A model of dynamic, within-trial conflict resolution for decision making

Growing evidence for moment-to-moment fluctuations in visual attention has led to questions about the impetus and time course of cognitive control. These questions are typically investigated with paradigms like the flanker task, which require participants to inhibit an automatic response before making a decision. Connectionist modeling work suggests that between-trial changes in attention result from fluctuations in conflict--as conflict occurs, attention needs to be up-regulated in order to resolve it. Current sequential sampling models (SSMs) of within-trial effects, however, suggest that attention focuses on a goal-relevant target as a function of time. We propose that within-trial changes in cognitive control and attention are emergent properties of the dynamics of the decision itself. We tested our hypothesis by developing a set of SSMs, each making alternative assumptions about attention modulation and evidence accumulation mechanisms. Combining the SSM framework with likelihood-free Bayesian approximation methods allowed us to conduct quantified comparisons between subject-level fits. Models included either time- or control-based attention mechanisms, and either strongly- (via feedforward inhibition) or weakly-correlated (via leak and lateral inhibition) evidence accumulation mechanisms. We fit all models to behavioral data collected in variants of the flanker task, one accompanied by EEG measures. Across three experiments, we found converging evidence that control-based attention processes in combination with evidence accumulation mechanisms governed by leak and lateral inhibition provided the best fits to behavioral data, and uniquely mapped onto observed decision-related signals in the brain.

Download Full-text

Unification of Countermanding and Perceptual Decision-making

10.1101/158170 ◽

2017 ◽

Author(s):

Paul G. Middlebrooks ◽

Bram B. Zandbelt ◽

Gordon D. Logan ◽

Thomas J. Palmeri ◽

Jeffrey D. Schall

Keyword(s):

Decision Making ◽

Response Inhibition ◽

Sequential Sampling ◽

Race Model ◽

Decision Time ◽

Perceptual Decision Making ◽

Perceptual Decision ◽

Evidence Accumulation ◽

Sequential Sampling Models ◽

Choice Tasks

Perceptual decision-making, studied using two-alternative forced-choice tasks, is explained by sequential sampling models of evidence accumulation, which correspond to the dynamics of neurons in sensorimotor structures of the brain1 2. Response inhibition, studied using stop-signal (countermanding) tasks, is explained by a race model of the initiation or canceling of a response, which correspond to the dynamics of neurons in sensorimotor structures3 4. Neither standard model accounts for performance of the other task. Sequential sampling models incorporate response initiation as an uninterrupted non-decision time parameter independent of task-related variables. The countermanding race model does not account for the choice process. Here we show with new behavioral, neural and computational results that perceptual decision making of varying difficulty can be countermanded with invariant efficiency, that single prefrontal neurons instantiate both evidence accumulation and response inhibition, and that an interactive race between two GO and one STOP stochastic accumulator fits countermanding choice behavior. Thus, perceptual decision-making and response control, previously regarded as distinct mechanisms, are actually aspects of more flexible behavior supported by a common neural and computational mechanism. The identification of this aspect of decision-making with response production clarifies the component processes of decision-making.

Download Full-text

Timing of readiness potentials reflect a decision-making process in the human brain

10.1101/338806 ◽

2018 ◽

Cited By ~ 4

Author(s):

Kitty K. Lui ◽

Michael D. Nunez ◽

Jessica M. Cassidy ◽

Joachim Vandekerckhove ◽

Steven C. Cramer ◽

...

Keyword(s):

Decision Making ◽

Response Time ◽

Response Selection ◽

Sequential Sampling ◽

Perceptual Categorization ◽

Accumulation Process ◽

Time Data ◽

Evidence Accumulation ◽

Sequential Sampling Models ◽

Readiness Potentials

AbstractDecision-making in two-alternative forced choice tasks has several underlying components including stimulus encoding, perceptual categorization, response selection, and response execution. Sequential sampling models of decision-making are based on an evidence accumulation process to a decision boundary. Animal and human studies have focused on perceptual categorization and provide evidence linking brain signals in parietal cortex to the evidence accumulation process. In this exploratory study, we use a task where the dominant contribution to response time is response selection and model the response time data with the drift-diffusion model. EEG measurement during the task show that the Readiness Potential (RP) recorded over motor areas has timing consistent with the evidence accumulation process. The duration of the RP predicts decision-making time, the duration of evidence accumulation, suggesting that the RP partly reflects an evidence accumulation process for response selection in the motor system. Thus, evidence accumulation may be a neural implementation of decision-making processes in both perceptual and motor systems. The contributions of perceptual categorization and response selection to evidence accumulation processes in decision-making tasks can be potentially evaluated by examining the timing of perceptual and motor EEG signals.

Download Full-text

Impaired Evidence Accumulation as a Transdiagnostic Vulnerability Factor in Psychopathology

Frontiers in Psychiatry ◽

10.3389/fpsyt.2021.627179 ◽

2021 ◽

Vol 12 ◽

Cited By ~ 1

Author(s):

Chandra Sripada ◽

Alexander Weigard

Keyword(s):

Computational Models ◽

Sequential Sampling ◽

Self Report ◽

Evidence Accumulation ◽

Hyperactivity Disorder ◽

Sequential Sampling Models ◽

Intelligence Scores ◽

Choice Tasks ◽

Substantial Interest ◽

Healthy Participants

There is substantial interest in identifying biobehavioral dimensions of individual variation that cut across heterogenous disorder categories, and computational models can play a major role in advancing this goal. In this report, we focused on efficiency of evidence accumulation (EEA), a computationally characterized variable derived from sequential sampling models of choice tasks. We created an EEA factor from three behavioral tasks in the UCLA Phenomics dataset (n = 272), which includes healthy participants (n = 130) as well-participants with schizophrenia (n = 50), bipolar disorder (n = 49), and attention-deficit/hyperactivity disorder (n = 43). We found that the EEA factor was significantly reduced in all three disorders, and that it correlated with an overall severity score for psychopathology as well as self-report measures of impulsivity. Although EEA was significantly correlated with general intelligence, it remained associated with psychopathology and symptom scales even after controlling for intelligence scores. Taken together, these findings suggest EEA is a promising computationally-characterized dimension of neurocognitive variation, with diminished EEA conferring transdiagnostic vulnerability to psychopathology.

Download Full-text

Sequential Sampling Models Without Random Between-Trial Variability: The Racing Diffusion Model of Speeded Decision

10.31234/osf.io/xuwbk ◽

2017 ◽

Cited By ~ 3

Author(s):

Gabriel Tillman

Keyword(s):

Response Time ◽

Diffusion Model ◽

Response Times ◽

Sequential Sampling ◽

Good Reason ◽

Accumulation Process ◽

Time Data ◽

Evidence Accumulation ◽

Sequential Sampling Models ◽

Sequential Sampling Model

Most current sequential sampling models have random between-trial variability in their parameters. These sources of variability make the models more complex in order to fit response time data, do not provide any further explanation to how the data were generated, and have recently been criticised for allowing infinite flexibility in the models. To explore and test the need of between-trial variability parameters we develop a simple sequential sampling model of N-choice speeded decision making: the racing diffusion model. The model makes speeded decisions from a race of evidence accumulators that integrate information in a noisy fashion within a trial. The racing diffusion does not assume that any evidence accumulation process varies between trial, and so, the model provides alternative explanations of key response time phenomena, such as fast and slow error response times relative to correct response times. Overall, our paper gives good reason to rethink including between-trial variability parameters in sequential sampling models

Download Full-text

Impaired Evidence Accumulation as a Transdiagnostic Vulnerability Factor in Psychopathology

10.31234/osf.io/fwr3m ◽

2020 ◽

Cited By ~ 1

Author(s):

Chandra Sripada ◽

Alexander Samuel Weigard

Keyword(s):

Computational Models ◽

Sequential Sampling ◽

Self Report ◽

Evidence Accumulation ◽

Hyperactivity Disorder ◽

Sequential Sampling Models ◽

Intelligence Scores ◽

Choice Tasks ◽

Substantial Interest ◽

Healthy Participants

There is substantial interest in identifying biobehavioral dimensions of individual variation that cut across heterogenous disorder categories, and computational models can play a major role in advancing this goal. In this report, we focused on efficiency of evidence accumulation (EEA), a computationally characterized variable derived from sequential sampling models of choice tasks. We created an EEA factor from three behavioral tasks in the UCLA Phenomics dataset (n=272), which includes healthy participants (n=130) as well participants with schizophrenia (n=50), bipolar disorder (n=49), and attention-deficit/hyperactivity disorder (n=43). We found that the EEA factor was significantly reduced in all three disorders, and that it correlated with an overall severity score for psychopathology as well as self-report measures of impulsivity. Although EEA was significantly correlated with general intelligence, it remained associated with psychopathology and symptom scales even after controlling for intelligence scores. Taken together, these findings suggest EEA is a promising computationally-characterized dimension of neurocognitive variation, with diminished EEA conferring transdiagnostic vulnerability to psychopathology.

Download Full-text

Exploring an Emotional Basis of Cognitive Control in the Flanker Task

10.31234/osf.io/nkjy6 ◽

2020 ◽

Author(s):

Motonori Yamaguchi ◽

Jack Dylan Moore ◽

Sarah Hendry ◽

Felicity Wolohan

Keyword(s):

Cognitive Control ◽

Facial Expressions ◽

Mood Induction ◽

Flanker Task ◽

Emotional Stimuli ◽

Emotional Facial Expressions ◽

Flanker Effect ◽

Sequential Modulation ◽

Emotional Basis ◽

Negative Stimuli

The emotional basis of cognitive control has been investigated in the flanker task with various procedures and materials across different studies. The present study examined the issue with the same flanker task but with different types of emotional stimuli and design. In seven experiments, the flanker effect and its sequential modulation according to the preceding trial type were assessed. Experiments 1 and 2 used affective pictures and emotional facial expressions as emotional stimuli, and positive and negative stimuli were intermixed. There was little evidence that emotional stimuli influenced cognitive control. Experiments 3 and 4 used the same affective pictures and facial expressions, but positive and negative stimuli were separated between different participant groups. Emotional stimuli reduced the flanker effect as well as its sequential modulation regardless of valence. Experiments 5 and 6 used affective pictures but manipulated arousal and valence of stimuli orthogonally The results did not replicate the reduced flanker effect or sequential modulation by valence, nor did they show consistent effects of arousal. Experiment 7 used a mood induction technique and showed that sequential modulation was positively correlated with valence rating (the higher the more positive) but was negatively correlated with arousal rating. These results are inconsistent with several previous findings and are difficult to reconcile within a single theoretical framework, confirming an elusive nature of the emotional basis of cognitive control in the flanker task.

Download Full-text

Age Moderates the Association of Aerobic Exercise with Initial Learning of an Online Task Requiring Cognitive Control

Journal of the International Neuropsychological Society ◽

10.1017/s1355617715000685 ◽

2015 ◽

Vol 21 (10) ◽

pp. 802-815 ◽

Cited By ~ 5

Author(s):

Patrick J. O’Connor ◽

Phillip D. Tomporowski ◽

Rodney K. Dishman

Keyword(s):

Cognitive Control ◽

Resistance Exercise ◽

Latent Class ◽

Flanker Task ◽

Linear Increase ◽

Free Play ◽

Exercise Frequency ◽

Aerobic Activity ◽

Initial Learning ◽

Increase In Accuracy

AbstractThe aim of this study was to examine whether people differed in change in performance across the first five blocks of an online flanker task and whether those trajectories of change were associated with self-reported aerobic or resistance exercise frequency according to age. A total of 8752 men and women aged 13–89 completed a lifestyle survey and five 45-s games (each game was a block of ~46 trials) of an online flanker task. Accuracy of the congruent and incongruent flanker stimuli was analyzed using latent class and growth curve modeling adjusting for time between blocks, whether the blocks occurred on the same or different days, education, smoking, sleep, caffeinated coffee and tea use, and Lumosity training status (“free play” or part of a “daily brain workout”). Aerobic and resistance exercise were unrelated to first block accuracies. For the more cognitively demanding incongruent flanker stimuli, aerobic activity was positively related to the linear increase in accuracy [B=0.577%, 95% confidence interval (CI), 0.112 to 1.25 per day above the weekly mean of 2.8 days] and inversely related to the quadratic deceleration of accuracy gains (B=−0.619% CI, −1.117 to −0.121 per day). An interaction of aerobic activity with age indicated that active participants younger than age 45 had a larger linear increase and a smaller quadratic deceleration compared to other participants. Age moderates the association between self-reported aerobic, but not self-reported resistance, exercise and changes in cognitive control that occur with practice during incongruent presentations across five blocks of a 45-s online, flanker task. (JINS, 2015, 21, 802–815)

Download Full-text

Second language (L2) proficiency, socioeconomic status (SES), and intelligence (IQ) are significant predictors of cognitive control differences among young adult unbalanced Chinese–English bilinguals

Bilingualism Language and Cognition ◽

10.1017/s1366728918000822 ◽

2018 ◽

Vol 22 (04) ◽

pp. 866-882 ◽

Cited By ~ 5

Author(s):

ZHILONG XIE ◽

TERESA SIGNORELLI PISANO

Keyword(s):

Socioeconomic Status ◽

Second Language ◽

Young Adult ◽

Cognitive Control ◽

Flanker Task ◽

Incongruent Condition ◽

Wisconsin Card Sorting Test ◽

Card Sorting ◽

Conflict Monitoring ◽

L2 Proficiency

The current study investigates how second-language (L2) proficiency contributes to cognitive control differences among three groups of unbalanced Chinese–English bilinguals matched for socioeconomic status (SES), intelligence (IQ), education, age, culture, and L1 background. A Flanker task and the Wisconsin Card Sorting Test (WCST) were administered to measure conflict monitoring, inhibition, and mental set shifting. ANOVA analyses revealed faster performance for the High-L2 Group compared to the Low-L2 Group in the congruent, neutral, and incongruent conditions of the Flanker task. However, there were no group differences on the WCST. Multiple step-wise regression analyses showed that L2 proficiency was a predictor for the Flanker task performance in all three conditions, SES in the neutral and the incongruent condition, and IQ in the congruent condition. These results suggest that L2 proficiency, along with SES and IQ, contribute significantly to cognitive control differences in conflict monitoring among young-adult bilinguals.

Download Full-text