Open AccessDynamic causal modeling of load‐dependent modulation of effective connectivity within the verbal working memory network
Author(s) -
Dima Danai,
Jogia Jigar,
Frangou Sophia
Publication year - 2014
Publication title -
human brain mapping
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.005
H-Index - 191
eISSN - 1097-0193
pISSN - 1065-9471
DOI - 10.1002/hbm.22382
Subject(s) - working memory , functional magnetic resonance imaging , psychology , neuroimaging , anterior cingulate cortex , neuroscience , posterior cingulate , prefrontal cortex , dorsolateral prefrontal cortex , cognitive psychology , posterior parietal cortex , causal model , cognition , medicine , pathology
Neuroimaging studies have consistently shown that working memory (WM) tasks engage a distributed neural network that primarily includes the dorsolateral prefrontal cortex, the parietal cortex, and the anterior cingulate cortex. The current challenge is to provide a mechanistic account of the changes observed in regional activity. To achieve this, we characterized neuroplastic responses in effective connectivity between these regions at increasing WM loads using dynamic causal modeling of functional magnetic resonance imaging data obtained from healthy individuals during a verbal n ‐back task. Our data demonstrate that increasing memory load was associated with (a) right‐hemisphere dominance, (b) increasing forward (i.e., posterior to anterior) effective connectivity within the WM network, and (c) reduction in individual variability in WM network architecture resulting in the right‐hemisphere forward model reaching an exceedance probability of 99% in the most demanding condition. Our results provide direct empirical support that task difficulty, in our case WM load, is a significant moderator of short‐term plasticity, complementing existing theories of task‐related reduction in variability in neural networks. Hum Brain Mapp 35:3025–3035, 2014 . © 2013 Wiley Periodicals, Inc.