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 Neural correlates of evidence and urgency during human perceptual decision-making in dynamically changing conditions

2019 ◽  
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

AbstractCurrent models of decision-making assume that the brain gradually accumulates evidence and drifts towards a threshold which, 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 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.

Credo for optimality

2018 ◽  
Vol 41 ◽  
Author(s):  
Alan A. Stocker
Keyword(s):  
Decision Making ◽  
Information Processing ◽  
Sensory Information ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Sensory Information Processing ◽  
The Brain ◽  
Additional Constraints

AbstractOptimal or suboptimal, Rahnev & Denison (R&D) rightly argue that this ill-defined distinction is not useful when comparing models of perceptual decision making. However, what they miss is how valuable the focus on optimality has been in deriving these models in the first place. Rather than prematurely abandon the optimality assumption, we should refine this successful normative hypothesis with additional constraints that capture specific limitations of (sensory) information processing in the brain.

scholarly journals Cortical circuit-based lossless neural integrator for perceptual decision-making

2017 ◽  
Author(s):  
Jung H. Lee ◽  
Joji Tsunada ◽  
Sujith Vijayan ◽  
Yale E. Cohen
Keyword(s):  
Decision Making ◽  
Computational Models ◽  
Empirical Studies ◽  
Activity Patterns ◽  
Sensory Information ◽  
Cortical Circuits ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Sensory Evidence ◽  
Cortical Circuit

AbstractThe intrinsic uncertainty of sensory information (i.e., evidence) does not necessarily deter an observer from making a reliable decision. Indeed, uncertainty can be reduced by integrating (accumulating) incoming sensory evidence. It is widely thought that this accumulation is instantiated via recurrent rate-code neural networks. Yet, these networks do not fully explain important aspects of perceptual decision-making, such as a subject’s ability to retain accumulated evidence during temporal gaps in the sensory evidence. Here, we utilized computational models to show that cortical circuits can switch flexibly between ‘retention’ and ‘integration’ modes during perceptual decision-making. Further, we found that, depending on how the sensory evidence was readout, we could simulate ‘stepping’ and ‘ramping’ activity patterns, which may be analogous to those seen in different studies of decision-making in the primate parietal cortex. This finding may reconcile these previous empirical studies because it suggests these two activity patterns emerge from the same mechanism.

scholarly journals Evidence accumulation during perceptual decision-making is sensitive to the dynamics of attentional selection

2019 ◽  
Author(s):  
Dragan Rangelov ◽  
Jason B. Mattingley
Keyword(s):  
Decision Making ◽  
Brain Activity ◽  
Sensory Information ◽  
Neural Correlates ◽  
Attentional Selection ◽  
Adaptive Behaviour ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Sensory Inputs

AbstractThe ability to select and combine multiple sensory inputs in support of accurate decisions is a hallmark of adaptive behaviour. Attentional selection is often needed to prioritize stimuli that are task-relevant and to attenuate potentially distracting sources of sensory information. As most studies of perceptual decision-making to date have made use of task-relevant stimuli only, relatively little is known about how attention modulates decision making. To address this issue, we developed a novel ‘integrated’ decision-making task, in which participants judged the average direction of successive target motion signals while ignoring concurrent and spatially overlapping distractor motion signals. In two experiments that varied the role of attentional selection, we used linear regression to quantify the influence of target and distractor stimuli on behaviour. Using electroencephalography, we characterised the neural correlates of decision making, attentional selection and feature-specific responses to target and distractor signals. While targets strongly influenced perceptual decisions and associated neural activity, we also found that concurrent and spatially coincident distractors exerted a measurable bias on both behaviour and brain activity. Our findings suggest that attention operates as a real-time but imperfect filter during perceptual decision-making by dynamically modulating the contributions of task-relevant and irrelevant sensory inputs.

scholarly journals Sensor-Level Wavelet Analysis Reveals EEG Biomarkers of Perceptual Decision-Making

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2461
Author(s):  
Alexander Kuc ◽  
Vadim V. Grubov ◽  
Vladimir A. Maksimenko ◽  
Natalia Shusharina ◽  
Alexander N. Pisarchik ◽  
...  
Keyword(s):  
Decision Making ◽  
Sensory Information ◽  
Stimulus Onset ◽  
Perceptual Process ◽  
Perceptual Decision Making ◽  
Beta Band ◽  
Perceptual Decision ◽  
Time Frequency ◽  
Band Power ◽  
Sensory Features

Perceptual decision-making requires transforming sensory information into decisions. An ambiguity of sensory input affects perceptual decisions inducing specific time-frequency patterns on EEG (electroencephalogram) signals. This paper uses a wavelet-based method to analyze how ambiguity affects EEG features during a perceptual decision-making task. We observe that parietal and temporal beta-band wavelet power monotonically increases throughout the perceptual process. Ambiguity induces high frontal beta-band power at 0.3–0.6 s post-stimulus onset. It may reflect the increasing reliance on the top-down mechanisms to facilitate accumulating decision-relevant sensory features. Finally, this study analyzes the perceptual process using mixed within-trial and within-subject design. First, we found significant percept-related changes in each subject and then test their significance at the group level. Thus, observed beta-band biomarkers are pronounced in single EEG trials and may serve as control commands for brain-computer interface (BCI).

scholarly journals Flexible categorization in perceptual decision making

2020 ◽  
Author(s):  
Genís Prat-Ortega ◽  
Klaus Wimmer ◽  
Alex Roxin ◽  
Jaime de la Rocha
Keyword(s):  
Decision Making ◽  
Large Body ◽  
Network Models ◽  
Perceptual Decision Making ◽  
Drift Diffusion ◽  
Perceptual Decision ◽  
Attractor Dynamics ◽  
Attractor Model ◽  
Winner Take All ◽  
The Brain

AbstractPerceptual decisions require the brain to make categorical choices based on accumulated sensory evidence. The underlying computations have been studied using either phenomenological drift diffusion models or neurobiological network models exhibiting winner-take-all attractor dynamics. Although both classes of models can account for a large body of experimental data, it remains unclear to what extent their dynamics are qualitatively equivalent. Here we show that, unlike the drift diffusion model, the attractor model can operate in different integration regimes: an increase in the stimulus fluctuations or the stimulus duration promotes transitions between decision-states leading to a crossover between weighting mostly early evidence (primacy regime) to weighting late evidence (recency regime). Between these two limiting cases, we found a novel regime, which we name flexible categorization, in which fluctuations are strong enough to reverse initial categorizations, but only if they are incorrect. This asymmetry in the reversing probability results in a non-monotonic psychometric curve, a novel and distinctive feature of the attractor model. Finally, we show psychophysical evidence for the crossover between integration regimes predicted by the attractor model and for the relevance of this new regime. Our findings point to correcting transitions as an important yet overlooked feature of perceptual decision making.

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 Strategy-dependent effects of working-memory limitations on human perceptual decision-making

2021 ◽  
Author(s):  
Kyra Schapiro ◽  
Kresimir Josic ◽  
Zachary Kilpatrick ◽  
Joshua I Gold
Keyword(s):  
Decision Making ◽  
Working Memory ◽  
Decision Variable ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Human Psychophysics ◽  
Decision Variables ◽  
The Impact ◽  
The Brain ◽  
Over Time

Deliberative decisions based on an accumulation of evidence over time depend on working memory, and working memory has limitations, but how these limitations affect deliberative decision-making is not understood. We used human psychophysics to assess the impact of working-memory limitations on the fidelity of a continuous decision variable. Participants decided the average location of multiple visual targets. This computed, continuous decision variable degraded with time and capacity in a manner that depended critically on the strategy used to form the decision variable. This dependence reflected whether the decision variable was computed either: 1) immediately upon observing the evidence, and thus stored as a single value in memory; or 2) at the time of the report, and thus stored as multiple values in memory. These results provide important constraints on how the brain computes and maintains temporally dynamic decision variables.

scholarly journals A cerebellar role in evidence-guided decision-making

2018 ◽  
Author(s):  
Ben Deverett ◽  
Sue Ann Koay ◽  
Marlies Oostland ◽  
Samuel S.-H. Wang
Keyword(s):  
Decision Making ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Two Photon ◽  
Related Information ◽  
Distributed Computations ◽  
Lateral Posterior ◽  
Crus I ◽  
The Brain ◽  
Decision Errors

To make successful evidence-based decisions, the brain must rapidly and accurately transform sensory inputs into specific goal-directed behaviors. Most experimental work on this subject has focused on forebrain mechanisms. Here we show that during perceptual decision-making over a period of seconds, decision-, sensory-, and error-related information converge on the lateral posterior cerebellum in crus I, a structure that communicates bidirectionally with numerous forebrain regions. We trained mice on a novel evidence-accumulation task and demonstrated that cerebellar inactivation reduces behavioral accuracy without impairing motor parameters of action. Using two-photon calcium imaging, we found that Purkinje cell somatic activity encoded choice- and evidence-related variables. Decision errors were represented by dendritic calcium spikes, which are known to drive plasticity. We propose that cerebellar circuitry may contribute to the set of distributed computations in the brain that support accurate perceptual decision-making.

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