Temporal progression in functional connectivity determines individual differences in working memory capacity
Working memory (WM) plays a critical role in cognitive skills such as, learning, reasoning, and language comprehension. WM capacity is widely used as a predictor of academic performance and many other cognitive skills. Yet, how the human brain coordinates this complex skill through its functional networks and also whether individual's WM limitations are due to contrasts in regional activation or cross-regional interconnections, remain controversial. We hypothesized that, individual differences in behavioral WM capacity could be explained by temporal dynamics in functional coupling, and the information flow within the connectome of the WM network. We recorded electrical brain activity as participants performed a visual WM task with varying degrees of cognitive load. Functional connectivity analyses on the EEG recordings were performed to identify prominent hubs and the temporal segmentation of inter-regional activities as WM processing unfolds over time. We found that neural communication during memory processing occurs predominately through short pulses of alpha-band (8-13 Hz) phase coupling that propagate in a temporally sequential manner with feedforward (bottom-up) and feedback (top-down) communication within a set of frontoparietal and fronto-temporal regions of brain. We also observed that the degree of phase coupling within fronto-parietal/temporal pathways strongly predicts working memory capacity. Additionally, this functional connectivity could distinguish individual with low vs. high WM capacity. These results underscore the importance of long-range neural network communication (phase synchrony) in WM skills and additionally the significance of temporal dynamics in functional connectivity and in particular phase synchrony.
Proceedings of the International Joint Conference on Neural Networks
Bashivan, P., Yeasin, M., & Bidelman, G. (2017). Temporal progression in functional connectivity determines individual differences in working memory capacity. Proceedings of the International Joint Conference on Neural Networks, 2017-May, 2943-2949. https://doi.org/10.1109/IJCNN.2017.7966220