Aponte Perez, E. A. | bioRxiv Science

bioRxiv2022

GABAergic modulation of conflict adaptation and response inhibition

Adaptive behavior is only possible by stopping stereotypical actions to generate new plans according to internal goals. It is response inhibition --the ability to stop actions automatically triggered by exogenous cues-- that allows for the flexible interplay between bottom-up, stimulus driven behaviors, and top-down strategies. In addition to response inhibition, cognitive control draws on conflict adaptation, the facilitation of top-down actions following high conflict situations. It is currently unclear whether and how response inhibition and conflict adaptation depend on GABAergic signaling, the main inhibitory neurotransmitter in the human brain. Here, we applied a recently developed computational model (SERIA) to data from two studies (N=150 & 50) of healthy volunteers performing Simon and antisaccade tasks. One of these datasets was acquired under placebo-controlled pharmacological enhancement of GABAergic transmission (lorazepam, an allosteric modulator of the GABA-A receptor). Our model-based results suggest that enhanced GABA-A signaling boosts conflict adaptation but impairs response inhibition. More generally, our computational approach establishes a unified account of response inhibition and conflict adaptation in the Simon and antisaccade tasks and provides a novel tool for quantifying specific aspects of cognitive control and their modulation by pharmacology or disease. Author SummaryOur capacity to prepare for situations that afford conflicting responses (conflict adaptation) and to stop our immediate impulses in these scenarios (response inhibition) are the hallmark of cognitive control. As these abilities require both the stopping or slowing of response tendencies, a natural question is whether they are mediated by inhibitory neurotransmission in the brain. Here, we combined computational modeling with two experiments to investigate how conflict adaptation and response inhibition interact with each other (experiment 1) and how these are modulated by lorazepam (experiment 2), a positive modulator of the GABA-A receptor, one of the main inhibitory receptors in the human brain. Using our computational model to disentangle conflict adaptation and response inhibition, our results indicate that while lorazepam impaired response inhibition, it improved conflict adaptation. Thus, our results suggests that conflict adaptation is mediated by GABA-A neurotransmission.

neuroscience↗

bioRxiv2017

The Stochastic Early Reaction, Inhibition, and Late Action (SERIA) Model for Antisaccades SERIA - A model for errors and reaction times in the antisaccade task

The antisaccade task is a classic paradigm used to study the voluntary control of eye movements. It requires participants to suppress a reactive eye movement to a visual target and to concurrently initiate a saccade in the opposite direction. Although several models have been proposed to explain error rates and reaction times in this task, no formal model comparison has yet been performed. Here, we describe a Bayesian modeling approach to the antisaccade task that allows us to formally compare different models on the basis of their evidence. First, we provide a formal likelihood function of actions (pro- and antisaccades) and reaction times based on previously published models. Second, we introduce the Stochastic Early Reaction, Inhibition, and late Action model (SERIA), a novel model postulating two different mechanisms that interact in the antisaccade task: an early GO/NO-GO race decision process and a late GO/GO decision process. Third, we apply these models to a data set from an experiment with three mixed blocks of pro- and antisaccade trials. Bayesian model comparison demonstrates that the SERIA model explains the data better than competing models that do not incorporate a late decision process. Moreover, we show that the race decision processes postulated by the SERIA model are, to a large extent, insensitive to the cue presented on a single trial. Finally, we use parameter estimates to demonstrate that changes in reaction time and error rate due to the probability of a trial type (prosaccade or antisaccade) are best explained by faster or slower inhibition and the probability of generating late voluntary prosaccades.\n\nAuthor summaryOne widely replicated finding in schizophrenia research is that patients tend to make more errors in the antisaccade task, a psychometric paradigm in which participants are required to look in the opposite direction of a visual cue. This deficit has been suggested to be an endophenotype of schizophrenia, as first order relatives of patients tend to show similar but milder deficits. Currently, most models applied to experimental findings in this task are limited to fit average reaction times and error rates. Here, we propose a novel statistical model that fits experimental data from the antisaccade task, beyond summary statistics. The model is inspired by the hypothesis that antisaccades are the result of several competing decision processes that interact nonlinearly with each other. In applying this model to a relatively large experimental data set, we show that mean reaction times and error rates do not fully reflect the complexity of the processes that are likely to underlie experimental findings. In the future, our model could help to understand the nature of the deficits observed in schizophrenia by providing a statistical tool to study their biological underpinnings.

neuroscience↗