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Neurochemical and functional interactions for improved perceptual decisions through training.

ABSTRACT: Learning and experience are known to improve our ability to make perceptual decisions. Yet, our understanding of the brain mechanisms that support improved perceptual decisions through training remains limited. Here, we test the neurochemical and functional interactions that support learning for perceptual decisions in the context of an orientation identification task. Using magnetic resonance spectroscopy (MRS), we measure neurotransmitters (i.e., glutamate, GABA) that are known to be involved in visual processing and learning in sensory [early visual cortex (EV)] and decision-related [dorsolateral prefrontal cortex (DLPFC)] brain regions. Using resting-state functional magnetic resonance imaging (rs-fMRI), we test for functional interactions between these regions that relate to decision processes. We demonstrate that training improves perceptual judgments (i.e., orientation identification), as indicated by faster rates of evidence accumulation after training. These learning-dependent changes in decision processes relate to lower EV glutamate levels and EV-DLPFC connectivity, suggesting that glutamatergic excitation and functional interactions between visual and dorsolateral prefrontal cortex facilitate perceptual decisions. Further, anodal transcranial direct current stimulation (tDCS) in EV impairs learning, suggesting a direct link between visual cortex excitation and perceptual decisions. Our findings advance our understanding of the role of learning in perceptual decision making, suggesting that glutamatergic excitation for efficient sensory processing and functional interactions between sensory and decision-related regions support improved perceptual decisions.NEW & NOTEWORTHY Combining multimodal brain imaging [magnetic resonance spectroscopy (MRS), functional connectivity] with interventions [transcranial direct current stimulation (tDCS)], we demonstrate that glutamatergic excitation and functional interactions between sensory (visual) and decision-related (dorsolateral prefrontal cortex) areas support our ability to optimize perceptual decisions through training.

SUBMITTER: Jia K

PROVIDER: S-EPMC8977131 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

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Neurochemical and functional interactions for improved perceptual decisions through training.

Jia Ke K Frangou Polytimi P Karlaftis Vasilis M VM Ziminski Joseph J JJ Giorgio Joseph J Rideaux Reuben R Zamboni Elisa E Hodgson Victoria V Emir Uzay U Kourtzi Zoe Z

Journal of neurophysiology 20220302 4

Learning and experience are known to improve our ability to make perceptual decisions. Yet, our understanding of the brain mechanisms that support improved perceptual decisions through training remains limited. Here, we test the neurochemical and functional interactions that support learning for perceptual decisions in the context of an orientation identification task. Using magnetic resonance spectroscopy (MRS), we measure neurotransmitters (i.e., glutamate, GABA) that are known to be involved ...[more]

PMID: 35235415

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Project description:Perceptual confidence is an important internal signal about the certainty of our decisions and there is a substantial debate on how it is computed. We highlight three confidence metric types from the literature: observers either use 1) the full probability distribution to compute probability correct (Probability metrics), 2) point estimates from the perceptual decision process to estimate uncertainty (Evidence-Strength metrics), or 3) heuristic confidence from stimulus-based cues to uncertainty (Heuristic metrics). These metrics are rarely tested against one another, so we examined models of all three types on a suprathreshold spatial discrimination task. Observers were shown a cloud of dots sampled from a dot generating distribution and judged if the mean of the distribution was left or right of centre. In addition to varying the horizontal position of the mean, there were two sensory uncertainty manipulations: the number of dots sampled and the spread of the generating distribution. After every two perceptual decisions, observers made a confidence forced-choice judgement whether they were more confident in the first or second decision. Model results showed that the majority of observers were best-fit by either: 1) the Heuristic model, which used dot cloud position, spread, and number of dots as cues; or 2) an Evidence-Strength model, which computed the distance between the sensory measurement and discrimination criterion, scaled according to sensory uncertainty. An accidental repetition of some sessions also allowed for the measurement of confidence agreement for identical pairs of stimuli. This N-pass analysis revealed that human observers were more consistent than their best-fitting model would predict, indicating there are still aspects of confidence that are not captured by our modelling. As such, we propose confidence agreement as a useful technique for computational studies of confidence. Taken together, these findings highlight the idiosyncratic nature of confidence computations for complex decision contexts and the need to consider different potential metrics and transformations in the confidence computation.

Dataset Information

Neurochemical and functional interactions for improved perceptual decisions through training.

Publications

Neurochemical and functional interactions for improved perceptual decisions through training.

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