Abstract
Several non-invasive imaging methods have contributed to shed light on the brain mechanisms underlying working memory (WM). The aim of the present study was to depict the topology of the relevant EEG-derived brain networks associated to distinct operations of WM function elicited by the Sternberg Item Recognition Task (SIRT) such as encoding, storage, and retrieval in healthy, middle age (46 ± 5 years) adults. High density EEG recordings were performed in 17 participants whilst attending a visual SIRT. Neural correlates of WM were assessed by means of a combination of EEG signal processing methods (i.e., time-varying connectivity estimation and graph theory), in order to extract synthetic descriptors of the complex networks underlying the encoding, storage, and retrieval phases of WM construct. The group analysis revealed that the encoding phase exhibited a significantly higher small-world topology of EEG networks with respect to storage and retrieval in all EEG frequency oscillations, thus indicating that during the encoding of items the global network organization could “optimally” promote the information flow between WM sub-networks. We also found that the magnitude of such configuration could predict subject behavioral performance when memory load increases as indicated by the negative correlation between Reaction Time and the local efficiency values estimated during the encoding in the alpha band in both 4 and 6 digits conditions. At the local scale, the values of the degree index which measures the degree of in- and out- information flow between scalp areas were found to specifically distinguish the hubs within the relevant sub-networks associated to each of the three different WM phases, according to the different role of the sub-network of regions in the different WM phases. Our findings indicate that the use of EEG-derived connectivity measures and their related topological indices might offer a reliable and yet affordable approach to monitor WM components and thus theoretically support the clinical assessment of cognitive functions in presence of WM decline/impairment, as it occurs after stroke.
Highlights
Several non-invasive imaging methods have contributed to shed light on the brain mechanisms underlying working memory (WM)
All the participants showed a percentage of correct answers above 80% and reaction times (RTs) comprised between 250 and 700 ms for the 4 Sternberg Item Recognition Task (SIRT) conditions
The variability ranges observed for the two behavioral parameters are in agreement with literature and comparable with those reported in other studies (Sternberg, 1966; Cummins and Finnigan, 2007; Tuladhar et al, 2007)
Summary
Several non-invasive imaging methods have contributed to shed light on the brain mechanisms underlying working memory (WM). To fully understand brain functions, functional neuroimaging methods have been applied to investigate the dynamics within networks of brain areas that underlie specific cognitive processes (such as WM), and how a brain damage-induced disruption of neural circuits could account for behavioral impairments (Honey and Sporns, 2008; Cramer et al, 2011; Grefkes and Fink, 2011, 2014) In this regard, functional connectivity estimation was applied to track age-related changes in brain connectivity in a group of children and adolescents performing a modified version of the SIRT (van den Bosch et al, 2014). Task-related networks were identified for encoding (including left motor area, right prefrontal, parietal, and occipital cortex cerebellum) and recognition (including anterior and posterior cingulate cortex, right motor area, cerebellum, left parietal, and prefrontal cortex) phases and their load-induced modulation correlated with age (Woodward et al, 2013; van den Bosch et al., 2014)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
