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Visual working memory and workload components in ECoG during n-Back task

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Dynamics of visual working memory and workload in ECoG during n-Back task

Neuromatch Academy - Computational Neuroscience 2021 project for group Spherical Drakarys of pod Spherical Scorpions.


Abstract

Working memory is an important system for complex cognitive behavior, such as communication, reasoning, learning, and navigation. Investigating the brain activity in experiments with differing visual working memory (VWM) workloads could be a powerful tool in understanding mechanisms underlying the formation and retention of VWM.

Existing research has successfully correlated the changes in workload (or cognitive load) of tasks to “shifts” in the power of typical brain rhythms, like alpha, beta, and theta. However, the role of changes of power in the broadband spectrum (50-250 Hz) with changing workload have generally been overlooked. Yet, these frequencies — high gamma (50-125 Hz) and ripple (125-250 Hz) — are known to be correlated with large-scale local network activity and higher cognitive phenomena, for example, memory recall as observed in different structures like primary visual cortex, limbic and higher cortical areas. EEG data is susceptible to a lot of environmental noise and broadband frequencies diminishing across the skull may not justify analyzing changes across them. On the other hand, ECoG data has a higher signal-to-noise ratio, and can be used reliably to investigate such changes.

The aim of this project is to highlight these shifts of neural activity in the broadband spectrum during VWM tasks as the tasks become more demanding and correlate these changes to the regions along the cortex. We expect to find significant differences in these frequency bands across different brain regions with respect to the dynamic changes in difficulty and fatigue across the set of n-Back memory tasks.

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Visual working memory and workload components in ECoG during n-Back task

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