Executive function updating level modulates connectivity network between brain regions in alpha band

INTRODUCTION To perform complex tasks, humans are required to handle multiple sensory stimuli, encode information, and make decisions. Humans have limited cognitive resources, resulting in cognitive bottlenecks that hinder performance (Schmorrow et al., 2008). The field of Augmented Cognition (AugCog) aims to “transform human-computer interaction by making systems adapt to changing [user] capabilities” by coupling neurophysiological sensing and cognitive modeling (St. John et al., 2004, p. 131). This study focuses on the executive function (EF) cognitive bottleneck. The three EF processes (updating, shifting, and inhibiting) control all other cognitive processes for execution of goal direct behavior (Baddeley, 1996). Simple tasks are used to investigate these EF processes separately. The flanker task is used to investigate inhibition (Eriksen and Eriksen, 1974), requiring the subject to distinguish between incongruent (i.e. << > <<) and congruent trials (i.e. << < <<). Updating is evaluated using the n-back task, requiring the subject to respond to the target stimulus only if it matches the stimulus presented n-levels previously. Updating demand is modulated by increasing the nback level (Owen et al., 2005). Behavioral metrics and neuroimaging analyses have been used to evaluate EF task performance. Under increasing cognitive loads, behavioral metrics are negatively impacted (e.g., decreased accuracy and increased reaction time (RT)). Activation of a common brain network, the cognitive control network (CCN), which includes the dorsolateral prefrontal cortex, anterior cingulate cortex, parietal lobe, prefrontal, temporal, and occipital cortices and thalamus, is involved in EF tasks (Niendam et al., 2012). Lastly, changes in alpha band power (8-13 Hz) have been observed during EF tasks under increased mental workload (Klimesch et al., 1999). However, these studies analyzed EEG signal power and phase, which lack a direct cause-and-effect interpretation. This can be addressed through effective connectivity analysis, which allows for insights into the causal relationships between brain regions. This study investigated the interplay of the updating and inhibition EF processes through behavioral performance metrics and effective connectivity, using Granger Causality analysis (GCA) (Coben and Mohammad-Rezazadeh, 2015). We hypothesized that increased working memory load (higher n-back level) would result in decreased performance on both tasks; that brain regions within the CCN would serve as information sources; and that alpha band effective connectivity between sources would be modulated by working memory (WM) load. These insights into the mechanisms underlying the interplay between two EFs will lead to development of richer cognitive models, thus improving AugCog systems. METHOD Participants and Experimental Design Twenty participants participated in the study. An arrowhead version of the flanker task was combined with a WM n-back task. One block of the experiment consisted of one n-back level. The experimental design was a 3 (updating level) x 2 (inhibition level) within-subject design.