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Individual differences in rate of acquiring stable neural representations of tasks in fMRI.

ABSTRACT: Task-related functional magnetic resonance imaging (fMRI) is a widely-used tool for studying the neural processing correlates of human behavior in both healthy and clinical populations. There is growing interest in mapping individual differences in fMRI task behavior and neural responses. By utilizing neuroadaptive task designs accounting for such individual differences, task durations can be personalized to potentially optimize neuroimaging study outcomes (e.g., classification of task-related brain states). To test this hypothesis, we first retrospectively tracked the volume-by-volume changes of beta weights generated from general linear models (GLM) for 67 adult subjects performing a stop-signal task (SST). We then modeled the convergence of the volume-by-volume changes of beta weights according to their exponential decay (ED) in units of half-life. Our results showed significant differences in beta weight convergence estimates of optimal stopping times (OSTs) between go following successful stop trials and failed stop trials for both cocaine dependent (CD) and control group (Con), and between go following successful stop trials and go following failed stop trials for Con group. Further, we implemented support vector machine (SVM) classification for 67 CD/Con labeled subjects and compared the classification accuracies of fMRI-based features derived from (1) the full fMRI task versus (2) the fMRI task truncated to multiples of the unit of half-life. Among the computed binary classification accuracies, two types of task durations based on 2 half-lives significantly outperformed the accuracies using fully acquired trials, supporting this length as the OST for the SST. In conclusion, we demonstrate the potential of a neuroadaptive task design that can be widely applied to personalizing other task-based fMRI experiments in either dynamic real-time fMRI applications or within fMRI preprocessing pipelines.

SUBMITTER: Chung MH

PROVIDER: S-EPMC6261022 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Individual differences in rate of acquiring stable neural representations of tasks in fMRI.

Chung Ming-Hua MH Martins Bradford B Privratsky Anthony A James G Andrew GA Kilts Clint D CD Bush Keith A KA

PloS one 20181126 11

Task-related functional magnetic resonance imaging (fMRI) is a widely-used tool for studying the neural processing correlates of human behavior in both healthy and clinical populations. There is growing interest in mapping individual differences in fMRI task behavior and neural responses. By utilizing neuroadaptive task designs accounting for such individual differences, task durations can be personalized to potentially optimize neuroimaging study outcomes (e.g., classification of task-related b ...[more]

PMID: 30475812

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Project description:The amygdala (AMG) has been repeatedly implicated in the processing of threatening and negatively valenced stimuli and multiple fMRI paradigms have reported personality, genetic, and psychopathological associations with individual differences in AMG activation in these paradigms. Yet the interchangeability of activations in these probes has not been established, thus it remains unclear if we can interpret AMG responses on specific tasks as general markers of its reactivity. In this study we aimed to assess if different tasks that have been widely used within the Affective Neuroscience literature consistently recruit the AMG.Thirty-two young healthy subjects completed four fMRI tasks that have all been previously shown to probe the AMG during processing of threatening stimuli: the Threat Face Matching (TFM), the Cued Aversive Picture (CAP), the Aversive and Erotica Pictures (AEP) and the Screaming Lady paradigm (SLp) tasks. Contrasts testing response to aversive stimuli relative to baseline or neutral stimuli were generated and correlations between activations in the AMG were calculated across tasks were performed for ROIs of the AMG.The TFM, CAP and AEP, but not the SLp, successfully recruit the AMG, among other brain regions, especially when contrasts were against baseline or nonsocial stimuli. Conjunction analysis across contrasts showed that visual cortices (VisCtx) were also consistently recruited. Correlation analysis between the extracted data for right and left AMG did not yield significant associations across tasks. By contrast, the extracted signal in VisCtx showed significant associations across tasks (range r=0.511-r=0.630).Three of the four paradigms revealed significant AMG reactivity, but individual differences in the magnitudes of AMG reactivity were not correlated across paradigms. By contrast, VisCtx activation appears to be a better candidate than the AMG as a measure of individual differences with convergent validity across negative emotion processing paradigms.

Project description:Through selective attention, decision-makers can learn to ignore behaviorally irrelevant stimulus dimensions. This can improve learning and increase the perceptual discriminability of relevant stimulus information. Across cognitive models of categorization, this is typically accomplished through the inclusion of attentional parameters, which provide information about the importance assigned to each stimulus dimension by each participant. The effect of these parameters on psychological representation is often described geometrically, such that perceptual differences over relevant psychological dimensions are accentuated (or stretched), and differences over irrelevant dimensions are down-weighted (or compressed). In sensory and association cortex, representations of stimulus features are known to covary with their behavioral relevance. Although this implies that neural representational space might closely resemble that hypothesized by formal categorization theory, to date, attentional effects in the brain have been demonstrated through powerful experimental manipulations (e.g., contrasts between relevant and irrelevant features). This approach sidesteps the role of idiosyncratic conceptual knowledge in guiding attention to useful information sources. To bridge this divide, we used formal categorization models, which were fit to behavioral data, to make inferences about the concepts and strategies used by individual participants during decision-making. We found that when greater attentional weight was devoted to a particular visual feature (e.g., "color"), its value (e.g., "red") was more accurately decoded from occipitotemporal cortex. We also found that this effect was sufficiently sensitive to reflect individual differences in conceptual knowledge, indicating that occipitotemporal stimulus representations are embedded within a space closely resembling that formalized by classic categorization theory. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Dataset Information

Individual differences in rate of acquiring stable neural representations of tasks in fMRI.

Publications

Individual differences in rate of acquiring stable neural representations of tasks in fMRI.

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