Pupil-Linked Arousal Biases Evidence Accumulation Toward Desirable Percepts During Perceptual Decision-Making

2021 ◽  
Vol 32 (9) ◽  
pp. 1494-1509
Author(s):  
Yuan Chang Leong ◽  
Roma Dziembaj ◽  
Mark D’Esposito
Keyword(s):  
Decision Making ◽  
Computational Models ◽  
Perceptual Decision Making ◽  
Categorization Task ◽  
Perceptual Decision ◽  
Evidence Accumulation ◽  
Perceptual Judgments ◽  
Significant Events ◽  
Arousal System ◽  
Objective Representation

People’s perceptual reports are biased toward percepts they are motivated to see. The arousal system coordinates the body’s response to motivationally significant events and is well positioned to regulate motivational effects on perceptual judgments. However, it remains unclear whether arousal would enhance or reduce motivational biases. Here, we measured pupil dilation as a measure of arousal while participants ( N = 38) performed a visual categorization task. We used monetary bonuses to motivate participants to perceive one category over another. Even though the reward-maximizing strategy was to perform the task accurately, participants were more likely to report seeing the desirable category. Furthermore, higher arousal levels were associated with making motivationally biased responses. Analyses using computational models suggested that arousal enhanced motivational effects by biasing evidence accumulation in favor of desirable percepts. These results suggest that heightened arousal biases people toward what they want to see and away from an objective representation of the environment.

scholarly journals Pupil-linked arousal biases evidence accumulation towards desirable percepts during perceptual decision-making

2020 ◽  
Author(s):  
Yuan Chang Leong ◽  
Roma Dziembaj ◽  
Mark D’Esposito
Keyword(s):  
Decision Making ◽  
Computational Models ◽  
Visual Image ◽  
Perceptual Decision Making ◽  
Evidence Accumulation ◽  
Perceptual Judgments ◽  
Arousal System ◽  
Sensory Evidence ◽  
Arousal Response ◽  
Objective Representation

AbstractPeople are biased towards seeing outcomes they are motivated to see. The arousal system coordinates the body’s response to motivationally significant events, and is well positioned to regulate motivational effects on sensory perception. However, it remains unclear whether arousal would enhance or reduce motivational biases. Here we measured pupil dilation as a measure of arousal while participants performed a visual categorization task. We used monetary bonuses to motivate participants to see one category over another. Even though the reward-maximizing strategy was to perform the task accurately, participants were more likely to report seeing the motivationally desirable category. Furthermore, higher arousal levels were associated with making motivationally biased responses. Analyses using computational models indicated that arousal enhanced motivational effects by biasing evidence accumulation in favor of motivationally desirable percepts. These results suggest heightened arousal biases people towards what they want to see and away from an objective representation of the environment.Statement of RelevanceWhen confronted with an event of motivational significance (e.g., an opportunity to earn a huge reward), people often experience a strong arousal response that includes increased sweating, faster heart-rate and larger pupils. Does this arousal response help individuals make more accurate decisions, or does it instead bias and impair decision-making? This work examines the effects of arousal on how people decide what they see when they are motivated to see a particular outcome. We found that heightened arousal, as measured by larger pupils, was associated with a bias in how participants accumulated sensory evidence to make their decisions. As a result, participants became more likely to report seeing an ambiguous visual image as the interpretation they were motivated to see. Our results suggest that arousal biases perceptual judgments towards desirable percepts, and that modulating arousal levels could be a promising approach in reducing motivational biases in decision-making.

A Neural Index of Inefficient Evidence Accumulation in Dyslexia Underlying Slow Perceptual Decision Making

Cortex ◽  
2021 ◽  
Author(s):  
Nicole R. Stefanac ◽  
Shou-Han Zhou ◽  
Megan M. Spencer-Smith ◽  
Redmond O’Connell ◽  
Mark A. Bellgrove
Keyword(s):  
Decision Making ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Evidence Accumulation

scholarly journals Catecholamine Modulation of Evidence Accumulation during Perceptual Decision Formation: A Randomized Trial

2019 ◽  
Vol 31 (7) ◽  
pp. 1044-1053 ◽  
Author(s):  
Gerard M. Loughnane ◽  
Méadhbh B. Brosnan ◽  
Jessica J. M. Barnes ◽  
Angela Dean ◽  
Sanjay L. Nandam ◽  
...  
Keyword(s):  
Decision Making ◽  
Behavioral Effect ◽  
Oddball Paradigm ◽  
Perceptual Decision Making ◽  
Neural Basis ◽  
Perceptual Decision ◽  
Evidence Accumulation ◽  
Double Blinded ◽  
The Impact ◽  
Catecholamine Levels

Recent behavioral modeling and pupillometry studies suggest that neuromodulatory arousal systems play a role in regulating decision formation but neurophysiological support for these observations is lacking. We employed a randomized, double-blinded, placebo-controlled, crossover design to probe the impact of pharmacological enhancement of catecholamine levels on perceptual decision-making. Catecholamine levels were manipulated using the clinically relevant drugs methylphenidate and atomoxetine, and their effects were compared with those of citalopram and placebo. Participants performed a classic EEG oddball paradigm that elicits the P3b, a centro-parietal potential that has been shown to trace evidence accumulation, under each of the four drug conditions. We found that methylphenidate and atomoxetine administration shortened RTs to the oddball targets. The neural basis of this behavioral effect was an earlier P3b peak latency, driven specifically by an increase in its buildup rate without any change in its time of onset or peak amplitude. This study provides neurophysiological evidence for the catecholaminergic enhancement of a discrete aspect of human decision-making, that is, evidence accumulation. Our results also support theoretical accounts suggesting that catecholamines may enhance cognition via increases in neural gain.

scholarly journals Making up your mind: Enhanced perceptual decision-making induced by stochastic resonance during non-invasive brain stimulation: Stochastic resonance in perceptual decision-making

2017 ◽  
Author(s):  
Onno van der Groen ◽  
Matthew F. Tang ◽  
Nicole Wenderoth ◽  
Jason B. Mattingley
Keyword(s):  
Decision Making ◽  
Visual Cortex ◽  
Stochastic Resonance ◽  
Decision Process ◽  
Random Noise ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Evidence Accumulation ◽  
Neural Noise ◽  
Stimulation Of

Summary:Perceptual decision-making relies on the gradual accumulation of noisy sensory evidence until a specified boundary is reached and an appropriate response is made. It might be assumed that adding noise to a stimulus, or to the neural systems involved in its processing, would interfere with the decision process. But it has been suggested that adding an optimal amount of noise can, under appropriate conditions, enhance the quality of subthreshold signals in nonlinear systems, a phenomenon known as stochastic resonance. Here we asked whether perceptual decisions obey these stochastic resonance principles by adding noise directly to the visual cortex using transcranial random noise stimulation (tRNS) while participants judged the direction of motion in foveally presented random-dot motion arrays. Consistent with the stochastic resonance account, we found that adding tRNS bilaterally to visual cortex enhanced decision-making when stimuli were just below, but not well below or above, perceptual threshold. We modelled the data under a drift diffusion framework to isolate the specific components of the multi-stage decision process that were influenced by the addition of neural noise. This modelling showed that tRNS increased drift rate, which indexes the rate of evidence accumulation, but had no effect on bound separation or non-decision time. These results were specific to bilateral stimulation of visual cortex; control experiments involving unilateral stimulation of left and right visual areas showed no influence of random noise stimulation. Our study is the first to provide causal evidence that perceptual decision-making is susceptible to a stochastic resonance effect induced by tRNS, and that this effect arises from selective enhancement of the rate of evidence accumulation for sub-threshold sensory events.

scholarly journals Visuo-spatial attention influences the rate of evidence accumulation during perceptual decision making

2015 ◽  
Vol 9 ◽  
Author(s):  
Loughnane Gerard ◽  
Newman Daniel ◽  
Bellgrove Mark ◽  
Lalor Edmund ◽  
Kelly Simon ◽  
...  
Keyword(s):  
Decision Making ◽  
Spatial Attention ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Evidence Accumulation

scholarly journals Neural Correlates of Evidence and Urgency During Human Perceptual Decision-Making in Dynamically Changing Conditions

2020 ◽  
Vol 30 (10) ◽  
pp. 5471-5483
Author(s):  
Y Yau ◽  
M Dadar ◽  
M Taylor ◽  
Y Zeighami ◽  
L K Fellows ◽  
...  
Keyword(s):  
Decision Making ◽  
Computational Models ◽  
Sensory Information ◽  
Neural Correlates ◽  
Primate Research ◽  
Perceptual Decision Making ◽  
Emotional Information ◽  
Perceptual Decision ◽  
The Face ◽  
The Brain

Abstract Current models of decision-making assume that the brain gradually accumulates evidence and drifts toward a threshold that, once crossed, results in a choice selection. These models have been especially successful in primate research; however, transposing them to human fMRI paradigms has proved it to be challenging. Here, we exploit the face-selective visual system and test whether decoded emotional facial features from multivariate fMRI signals during a dynamic perceptual decision-making task are related to the parameters of computational models of decision-making. We show that trial-by-trial variations in the pattern of neural activity in the fusiform gyrus reflect facial emotional information and modulate drift rates during deliberation. We also observed an inverse-urgency signal based in the caudate nucleus that was independent of sensory information but appeared to slow decisions, particularly when information in the task was ambiguous. Taken together, our results characterize how decision parameters from a computational model (i.e., drift rate and urgency signal) are involved in perceptual decision-making and reflected in the activity of the human brain.

scholarly journals Unification of Countermanding and Perceptual Decision-making

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.

scholarly journals Behavioural and neural signatures of perceptual evidence accumulation are modulated by pupil-linked arousal

2018 ◽  
Author(s):  
Jochem van Kempen ◽  
Gerard M. Loughnane ◽  
Daniel P. Newman ◽  
Simon P. Kelly ◽  
Alexander Thiele ◽  
...  
Keyword(s):  
Decision Making ◽  
Pupil Diameter ◽  
Target Selection ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Evidence Accumulation ◽  
Attentional Engagement ◽  
The Relationship ◽  
Processing Steps

AbstractThe timing and accuracy of perceptual decision making is exquisitely sensitive to fluctuations in arousal. Although extensive research has highlighted the role of neural evidence accumulation in forming decisions, our understanding of how arousal impacts these processes remains limited. Here we isolated electrophysiological signatures of evidence accumulation alongside signals reflecting target selection, attentional engagement and motor output and examined their modulation as a function of both tonic and phasic arousal, indexed by baseline and task-evoked pupil diameter, respectively. For both pupillometric measures, the relationship with reaction time was best described by a second-order, U-shaped, polynomial. Additionally, the two pupil measures were predictive of a unique set of EEG signatures that together represent multiple information processing steps of perceptual decision-making, including evidence accumulation. Finally, we found that behavioural variability associated with fluctuations in both tonic and phasic arousal was largely mediated by variability in evidence accumulation.

scholarly journals Inter-trial effects in visual pop-out search: Factorial comparison of Bayesian updating models

2018 ◽  
Author(s):  
Fredrik Allenmark ◽  
Hermann J. Müller ◽  
Zhuanghua Shi
Keyword(s):  
Decision Making ◽  
Reaction Time ◽  
Model Comparison ◽  
Accumulation Rate ◽  
Information Processing Speed ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Decision Bias ◽  
Evidence Accumulation ◽  
Starting Point

AbstractMany previous studies on visual search have reported inter-trial effects, that is, observers respond faster when some target property, such as a defining feature or dimension, or the response associated with the target repeats versus changes across consecutive trial episodes. However, what processes drive these inter-trial effects is still controversial. Here, we investigated this question using a combination of Bayesian modeling of belief updating and evidence accumulation modeling in perceptual decision-making. In three visual singleton (‘pop-out’) search experiments, we explored how the probability of the response-critical states of the search display (e.g., target presence/absence) and the repetition/switch of the target-defining dimension (color/ orientation) affect reaction time distributions. The results replicated the mean reaction time (RT) inter-trial and dimension repetition/switch effects that have been reported in previous studies. Going beyond this, to uncover the underlying mechanisms, we used the Drift-Diffusion Model (DDM) and the Linear Approach to Threshold with Ergodic Rate (LATER) model to explain the RT distributions in terms of decision bias (starting point) and information processing speed (evidence accumulation rate). We further investigated how these different aspects of the decision-making process are affected by different properties of stimulus history, giving rise to dissociable inter-trial effects. We approached this question by (i) combining each perceptual decision making model (DDM or LATER) with different updating models, each specifying a plausible rule for updating of either the starting point or the rate, based on stimulus history, and (ii) comparing every possible combination of trial-wise updating mechanism and perceptual decision model in a factorial model comparison. Consistently across experiments, we found that the (recent) history of the response-critical property influences the initial decision bias, while repetition/switch of the target-defining dimension affects the accumulation rate, likely reflecting an implicit ‘top-down’ modulation process. This provides strong evidence of a disassociation between response- and dimension-based inter-trial effects.

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