Neurological signs and morphological cerebral changes in schizophrenia: An analysis of NSS subscales in patients with first episode psychosis.
ABSTRACT Neurological soft signs (NSS) comprise a broad range of minor motor and sensory deficits which are frequently found in schizophrenia. However, the cerebral changes underlying NSS are only partly understood. We therefore investigated the cerebral correlates of NSS by using magnetic resonance imaging (MRI) in 102 patients with first episode schizophrenia. NSS were assessed after remission of acute psychotic symptoms using the Heidelberg scale (HS), which consists of five NSS subscales ("motor coordination", "complex motor tasks", "orientation", "integrative functions", and "hard signs"). Correlations between NSS scores and cerebral changes were established by optimized voxel-based morphometry. NSS total scores were significantly associated with reduced gray matter densities in the precentral and postcentral gyri, the inferior parietal lobule and the inferior occipital gyrus. Both of the NSS subscales "motor coordination" and "complex motor tasks", referred to motor strip changes but showed differential correlations with parietal, insular, cerebellar or frontal sites, respectively. The NSS subscales "orientation" and "integrative functions" were associated with left frontal, parietal, and occipital changes or bihemispheric frontal changes, respectively. The NSS subscale "hard signs" was associated with deficits in the right cerebellum and right parastriate cortex. Repeated analyses for white matter changes revealed similar results. These findings confirm the associations between NSS and cerebral changes in areas important for motor and sensory functioning. This variety of cerebral sites corresponds to the heterogeneity of NSS and are consistent with the hypothesis that NSS reflect both a rather generalized cerebral dysfunction and localized deficits specific for particular signs.
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ABSTRACT: Previous studies suggested that the topological properties of brain anatomical networks may be aberrant in schizophrenia (SCZ), and most of them focused on the chronic and antipsychotic-medicated SCZ patients which may introduce various confounding factors due to antipsychotic medication and duration of illness. To avoid those potential confounders, a desirable approach is to select medication-naïve, first-episode schizophrenia (FE-SCZ) patients. In this study, we acquired diffusion tensor imaging datasets from 30 FE-SCZ patients and 34 age- and gender-matched healthy controls. Taking a distinct gray matter region as a node, inter-regional connectivity as edge and the corresponding streamline counts as edge weight, we constructed whole-brain anatomical networks for both groups, calculated their topological parameters using graph theory, and compared their between-group differences using nonparametric permutation tests. In addition, network-based statistic method was utilized to identify inter-regional connections which were impaired in the FE-SCZ patients. We detected only significantly decreased inter-regional connections in the FE-SCZ patients compared to the controls. These connections were primarily located in the frontal, parietal, occipital, and subcortical regions. Although small-worldness was conserved in the FE-SCZ patients, we found that the network strength and global efficiency as well as the degree were significantly decreased, and shortest path length was significantly increased in the FE-SCZ patients compared to the controls. Most of the regions that showed significantly decreased nodal parameters belonged to the top-down control, sensorimotor, basal ganglia, and limbic-visual system systems. Correlation analysis indicated that the nodal efficiency in the sensorimotor system was negatively correlated with the severity of psychosis symptoms in the FE-SCZ patients. Our results suggest that the network organization is changed in the early stages of the SCZ disease process. Our findings provide useful information for further understanding the brain white matter dysconnectivity of schizophrenia.Brain Structure and Function 01/2014; 220(2). DOI:10.1007/s00429-014-0706-z · 4.57 Impact Factor
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ABSTRACT: Resilience research has usually focused on identifying protective factors associated with specific stress conditions (e.g., war, trauma) or psychopathologies (e.g., post-traumatic stress disorder [PTSD]). Implicit in this research is the concept that resilience is a global construct, invariant to the unfavorable circumstances or the psychopathologies that may develop (i.e., the mechanisms underlying the resilience of an individual in all cases are expected to be similar). Here we contribute to the understanding of resilience-and its counterpart, vulnerability-by employing an approach that makes use of this invariant quality. We outline two main characteristics that we would expect from indicators of a vulnerable state: that they should appear across disorders regardless of specific circumstances, and that they should appear much before the disorder is evident. Next, we identify two sets of factors that exhibit this pattern of association with psychopathological states. The first was a set of "low-level" sensory, motor and regulatory irregularities that have been reported across the clinical literature; we suggest that these can serve as behavioral indicators of a vulnerable state. The second was the set of aberrations in network metrics that have been reported in the field of systems neuroscience; we suggest that these can serve as network indicators of a vulnerable state. Finally, we explore how behavioral indicators may be related to network indicators and discuss the clinical and research-related implications of our work.Frontiers in Human Neuroscience 11/2011; 6:10. DOI:10.3389/fnhum.2012.00010 · 2.90 Impact Factor