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Keane BP, Abrham YT, Cole MW, Johnson BA, Hu B, Cocuzza CV. Functional dysconnectivity of visual and somatomotor networks yields a simple and robust biomarker for psychosis. Mol Psychiatry 2024:10.1038/s41380-024-02767-3. [PMID: 39367056 DOI: 10.1038/s41380-024-02767-3] [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: 10/28/2023] [Revised: 09/21/2024] [Accepted: 09/25/2024] [Indexed: 10/06/2024]
Abstract
People with psychosis exhibit thalamo-cortical hyperconnectivity and cortico-cortical hypoconnectivity with sensory networks, however, it remains unclear if this applies to all sensory networks, whether it arises from other illness factors, or whether such differences could form the basis of a viable biomarker. To address the foregoing, we harnessed data from the Human Connectome Early Psychosis Project and computed resting-state functional connectivity (RSFC) matrices for 54 healthy controls and 105 psychosis patients. Primary visual, secondary visual ("visual2"), auditory, and somatomotor networks were defined via a recent brain network partition. RSFC was determined for 718 regions via regularized partial correlation. Psychosis patients-both affective and non-affective-exhibited cortico-cortical hypoconnectivity and thalamo-cortical hyperconnectivity in somatomotor and visual2 networks but not in auditory or primary visual networks. When we averaged and normalized the visual2 and somatomotor network connections, and subtracted the thalamo-cortical and cortico-cortical connectivity values, a robust psychosis biomarker emerged (p = 2e-10, Hedges' g = 1.05). This "somato-visual" biomarker was present in antipsychotic-naive patients and did not depend on confounds such as psychiatric comorbidities, substance/nicotine use, stress, anxiety, or demographics. It had moderate test-retest reliability (ICC = 0.62) and could be recovered in five-minute scans. The marker could discriminate groups in leave-one-site-out cross-validation (AUC = 0.79) and improve group classification upon being added to a well-known neurocognition task. Finally, it could differentiate later-stage psychosis patients from healthy or ADHD controls in two independent data sets. These results introduce a simple and robust RSFC biomarker that can distinguish psychosis patients from controls by the early illness stages.
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Affiliation(s)
- Brian P Keane
- Departments of Psychiatry and Neuroscience, University of Rochester Medical Center, 430 Elmwood Ave, Rochester, NY, 14642, USA.
- Center for Visual Science, University of Rochester, 601 Elmwood Ave, P.O. Box 319, Rochester, NY, 14642, USA.
- Department of Brain & Cognitive Science, University of Rochester, 358 Meliora Hall, P.O. Box 270268, Rochester, NY, 14627-0268, USA.
| | - Yonatan T Abrham
- Center for Visual Science, University of Rochester, 601 Elmwood Ave, P.O. Box 319, Rochester, NY, 14642, USA
- Department of Brain & Cognitive Science, University of Rochester, 358 Meliora Hall, P.O. Box 270268, Rochester, NY, 14627-0268, USA
| | - Michael W Cole
- Center for Molecular and Behavioral Neuroscience, Rutgers, The State University of New Jersey, 197 University Ave, Newark, NJ, 07102, USA
| | - Brent A Johnson
- Department of Biostatistics, University of Rochester Medical Center, 601 Elmwood Ave, P.O. Box 630, Rochester, NY, USA
| | - Boyang Hu
- Department of Brain & Cognitive Science, University of Rochester, 358 Meliora Hall, P.O. Box 270268, Rochester, NY, 14627-0268, USA
| | - Carrisa V Cocuzza
- Department of Psychology, Yale University, 100 College St, New Haven, CT, 06510, USA
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Keane BP, Abrham Y, Cole MW, Johnson BA, Hu B, Cocuzza CV. Functional dysconnectivity of visual and somatomotor networks yields a simple and robust biomarker for psychosis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.06.14.24308836. [PMID: 38946974 PMCID: PMC11213076 DOI: 10.1101/2024.06.14.24308836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
People with psychosis exhibit thalamo-cortical hyperconnectivity and cortico-cortical hypoconnectivity with sensory networks, however, it remains unclear if this applies to all sensory networks, whether it arises from other illness factors, or whether such differences could form the basis of a viable biomarker. To address the foregoing, we harnessed data from the Human Connectome Early Psychosis Project and computed resting-state functional connectivity (RSFC) matrices for 54 healthy controls and 105 psychosis patients. Primary visual, secondary visual ("visual2"), auditory, and somatomotor networks were defined via a recent brain network partition. RSFC was determined for 718 regions via regularized partial correlation. Psychosis patients- both affective and non-affective-exhibited cortico-cortical hypoconnectivity and thalamo-cortical hyperconnectivity in somatomotor and visual2 networks but not in auditory or primary visual networks. When we averaged and normalized the visual2 and somatomotor network connections, and subtracted the thalamo-cortical and cortico-cortical connectivity values, a robust psychosis biomarker emerged (p=2e-10, Hedges' g=1.05). This "somato-visual" biomarker was present in antipsychotic-naive patients and did not depend on confounds such as psychiatric comorbidities, substance/nicotine use, stress, anxiety, or demographics. It had moderate test-retest reliability (ICC=.61) and could be recovered in five-minute scans. The marker could discriminate groups in leave-one-site-out cross-validation (AUC=.79) and improve group classification upon being added to a well-known neurocognition task. Finally, it could differentiate later-stage psychosis patients from healthy or ADHD controls in two independent data sets. These results introduce a simple and robust RSFC biomarker that can distinguish psychosis patients from controls by the early illness stages.
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Kamath RS, Weldon KB, Moser HR, Montoya S, Abdullahi KS, Burton PC, Sponheim SR, Olman CA, Schallmo MP. Impaired contour object perception in psychosis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.07.02.24309795. [PMID: 39006442 PMCID: PMC11245054 DOI: 10.1101/2024.07.02.24309795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Contour integration, the process of joining spatially separated elements into a single unified line, has consistently been found to be impaired in schizophrenia. Recent work suggests that this deficit could be associated with psychotic symptomatology, rather than a specific diagnosis such as schizophrenia. Examining a transdiagnostic sample of participants with psychotic psychopathology, we obtained quantitative indices of contour perception in a psychophysical behavioral task. We found impaired contour discrimination performance among people with psychotic psychopathology (PwPP, n = 62) compared to healthy controls (n = 34) and biological relatives of PwPP (n = 44). Participants with schizophrenia (n = 31) showed impaired task performance compared to participants with bipolar disorder (n = 18). We also measured responses during an analogous task using ultra-high field (7T) functional MRI and found higher responses in the lateral occipital cortex of PwPP compared to controls. Using task-based functional connectivity analyses, we observed abnormal connectivity between visual brain areas during contour perception among PwPP. These connectivity differences only emerged when participants had to distinguish the contour object from background distractors, suggesting that a failure to suppress noise elements relative to contour elements may underlie impaired contour processing in PwPP. Our results are consistent with impaired contour integration in psychotic psychopathology, and especially schizophrenia, that is related to cognitive dysfunction, and may be linked to impaired functional connectivity across visual regions.
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Affiliation(s)
- Rohit S. Kamath
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | - Kimberly B. Weldon
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
| | - Hannah R. Moser
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | - Samantha Montoya
- Graduate Program in Neuroscience, University of Minnesota, Minneapolis, MN, USA
| | - Kamar S. Abdullahi
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | - Philip C. Burton
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
- Office of the Associate Dean for Research, University of Minnesota, Minneapolis, MN, USA
| | - Scott R. Sponheim
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
- Veterans Affairs Health Care System, Minneapolis, MN, USA
| | - Cheryl A. Olman
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Michael-Paul Schallmo
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
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Keane BP, Abrham YT, Hearne LJ, Bi H, Hu B. Increased whole-brain functional heterogeneity in psychosis during rest and task. Neuroimage Clin 2024; 43:103630. [PMID: 38875745 PMCID: PMC11225660 DOI: 10.1016/j.nicl.2024.103630] [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: 12/19/2023] [Revised: 05/09/2024] [Accepted: 06/06/2024] [Indexed: 06/16/2024]
Abstract
Past work has shown that people with schizophrenia exhibit more cross-subject heterogeneity in their functional connectivity patterns. However, it remains unclear whether specific brain networks are implicated, whether common confounds could explain the results, or whether task activations might also be more heterogeneous. Unambiguously establishing the existence and extent of functional heterogeneity constitutes a first step toward understanding why it emerges and what it means clinically. METHODS We first leveraged data from the HCP Early Psychosis project. Functional connectivity (FC) was extracted from 718 parcels via principal components regression. Networks were defined via a brain network partition (Ji et al., 2019). We also examined an independent data set with controls, later-stage schizophrenia patients, and ADHD patients during rest and during a working memory task. We quantified heterogeneity by averaging the Pearson correlation distance of each subject's FC or task activity pattern to that of every other subject of the same cohort. RESULTS Affective and non-affective early psychosis patients exhibited more cross-subject whole-brain heterogeneity than healthy controls (ps < 0.001, Hedges' g > 0.74). Increased heterogeneity could be found in up to seven networks. In-scanner motion, medication, nicotine, and comorbidities could not explain the results. Later-stage schizophrenia patients exhibited heterogeneous connectivity patterns and task activations compared to ADHD and control subjects. Interestingly, individual connection weights, parcel-wise task activations, and network averages thereof were not more variable in patients, suggesting that heterogeneity becomes most obvious over large-scale patterns. CONCLUSION Whole-brain cross-subject functional heterogeneity characterizes psychosis during rest and task. Developmental and pathophysiological consequences are discussed.
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Affiliation(s)
- Brian P Keane
- Department of Psychiatry, University of Rochester Medical Center, 601 Elmwood Ave, Rochester, NY 14642, USA; Department of Neuroscience, University of Rochester Medical Center, 601 Elmwood Ave, Rochester, NY 14642, USA; Center for Visual Science, University of Rochester, 601 Elmwood Ave, Rochester, NY 14642, USA; Department of Brain & Cognitive Science, University of Rochester, 358 Meliora Hall, P.O. Box 270268, Rochester, NY 14627, USA.
| | - Yonatan T Abrham
- Center for Visual Science, University of Rochester, 601 Elmwood Ave, Rochester, NY 14642, USA; Department of Brain & Cognitive Science, University of Rochester, 358 Meliora Hall, P.O. Box 270268, Rochester, NY 14627, USA
| | - Luke J Hearne
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Howard Bi
- Department of Psychiatry, University of Rochester Medical Center, 601 Elmwood Ave, Rochester, NY 14642, USA
| | - Boyang Hu
- Department of Brain & Cognitive Science, University of Rochester, 358 Meliora Hall, P.O. Box 270268, Rochester, NY 14627, USA
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Yan H, Zhang Y, Shan X, Li H, Liu F, Xie G, Li P, Guo W. Altered interhemispheric functional connectivity in patients with obsessive-compulsive disorder and its potential in therapeutic response prediction. J Neurosci Res 2024; 102. [PMID: 38284840 DOI: 10.1002/jnr.25272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Revised: 10/23/2023] [Accepted: 10/25/2023] [Indexed: 01/30/2024]
Abstract
The trajectory of voxel-mirrored homotopic connectivity (VMHC) after medical treatment in obsessive-compulsive disorder (OCD) and its value in prediction of treatment response remains unclear. This study aimed to investigate the pathophysiological mechanism of OCD, as well as biomarkers for prediction of pharmacological efficacy. Medication-free patients with OCD and healthy controls (HCs) underwent magnetic resonance imaging. The patients were scanned again after a 4-week treatment with paroxetine. The acquired data were subjected to VMHC, support vector regression (SVR), and correlation analyses. Compared with HCs (36 subjects), patients with OCD (34 subjects after excluding two subjects with excessive head movement) exhibited significantly lower VMHC in the bilateral superior parietal lobule (SPL), postcentral gyrus, and calcarine cortex, and VMHC in the postcentral gyrus was positively correlated with cognitive function. After treatment, the patients showed increased VMHC in the bilateral posterior cingulate cortex/precuneus (PCC/PCu) with the improvement of symptoms. SVR results showed that VMHC in the postcentral gyrus at baseline could aid to predict a change in the scores of OCD scales. This study revealed that SPL, postcentral gyrus, and calcarine cortex participate in the pathophysiological mechanism of OCD while PCC/PCu participate in the pharmacological mechanism. VMHC in the postcentral gyrus is a potential predictive biomarker of the treatment effects in OCD.
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Affiliation(s)
- Haohao Yan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Yingying Zhang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Xiaoxiao Shan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Huabing Li
- Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Feng Liu
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Guojun Xie
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, China
| | - Ping Li
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, China
| | - Wenbin Guo
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
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Yu X, Yu J, Li Y, Cong J, Wang C, Fan R, Wang W, Zhou L, Xu C, Li Y, Liu Y. Altered intrinsic functional brain architecture in patients with functional constipation: a surface-based network study. Front Neurosci 2023; 17:1241993. [PMID: 37811328 PMCID: PMC10551127 DOI: 10.3389/fnins.2023.1241993] [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: 06/18/2023] [Accepted: 09/06/2023] [Indexed: 10/10/2023] Open
Abstract
Background Functional constipation (FCon) is a common functional gastrointestinal disorder (FGID). Studies have indicated a higher likelihood of psychiatric disorders, such as anxiety, depression, sleep disturbances, and impaired concentration, among patients with FCon. However, the underlying pathophysiological mechanisms responsible for these symptoms in FCon patients remain to be fully elucidated. The human brain is a complex network architecture with several fundamental organizational properties. Neurological interactions between gut symptoms and psychiatric issues may be closely associated with these complex networks. Methods In the present study, a total of 35 patients with FCon and 40 healthy controls (HC) were recruited for a series of clinical examinations and resting-state functional magnetic imaging (RS-fMRI). We employed the surface-based analysis (SBA) approach, utilizing the Schaefer cortical parcellation template and Tikhonov regularization. Graph theoretical analysis (GTA) and functional connectivity (FC) analysis of RS-fMRI were conducted to investigate the aberrant network alterations between the two groups. Additionally, correlation analyses were performed between the network indices and clinical variables in patients with FCon. Results At the global level, we found altered topological properties and networks in patients with FCon, mainly including the significantly increased clustering coefficient (CP), local efficiency (Eloc), and shortest path length (LP), whereas the decreased global efficiency (Eglob) compared to HC. At the regional level, patients with FCon exhibited increased nodal efficiency in the frontoparietal network (FPN). Furthermore, FC analysis demonstrated several functional alterations within and between the Yeo 7 networks, particularly including visual network (VN), limbic network (LN), default mode network (DMN), and somatosensory-motor network (SMN) in sub-network and large-scale network analysis. Correlation analysis revealed that there were no significant associations between the network metrics and clinical variables in the present study. Conclusion These results highlight the altered topological architecture of functional brain networks associated with visual perception abilities, emotion regulation, sensorimotor processing, and attentional control, which may contribute to effectively targeted treatment modalities for patients with FCon.
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Affiliation(s)
- Xiang Yu
- Department of Radiology, Tianjin Union Medical Center, Tianjin, China
| | - Jingjie Yu
- Department of Psychiatry and Psychology, Tianjin Union Medical Center, Tianjin, China
| | - Yuwei Li
- Department of Colorectal Surgery, Tianjin Union Medical Center, Tianjin, China
| | - Jiying Cong
- Department of Colorectal Surgery, Tianjin Union Medical Center, Tianjin, China
| | - Chao Wang
- Department of Radiology, Tianjin Union Medical Center, Tianjin, China
| | - Ran Fan
- Department of Radiology, Tianjin Union Medical Center, Tianjin, China
| | - Wanbing Wang
- Graduate School of Tianjin Nankai University, Tianjin, China
| | - Lige Zhou
- Graduate School of Tianjin Medical University, Tianjin, China
| | - Chen Xu
- Department of Colorectal Surgery, Tianjin Union Medical Center, Tianjin, China
| | - Yiming Li
- Department of Radiology, Tianjin Union Medical Center, Tianjin, China
| | - Yawu Liu
- Department of Neurology, University of Eastern Finland, Kuopio, Finland
- Department of Clinical Radiology, Kuopio University Hospital, Kuopio, Finland
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Sanchez-Romero R, Ito T, Mill RD, Hanson SJ, Cole MW. Causally informed activity flow models provide mechanistic insight into network-generated cognitive activations. Neuroimage 2023; 278:120300. [PMID: 37524170 PMCID: PMC10634378 DOI: 10.1016/j.neuroimage.2023.120300] [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: 04/28/2023] [Revised: 07/06/2023] [Accepted: 07/28/2023] [Indexed: 08/02/2023] Open
Abstract
Brain activity flow models estimate the movement of task-evoked activity over brain connections to help explain network-generated task functionality. Activity flow models have been shown to accurately generate task-evoked brain activations across a wide variety of brain regions and task conditions. However, these models have had limited explanatory power, given known issues with causal interpretations of the standard functional connectivity measures used to parameterize activity flow models. We show here that functional/effective connectivity (FC) measures grounded in causal principles facilitate mechanistic interpretation of activity flow models. We progress from simple to complex FC measures, with each adding algorithmic details reflecting causal principles. This reflects many neuroscientists' preference for reduced FC measure complexity (to minimize assumptions, minimize compute time, and fully comprehend and easily communicate methodological details), which potentially trades off with causal validity. We start with Pearson correlation (the current field standard) to remain maximally relevant to the field, estimating causal validity across a range of FC measures using simulations and empirical fMRI data. Finally, we apply causal-FC-based activity flow modeling to a dorsolateral prefrontal cortex region (DLPFC), demonstrating distributed causal network mechanisms contributing to its strong activation during a working memory task. Notably, this fully distributed model is able to account for DLPFC working memory effects traditionally thought to rely primarily on within-region (i.e., not distributed) recurrent processes. Together, these results reveal the promise of parameterizing activity flow models using causal FC methods to identify network mechanisms underlying cognitive computations in the human brain.
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Affiliation(s)
- Ruben Sanchez-Romero
- Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ 07102, USA.
| | - Takuya Ito
- Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ 07102, USA
| | - Ravi D Mill
- Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ 07102, USA
| | - Stephen José Hanson
- Rutgers University Brain Imaging Center (RUBIC), Rutgers University, Newark, NJ 07102, USA
| | - Michael W Cole
- Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ 07102, USA
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Schallmo MP, Weldon KB, Kamath RS, Moser HR, Montoya SA, Killebrew KW, Demro C, Grant AN, Marjańska M, Sponheim SR, Olman CA. The Psychosis Human Connectome Project: Design and rationale for studies of visual neurophysiology. Neuroimage 2023; 272:120060. [PMID: 36997137 PMCID: PMC10153004 DOI: 10.1016/j.neuroimage.2023.120060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 03/22/2023] [Accepted: 03/27/2023] [Indexed: 04/01/2023] Open
Abstract
Visual perception is abnormal in psychotic disorders such as schizophrenia. In addition to hallucinations, laboratory tests show differences in fundamental visual processes including contrast sensitivity, center-surround interactions, and perceptual organization. A number of hypotheses have been proposed to explain visual dysfunction in psychotic disorders, including an imbalance between excitation and inhibition. However, the precise neural basis of abnormal visual perception in people with psychotic psychopathology (PwPP) remains unknown. Here, we describe the behavioral and 7 tesla MRI methods we used to interrogate visual neurophysiology in PwPP as part of the Psychosis Human Connectome Project (HCP). In addition to PwPP (n = 66) and healthy controls (n = 43), we also recruited first-degree biological relatives (n = 44) in order to examine the role of genetic liability for psychosis in visual perception. Our visual tasks were designed to assess fundamental visual processes in PwPP, whereas MR spectroscopy enabled us to examine neurochemistry, including excitatory and inhibitory markers. We show that it is feasible to collect high-quality data across multiple psychophysical, functional MRI, and MR spectroscopy experiments with a sizable number of participants at a single research site. These data, in addition to those from our previously described 3 tesla experiments, will be made publicly available in order to facilitate further investigations by other research groups. By combining visual neuroscience techniques and HCP brain imaging methods, our experiments offer new opportunities to investigate the neural basis of abnormal visual perception in PwPP.
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Affiliation(s)
- Michael-Paul Schallmo
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN.
| | - Kimberly B Weldon
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN; Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN
| | - Rohit S Kamath
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN
| | - Hannah R Moser
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN
| | - Samantha A Montoya
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN
| | - Kyle W Killebrew
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN
| | - Caroline Demro
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN; Department of Psychology, University of Minnesota, Minneapolis, MN
| | - Andrea N Grant
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN
| | - Małgorzata Marjańska
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN
| | - Scott R Sponheim
- Veterans Affairs Medical Center, Minneapolis, MN; Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN
| | - Cheryl A Olman
- Department of Psychology, University of Minnesota, Minneapolis, MN; Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN
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Amer T, Davachi L. Extra-hippocampal contributions to pattern separation. eLife 2023; 12:e82250. [PMID: 36972123 PMCID: PMC10042541 DOI: 10.7554/elife.82250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 03/21/2023] [Indexed: 03/29/2023] Open
Abstract
Pattern separation, or the process by which highly similar stimuli or experiences in memory are represented by non-overlapping neural ensembles, has typically been ascribed to processes supported by the hippocampus. Converging evidence from a wide range of studies, however, suggests that pattern separation is a multistage process supported by a network of brain regions. Based on this evidence, considered together with related findings from the interference resolution literature, we propose the 'cortico-hippocampal pattern separation' (CHiPS) framework, which asserts that brain regions involved in cognitive control play a significant role in pattern separation. Particularly, these regions may contribute to pattern separation by (1) resolving interference in sensory regions that project to the hippocampus, thus regulating its cortical input, or (2) directly modulating hippocampal processes in accordance with task demands. Considering recent interest in how hippocampal operations are modulated by goal states likely represented and regulated by extra-hippocampal regions, we argue that pattern separation is similarly supported by neocortical-hippocampal interactions.
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Affiliation(s)
- Tarek Amer
- Department of Psychology, University of VictoriaVictoriaCanada
| | - Lila Davachi
- Department of Psychology, Columbia UniversityNew YorkUnited States
- Nathan Kline Research InstituteOrangeburgUnited States
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Yu X, Yu J, Li Y, Cong J, Wang C, Fan R, Wang W, Zhou L, Xu C, Li Y, Liu Y. Aberrant intrinsic functional brain networks in patients with functional constipation. Neuroradiology 2023; 65:337-348. [PMID: 36216896 DOI: 10.1007/s00234-022-03064-y] [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: 07/23/2022] [Accepted: 10/03/2022] [Indexed: 01/25/2023]
Abstract
PURPOSE Patients with functional constipation (FCon) often suffer from mental and psychological problems. To explore the possible neurological interaction, we used resting-state functional magnetic imaging (RS-fMRI) to compare the alterations in intrinsic brain functional networks at multiple levels between patients with FCon and healthy controls (HC). METHODS Twenty-eight patients with FCon and twenty-nine HC were recruited for a series of examinations and RS-fMRI. Both graph theory analysis and functional connectivity (FC) analysis were used to investigate brain functional alterations between the two groups. Correlation analyses were performed among neuropsychological scores, clinical indexes, and neuroimaging data. RESULTS Compared with the HC, the assortativity showed significantly increased in global level in patients with FCon. In regional level, we found obviously increased nodal degree and nodal efficiency in somatosensory network (SMN), decreased nodal degree, and increased nodal efficiency in default mode network (DMN) in the FCon group. Furthermore, FC analysis demonstrated several functional alterations within and between the networks, particularly including the SMN and visual network (VN) in sub-network and large-scale network analysis. Moreover, correlation analysis indicated that nodal metrics and aberrant FC among functional brain networks were associated with emotion and scores of constipation in patients with FCon. CONCLUSION All these findings reflect the differences in intrinsic brain functional networks between FCon and HC. Our study highlighted SMN, DMN, and VN as critical network and may be involved in the neurophysiology of FCon, which may contribute to improve personalized treatment in patients with FCon.
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Affiliation(s)
- Xiang Yu
- Department of Radiology, Tianjin Union Medical Center, No. 190, Jieyuan Road, Hongqiao District, Tianjin, 300121, China
| | - Jingjie Yu
- Department of Psychiatry and Psychology, Tianjin Union Medical Center, No. 190, Jieyuan Road, Hongqiao District, Tianjin, 300121, China
| | - Yuwei Li
- Department of Colorectal Surgery, Tianjin Union Medical Center, No. 190, Jieyuan Road, Hongqiao District, Tianjin, 300121, China
| | - Jiying Cong
- Department of Colorectal Surgery, Tianjin Union Medical Center, No. 190, Jieyuan Road, Hongqiao District, Tianjin, 300121, China
| | - Chao Wang
- Department of Radiology, Tianjin Union Medical Center, No. 190, Jieyuan Road, Hongqiao District, Tianjin, 300121, China
| | - Ran Fan
- Department of Radiology, Tianjin Union Medical Center, No. 190, Jieyuan Road, Hongqiao District, Tianjin, 300121, China
| | - Wanbing Wang
- Graduate School of Tianjin Nankai University, Tianjin, China
| | - Lige Zhou
- Graduate School of Tianjin Medical University, Tianjin, China
| | - Chen Xu
- Department of Colorectal Surgery, Tianjin Union Medical Center, No. 190, Jieyuan Road, Hongqiao District, Tianjin, 300121, China.
| | - Yiming Li
- Department of Radiology, Tianjin Union Medical Center, No. 190, Jieyuan Road, Hongqiao District, Tianjin, 300121, China.
| | - Yawu Liu
- Department of Neurology, University of Eastern Finland, Kuopio, Finland.,Department of Clinical Radiology, Kuopio University Hospital, Kuopio, Finland
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Keane BP, Krekelberg B, Mill RD, Silverstein SM, Thompson JL, Serody MR, Barch DM, Cole MW. Dorsal attention network activity during perceptual organization is distinct in schizophrenia and predictive of cognitive disorganization. Eur J Neurosci 2023; 57:458-478. [PMID: 36504464 DOI: 10.1111/ejn.15889] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Revised: 12/02/2022] [Accepted: 12/07/2022] [Indexed: 12/14/2022]
Abstract
Visual shape completion is a canonical perceptual organization process that integrates spatially distributed edge information into unified representations of objects. People with schizophrenia show difficulty in discriminating completed shapes, but the brain networks and functional connections underlying this perceptual difference remain poorly understood. Also unclear is whether brain network differences in schizophrenia occur in related illnesses or vary with illness features transdiagnostically. To address these topics, we scanned (functional magnetic resonance imaging, fMRI) people with schizophrenia, bipolar disorder, or no psychiatric illness during rest and during a task in which they discriminated configurations that formed or failed to form completed shapes (illusory and fragmented condition, respectively). Multivariate pattern differences were identified on the cortical surface using 360 predefined parcels and 12 functional networks composed of such parcels. Brain activity flow mapping was used to evaluate the likely involvement of resting-state connections for shape completion. Illusory/fragmented task activation differences ('modulations') in the dorsal attention network (DAN) could distinguish people with schizophrenia from the other groups (AUCs > .85) and could transdiagnostically predict cognitive disorganization severity. Activity flow over functional connections from the DAN could predict secondary visual network modulations in each group, except in schizophrenia. The secondary visual network was strongly and similarly modulated in each group. Task modulations were dispersed over more networks in patients compared to controls. In summary, DAN activity during visual perceptual organization is distinct in schizophrenia, symptomatically relevant, and potentially related to improper attention-related feedback into secondary visual areas.
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Affiliation(s)
- Brian P Keane
- University Behavioral Health Care, Department of Psychiatry, and Center for Cognitive Science, Rutgers, The State University of New Jersey, Piscataway, New Jersey, USA
- Departments of Psychiatry and Neuroscience, University of Rochester Medical Center, Rochester, New York, USA
| | - Bart Krekelberg
- Center for Molecular and Behavioral Neuroscience, Rutgers, The State University of New Jersey, Newark, New Jersey, USA
| | - Ravi D Mill
- Center for Molecular and Behavioral Neuroscience, Rutgers, The State University of New Jersey, Newark, New Jersey, USA
| | - Steven M Silverstein
- University Behavioral Health Care, Department of Psychiatry, and Center for Cognitive Science, Rutgers, The State University of New Jersey, Piscataway, New Jersey, USA
- Departments of Psychiatry and Neuroscience, University of Rochester Medical Center, Rochester, New York, USA
- Department of Ophthalmology, University of Rochester Medical Center, Rochester, New York, USA
| | - Judy L Thompson
- Departments of Psychiatry and Neuroscience, University of Rochester Medical Center, Rochester, New York, USA
- Department of Psychiatric Rehabilitation and Counseling Professions, Rutgers, The State University of New Jersey, Piscataway, New Jersey, USA
| | - Megan R Serody
- University Behavioral Health Care, Department of Psychiatry, and Center for Cognitive Science, Rutgers, The State University of New Jersey, Piscataway, New Jersey, USA
- Departments of Psychiatry and Neuroscience, University of Rochester Medical Center, Rochester, New York, USA
| | - Deanna M Barch
- Departments of Psychological & Brain Sciences, Psychiatry, and Radiology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Michael W Cole
- Center for Molecular and Behavioral Neuroscience, Rutgers, The State University of New Jersey, Newark, New Jersey, USA
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12
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Barch DM, Boudewyn MA, Carter CC, Erickson M, Frank MJ, Gold JM, Luck SJ, MacDonald AW, Ragland JD, Ranganath C, Silverstein SM, Yonelinas A. Cognitive [Computational] Neuroscience Test Reliability and Clinical Applications for Serious Mental Illness (CNTRaCS) Consortium: Progress and Future Directions. Curr Top Behav Neurosci 2022; 63:19-60. [PMID: 36173600 DOI: 10.1007/7854_2022_391] [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] [Indexed: 11/25/2022]
Abstract
The development of treatments for impaired cognition in schizophrenia has been characterized as the most important challenge facing psychiatry at the beginning of the twenty-first century. The Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia (CNTRICS) project was designed to build on the potential benefits of using tasks and tools from cognitive neuroscience to better understanding and treat cognitive impairments in psychosis. These benefits include: (1) the use of fine-grained tasks that measure discrete cognitive processes; (2) the ability to design tasks that distinguish between specific cognitive domain deficits and poor performance due to generalized deficits resulting from sedation, low motivation, poor test taking skills, etc.; and (3) the ability to link cognitive deficits to specific neural systems, using animal models, neuropsychology, and functional imaging. CNTRICS convened a series of meetings to identify paradigms from cognitive neuroscience that maximize these benefits and identified the steps need for translation into use in clinical populations. The Cognitive Neuroscience Test Reliability and Clinical Applications for Schizophrenia (CNTRaCS) Consortium was developed to help carry out these steps. CNTRaCS consists of investigators at five different sites across the country with diverse expertise relevant to a wide range of the cognitive systems identified as critical as part of CNTRICs. This work reports on the progress and current directions in the evaluation and optimization carried out by CNTRaCS of the tasks identified as part of the original CNTRICs process, as well as subsequent extensions into the Positive Valence systems domain of Research Domain Criteria (RDoC). We also describe the current focus of CNTRaCS, which involves taking a computational psychiatry approach to measuring cognitive and motivational function across the spectrum of psychosis. Specifically, the current iteration of CNTRaCS is using computational modeling to isolate parameters reflecting potentially more specific cognitive and visual processes that may provide greater interpretability in understanding shared and distinct impairments across psychiatric disorders.
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Affiliation(s)
- Deanna M Barch
- Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA.
| | | | | | | | | | - James M Gold
- Maryland Psychiatric Research Center, Baltimore, MD, USA
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13
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Cocuzza CV, Sanchez-Romero R, Cole MW. Protocol for activity flow mapping of neurocognitive computations using the Brain Activity Flow Toolbox. STAR Protoc 2022; 3:101094. [PMID: 35128473 PMCID: PMC8808261 DOI: 10.1016/j.xpro.2021.101094] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Traditional cognitive neuroscience uses task-evoked activations to map neurocognitive processes (and information) to brain regions; however, how those processes are generated is unknown. We developed activity flow mapping to identify and empirically validate network mechanisms underlying the generation of neurocognitive processes. This approach models the movement of task-evoked activity over brain connections to predict task-evoked activations. We present a protocol for using the Brain Activity Flow Toolbox (https://colelab.github.io/ActflowToolbox/) to identify network mechanisms underlying neurocognitive processes of interest. For complete details on the use and execution of this protocol, please refer to Cole et al., 2021.
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Affiliation(s)
- Carrisa V. Cocuzza
- Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ 07102, USA
- Behavioral and Neural Sciences PhD Program, Rutgers University, Newark, NJ 07102, USA
| | - Ruben Sanchez-Romero
- Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ 07102, USA
| | - Michael W. Cole
- Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ 07102, USA
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14
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Hang Y, Xiaohua Y, Xiang L, Sijun Q, Guixiang L, Tianyu B, Benzheng W. Research on resting spontaneous brain activity and functional connectivity of acupuncture at uterine acupoints. DIGITAL CHINESE MEDICINE 2022. [DOI: 10.1016/j.dcmed.2022.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
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15
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Keane BP, Erlikhman G, Serody M, Silverstein SM. A brief psychometric test reveals robust shape completion deficits in schizophrenia that are less severe in bipolar disorder. Schizophr Res 2022; 240:78-80. [PMID: 34974396 PMCID: PMC8917988 DOI: 10.1016/j.schres.2021.12.015] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 12/09/2021] [Accepted: 12/11/2021] [Indexed: 02/03/2023]
Affiliation(s)
- Brian P. Keane
- University Behavioral Health Care, Rutgers, The State University of New Jersey, 671 Hoes Lane West, Piscataway, NJ 08854, USA,Department of Psychiatry, University of Rochester Medical Center, 601 Elmwood Ave, Rochester 14642, NY,Department of Neuroscience and Center for Visual Science, University of Rochester Medical Center, 601 Elmwood Ave, Rochester, NY 14642, USA,Department of Brain and Cognitive Science, University of Rochester, 363 Meliora Hall, Rochester, NY 14627, USA
| | - Gennady Erlikhman
- UCLA Human Perception Laboratory and Psychology Department, University of California, Los Angeles, 1285 Franz Hall, Los Angeles, CA 90095-1563, USA
| | - Megan Serody
- University Behavioral Health Care, Rutgers, The State University of New Jersey, 671 Hoes Lane West, Piscataway, NJ 08854, USA,Department of Psychiatry, University of Rochester Medical Center, 601 Elmwood Ave, Rochester 14642, NY
| | - Steven M. Silverstein
- University Behavioral Health Care, Rutgers, The State University of New Jersey, 671 Hoes Lane West, Piscataway, NJ 08854, USA,Department of Psychiatry, University of Rochester Medical Center, 601 Elmwood Ave, Rochester 14642, NY,Department of Neuroscience and Center for Visual Science, University of Rochester Medical Center, 601 Elmwood Ave, Rochester, NY 14642, USA,Department of Ophthalmology, University of Rochester Medical Center, 601 Elmwood Ave, Rochester, NY 14642, USA
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