Biology subjects

Freund, M. C.

Publications and source records attributed to Freund, M. C..

5 recordsLinked to original sources

bioRxiv2025

Selective distractor representations resolve multidimensional interference

Navigating competing attentional demands is a core cognitive function, yet how the brain tunes control in multidimensional environments remains poorly understood. Here, we used a multidimensional task-set interference paradigm in which participants attended to one of four stimulus dimensions while three others acted as distractors, combining multivariate decoding, representational similarity analysis, and encoding models applied to human EEG. Targets and distractors were initially encoded in parallel, but distractor representations were rapidly suppressed [~]250 ms after stimulus onset, with suppression scaling with each distractors own conflict history. Neither trial-to-trial adaptation nor block-level learning produced anticipatory changes in task-relevant representations. Instead, proactive control modulated the speed and efficiency of stimulus-triggered suppression. Encoding models further revealed that conflict is represented in orthogonal, dimension-specific subspaces that eventually collapse onto a shared conflict signal. These results show that multidimensional attentional control operates through selective, reactive suppression of distractor representations, guided by a structured multivariate conflict signal.

neuroscience↗

bioRxiv2024

Complementary benefits of multivariate and hierarchical models for identifying individual differences in cognitive control

Understanding individual differences in cognitive control is a central goal in psychology and neuroscience. Reliably measuring these differences, however, has proven extremely challenging, at least when using standard measures in cognitive neuroscience such as response times or task-based fMRI activity. While prior work has pinpointed the source of the issue -- the vast amount of cross-trial variability within these measures -- solutions remain elusive. Here, we propose one potential way forward: an analytic framework that combines hierarchical Bayesian modeling with multivariate decoding of trial-level fMRI data. Using this framework and longitudinal data from the Dual Mechanisms of Cognitive Control project, we estimated individuals neural responses associated with cognitive control within a color-word Stroop task, then assessed the reliability of these individuals responses across a time interval of several months. We show that in many prefrontal and parietal brain regions, test-retest reliability was near maximal, and that only hierarchical models were able to reveal this state of affairs. Further, when compared to traditional univariate contrasts, multivariate decoding enabled individual-level correlations to be estimated with significantly greater precision. We specifically link these improvements in precision to the optimized suppression of cross-trial variability in decoding. Together, these findings not only indicate that cognitive control-related neural responses individuate people in a highly stable manner across time, but also suggest that integrating hierarchical and multivariate models provides a powerful approach for investigating individual differences in cognitive control, one that can effectively address the issue of high-variability measures.

neuroscience↗

bioRxiv2021

The Dual Mechanisms of Cognitive Control dataset: A theoretically-guided within-subject task fMRI battery

Cognitive control is a critical higher mental function, which is subject to considerable individual variation, and is impaired in a range of mental health disorders. We describe here the initial release of Dual Mechanisms of Cognitive Control (DMCC) project data, the DMCC55B dataset, with 55 healthy unrelated young adult participants. Each participant performed four well-established cognitive control tasks (AX-CPT, Cued Task-Switching, Sternberg Working Memory, and Stroop) while undergoing functional MRI scanning. The dataset includes a range of state and trait self-report questionnaires, as well as behavioural tasks assessing individual differences in cognitive ability. The DMCC project is on-going and features additional components (e.g., related participants, manipulations of cognitive control mode, resting state fMRI, longitudinal testing) that will be publicly released following study completion. This DMCC55B subset is released early with the aim of encouraging wider use and greater benefit to the scientific community. The DMCC55B dataset is suitable for benchmarking and methods exploration, as well as analyses of task performance and individual differences.

neuroscience↗

bioRxiv2020

A representational similarity analysis of cognitive control during color-word Stroop

Progress in understanding the neural bases of cognitive control has been supported by the paradigmatic color-word Stroop task, in which a target response (color name) must be selected over a more automatic, yet potentially incongruent, distractor response (word). For this paradigm, models have postulated complementary coding schemes: dorsomedial frontal cortex (DMFC) is proposed to evaluate the demand for control via incongruency-related coding, whereas dorsolateral prefrontal cortex (DLPFC) is proposed to implement control via goal and target-related coding. Yet, mapping these theorized schemes to measured neural activity within this task has been challenging. Here, we tested for these coding schemes relatively directly, by decomposing an event-related color-word Stroop task via representational similarity analysis (RSA). Three neural coding models were fit to the similarity structure of multi-voxel patterns of human fMRI activity, acquired from 65 healthy, young-adult males and females. Incongruency coding was predominant in DMFC, whereas both target and incongruency coding were present with indistinguishable strength in DLPFC. In contrast, distractor coding was strongly encoded within early visual cortex. Further, these coding schemes were differentially related to behavior: individuals with stronger DLPFC (and lateral posterior parietal cortex) target coding, but weaker DMFC incongruency coding, exhibited less behavioral Stroop interference. These results highlight the utility of the RSA framework for investigating neural mechanisms of cognitive control and point to several promising directions to extend the Stroop paradigm. Significant StatementHow the human brain enables cognitive control -- the ability to override behavioral habits to pursue internal goals -- has been a major focus of neuroscience research. This ability has been frequently investigated by using the Stroop color-word naming task. With the Stroop as a test-bed, many theories have proposed specific neuroanatomical dissociations, in which medial and lateral frontal brain regions underlie cognitive control by encoding distinct types of information. Yet providing a direct confirmation of these claims has been challenging. Here, we demonstrate that representational similarity analysis (RSA), which estimates and models the similarity structure of brain activity patterns, can successfully establish the hypothesized functional dissociations within the Stroop task. RSA may provide a useful approach for investigating cognitive control mechanisms.

neuroscience↗

bioRxiv2020

The Dual Mechanisms of Cognitive Control (DMCC) Project

The Dual Mechanisms of Cognitive Control (DMCC) project provides an ambitious and rigorous empirical test of a theoretical framework that posits two key cognitive control modes: proactive and reactive. The frameworks central tenets are that proactive and reactive control reflect domain-general dimensions of individual variation, with distinctive neural signatures, involving lateral prefrontal cortex (PFC) in interactions with other brain networks and circuits (e.g., frontoparietal, cingulo-opercular). In the DMCC project, each participant is scanned while performing theoretically-targeted variants of multiple well-established cognitive control tasks (Stroop, Cued Task-Switching, AX-CPT, Sternberg Working Memory) in three separate imaging sessions, that each encourage utilization of different control modes, plus also completes an extensive out-of-scanner individual differences battery. Additional key features of the project include a high spatio-temporal resolution (multiband) acquisition protocol, and a sample that includes a substantial subset of monozygotic twin pairs and participants recruited from the Human Connectome Project. Although data collection is still continuing (target N=200), we provide an overview of the study design and protocol, planned analytic approaches and methodological development, along with initial results (N=80) revealing novel evidence of a domain-general neural signature of reactive control. In the interests of scientific community building, the dataset will be made public at project completion, so it can serve as a valuable resource.

neuroscience↗