Decoding task engagement from distributed network electrophysiology in humans

Abstract

Objective.Here, our objective was to develop a binary decoder to detect task engagement in humans during two distinct, conflict-based behavioral tasks. Effortful, goal-directed decision-making requires the coordinated action of multiple cognitive processes, including attention, working memory and action selection. That type of mental effort is often dysfunctional in mental disorders, e.g. when a patient attempts to overcome a depression or anxiety-driven habit but feels unable. If the onset of engagement in this type of focused mental activity could be reliably detected, decisional function might be augmented, e.g. through neurostimulation. However, there are no known algorithms for detecting task engagement with rapid time resolution.Approach.We defined a new network measure, fixed canonical correlation (FCCA), specifically suited for neural decoding applications. We extracted FCCA features from local field potential recordings in human volunteers to give a temporally continuous estimate of mental effort, defined by engagement in experimental conflict tasks.Main results.Using a small number of features per participant, we accurately decoded and distinguished task engagement from other mental activities. Further, the decoder distinguished between engagement in two different conflict-based tasks within seconds of their onset.Significance.These results demonstrate that network-level brain activity can detect specific types of mental efforts. This could form the basis of a responsive intervention strategy for decision-making deficits.

Prefrontal cortex and cognitive control: new insights from human electrophysiology

“…Furthermore, that information transfer (assessed by mutual information calculations) is strongest between 4 and 8 Hz, the canonical theta band. Using the same task, our group recently showed that this theta synchrony extends well beyond PFC 105 . We showed that cognitive control tasks engage pairwise correlations between PFC, cingulate, and subcortical structures and that the majority of high-influence correlations were in the theta band 105 .…”

“…Using the same task, our group recently showed that this theta synchrony extends well beyond PFC 105 . We showed that cognitive control tasks engage pairwise correlations between PFC, cingulate, and subcortical structures and that the majority of high-influence correlations were in the theta band 105 . This may reflect a link between control and attention; PFC synchronizes with parietal cortex to entrain parietal oscillations to ongoing intermittent signals, increasing their chance of successful detection 100 .…”

Deep brain stimulation for psychiatric disorders: From focal brain targets to cognitive networks

“…It is not yet clear at what level a “network” could/should be defined. That term, and its close cousin “connectome”, may refer to anatomic connections inferred through diffusion imaging ( Haber et al 2020 ), putative functional relationships inferred from correlations in slow hemodynamic signals ( Smith et al 2013 , Eickhoff et al 2018 ), or similar correlations identified in sub-second physiologic recordings ( Sani et al 2018 , Provenza et al 2019 ). All remain viable levels of analysis at present, and identifying the most useful is an ongoing area of DBS-related investigation.…”

Patterns of Focal- and Large-Scale Synchronization in Cognitive Control and Inhibition: A Review

“…ECoG theta coupling accompanies information exchange from fronto medial to parietal areas upon error feedback in a Stroop-like paradigm (Smith et al, 2015 ), likely acting as a modulatory attentional mechanism over motor areas, augmenting the stimulus-detection probability. Theta synchrony circuits during conflict detection also convolve the dorsal cingulate cortex and subcortical structures (Provenza et al, 2019 ; Smith et al, 2019 ).…”

“…Cross-frequency phase-phase/amplitude coupling dynamics have been described in working memory processes. However, it is yet to be established how they apply to behavioral inhibition, a complex function that relies on a combination of cognitive processes, including attention, working memory, action selection (Hampshire et al, 2007 ; Stokes et al, 2013 ; Provenza et al, 2019 ; Widge et al, 2019a ), and that is likewise distributed across brain networks (Erika-Florence et al, 2014 ; Hampshire and Sharp, 2015 ). Existing knowledge and evidence in this regard will be reviewed and elucidated in the following sections.…”