Conflict & Control

Inhibitory control—the ability to withhold or cancel maladaptive actions, thoughts, and emotions—is fundamental to goal-directed behaviors. Here, we use stop-signal task (SST) data from nearly 5000 9- to 10-year-olds in the Adolescent Brain Cognitive Development (ABCD) study to investigate neuro-cognitive dynamics underlying inhibitory control. It is traditional to infer neural mechanisms of cognition based on between-subject analyses, for example by finding brain regions where subject-averaged task activation covaries with a subject-averaged measure of inhibitory control, such as stop signal reaction time (SSRT). However, there is growing evidence of non-ergodicity within psychological and neuroscience data, implying that between-subject inferences, from data aggregated in individuals, may not be valid for interpreting how behavior unfolds over time within subjects. To study mechanisms of inhibitory control while allowing for non-ergodicity, we developed a dynamic computational model that characterizes the latent cognitive constructs governing action execution and inhibition in the SST. We then combined task fMRI data with the dynamic cognitive model of the SST to understand the relationship between task-evoked brain responses and dynamic inhibitory control processes at both between- and within- subject levels. Consistent with previous studies, inhibitory control showed activations in the salience and fronto-parietal networks. Between subjects, these activations correlated with the cognitive model parameters: throughout most of the cortex, inhibitory-control activations were negatively correlated with subject-averaged SSRTs and positively correlated with subject-averaged proactive delays and drift rates of the go process. The model’s trial-by-trial description of behavior also enabled us to study how cognitive representations related to brain activity within each subject’s SST sessions. Trial-by-trial, the model’s cognitive parameters parametrically modulated brain activity—but notably, these associations within subjects were largely the reverse of those identified between subjects. In regions of the anterior salience, dorsal attention, and executive control networks, brain activity within sessions was associated positively with SSRTs, and negatively with proactive delays and go-process drift-rates. Our work emphasizes that cognition, its component processes, and their representations in the brain, are dynamic and can be non-ergodic. The results highlight the importance of studying cognition with dynamic models of cognition that can infer latent neuro-cognitive measures at a trial level

Recent studies using the diffusion decision model find that drift rate parameter estimates across many cognitive control tasks are largely driven by a task-general latent factor that reflects individuals' efficiency of accumulating evidence relevant to task goals. However, drift rate estimates from an n-back "conflict recognition" paradigm in the Adolescent Brain Cognitive Development (ABCD) Study, a large, diverse sample of youth, appear to contradict these findings. Drift rate estimates from "lure" trials, which present stimuli that are familiar (i.e., presented previously) but do not meet formal criteria for being a target, show inconsistent relations with drift rate estimates from other trials and display atypical v-shaped bivariate distributions. This pattern suggests that many individuals are responding based largely on stimulus familiarity rather than goal-relevant stimulus features. We present a new formal model of evidence integration in conflict recognition tasks that distinguishes individuals' accumulation of goal-relevant evidence from their use of goal-irrelevant familiarity. We then investigate developmental, cognitive, and clinical correlates of these novel parameters. Parameters for accumulation of goal-relevant and goal-irrelevant evidence showed strong correlations across levels of n-back load, suggesting they are task-general dimensions that influence performance regardless of working memory demands. Only accumulation of goal-relevant evidence showed developmental differences in the ABCD sample and an independent age-diverse sample. This parameter also exhibited higher test-retest reliability and uniquely meaningful associations with clinical measures. These findings establish a principled modeling framework for characterizing conflict recognition mechanisms and have several broader implications for research on individual and developmental differences in cognitive control.

Conflict processing is a fundamental aspect of decision-making, traditionally studied using discrete-choice paradigms, where a response should be provided based on relevant informational sources while conflicting irrelevant sources must be ignored. However, real-world decisions often require selecting responses along continuous scales rather than between binary options. To bridge this gap, we introduce a novel adaptation of the Flanker task that employs a continuous decision space. Instead of discrete left/right arrow stimuli, targets and flankers are presented at varying angles within a 360-degree space, allowing for a graded spectrum of congruency based on the angular difference between target and flanker. An angular difference of 0 indicates the highest level of congruency, while a difference of 180 degrees represents the lowest level of congruency. Our results reveal systematic variations in response error and reaction time (RT) as a function of congruency. Specifically, response errors followed a structured pattern: at congruencies of 0°, 90°, -90°, and 180°, errors were minimized, indicating accurate identification of the target’s direction. At intermediate congruencies, systematic biases emerged—at 45° and -135°, participants tended to deviate in the negative direction relative to the flanker, whereas at -45° and 135°, deviations occurred in the positive direction. RTs were lowest for high-congruency trials and increased as congruency decreased. These findings suggest that conflict effects in continuous decision spaces follow structured, predictable patterns, highlighting the necessity of expanding theoretical models of conflict processing beyond discrete-choice frameworks. Our study lays the groundwork for future investigations into dynamic response strategies and attentional control in continuous conflict tasks.