Distinct neural patterns for various information in working memory: A brain connectivity study - Sadaf Sazesh; Ashkan Farrokhi; Vahid Shalchyan; Elizabeth L. Johnson; Mohammad Reza Daliri (PLoS ONE, 2025)
Working memory (WM) relies on brain networks including the prefrontal cortex (PFC) and medial temporal lobe (MTL) as key nodes. Graph theory analysis has recently played an important role in uncovering brain connectivity architectures due to its ability to characterize complex brain networks. Yet, it remains unclear whether the PFC and MTL exhibit distinct effective connectivity patterns during information processing in WM. We employed graph theoretical analysis to investigate connectivity patterns involved in processing of various types of information (i.e., identity, spatial and temporal) in WM and predict behavioral reaction times (RT). Here, we hypothesized that WM processes identity, spatial, and temporal information via frequency-specific and regionally organized brain network mechanism. We analyzed intracranial EEG data from eight surgical epilepsy patients completing a WM task for everyday ‘what’, ‘where’, and ‘when’ information. To measure the effective connectivity between PFC and MTL, we used the directed transfer function and assessed the outputs for multiple graph theoretical metrics (i.e., degree, strength, clustering coefficient, eigenvector centrality, and betweenness centrality). Our findings reveal that theta-band oscillations predominantly support spatial and temporal information processing, with the PFC and orbitofrontal cortex (OFC) playing pivotal roles in spatial and temporal sequencing, respectively. The MTL was central to spatial and spatial-temporal integration. Alpha band connectivity was fundamental for spatial-temporal decoding, whereas beta and high-gamma bands were significant in RT differentiation, particularly in identity and spatial conditions. Notably, the PFC demonstrated widespread engagement across various graph metrics, underscoring its dominance in coordinating WM tasks and modulating cognitive processes. Our findings contribute to the broader understanding of WM’s neural mechanisms and offer insights into the dynamic coordination of brain regions supporting cognitive tasks.