On the relevance of the alpha frequency oscillation’s small-world network architecture for cognitive flexibility

Abstract

Cognitive flexibility is a major requirement for successful behavior. nNeural oscillations in the alpha frequency band were repeatedly associated with cognitive flexibility in task-switching paradigms. Alpha frequencies are modulated by working memory load and are used to process information during task switching, however we do not know how this oscillatory network communication is modulated. In order to understand the mechanisms that drive cognitive flexibility, ERPs, oscillatory power and how the communication within these networks is organized are of importance. The EEG data show that during phases reflecting preparatory processes to pre-activate task sets, alpha oscillatory power but not the small world properties of the alpha network architecture was modulated. During the switching only the N2 ERP component showed clear modulations. After the response, alpha oscillatory power reinstates and therefore seems to be important to deactivate or maintain the previous task set. For these reactive control processes the network architecture in terms of small-world properties is modulated. Effects of memory load on small-world aspects were seen in repetition trials, where small-world properties were higher when memory processes were relevant. These results suggest that the alpha oscillatory network becomes more small-world-like when reactive control processes during task switching are less complex.

Characterization of Visuomotor/Imaginary Movements in EEG: An Information Theory and Complex Network Approach

“…It has been found that alpha frequency oscillations posses an important role in inhibitory control actions managing access of data of a cognition procedure and working memory [75][76][77]. Our findings show that several nodes within the gamma 1 band have an overall higher amount of closeness centrality during the imagined task in comparison to realized tasks.…”

When repetitive mental sets increase cognitive flexibility in adolescent obsessive–compulsive disorder

“…This suggests that OCD patients, in contrast to controls, differentiate between the processing of repetitive (BI) and nonrepetitive (BASE) information. Well established findings suggest that the P1 reflects inhibitory, perceptual categorization processes needed to filter out relevant stimulus features in task‐relevant networks and to block information processing in potentially competing task‐irrelevant networks (Klimesch, ; Wolff, Zink, Stock, & Beste, ). The P1 reflects mechanisms regulating access to a knowledge system in which also previous task sets are stored (Klimesch, ).…”

Connecting EEG signal decomposition and response selection processes using the theory of event coding framework

“…We used the Watts and Strogatz method to study small‐world networks (Watts & Strogatz, ). As done in previous studies, this method was applied to each single subject (Beste et al, ; Wolff, Zink, et al, ; Zink et al, ): Using this method, one starts from a one‐dimensional network, where each node in the network (in the current study, the EEG electrode) is only connected to its k nearest neighbors on either side, representing a “regular” network with randomness = 0, a ring lattice with N nodes of mean degree 2 k is created. Next, more connections (“edges”) are randomly chosen to another random node with increasing randomness ( > 0 ) .…”