Neurological soft signs and grey matter abnormalities in individuals with ultra-high risk for psychosis
Author(s)
Kong, L
Cui, H
Zhang, T
Wang, Y
Huang, J
Zhu, Y
Tang, Y
Herold, CJ
Schröder, J
Cheung, EFC
Chan, RCK
Wang, J
Griffith University Author(s)
Year published
2019
Metadata
Show full item recordAbstract
Neurological soft signs (NSSs), conventionally defined as subtle neurological abnormalities, are frequently found in individuals with schizophrenia. Many neuroimaging studies have also reported that NSSs are associated with grey matter changes in patients with schizophrenia at different stages of the illness. However, these findings may be confounded by the effect of antipsychotic medications, chronicity, and duration of untreated psychosis. Examining NSSs in individuals with ultra-high risk (UHR) for psychosis may help to identify the neuroanatomical substrates of NSSs related to the illness itself and to avoid these potential ...
View more >Neurological soft signs (NSSs), conventionally defined as subtle neurological abnormalities, are frequently found in individuals with schizophrenia. Many neuroimaging studies have also reported that NSSs are associated with grey matter changes in patients with schizophrenia at different stages of the illness. However, these findings may be confounded by the effect of antipsychotic medications, chronicity, and duration of untreated psychosis. Examining NSSs in individuals with ultra-high risk (UHR) for psychosis may help to identify the neuroanatomical substrates of NSSs related to the illness itself and to avoid these potential confounding effects. A sample of 21 individuals with UHR were included in the present study. NSSs were rated using the abridged version of the Cambridge Neurological Inventory. Grey matter volume was assessed using optimized voxel-based morphometry on images acquired by a high-resolution 3-T magnetic resonance imaging scanner. We found that higher NSS scores in individuals with UHR were associated with decreased grey matter volume at the superior and medial frontal cortex, the rectal cortex, the pre- and post-central cortex, the insula, the caudate, and the cerebellum. Our results suggest that these brain structural characteristics may represent the neuroanatomical substrate of NSSs in individuals with UHR. These findings contribute to the understanding of the intrinsic features of psychosis associated with NSSs and may provide insights into pre-schizophrenia pathophysiology.
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View more >Neurological soft signs (NSSs), conventionally defined as subtle neurological abnormalities, are frequently found in individuals with schizophrenia. Many neuroimaging studies have also reported that NSSs are associated with grey matter changes in patients with schizophrenia at different stages of the illness. However, these findings may be confounded by the effect of antipsychotic medications, chronicity, and duration of untreated psychosis. Examining NSSs in individuals with ultra-high risk (UHR) for psychosis may help to identify the neuroanatomical substrates of NSSs related to the illness itself and to avoid these potential confounding effects. A sample of 21 individuals with UHR were included in the present study. NSSs were rated using the abridged version of the Cambridge Neurological Inventory. Grey matter volume was assessed using optimized voxel-based morphometry on images acquired by a high-resolution 3-T magnetic resonance imaging scanner. We found that higher NSS scores in individuals with UHR were associated with decreased grey matter volume at the superior and medial frontal cortex, the rectal cortex, the pre- and post-central cortex, the insula, the caudate, and the cerebellum. Our results suggest that these brain structural characteristics may represent the neuroanatomical substrate of NSSs in individuals with UHR. These findings contribute to the understanding of the intrinsic features of psychosis associated with NSSs and may provide insights into pre-schizophrenia pathophysiology.
View less >
Journal Title
PsyCh Journal
Volume
8
Issue
2
Subject
Psychology
Cognitive and computational psychology
grey matter volume
magnetic resonance imaging
neurological soft signs
ultra-high risk for psychosis
voxel-based morphometry