1
|
Moussa-Tooks AB, Beermann A, Manzanarez Felix K, Coleman M, Bouix S, Holt D, Lewandowski KE, Öngür D, Breier A, Shenton ME, Heckers S, Walther S, Brady RO, Ward HB. Isolation of Distinct Networks Driving Action and Cognition in Psychomotor Processes. Biol Psychiatry 2024; 96:390-400. [PMID: 38452884 DOI: 10.1016/j.biopsych.2024.02.1013] [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: 08/30/2023] [Revised: 02/02/2024] [Accepted: 02/23/2024] [Indexed: 03/09/2024]
Abstract
BACKGROUND Psychomotor disturbances are observed across psychiatric disorders and often manifest as psychomotor slowing, agitation, disorganized behavior, or catatonia. Psychomotor function includes both cognitive and motor components, but the neural circuits driving these subprocesses and how they relate to symptoms have remained elusive for centuries. METHODS We analyzed data from the HCP-EP (Human Connectome Project for Early Psychosis), a multisite study of 125 participants with early psychosis and 58 healthy participants with resting-state functional magnetic resonance imaging and clinical characterization. Psychomotor function was assessed using the 9-hole pegboard task, a timed motor task that engages mechanical and psychomotor components of action, and tasks assessing processing speed and task switching. We used multivariate pattern analysis of whole-connectome data to identify brain correlates of psychomotor function. RESULTS We identified discrete brain circuits driving the cognitive and motor components of psychomotor function. In our combined sample of participants with psychosis (n = 89) and healthy control participants (n = 52), the strongest correlates of psychomotor function (pegboard performance) (p < .005) were between a midline cerebellar region and left frontal region and presupplementary motor area. Psychomotor function was correlated with both cerebellar-frontal connectivity (r = 0.33) and cerebellar-presupplementary motor area connectivity (r = 0.27). However, the cognitive component of psychomotor performance (task switching) was correlated only with cerebellar-frontal connectivity (r = 0.19), whereas the motor component (processing speed) was correlated only with cerebellar-presupplementary motor area connectivity (r = 0.15), suggesting distinct circuits driving unique subprocesses of psychomotor function. CONCLUSIONS We identified cerebellar-cortical circuits that drive distinct subprocesses of psychomotor function. Future studies should probe relationships between cerebellar connectivity and psychomotor performance using neuromodulation.
Collapse
Affiliation(s)
- Alexandra B Moussa-Tooks
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee; Department of Psychological and Brain Sciences and Program in Neuroscience, Indiana University Bloomington, Bloomington, Indiana
| | - Adam Beermann
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | | | - Michael Coleman
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts; Department of Psychiatry, Brigham & Women's Hospital, Boston, Massachusetts
| | - Sylvain Bouix
- Department of Software Engineering and Information Technology, École de technologie supérieure, Montréal, Québec, Canada
| | - Daphne Holt
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts; Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts
| | - Kathryn E Lewandowski
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts; McLean Hospital, Belmont, Massachusetts
| | - Dost Öngür
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts; McLean Hospital, Belmont, Massachusetts
| | - Alan Breier
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, Indiana
| | - Martha E Shenton
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts; Department of Psychiatry, Brigham & Women's Hospital, Boston, Massachusetts; Department of Radiology, Harvard Medical School and Brigham & Women's Hospital, Boston, Massachusetts
| | - Stephan Heckers
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Sebastian Walther
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Roscoe O Brady
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, Massachusetts; Department of Psychiatry, Harvard Medical School, Boston, Massachusetts; McLean Hospital, Belmont, Massachusetts
| | - Heather Burrell Ward
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee.
| |
Collapse
|
2
|
Kyrou A, Grünert E, Wüthrich F, Nadesalingam N, Chapellier V, Nuoffer MG, Pavlidou A, Lefebvre S, Walther S. Test-retest reliability of resting-state cerebral blood flow quantification using pulsed Arterial Spin Labeling (PASL) over 3 weeks vs 8 weeks in healthy controls. Psychiatry Res Neuroimaging 2024; 341:111823. [PMID: 38735229 DOI: 10.1016/j.pscychresns.2024.111823] [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: 05/04/2023] [Revised: 04/25/2024] [Accepted: 05/01/2024] [Indexed: 05/14/2024]
Abstract
Arterial Spin Labeling is a valuable functional imaging tool for both clinical and research purposes. However, little is known about the test-retest reliability of cerebral blood flow measurements over longer periods. In this study, we investigated the reliability of pulsed Arterial Spin Labeling in assessing cerebral blood flow over a 3 (n = 28) vs 8 (n = 19) weeks interscan interval in 47 healthy participants. As a measure of cerebral blood flow reliability, we calculated voxel-wise, whole-brain, and regions of interest intraclass correlation coefficients. The whole-brain mean resting-state cerebral blood flow showed good to excellent reliability over time for both periods (intraclass correlation coefficients = 0.85 for the 3-week delay, intraclass correlation coefficients = 0.53 for the 8-week delay). However, the voxel-wise and regions of interest intraclass correlation coefficients fluctuated at 8-week compared to the 3-week interval, especially within cortical areas. These results confirmed previous findings that Arterial Spin Labeling could be used as a reliable method to assess brain perfusion. However, as the reliability seemed to decrease over time, caution is warranted when performing correlations with other variables, especially in clinical populations.
Collapse
Affiliation(s)
- Alexandra Kyrou
- University Hospital of Psychiatry and Psychotherapy Bern, Translational Research Center, University of Bern, Switzerland; Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Bern, Switzerland
| | - Elina Grünert
- University Hospital of Psychiatry and Psychotherapy Bern, Translational Research Center, University of Bern, Switzerland; Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Bern, Switzerland
| | - Florian Wüthrich
- University Hospital of Psychiatry and Psychotherapy Bern, Translational Research Center, University of Bern, Switzerland; Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Bern, Switzerland
| | - Niluja Nadesalingam
- University Hospital of Psychiatry and Psychotherapy Bern, Translational Research Center, University of Bern, Switzerland; Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Bern, Switzerland
| | - Victoria Chapellier
- University Hospital of Psychiatry and Psychotherapy Bern, Translational Research Center, University of Bern, Switzerland; Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Bern, Switzerland
| | - Melanie G Nuoffer
- University Hospital of Psychiatry and Psychotherapy Bern, Translational Research Center, University of Bern, Switzerland; Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Bern, Switzerland; Graduate School for Health Sciences, University of Bern, Bern, Switzerland
| | - Anastasia Pavlidou
- University Hospital of Psychiatry and Psychotherapy Bern, Translational Research Center, University of Bern, Switzerland; Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Bern, Switzerland
| | - Stephanie Lefebvre
- University Hospital of Psychiatry and Psychotherapy Bern, Translational Research Center, University of Bern, Switzerland; Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Bern, Switzerland.
| | - Sebastian Walther
- University Hospital of Psychiatry and Psychotherapy Bern, Translational Research Center, University of Bern, Switzerland; Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Bern, Switzerland
| |
Collapse
|