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. 2021 Dec 20:111:110137.
doi: 10.1016/j.pnpbp.2020.110137. Epub 2020 Oct 11.

Relationship between neurological and cerebellar soft signs, and implicit motor learning in schizophrenia and bipolar disorder

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Relationship between neurological and cerebellar soft signs, and implicit motor learning in schizophrenia and bipolar disorder

Adrian Andrzej Chrobak et al. Prog Neuropsychopharmacol Biol Psychiatry. .

Abstract

Background: Schizophrenia (SZ) and bipolar disorder (BD) patients share deficits in motor functions in the form of neurological (NSS) and cerebellar soft signs (CSS), and implicit motor learning disturbances. Here, we use cluster analysis method to assess (1) the relationship between those abnormalities in SZ and BD and (2) the differences between those groups.

Methods: 33 SZ patients, 33 BD patients as well as 31 healthy controls (HC) took part in the study. We assessed CSS with the International Cooperative Ataxia Rating Scale (ICARS) and NSS with the Neurological Evaluation Scale (NES). Implicit motor learning was evaluated with the Serial Reaction Time Task (SRTT). Participants were divided into clusters (Ward's method) based on the mean response time and mean error rate in SRTT. The difference in ICARS and NES scores, and SRTT variables between clusters were evaluated. We have measured associations between SRTT parameters and both ICARS and NES total scores and subscores.

Results: Cluster analysis based on the SRTT parameters allowed to extract three clusters. Those were characterized by the increasing disruption of motor functioning (psychomotor retardation, the severity of NSS and CSS) regardless of the diagnosis. Cluster 1 covered almost all of HC and was characterized by faster reaction times and small number of errors. BD and SZ patients represented in cluster 1, although fully functional in performing the SRTT, showed higher rates of NSS and CSS. Patients with BD and SZ were set apart in clusters 2 and 3 in a similar proportion. Cluster 2 presented significantly slower reaction times but with the comparable number of errors to cluster 1. Cluster 3 consisted of participants with normal or decreased reaction time and significantly increased number of errors. None of the clusters were predominantly composed of the patients representing one psychiatric diagnosis.

Conclusions: To our best knowledge, we are presenting the first data indicating the relationship between implicit motor learning and NSS and CSS in SZ and BD patients' groups. Lack of clusters predominantly represented by patients with the diagnosis of SZ or BD may refer to the model of schizophrenia-bipolar disorder boundary, pointing out the similarities between those two disorders.

Keywords: Affective disorders; Cerebellum; Cognitive impairment; Motor learning; Schizophrenia.

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