Altered Cortico-Striatal Connectivity in Offspring of Schizophrenia Patients Relative to Offspring of Bipolar Patients and Controls

Schizophrenia (SZ) and bipolar disorder (BD) share clinical features, genetic risk factors and neuroimaging abnormalities. There is evidence of disrupted connectivity in resting state networks in patients with SZ and BD and their unaffected relatives. Resting state networks are known to undergo reorganization during youth coinciding with the period of increased incidence for both disorders. We therefore focused on characterizing resting state network connectivity in youth at familial risk for SZ or BD to identify alterations arising during this period. We measured resting-state functional connectivity in a sample of 106 youth, aged 7-19 years, comprising offspring of patients with SZ (N = 27), offspring of patients with BD (N = 39) and offspring of community control parents (N = 40). We used Independent Component Analysis to assess functional connectivity within the default mode, executive control, salience and basal ganglia networks and define their relationship to grey matter volume, clinical and cognitive measures. There was no difference in connectivity within any of the networks examined between offspring of patients with BD and offspring of community controls. In contrast, offspring of patients with SZ showed reduced connectivity within the left basal ganglia network compared to control offspring, and they showed a positive correlation between connectivity in this network and grey matter volume in the left caudate. Our findings suggest that dysconnectivity in the basal ganglia network is a robust correlate of familial risk for SZ and can be detected during childhood and adolescence

Functional brain networks before the onset of psychosis : a prospective fMRI study with graph theoretical analysis

Individuals with an at-risk mental state (ARMS) have a risk of developing a psychotic disorder significantly greater than the general population. However, it is not currently possible to predict which ARMS individuals will develop psychosis from clinical assessment alone. Comparison of ARMS subjects who do, and do not, develop psychosis can reveal which factors are critical for the onset of illness. In the present study, 37 patients with an ARMS were followed clinically at least 24 months subsequent to initial referral. Functional MRI data were collected at the beginning of the follow-up period during performance of an executive task known to recruit frontal lobe networks and to be impaired in psychosis. Graph theoretical analysis was used to compare the organization of a functional brain network in ARMS patients who developed a psychotic disorder following the scan (ARMS-T) to those who did not become ill during the same follow-up period (ARMS-NT) and aged-matched controls. The global properties of each group's representative network were studied (density, efficiency, global average path length) as well as regionally-specific contributions of network nodes to the organization of the system (degree, farness-centrality, betweenness-centrality). We focused our analysis on the dorsal anterior cingulate cortex (ACC), a region known to support executive function that is structurally and functionally impaired in ARMS patients. In the absence of between-group differences in global network organization, we report a significant reduction in the topological centrality of the ACC in the ARMS-T group relative to both ARMS-NT and controls. These results provide evidence that abnormalities in the functional organization of the brain predate the onset of psychosis, and suggest that loss of ACC topological centrality is a potential biomarker for transition to psychosis

Emerging Temporal Lobe Dysfunction in People at Clinical High Risk for Psychosis

Clinical high-risk (CHR) individuals have been increasingly utilized to investigate the prodromal phases of psychosis and progression to illness. Research has identified medial and lateral temporal lobe abnormalities in CHR individuals. Dysfunction in the medial temporal lobe, particularly the hippocampus, is linked to dysregulation of glutamate and dopamine via a hippocampal–striatal–midbrain network that may lead to aberrant signaling of salience underpinning the formation of delusions. Similarly, lateral temporal dysfunction may be linked to the disorganized speech and language impairments observed in the CHR stage. Here, we summarize the significance of these neurobiological findings in terms of emergent psychotic symptoms and conversion to psychosis in CHR populations. We propose key questions for future work with the aim to identify the neural mechanisms that underlie the development of psychosis

기능적 뇌네트워크 간 연결성의 차이를 통한 임상적 고위험군에서 정신증 발병 예측

학위논문 (박사)-- 서울대학교 대학원 자연과학대학 뇌인지과학과, 2017. 8. 권준수.Among individuals at clinical high risk for psychosis (CHR) who show prodromal symptoms of psychosis, some progress to full-blown psychosis. There have been attempts to find markers predicting the onset of psychosis, and brain structures related to onset of psychosis have been reported. However, no studies have examined wide-range interactions at the functional network level that can adequately account for the schizophrenia, a dysconnectivity disorder. To discover predicting markers for psychosis, I conducted a longitudinal study for a follow-up period of a minimum of 12 months. At the baseline, the resting-state functional magnetic resonance imaging was acquired from individuals at CHR (N = 69), individuals with first-episode psychosis (FEP) (N = 35), and healthy controls (HC) (N = 70). Eight psychosis-related functional networks were extracted, and interactions between paired functional networks were measured, resulting in estimations of 28 possible combinations. After the group comparison, correlation analyses between the altered network interactions and symptom severity were conducted to reveal clinical associations. Seven of 69 (10%) individuals at CHR proceeded to full-blown psychosis (CHR-C). There were no significant difference in age, gender, and handedness among FEP, CHR-C, CHR-NC, and HC. Of the 28 combinations, there were significant group differences in four functional network connectivity. The FEP group showed the most severe degree of decrement in functional network connectivity compared to HC. Among all four significantly different functional network interactions, CHR-C showed no significant difference from FEP, while the nonconverters (CHR-NC) had significantly higher functional network connectivity compared to FEP. Among the altered combinations, the interaction between the anterior default mode network and salience network of the FEP group was associated with the overall negative psychotic symptom severity. This is the first study to suggest that large network interactions can serve as potential markers of the psychosis onset by showing that the CHR-C is similar to FEP, while CHR-NC is comparable to HC. The degree of functional network connectivity in CHR may have prognostic implications regarding the risk of conversion to full-blown psychosis.Chapter 1. Introduction 1 Chapter 2. Methods 12 Chapter 3. Results 20 Chapter 4. Discussion 22 Chapter 5. Conclusion 31 References 32 Tables 44 Figures 57 Abstract in Korean 67Docto

Psychosis risk is associated with decreased white matter integrity in corticostriatal tracts

Psychosis is associated with increased striatal dopamine and it is thought that altered connectivity between the striatum and the cortex could contribute to psychosis. In particular, there is theory and research linking psychosis to altered connectivity between the striatum and several cortical networks, especially the limbic, default mode, and frontoparietal networks. However, it is still unclear whether psychosis risk is associated with altered white matter connectivity between the striatum with any cortical region. Further, no previous study has directly examined whether psychosis risk is associated with altered connectivity with specific cortical networks. In the current study, I examined integrity of white matter tracts in psychosis risk (n=18) and non-psychosis risk comparison participants (n=19). Tracts were identified using probabilistic tractography. I found that psychosis risk was associated with significantly decreased connectivity between the striatum and the limbic cortical network, especially in the right external capsule and with connections to the right prefrontal cortex. There was a trend for psychosis risk to also be associated with decreased striatal-default mode network connectivity. However, there were no significant group differences for striatal-frontoparietal network connectivity. Hence, the current research suggests that psychosis risk is associated with decreased white matter integrity in networks involved in processing emotional and personally relevant information.Includes bibliographical reference

Extrinsic and default mode networks in psychiatric conditions: Relationship to excitatory-inhibitory transmitter balance and early trauma.

Over the last three decades there has been an accumulation of Magnetic Resonance Imaging (MRI) studies reporting that aberrant functional networks may underlie cognitive deficits and other symptoms across a range of psychiatric diagnoses. The use of pharmacological MRI and H-1-Magnetic Resonance Spectroscopy (H-1-MRS) has allowed researchers to investigate how changes in network dynamics are related to perturbed excitatory and inhibitory neurotransmission in individuals with psychiatric conditions. More recently, changes in functional network dynamics and excitatory/inhibitory (E/I) neurotransmission have been linked to early childhood trauma, a major antecedents for psychiatric illness in adulthood. Here we review studies investigating whether perturbed network dynamics seen across psychiatric conditions are related to changes in E/I neurotransmission, and whether such changes could be linked to childhood trauma. Whilst there is currently a paucity of studies relating early traumatic experiences to altered E/I balance and network function, the research discussed here lead towards a plausible mechanistic hypothesis, linking early traumatic experiences to cognitive dysfunction and symptoms mediated by E/I neurotransmitter imbalances

Integrated metastate functional connectivity networks predict change in symptom severity in clinical high risk for psychosis

The ability to identify biomarkers of psychosis risk is essential in defining effective preventive measures to potentially circumvent the transition to psychosis. Using samples of people at clinical high risk for psychosis (CHR) and Healthy controls (HC) who were administered a task fMRI paradigm, we used a framework for labelling time windows of fMRI scans as ‘integrated’ FC networks to provide a granular representation of functional connectivity (FC). Periods of integration were defined using the ‘cartographic profile’ of time windows and k‐means clustering, and sub‐network discovery was carried out using Network Based Statistics (NBS). There were no network differences between CHR and HC groups. Within the CHR group, using integrated FC networks, we identified a sub‐network negatively associated with longitudinal changes in the severity of psychotic symptoms. This sub‐network comprised brain areas implicated in bottom‐up sensory processing and in integration with motor control, suggesting it may be related to the demands of the fMRI task. These data suggest that extracting integrated FC networks may be useful in the investigation of biomarkers of psychosis risk