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Trambaiolli L, Maffei C, Dann E, Biazoli C, Bezgin G, Yendiki A, Haber S. Translation of monosynaptic circuits underlying amygdala fMRI neurofeedback training. Neuropsychopharmacology 2024:10.1038/s41386-024-01944-w. [PMID: 39103495 DOI: 10.1038/s41386-024-01944-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/04/2024] [Revised: 07/16/2024] [Accepted: 07/23/2024] [Indexed: 08/07/2024]
Abstract
fMRI neurofeedback using autobiographical memory recall to upregulate the amygdala is associated with resting-state functional connectivity (rsFC) changes between the amygdala and the salience and default mode networks (SN and DMN, respectively). We hypothesize the existence of anatomical circuits underlying these rsFC changes. Using a cross-species brain parcellation, we identified in non-human primates locations homologous to the regions of interest (ROIs) from studies showing pre-to-post-neurofeedback changes in rsFC with the left amygdala. We injected bidirectional tracers in the basolateral, lateral, and central amygdala nuclei of adult macaques and used bright- and dark-field microscopy to identify cells and axon terminals in each ROI (SN: anterior cingulate, ventrolateral, and insular cortices; DMN: temporal pole, middle frontal gyrus, angular gyrus, precuneus, posterior cingulate cortex, parahippocampal gyrus, hippocampus, and thalamus). We also performed additional injections in specific ROIs to validate the results following amygdala injections and delineate potential disynaptic pathways. Finally, we used high-resolution diffusion MRI data from four post-mortem macaque brains and one in vivo human brain to translate our findings to the neuroimaging domain. Different amygdala nuclei had significant monosynaptic connections with all the SN and DMN ipsilateral ROIs. Amygdala connections with the DMN contralateral ROIs are disynaptic through the hippocampus and parahippocampal gyrus. Diffusion MRI in both species benefitted from using the ground-truth tracer data to validate its findings, as we identified false-negative ipsilateral and false-positive contralateral connectivity results. This study provides the foundation for future causal investigations of amygdala neurofeedback modulation of the SN and DMN through these anatomic connections.
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Affiliation(s)
- Lucas Trambaiolli
- McLean Hospital, Harvard Medical School, Boston, MA, USA.
- Department of Pharmacology and Physiology, University of Rochester, Rochester, NY, USA.
| | - Chiara Maffei
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Evan Dann
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Claudinei Biazoli
- Center for Mathematics Computation and Cognition, Federal University of ABC, Santo André, Brazil
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK
| | - Gleb Bezgin
- Neuroinformatics for Personalized Medicine lab, Montreal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Anastasia Yendiki
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Suzanne Haber
- McLean Hospital, Harvard Medical School, Boston, MA, USA.
- Department of Pharmacology and Physiology, University of Rochester, Rochester, NY, USA.
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2
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Ghane M, Trambaiolli L, Bertocci MA, Martinez-Rivera FJ, Chase HW, Brady T, Skeba A, Graur S, Bonar L, Iyengar S, Quirk GJ, Rasmussen SA, Haber SN, Phillips ML. Specific Patterns of Endogenous Functional Connectivity Are Associated With Harm Avoidance in Obsessive-Compulsive Disorder. Biol Psychiatry 2024; 96:137-146. [PMID: 38336216 DOI: 10.1016/j.biopsych.2023.12.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 11/11/2023] [Accepted: 12/06/2023] [Indexed: 02/12/2024]
Abstract
BACKGROUND Individuals with obsessive-compulsive disorder (OCD) show persistent avoidance behaviors, often in the absence of actual threat. Quality-of-life costs and heterogeneity support the need for novel brain-behavior intervention targets. Informed by mechanistic and anatomical studies of persistent avoidance in rodents and nonhuman primates, our goal was to test whether connections within a hypothesized persistent avoidance-related network predicted OCD-related harm avoidance (HA), a trait measure of persistent avoidance. We hypothesized that 1) HA, not an OCD diagnosis, would be associated with altered endogenous connectivity in at least one connection in the network; 2) HA-specific findings would be robust to comorbid symptoms; and 3) reliable findings would replicate in a holdout testing subsample. METHODS Using resting-state functional connectivity magnetic resonance imaging, cross-validated elastic net for feature selection, and Poisson generalized linear models, we tested which connections significantly predicted HA in our training subsample (n = 73; 71.8% female; healthy control group n = 36, OCD group n = 37); robustness to comorbidities; and replicability in a testing subsample (n = 30; 56.7% female; healthy control group n = 15, OCD group n = 15). RESULTS Stronger inverse connectivity between the right dorsal anterior cingulate cortex and right basolateral amygdala and stronger positive connectivity between the right ventral anterior insula and left ventral striatum were associated with greater HA across groups. Network connections did not discriminate OCD diagnostic status or predict HA-correlated traits, suggesting sensitivity to trait HA. The dorsal anterior cingulate cortex-basolateral amygdala relationship was robust to controlling for comorbidities and medication in individuals with OCD and was also predictive of HA in our testing subsample. CONCLUSIONS Stronger inverse dorsal anterior cingulate cortex-basolateral amygdala connectivity was robustly and reliably associated with HA across groups and in OCD. Results support the relevance of a cross-species persistent avoidance-related network to OCD, with implications for precision-based approaches and treatment.
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Affiliation(s)
- Merage Ghane
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.
| | - Lucas Trambaiolli
- Department of Psychiatry, McLean Hospital, Harvard Medical School, Boston, Massachusetts
| | - Michele A Bertocci
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | | | - Henry W Chase
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Tyler Brady
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Alex Skeba
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Simona Graur
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Lisa Bonar
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Satish Iyengar
- Department of Statistics, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Gregory J Quirk
- School of Medicine, University of Puerto Rico, San Juan, Puerto Rico
| | - Steven A Rasmussen
- Department of Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Providence, Rhode Island
| | - Suzanne N Haber
- Department of Psychiatry, McLean Hospital, Harvard Medical School, Boston, Massachusetts; School of Medicine and Dentistry, University of Rochester Medical Center, Rochester, New York
| | - Mary L Phillips
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
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3
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Heij J, van der Zwaag W, Knapen T, Caan MWA, Forstman B, Veltman DJ, van Wingen G, Aghajani M. Quantitative MRI at 7-Tesla reveals novel frontocortical myeloarchitecture anomalies in major depressive disorder. Transl Psychiatry 2024; 14:262. [PMID: 38902245 PMCID: PMC11190139 DOI: 10.1038/s41398-024-02976-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 05/31/2024] [Accepted: 06/04/2024] [Indexed: 06/22/2024] Open
Abstract
Whereas meta-analytical data highlight abnormal frontocortical macrostructure (thickness/surface area/volume) in Major Depressive Disorder (MDD), the underlying microstructural processes remain uncharted, due to the use of conventional MRI scanners and acquisition techniques. We uniquely combined Ultra-High Field MRI at 7.0 Tesla with Quantitative Imaging to map intracortical myelin (proxied by longitudinal relaxation time T1) and iron concentration (proxied by transverse relaxation time T2*), microstructural processes deemed particularly germane to cortical macrostructure. Informed by meta-analytical evidence, we focused specifically on orbitofrontal and rostral anterior cingulate cortices among adult MDD patients (N = 48) and matched healthy controls (HC; N = 10). Analyses probed the association of MDD diagnosis and clinical profile (severity, medication use, comorbid anxiety disorders, childhood trauma) with aforementioned microstructural properties. MDD diagnosis (p's < 0.05, Cohen's D = 0.55-0.66) and symptom severity (p's < 0.01, r = 0.271-0.267) both related to decreased intracortical myelination (higher T1 values) within the lateral orbitofrontal cortex, a region tightly coupled to processing negative affect and feelings of sadness in MDD. No relations were found with local iron concentrations. These findings allow uniquely fine-grained insights on frontocortical microstructure in MDD, and cautiously point to intracortical demyelination as a possible driver of macroscale cortical disintegrity in MDD.
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Affiliation(s)
- Jurjen Heij
- Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands
- Department of Computational Cognitive Neuroscience and Neuroimaging, NIN, Amsterdam, The Netherlands
- Department of Experimental and Applied Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Wietske van der Zwaag
- Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands
- Department of Computational Cognitive Neuroscience and Neuroimaging, NIN, Amsterdam, The Netherlands
| | - Tomas Knapen
- Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands
- Department of Computational Cognitive Neuroscience and Neuroimaging, NIN, Amsterdam, The Netherlands
- Department of Experimental and Applied Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Matthan W A Caan
- Department of Biomedical Engineering and Physics, Amsterdam UMC, Location University of Amsterdam, Amsterdam, The Netherlands
| | - Birte Forstman
- Department of Brain & Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - Dick J Veltman
- Department of Psychiatry, Amsterdam UMC, Location Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Guido van Wingen
- Department of Psychiatry, Amsterdam UMC, Location University of Amsterdam, Amsterdam, The Netherlands
| | - Moji Aghajani
- Department of Psychiatry, Amsterdam UMC, Location Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
- Institute of Education and Child Studies, Section Forensic Family & Youth Care, Leiden University, Leiden, The Netherlands.
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4
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Happer JP, Beaton LE, Wagner LC, Hodgkinson CA, Goldman D, Marinkovic K. Neural indices of heritable impulsivity: Impact of the COMT Val158Met polymorphism on frontal beta power during early motor preparation. Biol Psychol 2024; 191:108826. [PMID: 38862067 DOI: 10.1016/j.biopsycho.2024.108826] [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: 01/02/2024] [Revised: 05/14/2024] [Accepted: 05/31/2024] [Indexed: 06/13/2024]
Abstract
Studies of COMT Val158Met suggest that the neural circuitry subserving inhibitory control may be modulated by this functional polymorphism altering cortical dopamine availability, thus giving rise to heritable differences in behaviors. Using an anatomically-constrained magnetoencephalography method and stratifying the sample by COMT genotype, from a larger sample of 153 subjects, we examined the spatial and temporal dynamics of beta oscillations during motor execution and inhibition in 21 healthy Met158/Met158 (high dopamine) or 21 Val158/Val158 (low dopamine) genotype individuals during a Go/NoGo paradigm. While task performance was unaffected, Met158 homozygotes demonstrated an overall increase in beta power across regions essential for inhibitory control during early motor preparation (∼100 ms latency), suggestive of a global motor "pause" on behavior. This increase was especially evident on Go trials with slow response speed and was absent during inhibition failures. Such a pause could underlie the tendency of Met158 allele carriers to be more cautious and inhibited. In contrast, Val158 homozygotes exhibited a beta drop during early motor preparation, indicative of high response readiness. This decrease was associated with measures of behavioral disinhibition and consistent with greater extraversion and impulsivity observed in Val homozygotes. These results provide mechanistic insight into genetically-determined interindividual differences of inhibitory control with higher cortical dopamine associated with momentary response hesitation, and lower dopamine leading to motor impulsivity.
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Affiliation(s)
- Joseph P Happer
- San Diego State University/University of California, San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA
| | - Lauren E Beaton
- Department of Psychology, San Diego State University, San Diego, CA, USA
| | - Laura C Wagner
- Department of Psychology, San Diego State University, San Diego, CA, USA
| | | | - David Goldman
- Laboratory of Neurogenetics, NIAAA, NIH, Bethesda, MD, USA
| | - Ksenija Marinkovic
- San Diego State University/University of California, San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA; Department of Psychology, San Diego State University, San Diego, CA, USA; Department of Radiology, University of California, La Jolla, San Diego, CA, USA.
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5
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Gilmore N, Tseng CEJ, Maffei C, Tromly SL, Deary KB, McKinney IR, Kelemen JN, Healy BC, Hu CG, Ramos-Llordén G, Masood M, Cali RJ, Guo J, Belanger HG, Yao EF, Baxter T, Fischl B, Foulkes AS, Polimeni JR, Rosen BR, Perl DP, Hooker JM, Zürcher NR, Huang SY, Kimberly WT, Greve DN, Mac Donald CL, Dams-O’Connor K, Bodien YG, Edlow BL. Impact of repeated blast exposure on active-duty United States Special Operations Forces. Proc Natl Acad Sci U S A 2024; 121:e2313568121. [PMID: 38648470 PMCID: PMC11087753 DOI: 10.1073/pnas.2313568121] [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: 08/22/2023] [Accepted: 03/22/2024] [Indexed: 04/25/2024] Open
Abstract
United States (US) Special Operations Forces (SOF) are frequently exposed to explosive blasts in training and combat, but the effects of repeated blast exposure (RBE) on SOF brain health are incompletely understood. Furthermore, there is no diagnostic test to detect brain injury from RBE. As a result, SOF personnel may experience cognitive, physical, and psychological symptoms for which the cause is never identified, and they may return to training or combat during a period of brain vulnerability. In 30 active-duty US SOF, we assessed the relationship between cumulative blast exposure and cognitive performance, psychological health, physical symptoms, blood proteomics, and neuroimaging measures (Connectome structural and diffusion MRI, 7 Tesla functional MRI, [11C]PBR28 translocator protein [TSPO] positron emission tomography [PET]-MRI, and [18F]MK6240 tau PET-MRI), adjusting for age, combat exposure, and blunt head trauma. Higher blast exposure was associated with increased cortical thickness in the left rostral anterior cingulate cortex (rACC), a finding that remained significant after multiple comparison correction. In uncorrected analyses, higher blast exposure was associated with worse health-related quality of life, decreased functional connectivity in the executive control network, decreased TSPO signal in the right rACC, and increased cortical thickness in the right rACC, right insula, and right medial orbitofrontal cortex-nodes of the executive control, salience, and default mode networks. These observations suggest that the rACC may be susceptible to blast overpressure and that a multimodal, network-based diagnostic approach has the potential to detect brain injury associated with RBE in active-duty SOF.
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Affiliation(s)
- Natalie Gilmore
- Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA02114
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA02114
| | - Chieh-En J. Tseng
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA02129
| | - Chiara Maffei
- Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA02114
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA02114
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA02129
| | - Samantha L. Tromly
- Institute of Applied Engineering, University of South Florida, Tampa, FL33612
| | | | - Isabella R. McKinney
- Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA02114
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA02114
| | - Jessica N. Kelemen
- Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA02114
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA02114
| | - Brian C. Healy
- Harvard T.H. Chan School of Public Health, Boston, MA02115
| | - Collin G. Hu
- United States Army Special Operations Aviation Command, Fort Liberty, NC28307
- Department of Family Medicine, F. Edward Hebert School of Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD20814
| | - Gabriel Ramos-Llordén
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA02129
| | - Maryam Masood
- Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA02114
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA02114
| | - Ryan J. Cali
- Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA02114
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA02114
| | - Jennifer Guo
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA02114
| | - Heather G. Belanger
- Department of Psychiatry and Behavioral Neurosciences, University of South Florida, Tampa, FL33613
| | - Eveline F. Yao
- Office of the Air Force Surgeon General, Falls Church, VA22042
| | - Timothy Baxter
- Institute of Applied Engineering, University of South Florida, Tampa, FL33612
| | - Bruce Fischl
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA02129
| | | | - Jonathan R. Polimeni
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA02129
| | - Bruce R. Rosen
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA02129
| | - Daniel P. Perl
- Department of Pathology, F. Edward Hébert School of Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD20814
| | - Jacob M. Hooker
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA02129
| | - Nicole R. Zürcher
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA02129
| | - Susie Y. Huang
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA02129
| | - W. Taylor Kimberly
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA02114
| | - Douglas N. Greve
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA02129
| | | | - Kristen Dams-O’Connor
- Department of Rehabilitation and Human Performance, Icahn School of Medicine at Mount Sinai, New York, NY10029
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY10029
| | - Yelena G. Bodien
- Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA02114
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA02114
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital and Harvard Medical School, Charlestown, MA02129
| | - Brian L. Edlow
- Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA02114
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA02114
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA02129
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6
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Baldi S, Schuhmann T, Goossens L, Schruers KRJ. Individualized, connectome-based, non-invasive stimulation of OCD deep-brain targets: A proof-of-concept. Neuroimage 2024; 288:120527. [PMID: 38286272 DOI: 10.1016/j.neuroimage.2024.120527] [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: 09/08/2023] [Revised: 12/09/2023] [Accepted: 01/26/2024] [Indexed: 01/31/2024] Open
Abstract
Treatment-resistant obsessive-compulsive disorder (OCD) generally improves with deep-brain stimulation (DBS), thought to modulate neural activity at both the implantation site and in connected brain regions. However, its invasive nature, side-effects, and lack of customization, make non-invasive treatments preferable. Harnessing the established remote effects of cortical transcranial magnetic stimulation (TMS), connectivity-based approaches have emerged for depression that aim at influencing distant regions connected to the stimulation site. We here investigated whether effective OCD DBS targets (here subthalamic nucleus [STN] and nucleus accumbens [NAc]) could be modulated non-invasively with TMS. In a proof-of-concept study with nine healthy individuals, we used 7T magnetic resonance imaging (MRI) and probabilistic tractography to reconstruct the fiber tracts traversing manually segmented STN/NAc. Two TMS targets were individually selected based on the strength of their structural connectivity to either the STN, or both the STN and NAc. In a sham-controlled, within-subject cross-over design, TMS was administered over the personalized targets, located around the precentral and middle frontal gyrus. Resting-state functional 3T MRI was acquired before, and at 5 and 25 min after stimulation to investigate TMS-induced changes in the functional connectivity of the STN and NAc with other regions of the brain. Static and dynamic seed-to-voxel correlation analyses were conducted. TMS over both targets was able to modulate the functional connectivity of the STN and NAc, engaging both overlapping and distinct regions, and unfolding following different temporal dynamics. Given the relevance of the engaged connected regions to OCD pathology, we argue that a personalized, connectivity-based procedure is worth investigating as potential treatment for refractory OCD.
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Affiliation(s)
- Samantha Baldi
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands.
| | - Teresa Schuhmann
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands; Maastricht Brain Imaging Centre, Maastricht, the Netherlands
| | - Liesbet Goossens
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Koen R J Schruers
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
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7
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Chen Q, Bonduelle SLB, Wu GR, Vanderhasselt MA, De Raedt R, Baeken C. Unraveling how the adolescent brain deals with criticism using dynamic causal modeling. Neuroimage 2024; 286:120510. [PMID: 38184159 DOI: 10.1016/j.neuroimage.2024.120510] [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: 09/21/2023] [Revised: 12/20/2023] [Accepted: 01/03/2024] [Indexed: 01/08/2024] Open
Abstract
Sensitivity to criticism, which can be defined as a negative evaluation that a person receives from someone else, is considered a risk factor for the development of psychiatric disorders in adolescents. They may be more vulnerable to social evaluation than adults and exhibit more inadequate emotion regulation strategies such as rumination. The neural network involved in dealing with criticism in adolescents may serve as a biomarker for vulnerability to depression. However, the directions of the functional interactions between the brain regions within this neural network in adolescents are still unclear. In this study, 64 healthy adolescents (aged 14 to 17 years) were asked to listen to a series of self-referential auditory segments, which included negative (critical), positive (praising), and neutral conditions, during fMRI scanning. Dynamic Causal Modeling (DCM) with Parametric Empirical Bayesian (PEB) analysis was performed to map the interactions within the neural network that was engaged during the processing of these segments. Three regions were identified to form the interaction network: the left pregenual anterior cingulate cortex (pgACC), the left dorsolateral prefrontal cortex (DLPFC), and the right precuneus (preCUN). We quantified the modulatory effects of exposure to criticism and praise on the effective connectivity between these brain regions. Being criticized was found to significantly inhibit the effective connectivity from the preCUN to the DLPFC. Adolescents who scored high on the Perceived Criticism Measure (PCM) showed less inhibition of the preCUN-to-DLPFC connectivity when being criticized, which may indicate that they required more engagement of the Central Executive Network (which includes the DLPFC) to sufficiently disengage from negative self-referential processing. Furthermore, the inhibitory connectivity from the DLPFC to the pgACC was strengthened by exposure to praise as well as criticism, suggesting a recruitment of cognitive control over emotional responses when dealing with positive and negative evaluative feedback. Our novel findings contribute to a more profound understanding of how criticism affects the adolescent brain and can help to identify potential biomarkers for vulnerability to develop mood disorders before or during adulthood.
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Affiliation(s)
- Qinyuan Chen
- Faculty of Medicine and Health Sciences, Department of Head and Skin, Ghent Experimental Psychiatry (GHEP) Lab, Ghent University, Ghent, Belgium.
| | - Sam Luc Bart Bonduelle
- Faculty of Medicine and Health Sciences, Department of Head and Skin, Ghent Experimental Psychiatry (GHEP) Lab, Ghent University, Ghent, Belgium; Department of Child and Adolescent Psychiatry, Vrije Universiteit Brussel (VUB), Brussels University Hospital (UZ Brussel), Brussels, Belgium
| | - Guo-Rong Wu
- Faculty of Medicine and Health Sciences, Department of Head and Skin, Ghent Experimental Psychiatry (GHEP) Lab, Ghent University, Ghent, Belgium; Key Laboratory of Cognition and Personality, Faculty of Psychology, Southwest University, Chongqing, China
| | - Marie-Anne Vanderhasselt
- Faculty of Medicine and Health Sciences, Department of Head and Skin, Ghent Experimental Psychiatry (GHEP) Lab, Ghent University, Ghent, Belgium
| | - Rudi De Raedt
- Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium
| | - Chris Baeken
- Faculty of Medicine and Health Sciences, Department of Head and Skin, Ghent Experimental Psychiatry (GHEP) Lab, Ghent University, Ghent, Belgium; Department of Psychiatry, Vrije Universiteit Brussel (VUB), Brussels University Hospital (UZ Brussel), Brussels, Belgium; Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands
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8
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Yuan Z, Qi Z, Wang R, Cui Y, An S, Wu G, Feng Q, Lin R, Dai R, Li A, Gong H, Luo Q, Fu L, Luo M. A corticoamygdalar pathway controls reward devaluation and depression using dynamic inhibition code. Neuron 2023; 111:3837-3853.e5. [PMID: 37734380 DOI: 10.1016/j.neuron.2023.08.022] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 07/03/2023] [Accepted: 08/22/2023] [Indexed: 09/23/2023]
Abstract
Reward devaluation adaptively controls reward intake. It remains unclear how cortical circuits causally encode reward devaluation in healthy and depressed states. Here, we show that the neural pathway from the anterior cingulate cortex (ACC) to the basolateral amygdala (BLA) employs a dynamic inhibition code to control reward devaluation and depression. Fiber photometry and imaging of ACC pyramidal neurons reveal reward-induced inhibition, which weakens during satiation and becomes further attenuated in depression mouse models. Ablating or inhibiting these neurons desensitizes reward devaluation, causes reward intake increase and ultimate obesity, and ameliorates depression, whereas activating the cells sensitizes reward devaluation, suppresses reward consumption, and produces depression-like behaviors. Among various ACC neuron subpopulations, the BLA-projecting subset bidirectionally regulates reward devaluation and depression-like behaviors. Our study thus uncovers a corticoamygdalar circuit that encodes reward devaluation via blunted inhibition and suggests that enhancing inhibition within this circuit may offer a therapeutic approach for treating depression.
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Affiliation(s)
- Zhengwei Yuan
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China; School of Life Sciences, Tsinghua University, Beijing 100084, China; National Institute of Biological Sciences, Beijing 102206, China; Chinese Institute for Brain Research, Beijing 102206, China; Tsinghua Institute of Multidisciplinary Biomedical Research (TIMBR), Beijing 102206, China
| | - Zhongyang Qi
- National Institute of Biological Sciences, Beijing 102206, China; Wuhan National Laboratory for Optoelectronics-Huazhong, Britton Chance Center for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Ruiyu Wang
- National Institute of Biological Sciences, Beijing 102206, China; School of Life Sciences, Peking University, Beijing 100871, China
| | - Yuting Cui
- National Institute of Biological Sciences, Beijing 102206, China; Chinese Institute for Brain Research, Beijing 102206, China
| | - Sile An
- Wuhan National Laboratory for Optoelectronics-Huazhong, Britton Chance Center for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Guoli Wu
- National Institute of Biological Sciences, Beijing 102206, China
| | - Qiru Feng
- National Institute of Biological Sciences, Beijing 102206, China
| | - Rui Lin
- National Institute of Biological Sciences, Beijing 102206, China; Tsinghua Institute of Multidisciplinary Biomedical Research (TIMBR), Beijing 102206, China
| | - Ruicheng Dai
- National Institute of Biological Sciences, Beijing 102206, China; School of Life Sciences, Peking University, Beijing 100871, China; Chinese Institute for Brain Research, Beijing 102206, China
| | - Anan Li
- Wuhan National Laboratory for Optoelectronics-Huazhong, Britton Chance Center for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Hui Gong
- Wuhan National Laboratory for Optoelectronics-Huazhong, Britton Chance Center for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Qingming Luo
- Wuhan National Laboratory for Optoelectronics-Huazhong, Britton Chance Center for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Ling Fu
- Wuhan National Laboratory for Optoelectronics-Huazhong, Britton Chance Center for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Minmin Luo
- National Institute of Biological Sciences, Beijing 102206, China; Chinese Institute for Brain Research, Beijing 102206, China; Tsinghua Institute of Multidisciplinary Biomedical Research (TIMBR), Beijing 102206, China; Research Unit of Medical Neurobiology, Chinese Academy of Medical Sciences, Beijing 100005, China; New Cornerstone Science Laboratory, Shenzhen 518054, China; Beijing Tiantan Hospital, 100070 Beijing, China.
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9
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Lima Santos JP, Jia-Richards M, Kontos AP, Collins MW, Versace A. Emotional Regulation and Adolescent Concussion: Overview and Role of Neuroimaging. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:6274. [PMID: 37444121 PMCID: PMC10341732 DOI: 10.3390/ijerph20136274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 06/16/2023] [Accepted: 06/29/2023] [Indexed: 07/15/2023]
Abstract
Emotional dysregulation symptoms following a concussion are associated with an increased risk for emotional dysregulation disorders (e.g., depression and anxiety), especially in adolescents. However, predicting the emergence or worsening of emotional dysregulation symptoms after concussion and the extent to which this predates the onset of subsequent psychiatric morbidity after injury remains challenging. Although advanced neuroimaging techniques, such as functional magnetic resonance imaging and diffusion magnetic resonance imaging, have been used to detect and monitor concussion-related brain abnormalities in research settings, their clinical utility remains limited. In this narrative review, we have performed a comprehensive search of the available literature regarding emotional regulation, adolescent concussion, and advanced neuroimaging techniques in electronic databases (PubMed, Scopus, and Google Scholar). We highlight clinical evidence showing the heightened susceptibility of adolescents to experiencing emotional dysregulation symptoms following a concussion. Furthermore, we describe and provide empirical support for widely used magnetic resonance imaging modalities (i.e., functional and diffusion imaging), which are utilized to detect abnormalities in circuits responsible for emotional regulation. Additionally, we assess how these abnormalities relate to the emotional dysregulation symptoms often reported by adolescents post-injury. Yet, it remains to be determined if a progression of concussion-related abnormalities exists, especially in brain regions that undergo significant developmental changes during adolescence. We conclude that neuroimaging techniques hold potential as clinically useful tools for predicting and, ultimately, monitoring the treatment response to emotional dysregulation in adolescents following a concussion.
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Affiliation(s)
- João Paulo Lima Santos
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA; (M.J.-R.); (A.V.)
| | - Meilin Jia-Richards
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA; (M.J.-R.); (A.V.)
| | - Anthony P. Kontos
- Department of Orthopaedic Surgery, UPMC Sports Concussion Program, University of Pittsburgh, Pittsburgh, PA 15213, USA; (A.P.K.); (M.W.C.)
| | - Michael W. Collins
- Department of Orthopaedic Surgery, UPMC Sports Concussion Program, University of Pittsburgh, Pittsburgh, PA 15213, USA; (A.P.K.); (M.W.C.)
| | - Amelia Versace
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA; (M.J.-R.); (A.V.)
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10
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Jamieson GA, Page J, Evans ID, Hamlin A. Conflict and control in cortical responses to inconsistent emotional signals in a face-word Stroop. Front Hum Neurosci 2023; 17:955171. [PMID: 37457498 PMCID: PMC10349396 DOI: 10.3389/fnhum.2023.955171] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2022] [Accepted: 05/09/2023] [Indexed: 07/18/2023] Open
Abstract
Social communication is fraught with ambiguity. Negotiating the social world requires interpreting the affective signals we receive and often selecting between channels of conflicting affective information. The affective face-word Stroop (AFWS) provides an experimental paradigm which may identify cognitive-affective control mechanisms underpinning essential social-affective skills. Initial functional magnetic resonance imaging (fMRI) study of the AFWS identified right amygdala as driving this affective conflict and left rostral anterior cingulate cortex (rACC) as the locus of conflict control. We employed electroencephalogram (EEG) and eLORETA source localization to investigate the timing, location, and sequence of control processes when responding to affective conflict generated during the AFWS. However we designated affective word as the response target and affective face as the distractor to maximize conflict and control effects. Reaction times showed slowed responses in high vs. low control conditions, corresponding to a Rabbitt type control effect rather than the previously observed Grattan effect. Control related activation occurred in right rACC 96-118 ms post-stimulus, corresponding to the resolution of the P1 peak in the Visual Evoked Potential (VEP). Face distractors elicit right hemisphere control, while word distractors elicit left hemisphere control. Low control trials require rapid "booting up" control resources observable through VEPs. Incongruent trial activity in right fusiform face area is suppressed 118-156 ms post stimulus corresponding to onset and development of the N170 VEP component. Results are consistent with a predicted sequence of rapid early amygdala activation by affective conflict, then rACC inhibition of amygdala decreasing facilitation of affective face processing (however, amygdala activity is not observable with EEG).
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Affiliation(s)
- Graham A. Jamieson
- School of Psychology, University of New England, Armidale, NSW, Australia
| | - Julia Page
- School of Science and Technology, University of New England, Armidale, NSW, Australia
| | - Ian D. Evans
- Illawarra Health and Medical Research Institute, University of Wollongong, Wollongong, NSW, Australia
| | - Adam Hamlin
- School of Science and Technology, University of New England, Armidale, NSW, Australia
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11
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Feng T, Zhao C, Rao JS, Guo XJ, Bao SS, He LW, Zhao W, Liu Z, Yang ZY, Li XG. Different macaque brain network remodeling after spinal cord injury and NT3 treatment. iScience 2023; 26:106784. [PMID: 37378337 PMCID: PMC10291247 DOI: 10.1016/j.isci.2023.106784] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 03/08/2023] [Accepted: 04/26/2023] [Indexed: 06/29/2023] Open
Abstract
Graph theory-based analysis describes the brain as a complex network. Only a few studies have examined modular composition and functional connectivity (FC) between modules in patients with spinal cord injury (SCI). Little is known about the longitudinal changes in hubs and topological properties at the modular level after SCI and treatment. We analyzed differences in FC and nodal metrics reflecting modular interaction to investigate brain reorganization after SCI-induced compensation and neurotrophin-3 (NT3)-chitosan-induced regeneration. Mean inter-modular FC and participation coefficient of areas related to motor coordination were significantly higher in the treatment animals than in the SCI-only ones at the late stage. The magnocellular part of the red nucleus may reflect the best difference in brain reorganization after SCI and therapy. Treatment can enhance information flows between regions and promote the integration of motor functions to return to normal. These findings may reveal the information processing of disrupted network modules.
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Affiliation(s)
- Ting Feng
- School of Biological Science and Medical Engineering, Beijing Key Laboratory for Biomaterials and Neural Regeneration, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, PR China
| | - Can Zhao
- Institute of Rehabilitation Engineering, China Rehabilitation Science Institute, Beijing, PR China
| | - Jia-Sheng Rao
- School of Biological Science and Medical Engineering, Beijing Key Laboratory for Biomaterials and Neural Regeneration, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, PR China
| | - Xiao-Jun Guo
- School of Biological Science and Medical Engineering, Beijing Key Laboratory for Biomaterials and Neural Regeneration, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, PR China
| | - Shu-Sheng Bao
- School of Biological Science and Medical Engineering, Beijing Key Laboratory for Biomaterials and Neural Regeneration, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, PR China
| | - Le-Wei He
- School of Biological Science and Medical Engineering, Beijing Key Laboratory for Biomaterials and Neural Regeneration, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, PR China
| | - Wen Zhao
- Department of Neurobiology, School of Basic Medical Sciences, Capital Medical University, Beijing, PR China
| | - Zuxiang Liu
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, PR China
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, PR China
- Department of Biology, College of Life Sciences, University of Chinese Academy of Sciences, Beijing, PR China
| | - Zhao-Yang Yang
- Department of Neurobiology, School of Basic Medical Sciences, Capital Medical University, Beijing, PR China
| | - Xiao-Guang Li
- School of Biological Science and Medical Engineering, Beijing Key Laboratory for Biomaterials and Neural Regeneration, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, PR China
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12
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Martínez-Rivera FJ, Pérez-Torres J, Velázquez-Díaz CD, Sánchez-Navarro MJ, Huertas-Pérez CI, Diehl MM, Phillips ML, Haber SN, Quirk GJ. A Novel Insular/Orbital-Prelimbic Circuit That Prevents Persistent Avoidance in a Rodent Model of Compulsive Behavior. Biol Psychiatry 2023; 93:1000-1009. [PMID: 35491274 DOI: 10.1016/j.biopsych.2022.02.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Revised: 01/24/2022] [Accepted: 02/11/2022] [Indexed: 11/02/2022]
Abstract
BACKGROUND A common symptom of obsessive-compulsive disorder is the persistent avoidance of cues incorrectly associated with negative outcomes. This maladaptation becomes increasingly evident as subjects fail to respond to extinction-based treatments such as exposure-with-response prevention therapy. While previous studies have highlighted the role of the insular-orbital cortex in fine-tuning avoidance-based decisions, little is known about the projections from this area that might modulate compulsive-like avoidance. METHODS Here, we used anatomical tract-tracing, single-unit recording, and optogenetics to characterize the projections from the insular-orbital cortex. To model exposure-with-response prevention and persistent avoidance in rats, we used the platform-mediated avoidance task followed by extinction-with-response prevention training. RESULTS Using tract-tracing and unit recording, we found that projections from the agranular insular/lateral orbital (AI/LO) cortex to the prefrontal cortex predominantly target the rostral portion of the prelimbic (rPL) cortex and excite rPL neurons. Photoinhibiting this projection induced persistent avoidance after extinction-with-response prevention training, an effect that was still present 1 week later. Consistent with this, photoexcitation of this projection prevented persistent avoidance in overtrained rats. This projection to rPL appears to be key for AI/LO's effects, considering that there was no effect of photoinhibiting AI/LO projections to the ventral striatum or basolateral amygdala. CONCLUSIONS Our findings suggest that projections from the AI/LO to the rPL decreases the likelihood of avoidance behavior following extinction. In humans, this connectivity may share some homology of projections from lateral prefrontal cortices (i.e., ventrolateral prefrontal cortex, orbitofrontal cortex, and insula) to other prefrontal areas and the anterior cingulate cortex, suggesting that reduced activity in these pathways may contribute to obsessive-compulsive disorder.
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Affiliation(s)
- Freddyson J Martínez-Rivera
- Departments of Psychiatry and Anatomy & Neurobiology, School of Medicine, Medical Sciences Campus, University of Puerto Rico, San Juan, Puerto Rico.
| | - José Pérez-Torres
- Departments of Psychiatry and Anatomy & Neurobiology, School of Medicine, Medical Sciences Campus, University of Puerto Rico, San Juan, Puerto Rico
| | - Coraly D Velázquez-Díaz
- Departments of Psychiatry and Anatomy & Neurobiology, School of Medicine, Medical Sciences Campus, University of Puerto Rico, San Juan, Puerto Rico
| | - Marcos J Sánchez-Navarro
- Departments of Psychiatry and Anatomy & Neurobiology, School of Medicine, Medical Sciences Campus, University of Puerto Rico, San Juan, Puerto Rico
| | - Carlos I Huertas-Pérez
- Departments of Psychiatry and Anatomy & Neurobiology, School of Medicine, Medical Sciences Campus, University of Puerto Rico, San Juan, Puerto Rico
| | - Maria M Diehl
- Departments of Psychiatry and Anatomy & Neurobiology, School of Medicine, Medical Sciences Campus, University of Puerto Rico, San Juan, Puerto Rico
| | - Mary L Phillips
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Suzanne N Haber
- Department of Pharmacology and Physiology, University of Rochester School of Medicine, Rochester, New York; McLean Hospital, Harvard Medical School, Belmont, Massachusetts
| | - Gregory J Quirk
- Departments of Psychiatry and Anatomy & Neurobiology, School of Medicine, Medical Sciences Campus, University of Puerto Rico, San Juan, Puerto Rico
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13
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Cushnie AK, Tang W, Heilbronner SR. Connecting Circuits with Networks in Addiction Neuroscience: A Salience Network Perspective. Int J Mol Sci 2023; 24:9083. [PMID: 37240428 PMCID: PMC10219092 DOI: 10.3390/ijms24109083] [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: 02/07/2023] [Revised: 04/18/2023] [Accepted: 05/08/2023] [Indexed: 05/28/2023] Open
Abstract
Human neuroimaging has demonstrated the existence of large-scale functional networks in the cerebral cortex consisting of topographically distant brain regions with functionally correlated activity. The salience network (SN), which is involved in detecting salient stimuli and mediating inter-network communication, is a crucial functional network that is disrupted in addiction. Individuals with addiction display dysfunctional structural and functional connectivity of the SN. Furthermore, while there is a growing body of evidence regarding the SN, addiction, and the relationship between the two, there are still many unknowns, and there are fundamental limitations to human neuroimaging studies. At the same time, advances in molecular and systems neuroscience techniques allow researchers to manipulate neural circuits in nonhuman animals with increasing precision. Here, we describe attempts to translate human functional networks to nonhuman animals to uncover circuit-level mechanisms. To do this, we review the structural and functional connections of the salience network and its homology across species. We then describe the existing literature in which circuit-specific perturbation of the SN sheds light on how functional cortical networks operate, both within and outside the context of addiction. Finally, we highlight key outstanding opportunities for mechanistic studies of the SN.
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Affiliation(s)
- Adriana K. Cushnie
- Department of Neuroscience, University of Minnesota Twin Cities, 2-164 Jackson Hall, 321 Church St. SE, Minneapolis, MN 55455, USA;
| | - Wei Tang
- Department of Computer Science, Indiana University Bloomington, Bloomington, IN 47408, USA
| | - Sarah R. Heilbronner
- Department of Neuroscience, University of Minnesota Twin Cities, 2-164 Jackson Hall, 321 Church St. SE, Minneapolis, MN 55455, USA;
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX 77030, USA
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14
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Schijven D, Postema MC, Fukunaga M, Matsumoto J, Miura K, de Zwarte SMC, van Haren NEM, Cahn W, Hulshoff Pol HE, Kahn RS, Ayesa-Arriola R, Ortiz-García de la Foz V, Tordesillas-Gutierrez D, Vázquez-Bourgon J, Crespo-Facorro B, Alnæs D, Dahl A, Westlye LT, Agartz I, Andreassen OA, Jönsson EG, Kochunov P, Bruggemann JM, Catts SV, Michie PT, Mowry BJ, Quidé Y, Rasser PE, Schall U, Scott RJ, Carr VJ, Green MJ, Henskens FA, Loughland CM, Pantelis C, Weickert CS, Weickert TW, de Haan L, Brosch K, Pfarr JK, Ringwald KG, Stein F, Jansen A, Kircher TTJ, Nenadić I, Krämer B, Gruber O, Satterthwaite TD, Bustillo J, Mathalon DH, Preda A, Calhoun VD, Ford JM, Potkin SG, Chen J, Tan Y, Wang Z, Xiang H, Fan F, Bernardoni F, Ehrlich S, Fuentes-Claramonte P, Garcia-Leon MA, Guerrero-Pedraza A, Salvador R, Sarró S, Pomarol-Clotet E, Ciullo V, Piras F, Vecchio D, Banaj N, Spalletta G, Michielse S, van Amelsvoort T, Dickie EW, Voineskos AN, Sim K, Ciufolini S, Dazzan P, Murray RM, Kim WS, Chung YC, Andreou C, Schmidt A, Borgwardt S, McIntosh AM, Whalley HC, Lawrie SM, du Plessis S, Luckhoff HK, Scheffler F, Emsley R, Grotegerd D, Lencer R, Dannlowski U, Edmond JT, Rootes-Murdy K, Stephen JM, Mayer AR, Antonucci LA, Fazio L, Pergola G, Bertolino A, Díaz-Caneja CM, Janssen J, Lois NG, Arango C, Tomyshev AS, Lebedeva I, Cervenka S, Sellgren CM, Georgiadis F, Kirschner M, Kaiser S, Hajek T, Skoch A, Spaniel F, Kim M, Kwak YB, Oh S, Kwon JS, James A, Bakker G, Knöchel C, Stäblein M, Oertel V, Uhlmann A, Howells FM, Stein DJ, Temmingh HS, Diaz-Zuluaga AM, Pineda-Zapata JA, López-Jaramillo C, Homan S, Ji E, Surbeck W, Homan P, Fisher SE, Franke B, Glahn DC, Gur RC, Hashimoto R, Jahanshad N, Luders E, Medland SE, Thompson PM, Turner JA, van Erp TGM, Francks C. Large-scale analysis of structural brain asymmetries in schizophrenia via the ENIGMA consortium. Proc Natl Acad Sci U S A 2023; 120:e2213880120. [PMID: 36976765 PMCID: PMC10083554 DOI: 10.1073/pnas.2213880120] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 02/03/2023] [Indexed: 03/29/2023] Open
Abstract
Left-right asymmetry is an important organizing feature of the healthy brain that may be altered in schizophrenia, but most studies have used relatively small samples and heterogeneous approaches, resulting in equivocal findings. We carried out the largest case-control study of structural brain asymmetries in schizophrenia, with MRI data from 5,080 affected individuals and 6,015 controls across 46 datasets, using a single image analysis protocol. Asymmetry indexes were calculated for global and regional cortical thickness, surface area, and subcortical volume measures. Differences of asymmetry were calculated between affected individuals and controls per dataset, and effect sizes were meta-analyzed across datasets. Small average case-control differences were observed for thickness asymmetries of the rostral anterior cingulate and the middle temporal gyrus, both driven by thinner left-hemispheric cortices in schizophrenia. Analyses of these asymmetries with respect to the use of antipsychotic medication and other clinical variables did not show any significant associations. Assessment of age- and sex-specific effects revealed a stronger average leftward asymmetry of pallidum volume between older cases and controls. Case-control differences in a multivariate context were assessed in a subset of the data (N = 2,029), which revealed that 7% of the variance across all structural asymmetries was explained by case-control status. Subtle case-control differences of brain macrostructural asymmetry may reflect differences at the molecular, cytoarchitectonic, or circuit levels that have functional relevance for the disorder. Reduced left middle temporal cortical thickness is consistent with altered left-hemisphere language network organization in schizophrenia.
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Affiliation(s)
- Dick Schijven
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen6525 XD, The Netherlands
| | - Merel C. Postema
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen6525 XD, The Netherlands
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam1081 HZ, The Netherlands
| | - Masaki Fukunaga
- Division of Cerebral Integration, National Institute for Physiological Sciences, Okazaki444-8585, Japan
| | - Junya Matsumoto
- Department of Pathology of Mental Diseases, National Center of Neurology and Psychiatry, National Institute of Mental Health, Tokyo187-8551, Japan
| | - Kenichiro Miura
- Department of Pathology of Mental Diseases, National Center of Neurology and Psychiatry, National Institute of Mental Health, Tokyo187-8551, Japan
| | - Sonja M. C. de Zwarte
- Department of Psychiatry, University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht3584 CG, The Netherlands
| | - Neeltje E. M. van Haren
- Department of Psychiatry, University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht3584 CG, The Netherlands
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center Sophia Children's Hospital, Rotterdam3015 CN, The Netherlands
| | - Wiepke Cahn
- Department of Psychiatry, University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht3584 CG, The Netherlands
| | - Hilleke E. Hulshoff Pol
- Department of Psychiatry, University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht3584 CG, The Netherlands
| | - René S. Kahn
- Department of Psychiatry, University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht3584 CG, The Netherlands
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY10029
- The Mental Illness Research, Education and Clinical Centers, James J. Peters VA Medical Center, New York, NY10468
| | - Rosa Ayesa-Arriola
- Department of Psychiatry, Instituto de Investigación Marqués de Valdecilla, University Hospital Marqués de Valdecilla, Santander39008, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid28029, Spain
- Department of Medicine and Psychiatry, School of Medicine, University of Cantabria, Santander39011, Spain
| | - Víctor Ortiz-García de la Foz
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid28029, Spain
- Department of Psychiatry, Marqués de Valdecilla University Hospital, Instituto de Investigación Sanitaria Valdecilla, School of Medicine, University of Cantabria, Santander39011, Spain
| | - Diana Tordesillas-Gutierrez
- Department of Radiology, Instituto de Investigación Marqués de Valdecilla, Marqués de Valdecilla University Hospital, Santander39011, Spain
- Advanced Computing and e-Science, Instituto de Física de Cantabria, Universidad de Cantabria - Consejo Superior de Investigaciones Científicas, Santander39005, Spain
| | - Javier Vázquez-Bourgon
- Department of Psychiatry, Instituto de Investigación Marqués de Valdecilla, University Hospital Marqués de Valdecilla, Santander39008, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid28029, Spain
| | - Benedicto Crespo-Facorro
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid28029, Spain
- Department of Psychiatry, School of Medicine, University of Sevilla, University Hospital Virgen del Rocío, Consejo Superior de Investigaciones Científicas - Instituto de Biomedicina de Sevilla, Sevilla41013, Spain
| | - Dag Alnæs
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo0450, Norway
- Department of Psychology, University of Oslo, Oslo0373, Norway
- Bjørknes College, Oslo0456, Norway
| | - Andreas Dahl
- Department of Psychology, University of Oslo, Oslo0373, Norway
| | - Lars T. Westlye
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo0450, Norway
- Department of Psychology, University of Oslo, Oslo0373, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo0372, Norway
- KG Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Oslo0450, Norway
| | - Ingrid Agartz
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo0450, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo0373, Norway
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm113 64, Sweden
| | - Ole A. Andreassen
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo0450, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo0372, Norway
| | - Erik G. Jönsson
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo0450, Norway
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm113 64, Sweden
| | - Peter Kochunov
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD21201
| | - Jason M. Bruggemann
- School of Psychiatry, University of New South Wales, Sydney2033, Australia
- Neuroscience Research Australia, Sydney2031, Australia
- Edith Collins Centre (Translational Research in Alcohol, Drugs & Toxicology), Sydney Local Health District, Sydney2050, Australia
- Specialty of Addiction Medicine, Central Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney2006, Australia
| | - Stanley V. Catts
- School of Medicine, The University of Queensland, Brisbane4006, Australia
| | - Patricia T. Michie
- School of Psychological Sciences, University of Newcastle, Newcastle2308, Australia
| | - Bryan J. Mowry
- Queensland Brain Institute, The University of Queensland, Brisbane4072, Australia
- Queensland Centre for Mental Health Research, The University of Queensland, Brisbane4076, Australia
| | - Yann Quidé
- School of Psychiatry, University of New South Wales, Sydney2033, Australia
- Neuroscience Research Australia, Sydney2031, Australia
| | - Paul E. Rasser
- Centre for Brain and Mental Health Research, University of Newcastle, Newcastle2308, Australia
- Priority Research Centre for Stroke and Brain Injury, University of Newcastle, Newcastle2308, Australia
- Hunter Medical Research Institute, Newcastle2305, Australia
| | - Ulrich Schall
- Centre for Brain and Mental Health Research, University of Newcastle, Newcastle2308, Australia
| | - Rodney J. Scott
- School of Biomedical Science and Pharmacy, Faculty of Health and Medicine, University of Newcastle, Newcastle2308, Australia
| | - Vaughan J. Carr
- School of Psychiatry, University of New South Wales, Sydney2033, Australia
- Neuroscience Research Australia, Sydney2031, Australia
| | - Melissa J. Green
- School of Psychiatry, University of New South Wales, Sydney2033, Australia
- Neuroscience Research Australia, Sydney2031, Australia
| | - Frans A. Henskens
- School of Medicine and Public Health, University of Newcastle, Newcastle2308, Australia
- PRC for Health Behaviour, Hunter Medical Research Institute, Newcastle2305, Australia
| | - Carmel M. Loughland
- School of Medicine and Public Health, University of Newcastle, Newcastle2308, Australia
- Hunter New England Mental Health Service, Newcastle2305, Australia
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Melbourne3053, Australia
| | - Cynthia Shannon Weickert
- School of Psychiatry, University of New South Wales, Sydney2033, Australia
- Neuroscience Research Australia, Sydney2031, Australia
- Department of Neuroscience and Physiology, Upstate Medical University, Syracuse, NY13210
| | - Thomas W. Weickert
- School of Psychiatry, University of New South Wales, Sydney2033, Australia
- Neuroscience Research Australia, Sydney2031, Australia
- Department of Neuroscience and Physiology, Upstate Medical University, Syracuse, NY13210
| | - Lieuwe de Haan
- Early Psychosis Department, Department of Psychiatry, Amsterdam UMC (location AMC), Amsterdam1105 AZ, The Netherlands
- Arkin Institute for Mental Health, Amsterdam1033 NN, The Netherlands
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg35039, Germany
- Center for Mind, Brain and Behavior, Marburg35032, Germany
| | - Julia-Katharina Pfarr
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg35039, Germany
- Center for Mind, Brain and Behavior, Marburg35032, Germany
| | - Kai G. Ringwald
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg35039, Germany
- Center for Mind, Brain and Behavior, Marburg35032, Germany
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg35039, Germany
- Center for Mind, Brain and Behavior, Marburg35032, Germany
| | - Andreas Jansen
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg35039, Germany
- Center for Mind, Brain and Behavior, Marburg35032, Germany
- Core-Facility Brainimaging, Faculty of Medicine, Philipps-Universität Marburg, Marburg35032, Germany
| | - Tilo T. J. Kircher
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg35039, Germany
- Center for Mind, Brain and Behavior, Marburg35032, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg35039, Germany
- Center for Mind, Brain and Behavior, Marburg35032, Germany
| | - Bernd Krämer
- Department of General Psychiatry, Section for Experimental Psychopathology and Neuroimaging, Heidelberg University, Heidelberg69115, Germany
| | - Oliver Gruber
- Department of General Psychiatry, Section for Experimental Psychopathology and Neuroimaging, Heidelberg University, Heidelberg69115, Germany
| | - Theodore D. Satterthwaite
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
- Lifespan Brain Institute, University of Pennsylvania & Children's Hospital of Philadelphia, Philadelphia, PA19104
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
| | - Juan Bustillo
- Department of Psychiatry and Neuroscience, University of New Mexico, Albuquerque, NM87106
| | - Daniel H. Mathalon
- Department of Psychiatry and Behavioral Sciences and Weill Institute for Neurosciences, University of California, San Francisco, CA94143
- Mental Health Service, Veterans Affairs San Francisco Healthcare System, San Francisco, CA94121
| | - Adrian Preda
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA92697
| | - Vince D. Calhoun
- Psychology Department and Neuroscience Institute, Georgia State University, Atlanta, GA30303
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute of Technology and Emory University, Atlanta, GA30303
| | - Judith M. Ford
- San Francisco VA Medical Center, University of California, San Francisco, CA94121
| | - Steven G. Potkin
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA92697
- Long Beach VA Health Care System, Long Beach, CA90822
| | - Jingxu Chen
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing100096, P.R. China
| | - Yunlong Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing100096, P.R. China
| | - Zhiren Wang
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing100096, P.R. China
| | - Hong Xiang
- Chongqing University Three Gorges Hospital, Chongqing404188, P.R. China
| | - Fengmei Fan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing100096, P.R. China
| | - Fabio Bernardoni
- Division of Psychological and Social Medicine and Developmental Neurosciences, Translational Developmental Neuroscience Section, Technische Universität Dresden, University Hospital C.G. Carus, Dresden01307, Germany
- Department of Child and Adolescent Psychiatry, Eating Disorder Treatment and Research Center, Technische Universität Dresden, Faculty of Medicine, University Hospital C.G. Carus, Dresden01307, Germany
| | - Stefan Ehrlich
- Division of Psychological and Social Medicine and Developmental Neurosciences, Translational Developmental Neuroscience Section, Technische Universität Dresden, University Hospital C.G. Carus, Dresden01307, Germany
- Department of Child and Adolescent Psychiatry, Eating Disorder Treatment and Research Center, Technische Universität Dresden, Faculty of Medicine, University Hospital C.G. Carus, Dresden01307, Germany
| | - Paola Fuentes-Claramonte
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona08035, Spain
- Mental Health Research Networking Center (Ciber del Área de Salud Mental), Madrid28029, Spain
| | - Maria Angeles Garcia-Leon
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona08035, Spain
- Mental Health Research Networking Center (Ciber del Área de Salud Mental), Madrid28029, Spain
| | - Amalia Guerrero-Pedraza
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona08035, Spain
- Benito Menni Complex Assistencial en Salut Mental, Barcelona08830, Spain
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona08035, Spain
- Mental Health Research Networking Center (Ciber del Área de Salud Mental), Madrid28029, Spain
| | - Salvador Sarró
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona08035, Spain
- Mental Health Research Networking Center (Ciber del Área de Salud Mental), Madrid28029, Spain
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona08035, Spain
- Mental Health Research Networking Center (Ciber del Área de Salud Mental), Madrid28029, Spain
| | - Valentina Ciullo
- Laboratory of Neuropsychiatry, Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Rome00179, Italy
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Rome00179, Italy
| | - Daniela Vecchio
- Laboratory of Neuropsychiatry, Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Rome00179, Italy
| | - Nerisa Banaj
- Laboratory of Neuropsychiatry, Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Rome00179, Italy
| | - Gianfranco Spalletta
- Laboratory of Neuropsychiatry, Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Rome00179, Italy
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX77030
| | - Stijn Michielse
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht University, Maastricht6229 ER, The Netherlands
| | - Therese van Amelsvoort
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht University, Maastricht6229 ER, The Netherlands
| | - Erin W. Dickie
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, TorontoM5S 2S1, Canada
- Department of Psychiatry, University of Toronto, TorontoM5T 1R8, Canada
| | - Aristotle N. Voineskos
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, TorontoM5S 2S1, Canada
- Department of Psychiatry, University of Toronto, TorontoM5T 1R8, Canada
| | - Kang Sim
- West Region, Institute of Mental Health, Singapore539747, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore119228, Singapore
| | - Simone Ciufolini
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, LondonSE5 8AF, United Kingdom
| | - Paola Dazzan
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, LondonSE5 8AF, United Kingdom
| | - Robin M. Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, LondonSE5 8AF, United Kingdom
| | - Woo-Sung Kim
- Department of Psychiatry, Jeonbuk National University Medical School, Jeonju54896, Republic of Korea
- Research Institute of Clinical Medicine, Jeonbuk National University-Biomedical Research Institute, Jeonbuk National University Hospital, Jeonju54896, Republic of Korea
| | - Young-Chul Chung
- Department of Psychiatry, Jeonbuk National University Medical School, Jeonju54896, Republic of Korea
- Research Institute of Clinical Medicine, Jeonbuk National University-Biomedical Research Institute, Jeonbuk National University Hospital, Jeonju54896, Republic of Korea
| | - Christina Andreou
- Department of Psychiatry, University Psychiatric Clinics (Universitäre Psychiatrische Kliniken), University of Basel, Basel4002, Switzerland
- Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck23562, Germany
| | - André Schmidt
- Department of Psychiatry, University Psychiatric Clinics (Universitäre Psychiatrische Kliniken), University of Basel, Basel4002, Switzerland
| | - Stefan Borgwardt
- Department of Psychiatry, University Psychiatric Clinics (Universitäre Psychiatrische Kliniken), University of Basel, Basel4002, Switzerland
- Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck23562, Germany
| | - Andrew M. McIntosh
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, EdinburghEH16 4SB, United Kingdom
| | - Heather C. Whalley
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, EdinburghEH16 4SB, United Kingdom
| | - Stephen M. Lawrie
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, EdinburghEH16 4SB, United Kingdom
| | - Stefan du Plessis
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch7505, South Africa
- Stellenbosch University Genomics of Brain Disorders Research Unit, South African Medical Research Council, Cape Town7505, South Africa
| | - Hilmar K. Luckhoff
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch7505, South Africa
| | - Freda Scheffler
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch7505, South Africa
- Department of Psychiatry and Mental Health, Faculty of Health Sciences, University of Cape Town, Cape Town7935, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town7935, South Africa
| | - Robin Emsley
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch7505, South Africa
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster48149, Germany
| | - Rebekka Lencer
- Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck23562, Germany
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster48149, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster48149, Germany
| | - Jesse T. Edmond
- Psychology Department and Neuroscience Institute, Georgia State University, Atlanta, GA30303
| | - Kelly Rootes-Murdy
- Psychology Department and Neuroscience Institute, Georgia State University, Atlanta, GA30303
| | | | | | - Linda A. Antonucci
- Department of Education, Psychology, Communication, University of Bari Aldo Moro, Bari70121, Italy
| | - Leonardo Fazio
- Department of Basic Medical Science, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari70121, Italy
| | - Giulio Pergola
- Department of Basic Medical Science, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari70121, Italy
| | - Alessandro Bertolino
- Department of Basic Medical Science, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari70121, Italy
- Psychiatry Unit, Bari University Hospital, Bari70121, Italy
| | - Covadonga M. Díaz-Caneja
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid28009, Spain
- Ciber del Área de Salud Mental, Instituto de Salud Carlos III, Madrid28029, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid28009, Spain
- School of Medicine, Universidad Complutense, Madrid28040, Spain
| | - Joost Janssen
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid28009, Spain
- Ciber del Área de Salud Mental, Instituto de Salud Carlos III, Madrid28029, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid28009, Spain
| | - Noemi G. Lois
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid28009, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid28009, Spain
| | - Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid28009, Spain
- Ciber del Área de Salud Mental, Instituto de Salud Carlos III, Madrid28029, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid28009, Spain
- School of Medicine, Universidad Complutense, Madrid28040, Spain
| | - Alexander S. Tomyshev
- Laboratory of Neuroimaging and Multimodal Analysis, Mental Health Research Center, Moscow115522, Russian Federation
| | - Irina Lebedeva
- Laboratory of Neuroimaging and Multimodal Analysis, Mental Health Research Center, Moscow115522, Russian Federation
| | - Simon Cervenka
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm113 64, Sweden
- Department of Medical Sciences, Psychiatry, Uppsala University, Uppsala751 85, Sweden
| | - Carl M. Sellgren
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm113 64, Sweden
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm171 65, Sweden
| | - Foivos Georgiadis
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich (PUK), Zurich8008, Switzerland
| | - Matthias Kirschner
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich (PUK), Zurich8008, Switzerland
- Montreal Neurological Institute, McGill University, MontrealH3A 2B4, Canada
| | - Stefan Kaiser
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich (PUK), Zurich8008, Switzerland
- Department of Psychiatry, Division of Adult Psychiatry, Geneva University Hospitals, Geneva1202, Switzerland
| | - Tomas Hajek
- National Institute of Mental Health, Klecany250 67, Czech Republic
- Department of Psychiatry, Dalhousie University, HalifaxB3H 2E2, Canada
| | - Antonin Skoch
- National Institute of Mental Health, Klecany250 67, Czech Republic
- MR Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague140 21, Czech Republic
| | - Filip Spaniel
- National Institute of Mental Health, Klecany250 67, Czech Republic
| | - Minah Kim
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul08826, Republic of Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul08826, Republic of Korea
| | - Yoo Bin Kwak
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul08826, Republic of Korea
| | - Sanghoon Oh
- Department of Psychiatry, Seoul National University College of Medicine, Seoul08826, Republic of Korea
| | - Jun Soo Kwon
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul08826, Republic of Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul08826, Republic of Korea
| | - Anthony James
- Department of Psychiatry, University of Oxford, OxfordOX3 7JX, United Kingdom
| | - Geor Bakker
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht University, Maastricht6229 ER, The Netherlands
| | - Christian Knöchel
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Frankfurt am Main60528, Germany
| | - Michael Stäblein
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Frankfurt am Main60528, Germany
| | - Viola Oertel
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Frankfurt am Main60528, Germany
| | - Anne Uhlmann
- Department of Psychiatry and Mental Health, Faculty of Health Sciences, University of Cape Town, Cape Town7935, South Africa
- Department of Child and Adolescent Psychiatry, Technische Universität Dresden, Dresden01187, Germany
| | - Fleur M. Howells
- Department of Psychiatry and Mental Health, Faculty of Health Sciences, University of Cape Town, Cape Town7935, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town7935, South Africa
| | - Dan J. Stein
- Department of Psychiatry and Mental Health, Faculty of Health Sciences, University of Cape Town, Cape Town7935, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town7935, South Africa
- SA MRC Unit on Risk & Resilience in Mental Disorders, University of Cape Town, Cape Town7505, South Africa
| | - Henk S. Temmingh
- Department of Psychiatry and Mental Health, Faculty of Health Sciences, University of Cape Town, Cape Town7935, South Africa
| | - Ana M. Diaz-Zuluaga
- Department of Psychiatry, Research Group in Psychiatry (GIPSI), Faculty of Medicine, Universidad de Antioquia, Medellín050010, Colombia
| | - Julian A. Pineda-Zapata
- Department of Psychiatry, Research Group in Psychiatry (GIPSI), Faculty of Medicine, Universidad de Antioquia, Medellín050010, Colombia
| | - Carlos López-Jaramillo
- Department of Psychiatry, Research Group in Psychiatry (GIPSI), Faculty of Medicine, Universidad de Antioquia, Medellín050010, Colombia
| | - Stephanie Homan
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich (PUK), Zurich8008, Switzerland
- Experimental Psychopathology and Psychotherapy, Department of Psychology, University of Zurich, Zurich8050, Switzerland
| | - Ellen Ji
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich (PUK), Zurich8008, Switzerland
| | - Werner Surbeck
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich (PUK), Zurich8008, Switzerland
| | - Philipp Homan
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich (PUK), Zurich8008, Switzerland
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY11030
- Division of Psychiatry Research, Zucker Hillside Hospital, Northwell Health, New York, NY11004
- Department of Psychiatry, Zucker School of Medicine at Northwell/Hofstra, New York, NY11549
| | - Simon E. Fisher
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen6525 XD, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen6500 HB, The Netherlands
| | - Barbara Franke
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen6500 HB, The Netherlands
- Department of Human Genetics, Radboud University Medical Center, Nijmegen6525 GA, The Netherlands
- Department of Psychiatry, Radboud University Medical Center, Nijmegen6525 GA, The Netherlands
| | - David C. Glahn
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA02115
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT06102
| | - Ruben C. Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
- Lifespan Brain Institute, University of Pennsylvania & Children's Hospital of Philadelphia, Philadelphia, PA19104
- Department of Radiology, Perelman School of Medicine, Philadelphia, PA19104
- Department of Neurology, Perelman School of Medicine, Philadelphia, PA19104
| | - Ryota Hashimoto
- Department of Pathology of Mental Diseases, National Center of Neurology and Psychiatry, National Institute of Mental Health, Tokyo187-8551, Japan
| | - Neda Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA90033
| | - Eileen Luders
- School of Psychology, University of Auckland, Auckland1010, New Zealand
- Department of Women’s and Children’s Health, Uppsala University, Uppsala752 37, Sweden
- Laboratory of Neuro Imaging, School of Medicine, University of Southern California, Los Angeles, CA90033
| | - Sarah E. Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane4006, Australia
| | - Paul M. Thompson
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA90033
| | - Jessica A. Turner
- Psychology Department and Neuroscience Institute, Georgia State University, Atlanta, GA30303
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute of Technology and Emory University, Atlanta, GA30303
| | - Theo G. M. van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA92697
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine, CA92697
| | - Clyde Francks
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen6525 XD, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen6500 HB, The Netherlands
- Department of Human Genetics, Radboud University Medical Center, Nijmegen6525 GA, The Netherlands
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15
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Christova P, Georgopoulos AP. Differential reduction of gray matter volume with age in 35 cortical areas in men (more) and women (less). J Neurophysiol 2023; 129:894-899. [PMID: 36922162 PMCID: PMC10085548 DOI: 10.1152/jn.00066.2023] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 03/06/2023] [Accepted: 03/15/2023] [Indexed: 03/17/2023] Open
Abstract
It is known that brain volume decreases with age. Here, we assessed the rate of this decrease in gray matter volume of 35 cortical regions in a large sample of healthy participants (n = 712, age range 36-90 yr) of the Human Connectome Project-Aging. We evaluated the difference in this rate between men (n = 316) and women (n = 396) and found that the volumes of cortical areas decreased by an average of 5.25%/decade, with the highest rate of decrease observed in the rostral anterior cingulate cortex (7.28%/decade). The rate of decrease was higher in men than in women in general and in 30/35 (85.7%) areas in particular, involving most prominently the cingulate lobe. These findings could serve as a normative reference for clinical conditions that manifest with abnormal brain atrophy.NEW & NOTEWORTHY This study showed an overall decrease of cortical gray matter with age but with different rates of volume reduction in different areas, with smaller decrease rates in women than in men. The highest volume reduction rate was observed for the rostral anterior cingulate cortex, an area linked to depression. These findings could serve as a normative reference for clinical conditions that manifest with abnormal brain atrophy.
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Affiliation(s)
- Peka Christova
- Department of Veterans Affairs Health Care System, The Neuroimaging Research Group, Brain Sciences Center, Minneapolis, Minnesota, United States
- Department of Neuroscience, University of Minnesota Medical School, Minneapolis, Minnesota, United States
| | - Apostolos P Georgopoulos
- Department of Veterans Affairs Health Care System, The Neuroimaging Research Group, Brain Sciences Center, Minneapolis, Minnesota, United States
- Department of Neuroscience, University of Minnesota Medical School, Minneapolis, Minnesota, United States
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16
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Feng N, Palaniyappan L, Robbins TW, Cao L, Fang S, Luo X, Wang X, Luo Q. Working memory processing deficit associated with a nonlinear response pattern of the anterior cingulate cortex in first-episode and drug-naïve schizophrenia. Neuropsychopharmacology 2023; 48:552-559. [PMID: 36376466 PMCID: PMC9852448 DOI: 10.1038/s41386-022-01499-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 10/12/2022] [Accepted: 10/31/2022] [Indexed: 11/16/2022]
Abstract
Impaired working memory (WM) is a core neuropsychological dysfunction of schizophrenia, however complex interactions among the information storage, information processing and attentional aspects of WM tasks make it difficult to uncover the psychophysiological mechanisms of this deficit. Thirty-six first-episode and drug-naïve schizophrenia and 29 healthy controls (HCs) were enrolled in this study. Here, we modified a WM task to isolate components of WM storage and WM processing, while also varying the difficulty level (load) of the task to study regional differences in load-specific activation using mixed effects models, and its relationship to distributed gene expression. Comparing patients with HCs, we found both attentional deficits and WM deficits, with WM processing being more impaired than WM storage in patients. In patients, but not controls, a linear modulation of brain activation was observed mainly in the frontoparietal and dorsal attention networks. In controls, an inverted U-shaped response pattern was identified in the left anterior cingulate cortex. The vertex of this inverted U-shape was lower in patients than controls, and a left-shifting axis of symmetry was associated with better WM performance in patients. Both the above linear and U-shaped modulation effects were associated with the expressions of the genes enriched in the dopamine neurotransmitter system across all cortical brain regions. These findings indicate that a WM processing deficit is evident in schizophrenia from an early stage before antipsychotic treatment, and associated with a dopamine pathway related aberration in nonlinear response pattern at the cingulate cortex when processing WM load.
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Affiliation(s)
- Nana Feng
- National Clinical Research Center for Aging and Medicine at Huashan Hospital, MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200433, PR China
| | - Lena Palaniyappan
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, QC, Canada
- Robarts Research Institute, London, ON, Canada
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Trevor W Robbins
- Department Psychology and the Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, CB2 3EB, UK
- State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science and Human Phenome Institute, Research Institute of Intelligent Complex Systems, Fudan University, Shanghai, 200032, PR China
| | - Luolong Cao
- National Clinical Research Center for Aging and Medicine at Huashan Hospital, MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200433, PR China
| | - Shuanfeng Fang
- Department of Children Health Care, Children's Hospital Affiliated to Zhengzhou University, Zhengzhou, 450007, PR China
| | - Xingwei Luo
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, PR China
| | - Xiang Wang
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, PR China.
- China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, Hunan, PR China.
| | - Qiang Luo
- National Clinical Research Center for Aging and Medicine at Huashan Hospital, MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200433, PR China.
- State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science and Human Phenome Institute, Research Institute of Intelligent Complex Systems, Fudan University, Shanghai, 200032, PR China.
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17
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Goldstein KE, Feinberg A, Vaccaro DH, Ahmed T, Chu KW, Goodman M, Govindarajulu U, Challman KN, Haghighi F, Yehuda R, Szeszko PR, Osterberg T, Tang CY, Haznedar MM, Hazlett EA. Smaller rostral cingulate volume and psychosocial correlates in veterans at risk for suicide. Psychiatry Res 2023; 320:115032. [PMID: 36610318 DOI: 10.1016/j.psychres.2022.115032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 12/17/2022] [Accepted: 12/24/2022] [Indexed: 12/26/2022]
Abstract
Suicide research/clinical work remain in dire need of effective tools that can better predict suicidal behavior. A growing body of literature has started to focus on the role that neuroimaging may play in helping explain the path towards suicide. Specifically, structural alterations of rostral anterior cingulate cortex (rost-ACC) may represent a biological marker and/or indicator of suicide risk in Major Depressive Disorder (MDD). Furthermore, the construct of "grit," defined as perseverance for goal-attainment and shown to be associated with suicidality, is modulated by rost-ACC. The aim was to examine relationships among rost-ACC gray matter volume, grit, and suicidality in U.S. Military Veterans. Participants were age-and-sex-matched Veterans with MDD: with suicide attempt (MDD+SA:n = 23) and without (MDD-SA:n = 37). Groups did not differ in depression symptomatology. Participants underwent diagnostic interview, clinical symptom assessment, and 3T-MRI-scan. A Group (SA-vs.-No-SA) x Cingulate-region (rostral-caudal-posterior) x Hemisphere (left-right) mixed-model-multivariate-ANOVA was conducted. Left-rost-ACC was significantly smaller in MDD+SA, Group x Cingulate-region x Hemisphere-interaction. Lower grit and less left-rost-ACC gray matter each predicted suicide attempt history, but grit level was a more robust predictor of SA. Both structural alterations of rost-ACC and grit level represent potentially valuable tools for suicide risk assessment.
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Affiliation(s)
- Kim E Goldstein
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Abigail Feinberg
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Research & Development, James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA
| | - Daniel H Vaccaro
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Research & Development, James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA
| | - Tasnova Ahmed
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Research & Development, James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA
| | - King-Wai Chu
- Mental Illness Research, Education, and Clinical Center (MIRECC VISN 2), James J. Peters VA Medical Center, Bronx, NY, USA; Research & Development, James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA
| | - Marianne Goodman
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Mental Illness Research, Education, and Clinical Center (MIRECC VISN 2), James J. Peters VA Medical Center, Bronx, NY, USA
| | - Usha Govindarajulu
- Center for Biostatistics, Department of Population Health Science & Policy, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Katelyn N Challman
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Mental Illness Research, Education, and Clinical Center (MIRECC VISN 2), James J. Peters VA Medical Center, Bronx, NY, USA; Research & Development, James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA
| | - Fatemeh Haghighi
- Research & Development, James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Rachel Yehuda
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Mental Health Patient Care Center, James J. Peters VA Medical Center, Bronx, NY, USA
| | - Philip R Szeszko
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Mental Illness Research, Education, and Clinical Center (MIRECC VISN 2), James J. Peters VA Medical Center, Bronx, NY, USA; Mental Health Patient Care Center, James J. Peters VA Medical Center, Bronx, NY, USA
| | - Terra Osterberg
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Mental Illness Research, Education, and Clinical Center (MIRECC VISN 2), James J. Peters VA Medical Center, Bronx, NY, USA; Research & Development, James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA
| | - Cheuk Y Tang
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Diagnostic, Molecular, and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - M Mehmet Haznedar
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Mental Health Patient Care Center, James J. Peters VA Medical Center, Bronx, NY, USA
| | - Erin A Hazlett
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Mental Illness Research, Education, and Clinical Center (MIRECC VISN 2), James J. Peters VA Medical Center, Bronx, NY, USA; Research & Development, James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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18
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Arnsten AFT, Joyce MKP, Roberts AC. The Aversive Lens: Stress effects on the prefrontal-cingulate cortical pathways that regulate emotion. Neurosci Biobehav Rev 2023; 145:105000. [PMID: 36529312 PMCID: PMC9898199 DOI: 10.1016/j.neubiorev.2022.105000] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Revised: 12/08/2022] [Accepted: 12/10/2022] [Indexed: 12/23/2022]
Abstract
ARNSTEN, A.F.T., M.K.P. Joyce and A.C. Roberts. The Aversive Lens: Stress effects on the prefrontal-cingulate cortical pathways that regulate emotion. NEUROSCI BIOBEHAV REV XXX-XXX, 2022. The symptoms of major-depressive-disorder include psychic pain and anhedonia, i.e. seeing the world through an "aversive lens". The neurobiology underlying this shift in worldview is emerging. Here these data are reviewed, focusing on how activation of subgenual cingulate (BA25) induces an "aversive lens", and how higher prefrontal cortical (PFC) areas (BA46/10/32) provide top-down regulation of BA25 but are weakened by excessive dopamine and norepinephrine release during stress exposure, and dendritic spine loss with chronic stress exposure. These changes may generate an attractor state, which maintains the brain under the control of BA25, requiring medication or neuromodulatory treatments to return connectivity to a more flexible state. In line with this hypothesis, effective anti-depressant treatments reduce the activity of BA25 and restore top-down regulation by higher circuits, e.g. as seen with SSRI medications, ketamine, deep brain stimulation of BA25, or rTMS to strengthen dorsolateral PFC. This research has special relevance in an era of chronic stress caused by the COVID19 pandemic, political unrest and threat of climate change.
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Affiliation(s)
- Amy F T Arnsten
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT 06510, USA.
| | - Mary Kate P Joyce
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT 06510, USA.
| | - Angela C Roberts
- Department Physiology, Development and Neuroscience, and Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge CB2 3DY, UK.
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19
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Stout DM, Harlé KM, Norman SB, Simmons AN, Spadoni AD. Resting-state connectivity subtype of comorbid PTSD and alcohol use disorder moderates improvement from integrated prolonged exposure therapy in Veterans. Psychol Med 2023; 53:332-341. [PMID: 33926595 PMCID: PMC10880798 DOI: 10.1017/s0033291721001513] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
BACKGROUND Posttraumatic stress disorder (PTSD) and alcohol use disorder (AUD) are highly comorbid and are associated with significant functional impairment and inconsistent treatment outcomes. Data-driven subtyping of this clinically heterogeneous patient population and the associated underlying neural mechanisms are highly needed to identify who will benefit from psychotherapy. METHODS In 53 comorbid PTSD/AUD patients, resting-state functional magnetic resonance imaging was collected prior to undergoing individual psychotherapy. We used a data-driven approach to subgroup patients based on directed connectivity profiles. Connectivity subgroups were compared on clinical measures of PTSD severity and heavy alcohol use collected at pre- and post-treatment. RESULTS We identified a subgroup of patients associated with improvement in PTSD symptoms from integrated-prolonged exposure therapy. This subgroup was characterized by lower insula to inferior parietal cortex (IPC) connectivity, higher pregenual anterior cingulate cortex (pgACC) to posterior midcingulate cortex connectivity and a unique pgACC to IPC path. We did not observe any connectivity subgroup that uniquely benefited from integrated-coping skills or subgroups associated with change in alcohol consumption. CONCLUSIONS Data-driven approaches to characterize PTSD/AUD subtypes have the potential to identify brain network profiles that are implicated in the benefit from psychological interventions - setting the stage for future research that targets these brain circuit communication patterns to boost treatment efficacy.
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Affiliation(s)
- Daniel M. Stout
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
- Research Service, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Katia M. Harlé
- Research Service, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Sonya B. Norman
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
- Research Service, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
- National Center for PTSD, White River Junction, Vermont, USA
| | - Alan N. Simmons
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
- Research Service, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Andrea D. Spadoni
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
- Research Service, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
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20
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Kulkarni M, Covey TJ. Examination of the temporal-spatial dynamics of working memory training-induced neuroplasticity. Brain Res 2023; 1798:148135. [DOI: 10.1016/j.brainres.2022.148135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 10/24/2022] [Accepted: 10/26/2022] [Indexed: 11/16/2022]
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21
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Chen ZS. Hierarchical predictive coding in distributed pain circuits. Front Neural Circuits 2023; 17:1073537. [PMID: 36937818 PMCID: PMC10020379 DOI: 10.3389/fncir.2023.1073537] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 02/07/2023] [Indexed: 03/06/2023] Open
Abstract
Predictive coding is a computational theory on describing how the brain perceives and acts, which has been widely adopted in sensory processing and motor control. Nociceptive and pain processing involves a large and distributed network of circuits. However, it is still unknown whether this distributed network is completely decentralized or requires networkwide coordination. Multiple lines of evidence from human and animal studies have suggested that the cingulate cortex and insula cortex (cingulate-insula network) are two major hubs in mediating information from sensory afferents and spinothalamic inputs, whereas subregions of cingulate and insula cortices have distinct projections and functional roles. In this mini-review, we propose an updated hierarchical predictive coding framework for pain perception and discuss its related computational, algorithmic, and implementation issues. We suggest active inference as a generalized predictive coding algorithm, and hierarchically organized traveling waves of independent neural oscillations as a plausible brain mechanism to integrate bottom-up and top-down information across distributed pain circuits.
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Affiliation(s)
- Zhe Sage Chen
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY, United States
- Department of Neuroscience and Physiology, New York University Grossman School of Medicine, New York, NY, United States
- Neuroscience Institute, NYU Grossman School of Medicine, New York, NY, United States
- Department of Biomedical Engineering, NYU Tandon School of Engineering, Brooklyn, NY, United States
- Interdisciplinary Pain Research Program, NYU Langone Health, New York, NY, United States
- *Correspondence: Zhe Sage Chen
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22
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Haber SN, Lehman J, Maffei C, Yendiki A. The rostral zona incerta: a subcortical integrative hub and potential DBS target for OCD. Biol Psychiatry 2023; 93:1010-1022. [PMID: 37055285 DOI: 10.1016/j.biopsych.2023.01.006] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 12/13/2022] [Accepted: 01/08/2023] [Indexed: 01/20/2023]
Abstract
BACKGROUND The zona incerta (ZI) is involved in mediating survival behaviors and is connected to a wide range of cortical and subcortical structures, including key basal ganglia nuclei. Based on these connections and their links to behavioral modulation, we propose that the ZI is a connectional hub for mediating between top-down and bottom-up control and a possible target for deep brain stimulation for obsessive-compulsive disorder. METHODS We analyzed the trajectory of cortical fibers to the ZI in nonhuman and human primates based on tracer injections in monkeys and high-resolution diffusion magnetic resonance imaging in humans. The organization of cortical and subcortical connections within the ZI were identified in the nonhuman primate studies. RESULTS Monkey anatomical data and human diffusion magnetic resonance imaging data showed a similar trajectory of fibers/streamlines to the ZI. Prefrontal cortex/anterior cingulate cortex terminals all converged within the rostral ZI, with dorsal and lateral areas being most prominent. Motor areas terminated caudally. Dense subcortical reciprocal connections included the thalamus, medial hypothalamus, substantia nigra/ventral tegmental area, reticular formation, and pedunculopontine nucleus and a dense nonreciprocal projection to the lateral habenula. Additional connections included the amygdala, dorsal raphe nucleus, and periaqueductal gray. CONCLUSIONS Dense connections with dorsal and lateral prefrontal cortex/anterior cingulate cortex cognitive control areas and the lateral habenula and the substantia nigra/ventral tegmental area, coupled with inputs from the amygdala, hypothalamus, and brainstem, suggest that the rostral ZI is a subcortical hub positioned to modulate between top-down and bottom-up control. A deep brain stimulation electrode placed in the rostral ZI would not only involve connections common to other deep brain stimulation sites but also capture several critically distinctive connections.
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Affiliation(s)
- Suzanne N Haber
- Department of Pharmacology & Physiology, University of Rochester School of Medicine and Dentistry, Rochester, New York; Department of Psychiatry, McLean Hospital, Harvard Medical School, Belmont, Massachusetts.
| | - Julia Lehman
- Department of Pharmacology & Physiology, University of Rochester School of Medicine and Dentistry, Rochester, New York
| | - Chiara Maffei
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Anastasia Yendiki
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
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23
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Effects of Mental Fatigue on Strength Endurance: A Systematic Review and Meta-Analysis. Motor Control 2022; 27:442-461. [PMID: 36509089 DOI: 10.1123/mc.2022-0051] [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: 04/13/2022] [Revised: 10/14/2022] [Accepted: 10/15/2022] [Indexed: 12/14/2022]
Abstract
The purpose of the present systematic review and meta-analysis was to explore the effects of mental fatigue on upper and lower body strength endurance. Searches for studies were performed in the PubMed/MEDLINE and Web of Science databases. We included studies that compared the effects of a demanding cognitive task (set to induce mental fatigue) with a control condition on strength endurance in dynamic resistance exercise (i.e., expressed as the number of performed repetitions at a given load). The data reported in the included studies were pooled in a random-effects meta-analysis of standardized mean differences. Seven studies were included in the review. We found that mental fatigue significantly reduced the number of performed repetitions for upper body exercises (standardized mean difference: -0.41; 95% confidence interval [-0.70, -0.12]; p = .006; I2 = 0%). Mental fatigue also significantly reduced the number of performed repetitions in the analysis for lower body exercises (standardized mean difference: -0.39; 95% confidence interval [-0.75, -0.04]; p = .03; I2 = 0%). Our results showed that performing a demanding cognitive task-which induces mental fatigue-impairs strength endurance performance. Collectively, our findings suggest that exposure to cognitive tasks that may induce mental fatigue should be minimized before strength endurance-based resistance exercise sessions.
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24
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Jamshidi J, Park HRP, Montalto A, Fullerton JM, Gatt JM. Wellbeing and brain structure: A comprehensive phenotypic and genetic study of image-derived phenotypes in the UK Biobank. Hum Brain Mapp 2022; 43:5180-5193. [PMID: 35765890 PMCID: PMC9812238 DOI: 10.1002/hbm.25993] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 06/07/2022] [Accepted: 06/13/2022] [Indexed: 01/15/2023] Open
Abstract
Wellbeing, an important component of mental health, is influenced by genetic and environmental factors. Previous association studies between brain structure and wellbeing have typically focused on volumetric measures and employed small cohorts. Using the UK Biobank Resource, we explored the relationships between wellbeing and brain morphometrics (volume, thickness and surface area) at both phenotypic and genetic levels. The sample comprised 38,982 participants with neuroimaging and wellbeing phenotype data, of which 19,234 had genotypes from which wellbeing polygenic scores (PGS) were calculated. We examined the association of wellbeing phenotype and PGS with all brain regions (including cortical, subcortical, brainstem and cerebellar regions) using multiple linear models, including (1) basic neuroimaging covariates and (2) additional demographic factors that may synergistically impact wellbeing and its neural correlates. Genetic correlations between genomic variants influencing wellbeing and brain structure were also investigated. Small but significant associations between wellbeing and volumes of several cerebellar structures (β = 0.015-0.029, PFDR = 0.007-3.8 × 10-9 ), brainstem, nucleus accumbens and caudate were found. Cortical associations with wellbeing included volume of right lateral occipital, thickness of bilateral lateral occipital and cuneus, and surface area of left superior parietal, supramarginal and pre-/post-central regions. Wellbeing-PGS was associated with cerebellar volumes and supramarginal surface area. Small mediation effects of wellbeing phenotype and PGS on right VIIIb cerebellum were evident. No genetic correlation was found between wellbeing and brain morphometric measures. We provide a comprehensive overview of wellbeing-related brain morphometric variation. Notably, small effect sizes reflect the multifaceted nature of this concept.
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Affiliation(s)
- Javad Jamshidi
- Neuroscience Research Australia, Sydney, New South Wales, Australia.,School of Psychology, University of New South Wales, Sydney, New South Wales, Australia
| | - Haeme R P Park
- Neuroscience Research Australia, Sydney, New South Wales, Australia.,School of Psychology, University of New South Wales, Sydney, New South Wales, Australia
| | - Arthur Montalto
- Neuroscience Research Australia, Sydney, New South Wales, Australia.,School of Psychology, University of New South Wales, Sydney, New South Wales, Australia
| | - Janice M Fullerton
- Neuroscience Research Australia, Sydney, New South Wales, Australia.,School of Medical Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | - Justine M Gatt
- Neuroscience Research Australia, Sydney, New South Wales, Australia.,School of Psychology, University of New South Wales, Sydney, New South Wales, Australia
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25
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Stout DM, Simmons AN, Nievergelt CM, Minassian A, Biswas N, Maihofer AX, Risbrough VB, Baker DG. Deriving psychiatric symptom-based biomarkers from multivariate relationships between psychophysiological and biochemical measures. Neuropsychopharmacology 2022; 47:2252-2260. [PMID: 35347268 PMCID: PMC9630445 DOI: 10.1038/s41386-022-01303-7] [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: 10/21/2021] [Revised: 01/18/2022] [Accepted: 02/28/2022] [Indexed: 11/08/2022]
Abstract
Identification of biomarkers for psychiatric disorders remains very challenging due to substantial symptom heterogeneity and diagnostic comorbidity, limiting the ability to map symptoms to underlying neurobiology. Dimensional symptom clusters, such as anhedonia, hyperarousal, etc., are complex and arise due to interactions of a multitude of complex biological relationships. The primary aim of the current investigation was to use multi-set canonical correlation analysis (mCCA) to derive biomarkers (biochemical, physiological) linked to dimensional symptoms across the anxiety and depressive spectrum. Active-duty service members (N = 2,592) completed standardized depression, anxiety and posttraumatic stress questionnaires and several psychophysiological and biochemical assays. Using this approach, we identified two phenotype associations between distinct physiological and biological phenotypes. One was characterized by symptoms of dysphoric arousal (anhedonia, anxiety, hypervigilance) which was associated with low blood pressure and startle reactivity. This finding is in line with previous studies suggesting blunted physiological reactivity is associated with subpopulations endorsing anxiety with comorbid depressive features. A second phenotype of anxious fatigue (high anxiety and reexperiencing/avoidance symptoms coupled with fatigue) was associated with elevated blood levels of norepinephrine and the inflammatory marker C-reactive protein in conjunction with high blood pressure. This second phenotype may describe populations in which inflammation and high sympathetic outflow might contribute to anxious fatigue. Overall, these findings support the growing consensus that distinct neuropsychiatric symptom patterns are associated with differential physiological and blood-based biological profiles and highlight the potential of mCCA to reveal important psychiatric symptom biomarkers from several psychophysiological and biochemical measures.
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Affiliation(s)
- Daniel M Stout
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, 92161, USA.
- Department of Psychiatry, University of California San Diego, La Jolla, CA, 92093, USA.
| | - Alan N Simmons
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, 92161, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, 92093, USA
| | - Caroline M Nievergelt
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, 92161, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, 92093, USA
| | - Arpi Minassian
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, 92161, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, 92093, USA
| | - Nilima Biswas
- Department of Pathology, University of California San Diego, La Jolla, CA, 92093, USA
| | - Adam X Maihofer
- Department of Psychiatry, University of California San Diego, La Jolla, CA, 92093, USA
| | - Victoria B Risbrough
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, 92161, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, 92093, USA
| | - Dewleen G Baker
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, 92161, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, 92093, USA
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26
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Ravindranath O, Calabro FJ, Foran W, Luna B. Pubertal development underlies optimization of inhibitory control through specialization of ventrolateral prefrontal cortex. Dev Cogn Neurosci 2022; 58:101162. [PMID: 36308857 PMCID: PMC9618767 DOI: 10.1016/j.dcn.2022.101162] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 10/04/2022] [Accepted: 10/11/2022] [Indexed: 01/13/2023] Open
Abstract
Inhibitory control improves into young adulthood after specialization of relevant brain systems during adolescence. However, the biological mechanisms supporting this unique transition are not well understood. Given that adolescence is defined by puberty, we examined relative contributions of chronological age and pubertal maturation to inhibitory control development. 105 8-19-year-olds completed 1-5 longitudinal visits (227 visits total) in which pubertal development was assessed via self-reported Tanner stage and inhibitory control was assessed with an in-scanner antisaccade task. As expected, percentage and latency of correct antisaccade responses improved with age and pubertal stage. When controlling for pubertal stage, chronological age was distinctly associated with correct response rate. In contrast, pubertal stage was uniquely associated with antisaccade latency even when controlling for age. Chronological age was associated with fMRI task activation in several regions including the right dorsolateral prefrontal cortex, while puberty was associated with right ventrolateral prefrontal cortex (VLPFC) activation. Furthermore, task-related connectivity between VLPFC and cingulate was associated with both pubertal stage and response latency. These results suggest that while age-related developmental processes may support maturation of brain systems underlying the ability to inhibit a response, puberty may play a larger role in the effectiveness of generating cognitive control responses.
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Affiliation(s)
- Orma Ravindranath
- Psychology, University of Pittsburgh, USA; Center for Neural Basis of Cognition, University of Pittsburgh, USA.
| | - Finnegan J Calabro
- Center for Neural Basis of Cognition, University of Pittsburgh, USA; Psychiatry, University of Pittsburgh, USA; Bioengineering, University of Pittsburgh, USA
| | | | - Beatriz Luna
- Psychology, University of Pittsburgh, USA; Center for Neural Basis of Cognition, University of Pittsburgh, USA; Psychiatry, University of Pittsburgh, USA
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27
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Korponay C, Stein EA, Ross TJ. Misconfigured striatal connectivity profiles in smokers. Neuropsychopharmacology 2022; 47:2081-2089. [PMID: 35752682 PMCID: PMC9556661 DOI: 10.1038/s41386-022-01366-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 05/19/2022] [Accepted: 06/14/2022] [Indexed: 11/09/2022]
Abstract
Dysregulation of frontal cortical inputs to the striatum is foundational in the neural basis of substance use disorder (SUD). Neuroanatomical and electrophysiological data increasingly show that striatal nodes receive appreciable input from numerous cortical areas, and that the combinational properties of these multivariate "connectivity profiles" play a predominant role in shaping striatal activity and function. Yet, how abnormal configuration of striatal connectivity profiles might contribute to SUD is unknown. Here, we implemented a novel "connectivity profile analysis" (CPA) approach using resting-state functional connectivity data to facilitate detection of different types of connectivity profile "misconfiguration" that may reflect distinct forms of aberrant circuit plasticity in SUD. We examined 46 nicotine-dependent smokers and 33 non-smokers and showed that both dorsal striatum (DS) and ventral striatum (VS) connectivity profiles with frontal cortex were misconfigured in smokers-but in doubly distinct fashions. DS misconfigurations were stable across sated and acute abstinent states (indicative of a "trait" circuit adaptation) whereas VS misconfigurations emerged only during acute abstinence (indicative of a "state" circuit adaptation). Moreover, DS misconfigurations involved abnormal connection strength rank order arrangement, whereas VS misconfigurations involved abnormal aggregate strength. We found that caudal ventral putamen in smokers uniquely displayed multiple types of connectivity profile misconfiguration, whose interactive magnitude was linked to dependence severity, and that VS misconfiguration magnitude correlated positively with withdrawal severity during acute abstinence. Findings underscore the potential for approaches that more aptly model the neurobiological composition of corticostriatal circuits to yield deeper insights into the neural basis of SUD.
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Affiliation(s)
- Cole Korponay
- Basic Neuroscience Division, McLean Hospital, Belmont, MA, USA.
| | - Elliot A Stein
- Neuroimaging Research Branch, Intramural Research Program, National Institute on Drug Abuse, Baltimore, MD, USA
| | - Thomas J Ross
- Neuroimaging Research Branch, Intramural Research Program, National Institute on Drug Abuse, Baltimore, MD, USA
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Sawrikar V, Macbeth A, Gillespie-Smith K, Brown M, Lopez-Williams A, Boulton K, Guestella A, Hickie I. Transdiagnostic Clinical Staging for Childhood Mental Health: An Adjunctive Tool for Classifying Internalizing and Externalizing Syndromes that Emerge in Children Aged 5-11 Years. Clin Child Fam Psychol Rev 2022; 25:613-626. [PMID: 35598197 PMCID: PMC9427921 DOI: 10.1007/s10567-022-00399-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/03/2022] [Indexed: 11/20/2022]
Abstract
Clinical staging is now recognized as a key tool for facilitating innovation in personalized and preventative mental health care. It places a strong emphasis on the salience of indicated prevention, early intervention, and secondary prevention of major mental disorders. By contrast to established models for major mood and psychotic syndromes that emerge after puberty, developments in clinical staging for childhood-onset disorders lags significantly behind. In this article, criteria for a transdiagnostic staging model for those internalizing and externalizing disorders that emerge in childhood is presented. This sits alongside three putative pathophysiological profiles (developmental, circadian, and anxious-arousal) that may underpin these common illness trajectories. Given available evidence, we argue that it is now timely to develop a transdiagnostic staging model for childhood-onset syndromes. It is further argued that a transdiagnostic staging model has the potential to capture more precisely the dimensional, fluctuating developmental patterns of illness progression of childhood psychopathology. Given potential improvements in modelling etiological processes, and delivering more personalized interventions, transdiagnostic clinical staging for childhood holds much promise for assisting to improve outcomes. We finish by presenting an agenda for research in developments of transdiagnostic clinical staging for childhood mental health.
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Affiliation(s)
- Vilas Sawrikar
- Centre of Applied Developmental Psychology, University of Edinburgh, Edinburgh, UK.
- Department of Clinical & Health Psychology, School of Health in Social Sciences, The University of Edinburgh, Medical School (Doorway 6), Room 1M.8, Teviot Place, Edinburgh, EH8 9AG, UK.
| | - Angus Macbeth
- Centre of Applied Developmental Psychology, University of Edinburgh, Edinburgh, UK
- Department of Clinical & Health Psychology, School of Health in Social Sciences, The University of Edinburgh, Medical School (Doorway 6), Room 1M.8, Teviot Place, Edinburgh, EH8 9AG, UK
| | - Karri Gillespie-Smith
- Centre of Applied Developmental Psychology, University of Edinburgh, Edinburgh, UK
- Department of Clinical & Health Psychology, School of Health in Social Sciences, The University of Edinburgh, Medical School (Doorway 6), Room 1M.8, Teviot Place, Edinburgh, EH8 9AG, UK
| | - Megan Brown
- ADHD & Autism Psychological Services and Advocacy, Utica, NY, USA
| | | | - Kelsie Boulton
- Brain and Mind Centre, University of Sydney, Sydney, Australia
| | - Adam Guestella
- Brain and Mind Centre, University of Sydney, Sydney, Australia
| | - Ian Hickie
- Brain and Mind Centre, University of Sydney, Sydney, Australia
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29
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Maffei C, Girard G, Schilling KG, Aydogan DB, Adluru N, Zhylka A, Wu Y, Mancini M, Hamamci A, Sarica A, Teillac A, Baete SH, Karimi D, Yeh FC, Yildiz ME, Gholipour A, Bihan-Poudec Y, Hiba B, Quattrone A, Quattrone A, Boshkovski T, Stikov N, Yap PT, de Luca A, Pluim J, Leemans A, Prabhakaran V, Bendlin BB, Alexander AL, Landman BA, Canales-Rodríguez EJ, Barakovic M, Rafael-Patino J, Yu T, Rensonnet G, Schiavi S, Daducci A, Pizzolato M, Fischi-Gomez E, Thiran JP, Dai G, Grisot G, Lazovski N, Puch S, Ramos M, Rodrigues P, Prčkovska V, Jones R, Lehman J, Haber SN, Yendiki A. Insights from the IronTract challenge: Optimal methods for mapping brain pathways from multi-shell diffusion MRI. Neuroimage 2022; 257:119327. [PMID: 35636227 PMCID: PMC9453851 DOI: 10.1016/j.neuroimage.2022.119327] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 05/06/2022] [Accepted: 05/19/2022] [Indexed: 01/25/2023] Open
Abstract
Limitations in the accuracy of brain pathways reconstructed by diffusion MRI (dMRI) tractography have received considerable attention. While the technical advances spearheaded by the Human Connectome Project (HCP) led to significant improvements in dMRI data quality, it remains unclear how these data should be analyzed to maximize tractography accuracy. Over a period of two years, we have engaged the dMRI community in the IronTract Challenge, which aims to answer this question by leveraging a unique dataset. Macaque brains that have received both tracer injections and ex vivo dMRI at high spatial and angular resolution allow a comprehensive, quantitative assessment of tractography accuracy on state-of-the-art dMRI acquisition schemes. We find that, when analysis methods are carefully optimized, the HCP scheme can achieve similar accuracy as a more time-consuming, Cartesian-grid scheme. Importantly, we show that simple pre- and post-processing strategies can improve the accuracy and robustness of many tractography methods. Finally, we find that fiber configurations that go beyond crossing (e.g., fanning, branching) are the most challenging for tractography. The IronTract Challenge remains open and we hope that it can serve as a valuable validation tool for both users and developers of dMRI analysis methods.
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Affiliation(s)
- Chiara Maffei
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, 149 13th Street, Charlestown, MA 02129, United States.
| | - Gabriel Girard
- University Hospital Center (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland; CIBM Center for Biomedical Imaging, Lausanne, Switzerland; Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne (EPFL), Switzerland
| | - Kurt G Schilling
- Vanderbilt Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Dogu Baran Aydogan
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland; Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland
| | | | - Andrey Zhylka
- Biomedical Engineering, Eindhoven University of Technology, Netherlands
| | - Ye Wu
- Department of Radiology and Biomedical Research Imaging Center (BRIC), University of North Carolina, Chapel Hill, United States
| | - Matteo Mancini
- Cardiff University Brain Research Imaging Center (CUBRIC), Cardiff University, Cardiff, United Kingdom; NeuroPoly, Polytechnique Montreal, Montreal, Canada
| | - Andac Hamamci
- Department of Biomedical Engineering, Faculty of Engineering, Yeditepe University, Istanbul, Turkey
| | - Alessia Sarica
- Neuroscience Research Center, University "Magna Graecia", Catanzaro, Italy
| | - Achille Teillac
- Institute of Cognitive Neuroscience Marc Jeannerod, CNRS / UMR 5229, Bron 69500, France; Université Claude Bernard, Lyon 1, Villeurbanne 69100, France
| | - Steven H Baete
- Center for Advanced Imaging Innovation and Research (CAI2R), NYU School of Medicine, New York, NY, United States; Department of Radiology, Center for Biomedical Imaging, NYU School of Medicine, New York, NY, United States
| | - Davood Karimi
- Department of Radiology, Computational Radiology Laboratory, Boston Children's Hospital, Harvard Medical School, Boston, MA, United States
| | - Fang-Cheng Yeh
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, United States
| | - Mert E Yildiz
- Department of Biomedical Engineering, Faculty of Engineering, Yeditepe University, Istanbul, Turkey
| | - Ali Gholipour
- Department of Radiology, Computational Radiology Laboratory, Boston Children's Hospital, Harvard Medical School, Boston, MA, United States
| | - Yann Bihan-Poudec
- Institute of Cognitive Neuroscience Marc Jeannerod, CNRS / UMR 5229, Bron 69500, France; Université Claude Bernard, Lyon 1, Villeurbanne 69100, France
| | - Bassem Hiba
- Institute of Cognitive Neuroscience Marc Jeannerod, CNRS / UMR 5229, Bron 69500, France; Université Claude Bernard, Lyon 1, Villeurbanne 69100, France
| | - Andrea Quattrone
- Institute of Neurology, University "Magna Graecia", Catanzaro, Italy
| | - Aldo Quattrone
- Neuroscience Research Center, University "Magna Graecia", Catanzaro, Italy
| | | | | | - Pew-Thian Yap
- Department of Radiology and Biomedical Research Imaging Center (BRIC), University of North Carolina, Chapel Hill, United States
| | - Alberto de Luca
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands; Neurology Department, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Josien Pluim
- Biomedical Engineering, Eindhoven University of Technology, Netherlands
| | - Alexander Leemans
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands
| | | | | | | | - Bennett A Landman
- Vanderbilt Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States; Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, United States
| | - Erick J Canales-Rodríguez
- Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne (EPFL), Switzerland
| | - Muhamed Barakovic
- Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Neurologic Clinic and Polyclinic, Basel, Switzerland
| | - Jonathan Rafael-Patino
- Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne (EPFL), Switzerland
| | - Thomas Yu
- Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne (EPFL), Switzerland
| | - Gaëtan Rensonnet
- Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne (EPFL), Switzerland
| | - Simona Schiavi
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland; University of Verona, Verona, Italy
| | | | - Marco Pizzolato
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kgs. Lyngby, Denmark; Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne (EPFL), Switzerland
| | - Elda Fischi-Gomez
- Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne (EPFL), Switzerland
| | - Jean-Philippe Thiran
- University Hospital Center (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland; CIBM Center for Biomedical Imaging, Lausanne, Switzerland; Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne (EPFL), Switzerland
| | - George Dai
- Wellesley College, Wellesley, MA, United States
| | | | | | | | | | | | | | - Robert Jones
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, 149 13th Street, Charlestown, MA 02129, United States
| | - Julia Lehman
- Department of Pharmacology and Physiology, University of Rochester School of Medicine, Rochester, NY, United States
| | - Suzanne N Haber
- Department of Pharmacology and Physiology, University of Rochester School of Medicine, Rochester, NY, United States
| | - Anastasia Yendiki
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, 149 13th Street, Charlestown, MA 02129, United States
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30
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Fan Q, Eichner C, Afzali M, Mueller L, Tax CMW, Davids M, Mahmutovic M, Keil B, Bilgic B, Setsompop K, Lee HH, Tian Q, Maffei C, Ramos-Llordén G, Nummenmaa A, Witzel T, Yendiki A, Song YQ, Huang CC, Lin CP, Weiskopf N, Anwander A, Jones DK, Rosen BR, Wald LL, Huang SY. Mapping the human connectome using diffusion MRI at 300 mT/m gradient strength: Methodological advances and scientific impact. Neuroimage 2022; 254:118958. [PMID: 35217204 PMCID: PMC9121330 DOI: 10.1016/j.neuroimage.2022.118958] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2021] [Revised: 01/27/2022] [Accepted: 01/31/2022] [Indexed: 12/20/2022] Open
Abstract
Tremendous efforts have been made in the last decade to advance cutting-edge MRI technology in pursuit of mapping structural connectivity in the living human brain with unprecedented sensitivity and speed. The first Connectom 3T MRI scanner equipped with a 300 mT/m whole-body gradient system was installed at the Massachusetts General Hospital in 2011 and was specifically constructed as part of the Human Connectome Project. Since that time, numerous technological advances have been made to enable the broader use of the Connectom high gradient system for diffusion tractography and tissue microstructure studies and leverage its unique advantages and sensitivity to resolving macroscopic and microscopic structural information in neural tissue for clinical and neuroscientific studies. The goal of this review article is to summarize the technical developments that have emerged in the last decade to support and promote large-scale and scientific studies of the human brain using the Connectom scanner. We provide a brief historical perspective on the development of Connectom gradient technology and the efforts that led to the installation of three other Connectom 3T MRI scanners worldwide - one in the United Kingdom in Cardiff, Wales, another in continental Europe in Leipzig, Germany, and the latest in Asia in Shanghai, China. We summarize the key developments in gradient hardware and image acquisition technology that have formed the backbone of Connectom-related research efforts, including the rich array of high-sensitivity receiver coils, pulse sequences, image artifact correction strategies and data preprocessing methods needed to optimize the quality of high-gradient strength diffusion MRI data for subsequent analyses. Finally, we review the scientific impact of the Connectom MRI scanner, including advances in diffusion tractography, tissue microstructural imaging, ex vivo validation, and clinical investigations that have been enabled by Connectom technology. We conclude with brief insights into the unique value of strong gradients for diffusion MRI and where the field is headed in the coming years.
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Affiliation(s)
- Qiuyun Fan
- Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Cornelius Eichner
- Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neuropsychology, Leipzig, Germany
| | - Maryam Afzali
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, Wales, UK; Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds LS2 9JT, UK
| | - Lars Mueller
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds LS2 9JT, UK
| | - Chantal M W Tax
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, Wales, UK; Image Sciences Institute, University Medical Center (UMC) Utrecht, Utrecht, the Netherlands
| | - Mathias Davids
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA; Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Mirsad Mahmutovic
- Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), Giessen, Germany
| | - Boris Keil
- Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), Giessen, Germany
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Kawin Setsompop
- Department of Radiology, Stanford University, Stanford, CA, USA; Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Hong-Hsi Lee
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Qiyuan Tian
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Chiara Maffei
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Gabriel Ramos-Llordén
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Aapo Nummenmaa
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA
| | | | - Anastasia Yendiki
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Yi-Qiao Song
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA USA
| | - Chu-Chung Huang
- Key Laboratory of Brain Functional Genomics (MOE & STCSM), Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China; Shanghai Changning Mental Health Center, Shanghai, China
| | - Ching-Po Lin
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany
| | - Alfred Anwander
- Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neuropsychology, Leipzig, Germany
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, Wales, UK
| | - Bruce R Rosen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Lawrence L Wald
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Susie Y Huang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA.
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31
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Ash H, Chang A, Ortiz RJ, Kulkarni P, Rauch B, Colman R, Ferris CF, Ziegler TE. Structural and functional variations in the prefrontal cortex are associated with learning in pre-adolescent common marmosets (Callithrix jacchus). Behav Brain Res 2022; 430:113920. [PMID: 35595058 PMCID: PMC9362994 DOI: 10.1016/j.bbr.2022.113920] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 04/06/2022] [Accepted: 05/04/2022] [Indexed: 12/27/2022]
Abstract
There is substantial evidence linking the prefrontal cortex (PFC) to a variety of cognitive abilities, with adolescence being a critical period in its development. In the current study, we investigated the neural basis of differences in learning in pre-adolescent common marmosets. At 8 months old, marmosets were given anatomical and resting state MRI scans (n=24). At 9 months old, association learning and inhibitory control was tested using a 'go/no go' visual discrimination (VD) task. Marmosets were grouped into 'learners' (n=12) and 'non-learners' (n=12), and associations between cognitive performance and sub-regional PFC volumes, as well as PFC connectivity patterns, were investigated. 'Learners' had significantly (p<0.05) larger volumes of areas 11, 25, 47 and 32 than 'non-learners', although 'non-learners' had significantly larger volumes of areas 24a and 8v than 'learners'. There was also a significant correlation between average % correct responses to the 'punished' stimulus and volume of area 47. Further, 'non-learners' had significantly greater global PFC connections, as well as significantly greater numbers of connections between the PFC and basal ganglia, cerebellum and hippocampus, compared to 'non-learners'. These results suggest that larger sub-regions of the orbitofrontal cortex and ventromedial PFC, as well more refined PFC connectivity patterns to other brain regions associated with learning, may be important in successful response inhibition. This study therefore offers new information on the neurodevelopment of individual differences in cognition during pre-adolescence in non-human primates.
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Affiliation(s)
- Hayley Ash
- Wisconsin National Primate Research Center, University of Wisconsin, Madison WI.
| | - Arnold Chang
- Center for Translational NeuroImaging, Northeastern University, Boston MA
| | - Richard J Ortiz
- Center for Translational NeuroImaging, Northeastern University, Boston MA; Department of Chemistry and Biochemistry, New Mexico State University, Las Cruces NM
| | - Praveen Kulkarni
- Center for Translational NeuroImaging, Northeastern University, Boston MA
| | - Beth Rauch
- Department of Medical Physics, University of Wisconsin, Madison WI
| | - Ricki Colman
- Wisconsin National Primate Research Center, University of Wisconsin, Madison WI; Department of Cell and Regenerative Biology, University of Wisconsin, Madison WI
| | - Craig F Ferris
- Center for Translational NeuroImaging, Northeastern University, Boston MA
| | - Toni E Ziegler
- Wisconsin National Primate Research Center, University of Wisconsin, Madison WI
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32
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Marinkovic K, Rosen BQ. Theta oscillatory dynamics of inhibitory control, error processing, and post-error adjustments: Neural underpinnings and alcohol-induced dysregulation. Alcohol Clin Exp Res 2022; 46:1220-1232. [PMID: 35567304 PMCID: PMC9543652 DOI: 10.1111/acer.14856] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 05/02/2022] [Accepted: 05/06/2022] [Indexed: 11/28/2022]
Abstract
BACKGROUND Alcohol intoxication impairs inhibitory control, resulting in disinhibited, impulsive behavior. The anterior cingulate cortex (ACC) plays an essential role in a range of executive functions and is sensitive to the effects of alcohol, which contributes to the top-down cognitive dysregulation. This study used a multimodal approach to examine the acute effects of alcohol on the neural underpinnings of inhibitory control, inhibition failures, and neurobehavioral optimization as reflected in trial-to-trial dynamics of post-error adjustments. METHODS Adult social drinkers served as their own controls by participating in the Go/NoGo task during acute alcohol and placebo conditions in a multi-session, counterbalanced design. Distributed source modeling of the magnetoencephalographic signal was combined with structural magnetic resonance imaging to characterize the spatio-temporal dynamics of inhibitory control in the time-frequency domain. RESULTS Successful response inhibition (NoGo) elicited right-lateralized event-related theta power (4 to 7 Hz). Errors elicited a short-latency increase in theta power in the dorsal (dACC), followed by activity in the rostral (rACC), which may underlie an affective "oh, no!" orienting response to errors. Error-related theta in the dACC was associated with subsequent activity of the motor areas on the first post-error trial, suggesting the occurrence of post-error output adjustments. Importantly, a gradual increase of the dACC theta across post-error trials closely tracked improvements in accuracy under placebo, which may reflect cognitive control engagement to optimize response accuracy. In contrast, alcohol increased NoGo commission errors, dysregulated theta during correct NoGo withholding, and abolished the post-error theta enhancement of cognitive control. CONCLUSIONS Confirming the sensitivity of frontal theta to inhibitory control and error monitoring, the results support functional and temporal dissociation along the dorso-rostral axis of the ACC and the deleterious effects of alcohol on the frontal circuitry subserving top-down regulation. Over time, alcohol-induced disinhibition may give rise to compulsive drinking and contribute to alcohol misuse.
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Affiliation(s)
- Ksenija Marinkovic
- Psychology Department, San Diego State University, San Diego, California, USA.,Radiology Department, University of California, San Diego, California, USA
| | - Burke Q Rosen
- Psychology Department, San Diego State University, San Diego, California, USA.,Department of Neurosciences, University of California, San Diego, California, USA
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Trambaiolli LR, Peng X, Lehman JF, Linn G, Russ BE, Schroeder CE, Liu H, Haber SN. Anatomical and functional connectivity support the existence of a salience network node within the caudal ventrolateral prefrontal cortex. eLife 2022; 11:e76334. [PMID: 35510840 PMCID: PMC9106333 DOI: 10.7554/elife.76334] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Accepted: 05/04/2022] [Indexed: 11/13/2022] Open
Abstract
Three large-scale networks are considered essential to cognitive flexibility: the ventral and dorsal attention (VANet and DANet) and salience (SNet) networks. The ventrolateral prefrontal cortex (vlPFC) is a known component of the VANet and DANet, but there is a gap in the current knowledge regarding its involvement in the SNet. Herein, we used a translational and multimodal approach to demonstrate the existence of a SNet node within the vlPFC. First, we used tract-tracing methods in non-human primates (NHP) to quantify the anatomical connectivity strength between different vlPFC areas and the frontal and insular cortices. The strongest connections were with the dorsal anterior cingulate cortex (dACC) and anterior insula (AI) - the main cortical SNet nodes. These inputs converged in the caudal area 47/12, an area that has strong projections to subcortical structures associated with the SNet. Second, we used resting-state functional MRI (rsfMRI) in NHP data to validate this SNet node. Third, we used rsfMRI in the human to identify a homologous caudal 47/12 region that also showed strong connections with the SNet cortical nodes. Taken together, these data confirm a SNet node in the vlPFC, demonstrating that the vlPFC contains nodes for all three cognitive networks: VANet, DANet, and SNet. Thus, the vlPFC is in a position to switch between these three networks, pointing to its key role as an attentional hub. Its additional connections to the orbitofrontal, dorsolateral, and premotor cortices, place the vlPFC at the center for switching behaviors based on environmental stimuli, computing value, and cognitive control.
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Affiliation(s)
- Lucas R Trambaiolli
- McLean Hospital, Harvard Medical SchoolBelmontUnited States
- University of Rochester School of Medicine & DentistryRochesterUnited States
| | - Xiaolong Peng
- Massachusetts General Hospital, Harvard Medical SchoolBostonUnited States
- Medical University of South CarolinaCharlestonUnited States
| | - Julia F Lehman
- University of Rochester School of Medicine & DentistryRochesterUnited States
| | - Gary Linn
- Translational Neuropscienc lab Division, Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric ResearchOrangeburgUnited States
| | - Brian E Russ
- Translational Neuropscienc lab Division, Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric ResearchOrangeburgUnited States
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount SinaiNew YorkUnited States
- Department of Psychiatry, New York University at LangoneNew YorkUnited States
| | - Charles E Schroeder
- Translational Neuropscienc lab Division, Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric ResearchOrangeburgUnited States
- Department of Psychiatry, Columbia University Medical CenterNew YorkUnited States
| | - Hesheng Liu
- Massachusetts General Hospital, Harvard Medical SchoolBostonUnited States
- Medical University of South CarolinaCharlestonUnited States
| | - Suzanne N Haber
- McLean Hospital, Harvard Medical SchoolBelmontUnited States
- University of Rochester School of Medicine & DentistryRochesterUnited States
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34
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Faskowitz J, Betzel RF, Sporns O. Edges in brain networks: Contributions to models of structure and function. Netw Neurosci 2022; 6:1-28. [PMID: 35350585 PMCID: PMC8942607 DOI: 10.1162/netn_a_00204] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Accepted: 08/02/2021] [Indexed: 11/16/2022] Open
Abstract
Network models describe the brain as sets of nodes and edges that represent its distributed organization. So far, most discoveries in network neuroscience have prioritized insights that highlight distinct groupings and specialized functional contributions of network nodes. Importantly, these functional contributions are determined and expressed by the web of their interrelationships, formed by network edges. Here, we underscore the important contributions made by brain network edges for understanding distributed brain organization. Different types of edges represent different types of relationships, including connectivity and similarity among nodes. Adopting a specific definition of edges can fundamentally alter how we analyze and interpret a brain network. Furthermore, edges can associate into collectives and higher order arrangements, describe time series, and form edge communities that provide insights into brain network topology complementary to the traditional node-centric perspective. Focusing on the edges, and the higher order or dynamic information they can provide, discloses previously underappreciated aspects of structural and functional network organization.
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Affiliation(s)
- Joshua Faskowitz
- Program in Neuroscience, Indiana University, Bloomington, IN, USA
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Richard F. Betzel
- Program in Neuroscience, Indiana University, Bloomington, IN, USA
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
- Indiana University Network Science Institute, Indiana University, Bloomington, IN, USA
- Cognitive Science Program, Indiana University, Bloomington, IN, USA
| | - Olaf Sporns
- Program in Neuroscience, Indiana University, Bloomington, IN, USA
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
- Indiana University Network Science Institute, Indiana University, Bloomington, IN, USA
- Cognitive Science Program, Indiana University, Bloomington, IN, USA
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35
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Zhao Q, Voon V, Zhang L, Shen C, Zhang J, Feng J. The ABCD Study: Brain Heterogeneity in Intelligence During a Neurodevelopmental Transition Stage. Cereb Cortex 2022; 32:3098-3109. [PMID: 35037940 PMCID: PMC9290553 DOI: 10.1093/cercor/bhab403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 08/31/2021] [Accepted: 09/28/2021] [Indexed: 11/29/2022] Open
Abstract
A complex curvilinear relationship exists between intelligence and age during the neurodevelopment of cortical thickness. To parse out a more fine-grained relationship between intelligence and cortical thickness and surface area, we used a large-scale data set focusing on a critical transition juncture in neurodevelopment in preadolescence. Cortical thickness was derived from T1-weighted structural magnetic resonance images of a large sample of 9- and 11-year-old children from the Adolescent Brain Cognitive Development study. The NIH Toolbox Cognition Battery composite scores, which included fluid, crystallized, and total scores, were used to assess intelligence. Using a double generalized linear model, we assessed the independent association between the mean and dispersion of cortical thickness/surface area and intelligence. Higher intelligence in preadolescents was associated with higher mean cortical thickness in orbitofrontal and primary sensory cortices but with lower thickness in the dorsolateral and medial prefrontal cortex and particularly in the rostral anterior cingulate. The rostral anterior cingulate findings were particularly evident across all subscales of intelligence. Higher intelligence was also associated with greater interindividual similarity in the rostral cingulate. Intelligence during this key transition juncture in preadolescence appears to reflect a dissociation between the cortical development of basic cognitive processes and higher-order executive and motivational processes.
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Affiliation(s)
| | | | - Lingli Zhang
- Developmental and Behavioral Pediatric & Child Primary Care Department, Ministry of Education-Shanghai Key Laboratory of Children’s Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200092, PR China
| | - Chun Shen
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai 200433, PR China
| | - Jie Zhang
- Address correspondence to Professor Jianfeng Feng, Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai 200433, PR China. ; Professor Jie Zhang, Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai 200433, PR China.
| | - Jianfeng Feng
- Address correspondence to Professor Jianfeng Feng, Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai 200433, PR China. ; Professor Jie Zhang, Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai 200433, PR China.
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36
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Foley P, Kong Y, Dirvanskiene R, Valdes-Hernandez M, Bastiani M, Murnane J, Sellar R, Roberts N, Pernet C, Weir C, Bak T, Colvin L, Chandran S, Fallon M, Tracey I. Coupling cognitive and brainstem dysfunction in multiple sclerosis-related chronic neuropathic limb pain. Brain Commun 2022; 4:fcac124. [PMID: 35663383 PMCID: PMC9155950 DOI: 10.1093/braincomms/fcac124] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Revised: 04/01/2022] [Accepted: 05/13/2022] [Indexed: 11/12/2022] Open
Abstract
Chronic pain in multiple sclerosis is common and difficult to treat. Its mechanisms remain incompletely understood. Dysfunction of the descending pain modulatory system is known to contribute to human chronic pain conditions. However, it is not clear how alterations in executive function influence this network, despite healthy volunteer studies linking function of the descending pain modulatory system, to cognition. In adults with multiple sclerosis-associated chronic neuropathic limb pain, compared to those without pain, we hypothesized altered functional connectivity of the descending pain modulatory system, coupled to executive dysfunction. Specifically we hypothesized reduced mental flexibility, because of potential importance in stimulus reappraisal. To investigate these hypotheses, we conducted a case-control cross-sectional study of 47 adults with relapsing remitting multiple sclerosis (31 with chronic neuropathic limb pain, 16 without pain), employing clinical, neuropsychological, structural, and functional MRI measures. We measured brain lesions and atrophy affecting descending pain modulatory system structures. Both cognitive and affective dysfunctions were confirmed in the chronic neuropathic limb pain group, including reduced mental flexibility (Delis Kaplan Executive Function System card sorting tests P < 0.001). Functional connectivity of rostral anterior cingulate and ventrolateral periaqueductal gray, key structures of the descending pain modulatory system, was significantly lower in the group experiencing chronic neuropathic pain. There was no significant between-group difference in whole-brain grey matter or lesion volumes, nor lesion volume affecting white matter tracts between rostral anterior cingulate and periaqueductal gray. Brainstem-specific lesion volume was higher in the chronic neuropathic limb pain group (P = 0.0017). Differential functional connectivity remained after correction for brainstem-specific lesion volume. Gabapentinoid medications were more frequently used in the chronic pain group. We describe executive dysfunction in people with multiple sclerosis affected by chronic neuropathic pain, along with functional and structural MRI evidence compatible with dysfunction of the descending pain modulatory system. These findings extend understanding of close inter-relationships between cognition, function of the descending pain modulatory system, and chronic pain, both in multiple sclerosis and more generally in human chronic pain conditions. These findings could support application of pharmacological and cognitive interventions in chronic neuropathic pain associated with multiple sclerosis.
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Affiliation(s)
- Peter Foley
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, 49 Little France Crescent, Edinburgh EH16 4SB, UK
| | - Yazhuo Kong
- CAS Key Laboratory of Behavioural Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Ramune Dirvanskiene
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, 49 Little France Crescent, Edinburgh EH16 4SB, UK
| | - Maria Valdes-Hernandez
- Dementia Research Institute, University of Edinburgh, Edinburgh, UK.,Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Matteo Bastiani
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK.,NIHR Biomedical Research Centre, University of Nottingham, Nottingham, UK.,Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Jonathan Murnane
- Clinical Research Imaging Centre, Edinburgh University, Edinburgh, UK
| | - Robin Sellar
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Neil Roberts
- Clinical Research Imaging Centre, Edinburgh University, Edinburgh, UK
| | - Cyril Pernet
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Christopher Weir
- Edinburgh Clinical Trials Unit, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Thomas Bak
- School of Philosophy, Psychology and Language Sciences, University of Edinburgh, Edinburgh, UK
| | - Lesley Colvin
- Division of Population Health and Genomics, University of Dundee, Dundee, UK
| | - Siddharthan Chandran
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, 49 Little France Crescent, Edinburgh EH16 4SB, UK.,Dementia Research Institute, University of Edinburgh, Edinburgh, UK.,Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Marie Fallon
- Department of Palliative Medicine, University of Edinburgh, Edinburgh, UK
| | - Irene Tracey
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.,Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
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37
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Haber SN, Liu H, Seidlitz J, Bullmore E. Prefrontal connectomics: from anatomy to human imaging. Neuropsychopharmacology 2022; 47:20-40. [PMID: 34584210 PMCID: PMC8617085 DOI: 10.1038/s41386-021-01156-6] [Citation(s) in RCA: 38] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Revised: 07/23/2021] [Accepted: 08/02/2021] [Indexed: 12/22/2022]
Abstract
The fundamental importance of prefrontal cortical connectivity to information processing and, therefore, disorders of cognition, emotion, and behavior has been recognized for decades. Anatomic tracing studies in animals have formed the basis for delineating the direct monosynaptic connectivity, from cells of origin, through axon trajectories, to synaptic terminals. Advances in neuroimaging combined with network science have taken the lead in developing complex wiring diagrams or connectomes of the human brain. A key question is how well these magnetic resonance imaging (MRI)-derived networks and hubs reflect the anatomic "hard wiring" first proposed to underlie the distribution of information for large-scale network interactions. In this review, we address this challenge by focusing on what is known about monosynaptic prefrontal cortical connections in non-human primates and how this compares to MRI-derived measurements of network organization in humans. First, we outline the anatomic cortical connections and pathways for each prefrontal cortex (PFC) region. We then review the available MRI-based techniques for indirectly measuring structural and functional connectivity, and introduce graph theoretical methods for analysis of hubs, modules, and topologically integrative features of the connectome. Finally, we bring these two approaches together, using specific examples, to demonstrate how monosynaptic connections, demonstrated by tract-tracing studies, can directly inform understanding of the composition of PFC nodes and hubs, and the edges or pathways that connect PFC to cortical and subcortical areas.
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Affiliation(s)
- Suzanne N. Haber
- grid.412750.50000 0004 1936 9166Department of Pharmacology and Physiology, University of Rochester School of Medicine & Dentistry, Rochester, NY 14642 USA ,grid.38142.3c000000041936754XDepartment of Psychiatry, McLean Hospital, Harvard Medical School, Belmont, MA 02478 USA
| | - Hesheng Liu
- grid.259828.c0000 0001 2189 3475Department of Neuroscience, Medical University of South Carolina, Charleston, SC USA ,grid.38142.3c000000041936754XDepartment of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA USA
| | - Jakob Seidlitz
- grid.25879.310000 0004 1936 8972Department of Psychiatry, University of Pennsylvania, Philadelphia, USA
| | - Ed Bullmore
- grid.5335.00000000121885934Department of Psychiatry, University of Cambridge, Herchel Smith Building for Brain and Mind Sciences, Cambridge Biomedical Campus, Cambridge, CB2 0SZ UK
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38
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Maffei C, Lee C, Planich M, Ramprasad M, Ravi N, Trainor D, Urban Z, Kim M, Jones RJ, Henin A, Hofmann SG, Pizzagalli DA, Auerbach RP, Gabrieli JDE, Whitfield-Gabrieli S, Greve DN, Haber SN, Yendiki A. Using diffusion MRI data acquired with ultra-high gradient strength to improve tractography in routine-quality data. Neuroimage 2021; 245:118706. [PMID: 34780916 PMCID: PMC8835483 DOI: 10.1016/j.neuroimage.2021.118706] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Revised: 10/11/2021] [Accepted: 11/01/2021] [Indexed: 11/27/2022] Open
Abstract
The development of scanners with ultra-high gradient strength, spearheaded by the Human Connectome Project, has led to dramatic improvements in the spatial, angular, and diffusion resolution that is feasible for in vivo diffusion MRI acquisitions. The improved quality of the data can be exploited to achieve higher accuracy in the inference of both microstructural and macrostructural anatomy. However, such high-quality data can only be acquired on a handful of Connectom MRI scanners worldwide, while remaining prohibitive in clinical settings because of the constraints imposed by hardware and scanning time. In this study, we first update the classical protocols for tractography-based, manual annotation of major white-matter pathways, to adapt them to the much greater volume and variability of the streamlines that can be produced from today’s state-of-the-art diffusion MRI data. We then use these protocols to annotate 42 major pathways manually in data from a Connectom scanner. Finally, we show that, when we use these manually annotated pathways as training data for global probabilistic tractography with anatomical neighborhood priors, we can perform highly accurate, automated reconstruction of the same pathways in much lower-quality, more widely available diffusion MRI data. The outcomes of this work include both a new, comprehensive atlas of WM pathways from Connectom data, and an updated version of our tractography toolbox, TRActs Constrained by UnderLying Anatomy (TRACULA), which is trained on data from this atlas. Both the atlas and TRACULA are distributed publicly as part of FreeSurfer. We present the first comprehensive comparison of TRACULA to the more conventional, multi-region-of-interest approach to automated tractography, and the first demonstration of training TRACULA on high-quality, Connectom data to benefit studies that use more modest acquisition protocols.
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Affiliation(s)
- C Maffei
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA.
| | - C Lee
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - M Planich
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - M Ramprasad
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - N Ravi
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - D Trainor
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Z Urban
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - M Kim
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - R J Jones
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - A Henin
- Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - S G Hofmann
- Department of Clinical Psychology, Philipps University Marburg, Germany; Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - D A Pizzagalli
- McLean Hospital and Harvard Medical School, Belmont, MA, USA
| | | | - J D E Gabrieli
- Massachusetts Institute of Technology, Cambridge, MA, USA
| | | | - D N Greve
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - S N Haber
- McLean Hospital and Harvard Medical School, Belmont, MA, USA; Department of Pharmacology and Physiology, University of Rochester School of Medicine, Rochester, NY, USA
| | - A Yendiki
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
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39
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Alderson Myers AB, Arienzo D, Molnar SM, Marinkovic K. Local and network-level dysregulation of error processing is associated with binge drinking. NEUROIMAGE-CLINICAL 2021; 32:102879. [PMID: 34768146 PMCID: PMC8591397 DOI: 10.1016/j.nicl.2021.102879] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 11/04/2021] [Accepted: 11/05/2021] [Indexed: 01/22/2023]
Abstract
Go/NoGo performance does not differ between binge (BDs) and light drinkers. BDs show greater BOLD activity to inhibition errors primarily in prefrontal areas. Greater functional connectivity in the frontal cortex correlates with drinking. Observed increase in error-related activity may serve a compensatory role. This is consistent with allostatic hyperexcitability reflecting neuroadaptation.
Binge drinking refers to the pattern of alcohol consumption that brings blood alcohol levels to or above legal intoxication levels. Commonly practiced by young adults, it is associated with neurofunctional alterations, raising health-related concerns. Executive deficits may contribute to the inability to refrain from excessive alcohol intake. As a facet of cognitive control, error processing allows for flexible modification of behavior to optimize future outcomes. It is highly relevant to addiction research, as a failure to inhibit excessive drinking results in relapses, which is a hallmark of alcohol use disorder. However, research on local and system-level neural underpinnings of inhibition failures as a function of binge drinking is limited. To address these gaps, functional magnetic resonance imaging (fMRI) was used to examine local changes and interregional functional connectivity during response inhibition errors on a Go/NoGo task. Young adult binge drinkers (BDs) performed equally well as light drinkers (LDs), a group of demographically matched individuals who drink regularly but in low-risk patterns. In contrast, BDs exhibited greater fMRI activity to inhibition errors contrasted with correct NoGo trials in the rostral anterior (rACC) and posterior cingulate cortices (PCC), as well as right middle frontal gyrus (R-MFG). Furthermore, BDs showed increased connectivity between the rACC and right lateral prefrontal cortex, in addition to greater connectivity between the R-MFG and the left ventrolateral and superior frontal cortices. Imaging indices were positively correlated only with alcohol-related measures, but not with those related to moods, disposition, or cognitive capacity. Taken together, greater error-related activity and expanded functional connectivity among prefrontal regions may serve a compensatory role to maintain efficiency of inhibitory control. Aligned with prominent models of addiction, these findings accentuate the importance of top-down control in maintaining low-risk drinking levels. They provide insight into potentially early signs of deteriorating cognitive control functions in BDs and may help guide intervention strategies aimed at preventing excessive drinking habits.
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Affiliation(s)
- Austin B Alderson Myers
- Department of Psychology, San Diego State University, 5500 Campanile Dr., San Diego, CA 92182, USA.
| | - Donatello Arienzo
- Department of Psychology, San Diego State University, 5500 Campanile Dr., San Diego, CA 92182, USA.
| | - Sean M Molnar
- Department of Psychology, San Diego State University, 5500 Campanile Dr., San Diego, CA 92182, USA.
| | - Ksenija Marinkovic
- Department of Psychology, San Diego State University, 5500 Campanile Dr., San Diego, CA 92182, USA; Department of Radiology, University of California, San Diego, 9500 Gilman Dr., La Jolla, CA 92093, USA.
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40
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Lopez-Vilaret KM, Cantero JL, Fernandez-Alvarez M, Calero M, Calero O, Lindín M, Zurrón M, Díaz F, Atienza M. Impaired glucose metabolism reduces the neuroprotective action of adipocytokines in cognitively normal older adults with insulin resistance. Aging (Albany NY) 2021; 13:23936-23952. [PMID: 34731089 PMCID: PMC8610113 DOI: 10.18632/aging.203668] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 10/26/2021] [Indexed: 12/26/2022]
Abstract
Evidence suggests that aging-related dysfunctions of adipose tissue and metabolic disturbances increase the risk of diabetes and metabolic syndrome (MtbS), eventually leading to cognitive impairment and dementia. However, the neuroprotective role of adipocytokines in this process has not been specifically investigated. The present study aims to identify metabolic alterations that may prevent adipocytokines from exerting their neuroprotective action in normal ageing. We hypothesize that neuroprotection may occur under insulin resistance (IR) conditions as long as there are no other metabolic alterations that indirectly impair the action of adipocytokines, such as hyperglycemia. This hypothesis was tested in 239 cognitively normal older adults (149 females) aged 52 to 87 years (67.4 ± 5.9 yr). We assessed whether the homeostasis model assessment-estimated insulin resistance (HOMA-IR) and the presence of different components of MtbS moderated the association of plasma adipocytokines (i.e., adiponectin, leptin and the adiponectin to leptin [Ad/L] ratio) with cognitive functioning and cortical thickness. The results showed that HOMA-IR, circulating triglyceride and glucose levels moderated the neuroprotective effect of adipocytokines. In particular, elevated triglyceride levels reduced the beneficial effect of Ad/L ratio on cognitive functioning in insulin-sensitive individuals; whereas under high IR conditions, it was elevated glucose levels that weakened the association of the Ad/L ratio with cognitive functioning and with cortical thickness of prefrontal regions. Taken together, these findings suggest that the neuroprotective action of adipocytokines is conditioned not only by whether cognitively normal older adults are insulin-sensitive or not, but also by the circulating levels of triglycerides and glucose, respectively.
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Affiliation(s)
| | - Jose L Cantero
- Laboratory of Functional Neuroscience, Universidad Pablo de Olavide, Seville, Spain.,CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, Madrid, Spain
| | - Marina Fernandez-Alvarez
- Laboratory of Functional Neuroscience, Universidad Pablo de Olavide, Seville, Spain.,CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, Madrid, Spain
| | - Miguel Calero
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, Madrid, Spain.,Chronic Disease Programme, Instituto de Salud Carlos III, Madrid, Spain
| | - Olga Calero
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, Madrid, Spain.,Chronic Disease Programme, Instituto de Salud Carlos III, Madrid, Spain
| | - Mónica Lindín
- Cognitive Neuroscience Laboratory, Universidade de Santiago de Compostela, Santiago de Compostela, Spain
| | - Montserrat Zurrón
- Cognitive Neuroscience Laboratory, Universidade de Santiago de Compostela, Santiago de Compostela, Spain
| | - Fernando Díaz
- Cognitive Neuroscience Laboratory, Universidade de Santiago de Compostela, Santiago de Compostela, Spain
| | - Mercedes Atienza
- Laboratory of Functional Neuroscience, Universidad Pablo de Olavide, Seville, Spain.,CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, Madrid, Spain
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41
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Bellato A, Norman L, Idrees I, Ogawa CY, Waitt A, Zuccolo PF, Tye C, Radua J, Groom MJ, Shephard E. A systematic review and meta-analysis of altered electrophysiological markers of performance monitoring in Obsessive-Compulsive Disorder (OCD), Gilles de la Tourette Syndrome (GTS), Attention-Deficit/Hyperactivity disorder (ADHD) and Autism. Neurosci Biobehav Rev 2021; 131:964-987. [PMID: 34687698 DOI: 10.1016/j.neubiorev.2021.10.018] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 10/14/2021] [Accepted: 10/15/2021] [Indexed: 12/15/2022]
Abstract
Altered performance monitoring is implicated in obsessive-compulsive disorder (OCD), Gilles de la Tourette syndrome (GTS), attention-deficit/hyperactivity disorder (ADHD) and autism. We conducted a systematic review and meta-analysis of electrophysiological correlates of performance monitoring (error-related negativity, ERN; error positivity, Pe; feedback-related negativity, FRN; feedback-P3) in individuals with OCD, GTS, ADHD or autism compared to control participants, or associations between correlates and symptoms/traits of these conditions. Meta-analyses on 97 studies (5890 participants) showed increased ERN in OCD (Hedge's g = 0.54[CIs:0.44,0.65]) and GTS (g = 0.99[CIs:0.05,1.93]). OCD also showed increased Pe (g = 0.51[CIs:0.21,0.81]) and FRN (g = 0.50[CIs:0.26,0.73]). ADHD and autism showed reduced ERN (ADHD: g=-0.47[CIs:-0.67,-0.26]; autism: g=-0.61[CIs:-1.10,-0.13]). ADHD also showed reduced Pe (g=-0.50[CIs:-0.69,-0.32]). These findings suggest overlap in electrophysiological markers of performance monitoring alterations in four common neurodevelopmental conditions, with increased amplitudes of the markers in OCD and GTS and decreased amplitudes in ADHD and autism. Implications of these findings in terms of shared and distinct performance monitoring alterations across these neurodevelopmental conditions are discussed. PROSPERO pre-registration code: CRD42019134612.
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Affiliation(s)
- Alessio Bellato
- Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, London, UK; Academic Unit of Mental Health & Clinical Neurosciences, School of Medicine, Institute of Mental Health, University of Nottingham, Nottingham, UK
| | - Luke Norman
- Section on Neurobehavioral and Clinical Research, Social and Behavioral Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Iman Idrees
- Academic Unit of Mental Health & Clinical Neurosciences, School of Medicine, Institute of Mental Health, University of Nottingham, Nottingham, UK
| | - Carolina Y Ogawa
- Department of Psychiatry, Faculdade de Medicina FMUSP, Universidade de São Paulo, São Paulo, Brazil
| | - Alice Waitt
- Academic Unit of Mental Health & Clinical Neurosciences, School of Medicine, Institute of Mental Health, University of Nottingham, Nottingham, UK
| | - Pedro F Zuccolo
- Department of Psychiatry, Faculdade de Medicina FMUSP, Universidade de São Paulo, São Paulo, Brazil
| | - Charlotte Tye
- Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, London, UK
| | - Joaquim Radua
- Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, London, UK; Imaging of Mood- and Anxiety-Related Disorders (IMARD) Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), CIBERSAM, Barcelona, Spain; Department of Clinical Neuroscience, Centre for Psychiatric Research and Education, Karolinska Institutet, Stockholm, Sweden
| | - Madeleine J Groom
- Academic Unit of Mental Health & Clinical Neurosciences, School of Medicine, Institute of Mental Health, University of Nottingham, Nottingham, UK
| | - Elizabeth Shephard
- Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, London, UK; Department of Psychiatry, Faculdade de Medicina FMUSP, Universidade de São Paulo, São Paulo, Brazil.
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42
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Grisot G, Haber SN, Yendiki A. Diffusion MRI and anatomic tracing in the same brain reveal common failure modes of tractography. Neuroimage 2021; 239:118300. [PMID: 34171498 PMCID: PMC8475636 DOI: 10.1016/j.neuroimage.2021.118300] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 04/29/2021] [Accepted: 06/21/2021] [Indexed: 12/15/2022] Open
Abstract
Anatomic tracing is recognized as a critical source of knowledge on brain circuitry that can be used to assess the accuracy of diffusion MRI (dMRI) tractography. However, most prior studies that have performed such assessments have used dMRI and tracer data from different brains and/or have been limited in the scope of dMRI analysis methods allowed by the data. In this work, we perform a quantitative, voxel-wise comparison of dMRI tractography and anatomic tracing data in the same macaque brain. An ex vivo dMRI acquisition with high angular resolution and high maximum b-value allows us to compare a range of q-space sampling, orientation reconstruction, and tractography strategies. The availability of tracing in the same brain allows us to localize the sources of tractography errors and to identify axonal configurations that lead to such errors consistently, across dMRI acquisition and analysis strategies. We find that these common failure modes involve geometries such as branching or turning, which cannot be modeled well by crossing fibers. We also find that the default thresholds that are commonly used in tractography correspond to rather conservative, low-sensitivity operating points. While deterministic tractography tends to have higher sensitivity than probabilistic tractography in that very conservative threshold regime, the latter outperforms the former as the threshold is relaxed to avoid missing true anatomical connections. On the other hand, the q-space sampling scheme and maximum b-value have less of an impact on accuracy. Finally, using scans from a set of additional macaque brains, we show that there is enough inter-individual variability to warrant caution when dMRI and tracer data come from different animals, as is often the case in the tractography validation literature. Taken together, our results provide insights on the limitations of current tractography methods and on the critical role that anatomic tracing can play in identifying potential avenues for improvement.
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Affiliation(s)
| | - Suzanne N Haber
- Department of Pharmacology and Physiology, University of Rochester, Rochester, NY, United States; McLean Hospital, Belmont, MA, United States
| | - Anastasia Yendiki
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States.
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43
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Shephard E, Stern ER, van den Heuvel OA, Costa DL, Batistuzzo MC, Godoy PB, Lopes AC, Brunoni AR, Hoexter MQ, Shavitt RG, Reddy JY, Lochner C, Stein DJ, Simpson HB, Miguel EC. Toward a neurocircuit-based taxonomy to guide treatment of obsessive-compulsive disorder. Mol Psychiatry 2021; 26:4583-4604. [PMID: 33414496 PMCID: PMC8260628 DOI: 10.1038/s41380-020-01007-8] [Citation(s) in RCA: 85] [Impact Index Per Article: 28.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Revised: 12/15/2020] [Accepted: 12/16/2020] [Indexed: 12/11/2022]
Abstract
An important challenge in mental health research is to translate findings from cognitive neuroscience and neuroimaging research into effective treatments that target the neurobiological alterations involved in psychiatric symptoms. To address this challenge, in this review we propose a heuristic neurocircuit-based taxonomy to guide the treatment of obsessive-compulsive disorder (OCD). We do this by integrating information from several sources. First, we provide case vignettes in which patients with OCD describe their symptoms and discuss different clinical profiles in the phenotypic expression of the condition. Second, we link variations in these clinical profiles to underlying neurocircuit dysfunctions, drawing on findings from neuropsychological and neuroimaging studies in OCD. Third, we consider behavioral, pharmacological, and neuromodulatory treatments that could target those specific neurocircuit dysfunctions. Finally, we suggest methods of testing this neurocircuit-based taxonomy as well as important limitations to this approach that should be considered in future research.
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Affiliation(s)
- Elizabeth Shephard
- Department of Psychiatry, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil. .,Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London, UK.
| | - Emily R. Stern
- Department of Psychiatry, The New York University School of Medicine, New York, USA.,Nathan Kline Institute for Psychiatric Research, Orangeburg, New York, USA
| | - Odile A. van den Heuvel
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Psychiatry, Department of Anatomy & Neurosciences, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Daniel L.C. Costa
- Department of Psychiatry, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | - Marcelo C. Batistuzzo
- Department of Psychiatry, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | - Priscilla B.G. Godoy
- Department of Psychiatry, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | - Antonio C. Lopes
- Department of Psychiatry, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | - Andre R. Brunoni
- Department of Psychiatry, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | - Marcelo Q. Hoexter
- Department of Psychiatry, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | - Roseli G. Shavitt
- Department of Psychiatry, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | - Janardhan Y.C Reddy
- Department of Psychiatry OCD Clinic, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, India
| | - Christine Lochner
- SA MRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry, Stellenbosch University, Cape Town, South Africa
| | - Dan J. Stein
- SA MRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - H. Blair Simpson
- Center for OCD and Related Disorders, New York State Psychiatric Institute and the Department of Psychiatry, Columbia University Irving Medical Center, New York New York
| | - Euripedes C. Miguel
- Department of Psychiatry, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
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44
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Bennett MS. Five Breakthroughs: A First Approximation of Brain Evolution From Early Bilaterians to Humans. Front Neuroanat 2021; 15:693346. [PMID: 34489649 PMCID: PMC8418099 DOI: 10.3389/fnana.2021.693346] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2021] [Accepted: 07/13/2021] [Indexed: 11/13/2022] Open
Abstract
Retracing the evolutionary steps by which human brains evolved can offer insights into the underlying mechanisms of human brain function as well as the phylogenetic origin of various features of human behavior. To this end, this article presents a model for interpreting the physical and behavioral modifications throughout major milestones in human brain evolution. This model introduces the concept of a "breakthrough" as a useful tool for interpreting suites of brain modifications and the various adaptive behaviors these modifications enabled. This offers a unique view into the ordered steps by which human brains evolved and suggests several unique hypotheses on the mechanisms of human brain function.
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45
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Duan LY, Horst NK, Cranmore SAW, Horiguchi N, Cardinal RN, Roberts AC, Robbins TW. Controlling one's world: Identification of sub-regions of primate PFC underlying goal-directed behavior. Neuron 2021; 109:2485-2498.e5. [PMID: 34171290 PMCID: PMC8346232 DOI: 10.1016/j.neuron.2021.06.003] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2020] [Revised: 04/13/2021] [Accepted: 06/02/2021] [Indexed: 12/30/2022]
Abstract
Impaired detection of causal relationships between actions and their outcomes can lead to maladaptive behavior. However, causal roles of specific prefrontal cortex (PFC) sub-regions and the caudate nucleus in mediating such relationships in primates are unclear. We inactivated and overactivated five PFC sub-regions, reversibly and pharmacologically: areas 24 (perigenual anterior cingulate cortex), 32 (medial PFC), 11 (anterior orbitofrontal cortex, OFC), 14 (rostral ventromedial PFC/medial OFC), and 14-25 (caudal ventromedial PFC) and the anteromedial caudate to examine their role in expressing learned action-outcome contingencies using a contingency degradation paradigm in marmoset monkeys. Area 24 or caudate inactivation impaired the response to contingency change, while area 11 inactivation enhanced it, and inactivation of areas 14, 32, or 14-25 had no effect. Overactivation of areas 11 and 24 impaired this response. These findings demonstrate the distinct roles of PFC sub-regions in goal-directed behavior and illuminate the candidate neurobehavioral substrates of psychiatric disorders, including obsessive-compulsive disorder. Monkey pgACC-24 is necessary for detecting causal control of actions over outcomes Its projection target in the caudate nucleus is also implicated Three other subregions of the ventromedial prefrontal cortex are not necessary Anterior OFC-11 may mediate Pavlovian influences on goal-directed behavior
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Affiliation(s)
- Lisa Y Duan
- Department of Psychology, University of Cambridge, Downing Street, Cambridge CB2 3EB, UK; Behavioural and Clinical Neuroscience Institute, Downing Street, University of Cambridge, Cambridge CB2 3EB, UK.
| | - Nicole K Horst
- Department of Psychology, University of Cambridge, Downing Street, Cambridge CB2 3EB, UK; Behavioural and Clinical Neuroscience Institute, Downing Street, University of Cambridge, Cambridge CB2 3EB, UK
| | - Stacey A W Cranmore
- Department of Psychology, University of Cambridge, Downing Street, Cambridge CB2 3EB, UK; Behavioural and Clinical Neuroscience Institute, Downing Street, University of Cambridge, Cambridge CB2 3EB, UK
| | - Naotaka Horiguchi
- Department of Psychology, University of Cambridge, Downing Street, Cambridge CB2 3EB, UK; Behavioural and Clinical Neuroscience Institute, Downing Street, University of Cambridge, Cambridge CB2 3EB, UK
| | - Rudolf N Cardinal
- Department of Psychiatry, University of Cambridge, Herchel Smith Building for Brain & Mind Sciences, Forvie Site, Robinson Way, Cambridge CB2 0SZ, UK; Behavioural and Clinical Neuroscience Institute, Downing Street, University of Cambridge, Cambridge CB2 3EB, UK; Cambridgeshire and Peterborough NHS Foundation Trust, Liaison Psychiatry Service, Box 190, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
| | - Angela C Roberts
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, UK; Behavioural and Clinical Neuroscience Institute, Downing Street, University of Cambridge, Cambridge CB2 3EB, UK
| | - Trevor W Robbins
- Department of Psychology, University of Cambridge, Downing Street, Cambridge CB2 3EB, UK; Behavioural and Clinical Neuroscience Institute, Downing Street, University of Cambridge, Cambridge CB2 3EB, UK
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46
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Shephard E, Batistuzzo MC, Hoexter MQ, Stern ER, Zuccolo PF, Ogawa CY, Silva RM, Brunoni AR, Costa DL, Doretto V, Saraiva L, Cappi C, Shavitt RG, Simpson HB, van den Heuvel OA, Miguel EC. Neurocircuit models of obsessive-compulsive disorder: limitations and future directions for research. REVISTA BRASILEIRA DE PSIQUIATRIA 2021; 44:187-200. [PMID: 35617698 PMCID: PMC9041967 DOI: 10.1590/1516-4446-2020-1709] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Accepted: 03/05/2021] [Indexed: 11/22/2022]
Affiliation(s)
- Elizabeth Shephard
- Universidade de São Paulo (USP), Brazil; Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King’s College London, UK
| | - Marcelo C. Batistuzzo
- Universidade de São Paulo (USP), Brazil; Pontifícia Universidade Católica de São Paulo, Brazil
| | | | - Emily R. Stern
- The New York University School of Medicine, USA; Orangeburg, USA
| | | | | | | | | | | | | | | | - Carolina Cappi
- Universidade de São Paulo (USP), Brazil; Icahn School of Medicine at Mount Sinai, USA
| | | | - H. Blair Simpson
- New York State Psychiatric Institute, Columbia University Irving Medical Center (CUIMC), USA; CUIMC, USA
| | - Odile A. van den Heuvel
- Vrije Universiteit Amsterdam, The Netherlands; Vrije Universiteit Amsterdam, The Netherlands
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47
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Kurtz M, Mohring P, Förster K, Bauer M, Kanske P. Deficits in explicit emotion regulation in bipolar disorder: a systematic review. Int J Bipolar Disord 2021; 9:15. [PMID: 33937951 PMCID: PMC8089068 DOI: 10.1186/s40345-021-00221-9] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Accepted: 02/11/2021] [Indexed: 12/20/2022] Open
Abstract
Background This study aimed to compile and synthesize studies investigating explicit emotion regulation in patients with bipolar disorder and individuals at risk of developing bipolar disorder. The importance of explicit emotion regulation arises from its potential role as a marker for bipolar disorders in individuals at risk and its potent role in therapy for bipolar disorder patients. Methods To obtain an exhaustive compilation of studies dealing specifically with explicit emotion regulation in bipolar disorder, we conducted a systematic literature search in four databases. In the 15 studies we included in our review, the emotion-regulation strategies maintenance, distraction, and reappraisal (self-focused and situation-focused) were investigated partly on a purely behavioral level and partly in conjunction with neural measures. The samples used in the identified studies included individuals at increased risk of bipolar disorder, patients with current affective episodes, and patients with euthymic mood state. Results In summary, the reviewed studies' results indicate impairments in explicit emotion regulation in individuals at risk for bipolar disorder, patients with manic and depressive episodes, and euthymic patients. These deficits manifest in subjective behavioral measures as well as in neural aberrations. Further, our review reveals a discrepancy between behavioral and neural findings regarding explicit emotion regulation in individuals at risk for bipolar disorders and euthymic patients. While these groups often do not differ significantly in behavioral measures from healthy and low-risk individuals, neural differences are mainly found in frontostriatal networks. Conclusion We conclude that these neural aberrations are a potentially sensitive measure of the probability of occurrence and recurrence of symptoms of bipolar disorders and that strengthening this frontostriatal route is a potentially protective measure for individuals at risk and patients who have bipolar disorders.
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Affiliation(s)
- Marcel Kurtz
- Clinical Psychology and Behavioral Neuroscience, Faculty of Psychology, Technische Universität Dresden, Chemnitzer Str. 46, 01187, Dresden, Germany.
| | - Pia Mohring
- Clinical Psychology and Behavioral Neuroscience, Faculty of Psychology, Technische Universität Dresden, Chemnitzer Str. 46, 01187, Dresden, Germany
| | - Katharina Förster
- Clinical Psychology and Behavioral Neuroscience, Faculty of Psychology, Technische Universität Dresden, Chemnitzer Str. 46, 01187, Dresden, Germany
| | - Michael Bauer
- Department of Psychiatry and Psychotherapy, Medical Faculty, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Philipp Kanske
- Clinical Psychology and Behavioral Neuroscience, Faculty of Psychology, Technische Universität Dresden, Chemnitzer Str. 46, 01187, Dresden, Germany.,Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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48
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Hartling C, Metz S, Pehrs C, Scheidegger M, Gruzman R, Keicher C, Wunder A, Weigand A, Grimm S. Comparison of Four fMRI Paradigms Probing Emotion Processing. Brain Sci 2021; 11:525. [PMID: 33919024 PMCID: PMC8142995 DOI: 10.3390/brainsci11050525] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 04/17/2021] [Accepted: 04/17/2021] [Indexed: 11/27/2022] Open
Abstract
Previous fMRI research has applied a variety of tasks to examine brain activity underlying emotion processing. While task characteristics are known to have a substantial influence on the elicited activations, direct comparisons of tasks that could guide study planning are scarce. We aimed to provide a comparison of four common emotion processing tasks based on the same analysis pipeline to suggest tasks best suited for the study of certain target brain regions. We studied an n-back task using emotional words (EMOBACK) as well as passive viewing tasks of emotional faces (FACES) and emotional scenes (OASIS and IAPS). We compared the activation patterns elicited by these tasks in four regions of interest (the amygdala, anterior insula, dorsolateral prefrontal cortex (dlPFC) and pregenual anterior cingulate cortex (pgACC)) in three samples of healthy adults (N = 45). The EMOBACK task elicited activation in the right dlPFC and bilateral anterior insula and deactivation in the pgACC while the FACES task recruited the bilateral amygdala. The IAPS and OASIS tasks showed similar activation patterns recruiting the bilateral amygdala and anterior insula. We conclude that these tasks can be used to study different regions involved in emotion processing and that the information provided is valuable for future research and the development of fMRI biomarkers.
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Affiliation(s)
- Corinna Hartling
- Department of Psychiatry and Psychotherapy, CBF, Charité Universitätsmedizin Berlin, 12203 Berlin, Germany; (S.M.); (R.G.); (S.G.)
| | - Sophie Metz
- Department of Psychiatry and Psychotherapy, CBF, Charité Universitätsmedizin Berlin, 12203 Berlin, Germany; (S.M.); (R.G.); (S.G.)
| | - Corinna Pehrs
- Bernstein Center for Computational Neuroscience, Humboldt-University Berlin, 10115 Berlin, Germany;
| | - Milan Scheidegger
- Department of Psychiatry, Psychotherapy and Psychosomatics, University of Zurich, 8032 Zurich, Switzerland;
| | - Rebecca Gruzman
- Department of Psychiatry and Psychotherapy, CBF, Charité Universitätsmedizin Berlin, 12203 Berlin, Germany; (S.M.); (R.G.); (S.G.)
| | | | - Andreas Wunder
- Translational Medicine and Clinical Pharmacology, Boehringer Ingelheim Pharma GmbH and Co. KG, 52216 Ingelheim am Rhein, Germany;
| | - Anne Weigand
- Department of Psychology, Medical School Berlin, 14197 Berlin, Germany;
| | - Simone Grimm
- Department of Psychiatry and Psychotherapy, CBF, Charité Universitätsmedizin Berlin, 12203 Berlin, Germany; (S.M.); (R.G.); (S.G.)
- Department of Psychology, Medical School Berlin, 14197 Berlin, Germany;
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49
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Ewers M, Luan Y, Frontzkowski L, Neitzel J, Rubinski A, Dichgans M, Hassenstab J, Gordon BA, Chhatwal JP, Levin J, Schofield P, Benzinger TLS, Morris JC, Goate A, Karch CM, Fagan AM, McDade E, Allegri R, Berman S, Chui H, Cruchaga C, Farlow M, Graff-Radford N, Jucker M, Lee JH, Martins RN, Mori H, Perrin R, Xiong C, Rossor M, Fox NC, O'Connor A, Salloway S, Danek A, Buerger K, Bateman RJ, Habeck C, Stern Y, Franzmeier N. Segregation of functional networks is associated with cognitive resilience in Alzheimer's disease. Brain 2021; 144:2176-2185. [PMID: 33725114 DOI: 10.1093/brain/awab112] [Citation(s) in RCA: 62] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Revised: 11/26/2020] [Accepted: 12/29/2020] [Indexed: 11/14/2022] Open
Abstract
Cognitive resilience is an important modulating factor of cognitive decline in Alzheimer's disease, but the functional brain mechanisms that support cognitive resilience remain elusive. Given previous findings in normal ageing, we tested the hypothesis that higher segregation of the brain's connectome into distinct functional networks represents a functional mechanism underlying cognitive resilience in Alzheimer's disease. Using resting-state functional MRI, we assessed both resting-state functional MRI global system segregation, i.e. the balance of between-network to within-network connectivity, and the alternate index of modularity Q as predictors of cognitive resilience. We performed all analyses in two independent samples for validation: (i) 108 individuals with autosomal dominantly inherited Alzheimer's disease and 71 non-carrier controls; and (ii) 156 amyloid-PET-positive subjects across the spectrum of sporadic Alzheimer's disease and 184 amyloid-negative controls. In the autosomal dominant Alzheimer's disease sample, disease severity was assessed by estimated years from symptom onset. In the sporadic Alzheimer's sample, disease stage was assessed by temporal lobe tau-PET (i.e. composite across Braak stage I and III regions). In both samples, we tested whether the effect of disease severity on cognition was attenuated at higher levels of functional network segregation. For autosomal dominant Alzheimer's disease, we found higher functional MRI-assessed system segregation to be associated with an attenuated effect of estimated years from symptom onset on global cognition (P = 0.007). Similarly, for patients with sporadic Alzheimer's disease, higher functional MRI-assessed system segregation was associated with less decrement in global cognition (P = 0.001) and episodic memory (P = 0.004) per unit increase of temporal lobe tau-PET. Confirmatory analyses using the alternate index of modularity Q revealed consistent results. In conclusion, higher segregation of functional connections into distinct large-scale networks supports cognitive resilience in Alzheimer's disease.
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Affiliation(s)
- Michael Ewers
- Institute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilian-University LMU, Munich, Germany.,German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Ying Luan
- Institute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilian-University LMU, Munich, Germany
| | - Lukas Frontzkowski
- Institute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilian-University LMU, Munich, Germany
| | - Julia Neitzel
- Institute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilian-University LMU, Munich, Germany
| | - Anna Rubinski
- Institute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilian-University LMU, Munich, Germany
| | - Martin Dichgans
- Institute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilian-University LMU, Munich, Germany.,German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.,Munich Cluster for Systems Neurology, SyNergy, Ludwig-Maximilian-University LMU, Munich, Germany
| | - Jason Hassenstab
- Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA.,Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA.,Department of Psychological and Brain Sciences, Washington University, St. Louis, MO, USA
| | - Brian A Gordon
- Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA.,Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA.,Department of Psychological and Brain Sciences, Washington University, St. Louis, MO, USA
| | - Jasmeer P Chhatwal
- Massachusetts General Hospital, Department of Neurology, Harvard Medical School, MA, USA
| | - Johannes Levin
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.,Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Peter Schofield
- Neuroscience Research Australia, Sydney, NSW, Australia.,School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia
| | - Tammie L S Benzinger
- Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA.,Department of Radiology, Washington University in St Louis, St Louis, MO, USA
| | - John C Morris
- Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA.,Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA.,Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
| | - Alison Goate
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Ronald M. Loeb Center for Alzheimer's Disease, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Celeste M Karch
- Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA.,Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA.,Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO, USA
| | - Anne M Fagan
- Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA.,Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA.,Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO, USA
| | - Eric McDade
- Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA.,Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Ricardo Allegri
- Department of Neurology, FLENI Fondation, Buenos Aires, Argentina
| | - Sarah Berman
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Helena Chui
- Alzheimer's Disease Research Center, Keck School of Medicine at the University of Southern California, Los Angeles, CA, USA.,Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Carlos Cruchaga
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA.,Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA.,Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO, USA.,NeuroGenomics and Informatics, Washington University School of Medicine, St. Louis, MO, USA
| | - Marty Farlow
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | | | - Mathias Jucker
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany.,Department of Cellular Neurology, Hertie Institute for Clinical Brain Research, Tübingen, Germany.,Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Jae-Hong Lee
- Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Ralph N Martins
- Centre of Excellence for Alzheimer's Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia.,Australian Alzheimer's Research Foundation, Ralph and Patricia Sarich Neuroscience Research Institute, Nedlands, WA, Australia.,Department of Biomedical Sciences, Macquarie University, Sydney, NSW, Australia.,KaRa Institute of Neurological Diseases, Sydney, NSW, Australia
| | - Hiroshi Mori
- Department of Clinical Neuroscience, Osaka City University Medical School, Osaka, Japan
| | - Richard Perrin
- Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA.,Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO, USA.,Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, USA
| | - Chengjie Xiong
- Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA.,Department of Biostatistics, Washington University, St Louis, MO, USA
| | - Martin Rossor
- Dementia Research Centre, University College London, Queen Square, London, UK
| | - Nick C Fox
- Dementia Research Centre, University College London, Queen Square, London, UK
| | - Antoinette O'Connor
- Dementia Research Centre, University College London, Queen Square, London, UK.,UK Dementia Research Institute at UCL, UCL, London, UK
| | - Stephen Salloway
- Department of Neurology, Warren Alpert Medical School of Brown University, Providence, RI, USA
| | - Adrian Danek
- Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Katharina Buerger
- Institute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilian-University LMU, Munich, Germany.,German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Randall J Bateman
- Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA.,Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Christian Habeck
- Cognitive Neuroscience Division, Department of Neurology, Columbia University, New York, NY, USA
| | - Yaakov Stern
- Cognitive Neuroscience Division, Department of Neurology, Columbia University, New York, NY, USA
| | - Nicolai Franzmeier
- Institute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilian-University LMU, Munich, Germany
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50
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Calderazzo SM, Busch SE, Moore TL, Rosene DL, Medalla M. Distribution and overlap of entorhinal, premotor, and amygdalar connections in the monkey anterior cingulate cortex. J Comp Neurol 2021; 529:885-904. [PMID: 32677044 PMCID: PMC8214921 DOI: 10.1002/cne.24986] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Revised: 06/17/2020] [Accepted: 07/11/2020] [Indexed: 12/22/2022]
Abstract
The anterior cingulate cortex (ACC) is important for decision-making as it integrates motor plans with affective and contextual limbic information. Disruptions in these networks have been observed in depression, bipolar disorder, and post-traumatic stress disorder. Yet, overlap of limbic and motor connections within subdivisions of the ACC is not well understood. Hence, we administered a combination of retrograde and anterograde tracers into structures important for contextual memories (entorhinal cortex), affective processing (amygdala), and motor planning (dorsal premotor cortex) to assess overlap of labeled projection neurons from (outputs) and axon terminals to (inputs) the ACC of adult rhesus monkeys (Macaca mulatta). Our data show that entorhinal and dorsal premotor cortical (dPMC) connections are segregated across ventral (A25, A24a) and dorsal (A24b,c) subregions of the ACC, while amygdalar connections are more evenly distributed across subregions. Among all areas, the rostral ACC (A32) had the lowest relative density of connections with all three regions. In the ventral ACC, entorhinal and amygdalar connections strongly overlap across all layers, especially in A25. In the dorsal ACC, outputs to dPMC and the amygdala strongly overlap in deep layers. However, dPMC input to the dorsal ACC was densest in deep layers, while amygdalar inputs predominantly localized in upper layers. These connection patterns are consistent with diverse roles of the dorsal ACC in motor evaluation and the ventral ACC in affective and contextual memory. Further, distinct laminar circuits suggest unique interactions within specific ACC compartments that are likely important for the temporal integration of motor and limbic information during flexible goal-directed behavior.
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Affiliation(s)
- Samantha M. Calderazzo
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, Massachusetts
- Center for Systems Neuroscience, Boston University, Boston, Massachusetts
| | - Silas E. Busch
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, Massachusetts
- Department of Neurobiology, University of Chicago, Chicago, Illinois
| | - Tara L. Moore
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, Massachusetts
- Center for Systems Neuroscience, Boston University, Boston, Massachusetts
| | - Douglas L. Rosene
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, Massachusetts
- Center for Systems Neuroscience, Boston University, Boston, Massachusetts
| | - Maria Medalla
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, Massachusetts
- Center for Systems Neuroscience, Boston University, Boston, Massachusetts
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