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 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.

scholarly journals Task complexity temporally extends the causal requirement for visual cortex in perception

2021 ◽  
Author(s):  
Matthijs N Oude Lohuis ◽  
Jean L Pie ◽  
Pietro Marchesi ◽  
Jorrit S Montijn ◽  
Christiaan P J de Kock ◽  
...  
Keyword(s):  
Decision Making ◽  
Task Complexity ◽  
Activity Patterns ◽  
Late Phase ◽  
Sensory Information ◽  
Visual Response ◽  
Perceptual Decision Making ◽  
Related Activity ◽  
Sensory Stimuli ◽  
Perceptual Decision

The transformation of sensory inputs into behavioral outputs is characterized by an interplay between feedforward and feedback operations in cortical hierarchies. Even in simple sensorimotor transformations, recurrent processing is often expressed in primary cortices in a late phase of the cortical response to sensory stimuli. This late phase is engaged by attention and stimulus complexity, and also encodes sensory-independent factors, including movement and report-related variables. However, despite its pervasiveness, the nature and function of late activity in perceptual decision-making remain unclear. We tested whether the function of late activity depends on the complexity of a sensory change-detection task. Complexity was based on increasing processing requirements for the same sensory stimuli. We found that the temporal window in which V1 is necessary for perceptual decision-making was extended when we increased task complexity, independently of the presented visual stimulus. This window overlapped with the emergence of report-related activity and decreased noise correlations in V1. The onset of these co-occurring activity patterns was time-locked to and preceded reaction time, and predicted the reduction in behavioral performance obtained by optogenetically silencing late V1 activity (>200 ms after stimulus onset), a result confirmed by a second multisensory task with different requirements. Thus, although early visual response components encode all sensory information necessary to solve the task, V1 is not simply relaying information to higher-order areas transforming it into behavioral responses. Rather, task complexity determines the temporal extension of a loop of recurrent activity, which overlaps with report-related activity and determines how perceptual decisions are built.

scholarly journals Flexible categorization in perceptual decision making

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Genís Prat-Ortega ◽  
Klaus Wimmer ◽  
Alex Roxin ◽  
Jaime de la Rocha
Keyword(s):  
Decision Making ◽  
Network Models ◽  
Drift Diffusion Model ◽  
Perceptual Decision Making ◽  
Drift Diffusion ◽  
Perceptual Decision ◽  
Attractor Dynamics ◽  
Attractor Model ◽  
Sensory Evidence ◽  
Winner Take All

AbstractPerceptual decisions rely on accumulating sensory evidence. This computation has been studied using either drift diffusion models or neurobiological network models exhibiting winner-take-all attractor dynamics. Although both models can account for a large amount of data, it remains unclear whether their dynamics are qualitatively equivalent. Here we show that in the attractor model, but not in the drift diffusion model, an increase in the stimulus fluctuations or the stimulus duration promotes transitions between decision states. The increase in the number of transitions leads to a crossover between weighting mostly early evidence (primacy) to weighting late evidence (recency), a prediction we validate with psychophysical data. Between these two limiting cases, we found a novel flexible categorization regime, in which fluctuations can reverse initially-incorrect categorizations. This reversal asymmetry results in a non-monotonic psychometric curve, a distinctive feature of the attractor model. Our findings point to correcting decision reversals as an important feature of perceptual decision making.

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 Decoupling sensory from decisional choice biases in perceptual decision making

2016 ◽  
Author(s):  
Daniel Linares ◽  
David Aguilar-Lleyda ◽  
Joan López-Moliner
Keyword(s):  
Decision Making ◽  
Theory Model ◽  
Decision Makers ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Response Mapping ◽  
Task Instructions ◽  
Detection Theory Model ◽  
Sensory Evidence ◽  
Choice Bias

ABSTRACTThe contribution of sensory and decisional processes to perceptual decision making is still unclear, even in simple perceptual tasks. When decision makers need to select an action from a set of balanced alternatives, any tendency to choose one alternative more often— choice bias—is consistent with a bias in the sensory evidence, but also with a preference to select that alternative independently of the sensory evidence. To decouple sensory from decisional biases, here we asked humans to perform a simple perceptual discrimination task with two symmetric alternatives under two different task instructions. The instructions varied the response mapping between perception and the category of the alternatives. We found that from 32 participants, 30 exhibited sensory biases and 15 decisional biases. The decisional biases were consistent with a criterion change in a simple signal detection theory model. Perceptual decision making, thus, even in simple scenarios, is affected by sensory and decisional choice biases.IMPACT STATEMENTPerceptual decision making, even in simple scenarios, is affected by sensory and decisional choice biases.

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.

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