Cross-task specificity and within-task invariance of cognitive control processes

Cognitive load during driving: EEG microstate metrics are sensitive to task difficulty and predict safety outcomes

Engaging in phone conversations or other cognitively challenging tasks while driving detrimentally impacts cognitive functions and has been associated with increased risk of accidents. Existing EEG methods have been shown to differentiate between load and no load, but not between different levels of cognitive load. Furthermore, it has not been investigated whether EEG measurements of load can be used to predict safety outcomes in critical events. EEG microstates analysis, categorizing EEG signals into a concise set of prototypical functional states, has been used in other task contexts with good results, but has not been applied in the driving context. Here, this gap is addressed by means of a driving simulation experiment. Three phone use conditions (no phone use, hands-free, and handheld), combined with two task difficulty levels (single- or double-digit addition and subtraction), were tested before and during a rear-end collision conflict. Both conventional EEG spectral power and EEG microstates were analyzed. The results showed that different levels of cognitive load influenced EEG microstates differently, while EEG spectral power remained unaffected. A distinct EEG pattern emerged when drivers engaged in phone tasks while driving, characterized by a simultaneous increase and decrease in two of the EEG microstates, suggesting a heightened focus on auditory information, potentially at a cost to attention reorientation ability. The increase and decrease in these two microstates follow a monotonic sequence from baseline to hands-free simple, hands-free complex, handheld simple, and finally handheld complex, showing sensitivity to task difficulty. This pattern was found both before and after the lead vehicle braked. Furthermore, EEG microstates prior to the lead vehicle braking improved predictions of safety outcomes in terms of minimum time headway after the lead vehicle braked, clearly suggesting that these microstates measure brain states which are indicative of impaired driving. Additionally, EEG microstates are more predictive of safety outcomes than task difficulty, highlighting individual differences in task effects. These findings enhance our understanding of the neural dynamics involved in distracted driving and can be used in methods for evaluating the cognitive load induced by in-vehicle systems.

Understanding the human conflict processing network: A review of the literature on direct neural recordings during performance of a modified stroop task

The Stroop Task is a well-known neuropsychological task developed to investigate conflict processing in the human brain. Our group has utilized direct intracranial neural recordings in various brain regions during performance of a modified color-word Stroop Task to gain a mechanistic understanding of non-emotional human conflict processing. The purpose of this review article is to: 1) synthesize our own studies into a model of human conflict processing, 2) review the current literature on the Stroop Task and other conflict tasks to put our research in context, and 3) describe how these studies define a network in conflict processing. The figures presented are reprinted from our prior publications and key publications referenced in the manuscript. We summarize all studies to date that employ invasive intracranial recordings in humans during performance of conflict-inducing tasks. For our own studies, we analyzed local field potentials (LFPs) from patients with implanted stereotactic electroencephalography (SEEG) electrodes, and we observed intracortical oscillation patterns as well as intercortical temporal relationships in the hippocampus, amygdala, and orbitofrontal cortex (OFC) during the cue-processing phase of a modified Stroop Task. Our findings suggest that non-emotional human conflict processing involves modulation across multiple frequency bands within and between brain structures.

Theta and alpha oscillatory signatures of auditory sensory and cognitive loads during complex listening

The neuronal signatures of sensory and cognitive load provide access to brain activities related to complex listening situations. Sensory and cognitive loads are typically reflected in measures like response time (RT) and event-related potentials (ERPs) components. It's, however, strenuous to distinguish the underlying brain processes solely from these measures. In this study, along with RT- and ERP-analysis, we performed time-frequency analysis and source localization of oscillatory activity in participants performing two different auditory tasks with varying degrees of complexity and related them to sensory and cognitive load. We studied neuronal oscillatory activity in both periods before the behavioral response (pre-response) and after it (post-response). Robust oscillatory activities were found in both periods and were differentially affected by sensory and cognitive load. Oscillatory activity under sensory load was characterized by decrease in pre-response (early) theta activity and increased alpha activity. Oscillatory activity under cognitive load was characterized by increased theta activity, mainly in post-response (late) time. Furthermore, source localization revealed specific brain regions responsible for processing these loads, such as temporal and frontal lobe, cingulate cortex and precuneus. The results provide evidence that in complex listening situations, the brain processes sensory and cognitive loads differently. These neural processes have specific oscillatory signatures and are long lasting, extending beyond the behavioral response.