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Is there a relationship between resting state connectivity within large-scale functional networks and implicit motor learning impairments in schizophrenia and bipolar disorder?
 
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1
Department of Adult Psychiatry, Jagiellonian University Medical College, Kraków, Poland
 
2
Department of Adult, Child and Adolescent Psychiatry, University Hospital in Cracow, Kraków, Poland
 
3
J. Dietl Specialist Hospital, Kraków, Poland
 
4
Doctoral School in the Social Sciences, Jagiellonian University, Kraków, Poland Centre for Brain Research, Jagiellonian University, Kraków, Poland
 
5
Department of Cognitive Neuroscience and Neuroergonomics, Institute of Applied Psychology, Jagiellonian University, Kraków, Poland
 
6
Jagiellonian University Medical College, Chair of Radiology, Kraków, Poland
 
7
Faculty of Psychology, SWPS University of Social Sciences and Humanities, Katowice, Poland
 
8
Department of Affective Disorders, Jagiellonian University Medical College, Kraków, Poland
 
 
Submission date: 2024-08-10
 
 
Acceptance date: 2024-08-19
 
 
Online publication date: 2024-08-28
 
 
Publication date: 2024-08-28
 
 
Corresponding author
Marcin Siwek   

Department of Affective Disorders, Jagiellonian University Medical College, Kraków, Poland
 
 
 
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ABSTRACT
Objectives:
The aim of this exploratory study is to evaluate whether implicit motor learning impairments observed in schizophrenia (SZ) and bipolar disorder (BD) are associated with the resting state functional connectivity (rs-FC) within large-scale functional networks.

Methods:
The study involved 30 BD patients, 30 SZ patients and 30 healthy controls (HC). Implicit motor learning was evaluated with the use of serial reaction time task (SRTT). Prior to the training patients underwent resting state functional magnetic resonance imaging (rsfMRI) examination. We have measured rs-FC within salience network (SAN), default mode network (DMN), frontoparietal network (FPN), sensorimotor network (SMN), limbic network (LN) and visual network (VIN) and their associations with implicit motor learning indices.

Results:
rs-FC within SAN, DMN, FPN, SMN, LN and VIN reveal no significant association with implicit motor learning indices. BD, SZ and HC groups did not differ in terms of rs-FC within abovementioned networks.

Conclusions:
We have shown that in the studied groups SRTT performance could not be predicted by rs-FC within the major large-scale functional networks, i.e., SMN, FPN, VIN, LN, SAN and DMN. The observation of the independence of implicit motor learning from the initial activity of these systems is important for proper understanding of neuronal underpinnings of this process and planning further neuroimaging research on this topic.

eISSN:2391-5854
ISSN:0033-2674
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