Functional Network Architectures are Distorted During Memory Formation and Consolidation in Schizophrenia

Emmanuel Meram, Shahira Baajour, Asadur Chowdury, Jeffrey Stanley, Vaibhav Diwadkar, Department of Psychiatry and Behavioral Neuroscience, Wayne State University School of Medicine, 540 E Canfield St, Detroit, MI 48201

Schizophrenia (SCZ) is a highly debilitating neuropsychiatric disorder characterized by cognitive impairments particularly related to associative learning and memory (Diwadkar et al., 2008). Recent studies have characterized dysfunctional modulation of brain regions during associative learning, presenting evidence for the primacy of dysfunctional frontal-hippocampal lobe interactions (Woodcock et al., 2016). However, the complex, integrative network of functional brain connections offers multiplex interactions that can be summarized using graph theoretic analyses. Our primary focus was to use graph theoretic approaches, such as betweenness centrality (BC), to characterize network disorganization in schizophrenia induced during associative learning. BC is a metric that estimates the number of shortest functional paths that traverse through a node (brain region), making it a useful tool to investigate the connectivity of bridges between nodes (Heuvel et al., 2010).  We modeled and applied BC to fMRI time series data collected while 59 subjects (32 SCZ) participated in an established associative learning and memory task (Wadehra et al., 2013). The task oscillates between periods of memory formation, wherein objects were presented in associated locations for naming, and retrieval, wherein recall cues were presented for association. A period of consolidation (rehearsal) follows formation. In SCZ, conditions of memory formation and consolidation induced significantly disorganized network structure. This was characterized by differential patterns of “hubness” (differences in BC) between groups. However, nodes with differences (p<0.05) did not always evince the highest levels of BC within each group. We hypothesize that differences in BC can be induced on nodes that support task-implementation without being hubs in the overall network. Task-induced effects on the fMRI signal are not entirely predictable, and we suggest that overt- and covert task induced effects are essential for understanding the limits of network dysfunction in conditions like schizophrenia.

Additional Abstract Information

Presenter: Emmanuel Meram

Institution: Wayne State University

Type: Poster

Subject: Psychology

Status: Approved

Time and Location

Session: Poster 10
Date/Time: Wed 1:30pm-2:30pm
Session Number: 6656