hippocampal subregions and reported decreased CA1, CA3, dentate gyrus, and subiculum volumes in PTSD. Fewer studies investigated amygdala subregions and reported altered lateral, basal, and central nuclei volumes in PTSD. This review further highlights the conceptual and methodological limitations of the current literature and identifies future directions to increase understanding of the distinct roles of hippocampal and amygdalar subregions in posttraumatic psychopathology.
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Affiliation(s)
- Ziv Ben-Zion
- Yale School of Medicine, Yale University, New Haven, Connecticut
- US Department of Veterans Affairs National Center for PTSD, Clinical Neuroscience Division, VA Connecticut Healthcare System, West Haven, Connecticut
- Wu Tsai Institute, Yale University, New Haven, Connecticut
- Department of Psychology, Yale University, New Haven, Connecticut
| | - Nachshon Korem
- Yale School of Medicine, Yale University, New Haven, Connecticut
- US Department of Veterans Affairs National Center for PTSD, Clinical Neuroscience Division, VA Connecticut Healthcare System, West Haven, Connecticut
| | - Naomi B Fine
- Sagol Brain Institute Tel-Aviv, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
- Faculty of Social Sciences, School of Psychological Science, Tel Aviv University, Tel Aviv, Israel
| | - Sophia Katz
- Yale School of Medicine, Yale University, New Haven, Connecticut
| | - Megha Siddhanta
- Yale School of Medicine, Yale University, New Haven, Connecticut
| | - Melissa C Funaro
- Harvey Cushing/John Hay Whitney Medical Library, Yale University, New Haven, Connecticut
| | - Or Duek
- Yale School of Medicine, Yale University, New Haven, Connecticut
- US Department of Veterans Affairs National Center for PTSD, Clinical Neuroscience Division, VA Connecticut Healthcare System, West Haven, Connecticut
- Department of Epidemiology, Biostatistics and Community Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel
| | - Tobias R Spiller
- Yale School of Medicine, Yale University, New Haven, Connecticut
- US Department of Veterans Affairs National Center for PTSD, Clinical Neuroscience Division, VA Connecticut Healthcare System, West Haven, Connecticut
- Department of Consultation-Liaison Psychiatry and Psychosomatic Medicine, University Hospital Zürich, University of Zürich, Zürich, Switzerland
| | - Sarah K Danböck
- Yale School of Medicine, Yale University, New Haven, Connecticut
- Division of Clinical Psychology and Psychopathology, Department of Psychology, Paris London University of Salzburg, Salzburg, Austria
| | - Ifat Levy
- Yale School of Medicine, Yale University, New Haven, Connecticut
- Wu Tsai Institute, Yale University, New Haven, Connecticut
- Department of Psychology, Yale University, New Haven, Connecticut
| | - Ilan Harpaz-Rotem
- Yale School of Medicine, Yale University, New Haven, Connecticut
- US Department of Veterans Affairs National Center for PTSD, Clinical Neuroscience Division, VA Connecticut Healthcare System, West Haven, Connecticut
- Wu Tsai Institute, Yale University, New Haven, Connecticut
- Department of Psychology, Yale University, New Haven, Connecticut
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13
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Aarts I, Vriend C, van den Heuvel OA, Thomaes K. Brain activation during an emotional task in participants with PTSD and borderline and/or cluster C personality disorders. Neuroimage Clin 2023; 41:103554. [PMID: 38128160 PMCID: PMC10777111 DOI: 10.1016/j.nicl.2023.103554] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 12/10/2023] [Accepted: 12/14/2023] [Indexed: 12/23/2023]
Abstract
INTRODUCTION Although comorbidity of post-traumatic stress disorder (PTSD) with borderline personality disorder (BPD) and/or cluster C personality disorders (CPD) is common, neural correlates of this comorbidity are unknown. METHODS We acquired functional MRI scans during an emotional face task in participants with PTSD + CPD (n = 34), PTSD + BPD (n = 24), PTSD + BPD + CPD (n = 18) and controls (n = 30). We used ANCOVAs and Bayesian analyses on specific ROIs in a fearful vs. scrambled faces contrast. We also investigated associations with clinical measures. RESULTS There were no robust differences in brain activation between the groups with ANCOVAs. Transdiagnostically, we found a negative association between severity of dissociation and right insula and right dmPFC activation, and emotion regulation problems with right dmPFC activation. Bayesian analyses showed credible evidence for higher activation in all ROIs in the PTSD + BPD + CPD group compared to PTSD + BPD and PTSD + CPD. DISCUSSION Our Bayesian and correlation analyses support new dimensional conceptualizations of personality disorders.
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Affiliation(s)
- Inga Aarts
- Sinai Centrum, Arkin, Amstelveen, the Netherlands; Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Psychiatry, Department of Anatomy and Neurosciences, Boelelaan 1117, Amsterdam, the Netherlands.
| | - Chris Vriend
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Psychiatry, Department of Anatomy and Neurosciences, Boelelaan 1117, Amsterdam, the Netherlands; Amsterdam Neuroscience, Compulsivity, Impulsivity & Attention program, Amsterdam, the Netherlands
| | - Odile A van den Heuvel
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Psychiatry, Department of Anatomy and Neurosciences, Boelelaan 1117, Amsterdam, the Netherlands; Amsterdam Neuroscience, Compulsivity, Impulsivity & Attention program, Amsterdam, the Netherlands
| | - Kathleen Thomaes
- Sinai Centrum, Arkin, Amstelveen, the Netherlands; Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Psychiatry, Department of Anatomy and Neurosciences, Boelelaan 1117, Amsterdam, the Netherlands
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14
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Sundermann B, Feldmann R, Mathys C, Rau JMH, Garde S, Braje A, Weglage J, Pfleiderer B. Functional connectivity of cognition-related brain networks in adults with fetal alcohol syndrome. BMC Med 2023; 21:496. [PMID: 38093292 PMCID: PMC10720228 DOI: 10.1186/s12916-023-03208-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 12/01/2023] [Indexed: 12/17/2023] Open
Abstract
BACKGROUND Fetal alcohol syndrome (FAS) can result in cognitive dysfunction. Cognitive functions affected are subserved by few functional brain networks. Functional connectivity (FC) in these networks can be assessed with resting-state functional MRI (rs-fMRI). Alterations of FC have been reported in children and adolescents prenatally exposed to alcohol. Previous reports varied substantially regarding the exact nature of findings. The purpose of this study was to assess FC of cognition-related networks in young adults with FAS. METHODS Cross-sectional rs-fMRI study in participants with FAS (n = 39, age: 20.9 ± 3.4 years) and healthy participants without prenatal alcohol exposure (n = 44, age: 22.2 ± 3.4 years). FC was calculated as correlation between cortical regions in ten cognition-related sub-networks. Subsequent modelling of overall FC was based on linear models comparing FC between FAS and controls. Results were subjected to a hierarchical statistical testing approach, first determining whether there is any alteration of FC in FAS in the full cognitive connectome, subsequently resolving these findings to the level of either FC within each network or between networks based on the Higher Criticism (HC) approach for detecting rare and weak effects in high-dimensional data. Finally, group differences in single connections were assessed using conventional multiple-comparison correction. In an additional exploratory analysis, dynamic FC states were assessed. RESULTS Comparing FAS participants with controls, we observed altered FC of cognition-related brain regions globally, within 7 out of 10 networks, and between networks employing the HC statistic. This was most obvious in attention-related network components. Findings also spanned across subcomponents of the fronto-parietal control and default mode networks. None of the single FC alterations within these networks yielded statistical significance in the conventional high-resolution analysis. The exploratory time-resolved FC analysis did not show significant group differences of dynamic FC states. CONCLUSIONS FC in cognition-related networks was altered in adults with FAS. Effects were widely distributed across networks, potentially reflecting the diversity of cognitive deficits in FAS. However, no altered single connections could be determined in the most detailed analysis level. Findings were pronounced in networks in line with attentional deficits previously reported.
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Affiliation(s)
- Benedikt Sundermann
- Institute of Radiology and Neuroradiology, Evangelisches Krankenhaus Oldenburg, Universitätsmedizin Oldenburg, Oldenburg, Germany
- Clinic of Radiology, Medical Faculty, University of Münster, Albert- Schweitzer-Campus 1, Building A1, 48149, Münster, Germany
- Research Center Neurosensory Science, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany
| | - Reinhold Feldmann
- Department of General Pediatrics, University Hospital Münster, Münster, Germany
| | - Christian Mathys
- Institute of Radiology and Neuroradiology, Evangelisches Krankenhaus Oldenburg, Universitätsmedizin Oldenburg, Oldenburg, Germany
- Research Center Neurosensory Science, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany
| | - Johanna M H Rau
- Clinic of Radiology, Medical Faculty, University of Münster, Albert- Schweitzer-Campus 1, Building A1, 48149, Münster, Germany
- Department of Neurology With Institute of Translational Neurology, University Hospital Münster, Münster, Germany
| | - Stefan Garde
- Clinic of Radiology, Medical Faculty, University of Münster, Albert- Schweitzer-Campus 1, Building A1, 48149, Münster, Germany
| | - Anna Braje
- Clinic of Radiology, Medical Faculty, University of Münster, Albert- Schweitzer-Campus 1, Building A1, 48149, Münster, Germany
| | - Josef Weglage
- Department of General Pediatrics, University Hospital Münster, Münster, Germany
| | - Bettina Pfleiderer
- Clinic of Radiology, Medical Faculty, University of Münster, Albert- Schweitzer-Campus 1, Building A1, 48149, Münster, Germany.
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15
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Reddy NA, Zvolanek KM, Moia S, Caballero-Gaudes C, Bright MG. Denoising task-correlated head motion from motor-task fMRI data with multi-echo ICA. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.19.549746. [PMID: 37503125 PMCID: PMC10370165 DOI: 10.1101/2023.07.19.549746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Motor-task functional magnetic resonance imaging (fMRI) is crucial in the study of several clinical conditions, including stroke and Parkinson's disease. However, motor-task fMRI is complicated by task-correlated head motion, which can be magnified in clinical populations and confounds motor activation results. One method that may mitigate this issue is multi-echo independent component analysis (ME-ICA), which has been shown to separate the effects of head motion from the desired BOLD signal but has not been tested in motor-task datasets with high amounts of motion. In this study, we collected an fMRI dataset from a healthy population who performed a hand grasp task with and without task-correlated amplified head motion to simulate a motor-impaired population. We analyzed these data using three models: single-echo (SE), multi-echo optimally combined (ME-OC), and ME-ICA. We compared the models' performance in mitigating the effects of head motion on the subject level and group level. On the subject level, ME-ICA better dissociated the effects of head motion from the BOLD signal and reduced noise. Both ME models led to increased t-statistics in brain motor regions. In scans with high levels of motion, ME-ICA additionally mitigated artifacts and increased stability of beta coefficient estimates, compared to SE. On the group level, all three models produced activation clusters in expected motor areas in scans with both low and high motion, indicating that group-level averaging may also sufficiently resolve motion artifacts that vary by subject. These findings demonstrate that ME-ICA is a useful tool for subject-level analysis of motor-task data with high levels of task-correlated head motion. The improvements afforded by ME-ICA are critical to improve reliability of subject-level activation maps for clinical populations in which group-level analysis may not be feasible or appropriate, for example in a chronic stroke cohort with varying stroke location and degree of tissue damage.
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Affiliation(s)
- Neha A. Reddy
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
- Department of Biomedical Engineering, McCormick School of Engineering and Applied Sciences, Northwestern University, Evanston, IL, United States
| | - Kristina M. Zvolanek
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
- Department of Biomedical Engineering, McCormick School of Engineering and Applied Sciences, Northwestern University, Evanston, IL, United States
| | - Stefano Moia
- Basque Center on Cognition, Brain and Language, Donostia, Gipuzkoa, Spain
- Neuro-X Institute, École polytechnique fédérale de Lausanne, Geneva, Switzerland
- Department of Radiology and Medical Informatics (DRIM), Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | | | - Molly G. Bright
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
- Department of Biomedical Engineering, McCormick School of Engineering and Applied Sciences, Northwestern University, Evanston, IL, United States
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16
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Boulakis PA, Mortaheb S, van Calster L, Majerus S, Demertzi A. Whole-Brain Deactivations Precede Uninduced Mind-Blanking Reports. J Neurosci 2023; 43:6807-6815. [PMID: 37643862 PMCID: PMC10552942 DOI: 10.1523/jneurosci.0696-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Revised: 07/11/2023] [Accepted: 08/07/2023] [Indexed: 08/31/2023] Open
Abstract
Mind-blanking (MB) is termed as the inability to report our immediate-past mental content. In contrast to mental states with reportable content, such as mind-wandering or sensory perceptions, the neural correlates of MB started getting elucidated only recently. A notable particularity that pertains to MB studies is the way MB is instructed for reporting, like by deliberately asking participants to "empty their minds." Such instructions were shown to induce fMRI activations in frontal brain regions, typically associated with metacognition and self-evaluative processes, suggesting that MB may be a result of intentional mental content suppression. Here, we aim at examining this hypothesis by determining the neural correlates of MB without induction. Using fMRI combined with experience-sampling in 31 participants (22 female), univariate analysis of MB reports revealed deactivations in occipital, frontal, parietal, and thalamic areas, but no activations in prefrontal regions. These findings were confirmed using Bayesian region-of-interest analysis on areas previously shown to be implicated in induced MB, where we report evidence for frontal deactivations during MB reports compared with other mental states. Contrast analysis between reports of MB and content-oriented mental states also revealed deactivations in the left angular gyrus. We propose that these effects characterize a neuronal profile of MB, where key thalamocortical nodes are unable to communicate and formulate reportable content. Collectively, we show that study instructions for MB lead to differential neural activation. These results provide mechanistic insights linked to the phenomenology of MB and point to the possibility of MB being expressed in different forms.SIGNIFICANCE STATEMENT This study explores how brain activity changes when individuals report unidentifiable thoughts, a phenomenon known as mind-blanking (MB). It aims to detect changes in brain activations and deactivations when MB is reported spontaneously, as opposed to the neural responses that have been previously reported when MB is induced. By means of brain imaging and experience-sampling, the study points to reduced brain activity in a wide number of regions, including those mesio-frontally which were previously detected as activated during induced MB. These results enhance our understanding of the complexity of spontaneous thinking and contribute to broader discussions on consciousness and reportable experience.
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Affiliation(s)
- Paradeisios Alexandros Boulakis
- Physiology of Cognition Lab, GIGA-Cyclotron Research Center In Vivo Imaging, University of Liège, Liège 4000, Belgium
- National Fund for Scientific Research (FNRS), Brussels 1000, Belgium
| | - Sepehr Mortaheb
- Physiology of Cognition Lab, GIGA-Cyclotron Research Center In Vivo Imaging, University of Liège, Liège 4000, Belgium
- National Fund for Scientific Research (FNRS), Brussels 1000, Belgium
| | - Laurens van Calster
- National Fund for Scientific Research (FNRS), Brussels 1000, Belgium
- Psychology and Neuroscience of Cognition Research Unit, University of Liège, Liège 4000, Belgium
- GIGA-Cyclotron Research Center In Vivo Imaging, University of Liège, Liège 4000, Belgium
- Department of Neurology, Cliniques Universitaires Saint-Luc, Brussels 1200, Belgium
| | - Steve Majerus
- National Fund for Scientific Research (FNRS), Brussels 1000, Belgium
- Psychology and Neuroscience of Cognition Research Unit, University of Liège, Liège 4000, Belgium
- GIGA-Cyclotron Research Center In Vivo Imaging, University of Liège, Liège 4000, Belgium
| | - Athena Demertzi
- Physiology of Cognition Lab, GIGA-Cyclotron Research Center In Vivo Imaging, University of Liège, Liège 4000, Belgium
- National Fund for Scientific Research (FNRS), Brussels 1000, Belgium
- Psychology and Neuroscience of Cognition Research Unit, University of Liège, Liège 4000, Belgium
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