Hybrid framework of fatigue: connecting motivational control and computational moderators to gamma oscillations

Abstract

Introduction: There is a need to develop a comprehensive account of time-on-task fatigue effects on performance (i.e., the vigilance decrement) to increase predictive accuracy. We address this need by integrating three independent accounts into a novel hybrid framework. This framework unites (1) a motivational system balancing goal and comfort drives as described by an influential cognitive-energetic theory with (2) accumulating microlapses from a recent computational model of fatigue, and (3) frontal gamma oscillations indexing fluctuations in motivational control. Moreover, the hybrid framework formally links brief lapses (occurring over milliseconds) to the dynamics of the motivational system at a temporal scale not otherwise described in the fatigue literature.

Methods: EEG and behavioral data was collected from a brief vigilance task. High frequency gamma oscillations were assayed, indexing effortful controlled processes with motivation as a latent factor. Binned and single-trial gamma power was evaluated for changes in real- and lagged-time and correlated with behavior. Functional connectivity analyses assessed the directionality of gamma power in frontal-parietal communication across time-on-task. As a high-resolution representation of latent motivation, gamma power was scaled by fatigue moderators in two computational models. Microlapses modulated transitions from an effortful controlled state to a minimal-effort default state. The hybrid models were compared to a computational microlapse-only model for goodness-of-fit with simulated data.

Results: Findings suggested real-time high gamma power exhibited properties consistent with effortful motivational control. However, gamma power failed to correlate with increases in response times over time, indicating electrophysiology and behavior relations are insufficient in capturing the full range of fatigue effects. Directional connectivity affirmed the dominance of frontal gamma activity in controlled processes in the frontal-parietal network. Parameterizing high frontal gamma power, as an index of fluctuating relative motivational control, produced results that are as accurate or superior to a previous microlapse-only computational model.

Discussion: The hybrid framework views fatigue as a function of a energetical motivational system, managing the trade-space between controlled processes and competing wellbeing needs. Two gamma computational models provided compelling and parsimonious support for this framework, which can potentially be applied to fatigue intervention technologies and related effectiveness measures.

Keywords: computational modeling; fatigue; high frequency gamma oscillations; microlapses; motivational control; vigilance.

Figure 1

Psychomotor Vigilance Test (PVT). Participants press a pre-designated keyboard button as soon as the numeric counter (center) is detected.

Figure 2

Patterns in gamma power (blue solid line) and RT (black dotted line) over time: (A) across the five 2-min time bins (error bars omitted for clarity); (B) across single trials. No significant correlations emerged at either timescale.

Figure 3

Stacked aggregate counts of fastest (Q1) to slowest (Q5) response time quintiles computed per participant across the five time bins during the 10-min PVT task. Consistent with the vigilance decrement, frequency of the fastest quintile decreases as frequency of slowest quintile increases with time-on-task.

Figure 4

Between-bin high gamma GP for Fz → Pz (black) and Pz → Fz (blue) for an early window (0–150 ms) after stimulus onset associated with perceptual gating and later window (200–400 ms) indexing central cognition; *p ≤ 0.10, **p ≤ 0.05, ns, not significant. Means (SDs) are listed in Table 2.

Figure 5

Process model of the Psychomotor Vigilance Test (PVT) in ACT-R. From Veksler and Gunzelmann (2018).

Figure 6

Single-trial utility values for the CMF (black) and Gamma model 2 (blue), excluding noise.