Network Profiles of the Dorsal Anterior Cingulate and Dorsal Prefrontal Cortex in Schizophrenia During Hippocampal-Based Associative Memory.

Schizophrenia is a disorder characterized by brain network dysfunction, particularly during behavioral tasks that depend on frontal and hippocampal mechanisms. Here, we investigated network profiles of the regions of the frontal cortex during memory encoding and retrieval, phases of processing essential to associative memory. Schizophrenia patients (n = 12) and healthy control (HC) subjects (n = 10) participated in an established object-location associative memory paradigm that drives frontal-hippocampal interactions. Network profiles were modeled of both the dorsal prefrontal (dPFC) and the dorsal anterior cingulate cortex (dACC) as seeds using psychophysiological interaction analyses, a robust framework for investigating seed-based connectivity in specific task contexts. The choice of seeds was motivated by previous evidence of involvement of these regions during associative memory. Differences between patients and controls were evaluated using second-level analyses of variance (ANOVA) with seed (dPFC vs. dACC), group (patients vs. controls), and memory process (encoding and retrieval) as factors. Patients showed a pattern of exaggerated modulation by each of the dACC and the dPFC during memory encoding and retrieval. Furthermore, group by memory process interactions were observed within regions of the hippocampus. In schizophrenia patients, relatively diminished modulation during encoding was associated with increased modulation during retrieval. These results suggest a pattern of complex dysfunctional network signatures of critical forebrain regions in schizophrenia. Evidence of dysfunctional frontal-medial temporal lobe network signatures in schizophrenia is consistent with the illness' characterization as a disconnection syndrome.

The 4th Schizophrenia International Research Society Conference, 5-9 April 2014, Florence, Italy: a summary of topics and trends.

The 4th Schizophrenia International Research Society Conference was held in Florence, Italy, April 5-9, 2014 and this year had as its emphasis, "Fostering Collaboration in Schizophrenia Research". Student travel awardees served as rapporteurs for each oral session, summarized the important contributions of each session and then each report was integrated into a final summary of data discussed at the entire conference by topic. It is hoped that by combining data from different presentations, patterns of interest will emerge and thus lead to new progress for the future. In addition, the following report provides an overview of the conference for those who were present, but could not participate in all sessions, and those who did not have the opportunity to attend, but who would be interested in an update on current investigations ongoing in the field of schizophrenia research.

Network dysfunction during associative learning in schizophrenia: Increased activation, but decreased connectivity: an fMRI study.

Schizophrenia (SCZ) is characterized by disordered activation and disordered connectivity, yet few fMRI studies have convergently investigated both. Here, we compared differences in activation and connectivity between SCZ and controls (HC). Twenty-two subjects (18≤age≤35yrs) participated in a paired-associative learning task, a behavioral domain particularly dependent on fronto-hippocampal connectivity and of relevance to the schizophrenia diathesis. Activation differences were assessed using standard approaches. Seed-based connectivity differences were compared using Psychophysiological Interaction (PPI) with a hippocampus-based seed. SCZ evinced significantly increased activation, but significantly decreased connectivity with the hippocampus across a cortical-striatal learning network. These results assess potentially complementary patterns of network dysfunction in schizophrenia: increased activation suggests inefficient responses relating to functional specialization; decreased connectivity suggests impaired integration of functional signals between regions. Inefficiency and dysconnection appear to collectively characterize functional deficits in schizophrenia.

Disordered corticolimbic interactions during affective processing in children and adolescents at risk for schizophrenia revealed by functional magnetic resonance imaging and dynamic causal modeling.

CONTEXT: Disordered functional architecture of brain networks may contribute to the well-documented increased risk for psychiatric disorders in offspring of patients with schizophrenia. OBJECTIVE: To investigate aberrant interactions between regions associated with affective processing in children and adolescent offspring of patients with schizophrenia (HR-SCZ group) and healthy control subjects using dynamic causal modeling of functional magnetic resonance imaging data. DESIGN: Subjects participated in a continuous affective processing task during which positive, negative, and neutral valenced faces were presented. Interactions between regions in the brain's face- and emotion-processing network were modeled using dynamic causal modeling. Multiple competing models were evaluated by a combinatorial approach and distinguished at the second level using Bayesian model selection before parameter inference. SETTING: Participants were recruited from the community. PARTICIPANTS: Twenty-four controls with no family history of psychosis (to the second degree) and 19 children and adolescent offspring of a parent with schizophrenia (age range, 8 to 20 years). RESULTS: Bayesian model selection revealed a winning model, the architecture of which revealed bidirectional frontolimbic connections that were modulated by valence. Analyses of parameter estimates revealed that HR-SCZ group members were characterized by (1) decreased driving inputs to the visual cortex; (2) decreased intrinsic coupling, most robustly between frontolimbic regions; and (3) increased modulatory inhibition by negative valence of frontolimbic connections (all P < .01, Bonferroni corrected). CONCLUSIONS: These results are the first demonstration of network analyses techniques for functional magnetic resonance imaging data in children and adolescents at risk for schizophrenia. Dysfunctional interactions within the emotional processing network provide evidence of latent vulnerabilities that may confer risk for disordered adolescent development and eventually the emergence of the manifest disorder.