First-episode psychosis is characterized by failure of deactivation but not by hypo- or hyperfrontality.
ABSTRACT It is not known whether first-episode psychosis is characterized by the same prefrontal cortex functional imaging abnormalities as chronic schizophrenia.
Thirty patients with a first episode of non-affective functional psychosis and 28 healthy controls underwent functional magnetic resonance imaging (fMRI) during performance of the n-back working memory task. Voxel-based analyses of brain activations and deactivations were carried out and compared between groups. The connectivity of regions of significant difference between the patients and controls was also examined.
The first-episode patients did not show significant prefrontal hypo- or hyperactivation compared to controls. However, they showed failure of deactivation in the medial frontal cortex. This area showed high levels of connectivity with the posterior cingulate gyrus/precuneus and parts of the parietal cortex bilaterally. Failure of deactivation was significantly greater in first-episode patients who had or went on to acquire a DSM-IV diagnosis of schizophrenia than in those who did not, and in those who met RDC criteria for schizophrenia compared to those who did not.
First-episode psychosis is not characterized by hypo- or hyperfrontality but instead by a failure of deactivation in the medial frontal cortex. The location and connectivity of this area suggest that it is part of the default mode network. The failure of deactivation seems to be particularly marked in first-episode patients who have, or progress to, schizophrenia.
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ABSTRACT: Computational modeling of functional brain networks in fMRI data has advanced the understanding of higher cognitive function. It is hypothesized that functional networks mediating higher cognitive processes are disrupted in people with schizophrenia. In this article, we review studies that applied measures of functional and effective connectivity to fMRI data during cognitive tasks, in particular working memory fMRI studies. We provide a conceptual summary of the main findings in fMRI data and their relationship with neurotransmitter systems, which are known to be altered in individuals with schizophrenia. We consider possible developments in computational neuropsychiatry, which are likely to further our understanding of how key functional networks are altered in schizophrenia.Frontiers in Psychiatry 01/2014; 5:30.
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ABSTRACT: Working memory (WM) deficit is an important component of impaired cognition in schizophrenia. However, between-studies inconsistencies as to the specific functional substrate imply that inter-individual variability (IIV) in the WM performance is associated with IIV in brain activity in schizophrenia. To examine the neural substrate of this WM IIV, we studied whether the neural mechanisms that underlie individual differences in WM capacity are the same in schizophrenia patients and healthy people. We correlated the IIV of the task-evoked brain activity and task performance during an n-back WM task with the IIV of the moment-to-moment variability in intrinsic resting-state activity, as measured by the amplitude of low-frequency fluctuations (ALFFs) and further compared this relationship between 17 patients with first-episode schizophrenia (FES) and 18 healthy controls. Between-group comparisons of the correlation patterns indicated aberrant ALFF-WM activation correlations and ALFF-WM performance correlations in the FES patients, but no significant changes were detected in any single measurement of these three characteristics. Specifically, we found increased positive ALFF-WM activation correlations in the bilateral lateral prefrontal cortices, posterior parietal cortices and fusiform gyri in the FES patients. We also observed significant increases in positive ALFF-WM performance correlations in the bilateral ventromedial prefrontal cortices in the FES patients. This hyper-coupling between the ALFF and fMRI measures during a WM task may indicate that it was difficult for the patients to detach themselves from one state to transition to another and suggests that the inefficient cortical function in schizophrenia stems from the intrinsic functional architecture of the brain.Schizophrenia Research 08/2014; · 4.59 Impact Factor
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ABSTRACT: Chronic stress has been widely reported to have deleterious impact in multiple biological systems. Specifically, structural and functional remodelling of several brain regions following prolonged stress exposure have been described; importantly, some of these changes are eventually reversible. Recently, we showed the impact of stress on resting state networks (RSNs), but nothing is known about the plasticity of RSNs after recovery from stress. Herein, we examined the “plasticity” of RSNs, both at functional and structural levels, by comparing the same individuals before and after recovery from the exposure to chronic stress; results were also contrasted with a control group. Here we show that the stressed individuals after recovery displayed a decreased resting functional connectivity in the default mode network (DMN), ventral attention network (VAN) and sensorimotor network (SMN) when compared to themselves immediately after stress; however, this functional plastic recovery was only partial as when compared with the control group, as there were still areas of increased connectivity in dorsal attention network (DAN), SMN and primary visual network (VN) in participants recovered from stress. Data also shows that participants after recovery from stress displayed increased deactivations in DMN, SMN and auditory network (AN), to levels similar to those of controls, showing a normalization of the deactivation pattern in RSNs after recovery from stress. In contrast, structural changes (volumetry) of the brain areas involving these networks are absent after the recovery period. These results reveal plastic phenomena in specific RSNs and a functional remodeling of the activation-deactivation pattern following recovery from chronic-stress, which is not accompanied by significant structural plasticity.Frontiers in Human Neuroscience 01/2013; 7. · 2.91 Impact Factor