scholarly journals A race between Proactive and Reactive processes during perceptual decisions

2020 ◽  
Author(s):  
Lluís Hernández-Navarro ◽  
Ainhoa Hermoso-Mendizabal ◽  
Daniel Duque ◽  
Jaime de la Rocha ◽  
Alexandre Hyafil
Keyword(s):  
Decision Making ◽  
Reaction Time ◽  
Stimulus Presentation ◽  
Auditory Task ◽  
Decision Threshold ◽  
Perceptual Decision Making ◽  
Evidence Accumulation ◽  
Standard Models ◽  
Reactive Processes ◽  
Action Initiation

Standard models of perceptual decision-making postulate that a response is triggered in reaction to stimulus presentation when the accumulated stimulus evidence reaches a decision threshold. This framework excludes however the possibility that informed responses are generated proactively at a time independent of stimulus. Here, we find that, in a free reaction time auditory task in rats, reactive and proactive responses coexist, suggesting that choice selection and motor initiation, commonly viewed as serial processes, are decoupled in general. We capture this behavior by a novel model in which proactive and reactive responses are triggered whenever either of two competing processes, respectively Action Initiation or Evidence Accumulation, reaches a bound. In both types of response, the choice is ultimately informed by the Evidence Accumulation process. By including the Action Initiation process, the model readily explains premature responses, urgency effects at long reaction times and the slowing of the responses as animals get satiated and tired during sessions. Moreover, it successfully predicts reaction time distributions when the stimulus was either delayed, advanced or omitted. Overall, these results fundamentally extend standard models of evidence accumulation in decision making by showing that proactive and reactive processes compete for the generation of responses.

scholarly journals Proactive and reactive accumulation-to-bound processes compete during perceptual decisions

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Lluís Hernández-Navarro ◽  
Ainhoa Hermoso-Mendizabal ◽  
Daniel Duque ◽  
Jaime de la Rocha ◽  
Alexandre Hyafil
Keyword(s):  
Decision Making ◽  
Reaction Time ◽  
Reaction Times ◽  
Stimulus Presentation ◽  
Auditory Task ◽  
Decision Threshold ◽  
Perceptual Decision Making ◽  
Evidence Accumulation ◽  
Standard Models ◽  
Action Initiation

AbstractStandard models of perceptual decision-making postulate that a response is triggered in reaction to stimulus presentation when the accumulated stimulus evidence reaches a decision threshold. This framework excludes however the possibility that informed responses are generated proactively at a time independent of stimulus. Here, we find that, in a free reaction time auditory task in rats, reactive and proactive responses coexist, suggesting that choice selection and motor initiation, commonly viewed as serial processes, are decoupled in general. We capture this behavior by a novel model in which proactive and reactive responses are triggered whenever either of two competing processes, respectively Action Initiation or Evidence Accumulation, reaches a bound. In both types of response, the choice is ultimately informed by the Evidence Accumulation process. The Action Initiation process readily explains premature responses, contributes to urgency effects at long reaction times and mediates the slowing of the responses as animals get satiated and tired during sessions. Moreover, it successfully predicts reaction time distributions when the stimulus was either delayed, advanced or omitted. Overall, these results fundamentally extend standard models of evidence accumulation in decision making by showing that proactive and reactive processes compete for the generation of responses.

Sensory evidence integration and action initiation occur in parallel during perceptual decisions

2020 ◽  
Author(s):  
Lluís Hernández-Navarro ◽  
Ainhoa Hermoso-Mendizabal ◽  
Daniel Duque ◽  
Alexandre Hyafil ◽  
Jaime de la Rocha
Keyword(s):  
Time Pressure ◽  
Reaction Times ◽  
Stimulus Presentation ◽  
Perceptual Decision Making ◽  
Evidence Accumulation ◽  
Action Preparation ◽  
Action Model ◽  
The Brain ◽  
Evidence Integration ◽  
Action Initiation

It is commonly assumed that, during perceptual decisions, the brain integrates stimulus evidence until reaching a decision, and then performs the response. There are conditions, however (e.g. time pressure), in which the initiation of the response must be prepared in anticipation of the stimulus presentation. It is therefore not clear when the timing and the choice of perceptual responses depend exclusively on evidence accumulation, or when preparatory motor signals may interfere with this process. Here, we find that, in a free reaction time auditory discrimination task in rats, the timing of fast responses does not depend on the stimulus, although the choices do, suggesting a decoupling of the mechanisms of action initiation and choice selection. This behavior is captured by a novel model, the Parallel Sensory Integration and Action Model (PSIAM), in which response execution is triggered whenever one of two processes, Action Initiation or Evidence Accumulation, reaches a bound, while choice category is always set by the latter. Based on this separation, the model accurately predicts the distribution of reaction times when the stimulus is omitted, advanced or delayed. Furthermore, we show that changes in Action Initiation mediates both post-error slowing and a gradual slowing of the responses within each session. Overall, these results extend the standard models of perceptual decision-making, and shed a new light on the interaction between action preparation and evidence accumulation.

scholarly journals Evidence or Confidence: What Really Accumulates During a Decision?

2021 ◽  
Author(s):  
Douglas G. Lee ◽  
Giovanni Pezzulo
Keyword(s):  
Decision Making ◽  
Empirical Evidence ◽  
Alternative Hypothesis ◽  
Decision Threshold ◽  
Drift Diffusion Model ◽  
Drift Diffusion ◽  
Evidence Accumulation ◽  
Confidence Assessment ◽  
Standard Models ◽  
Post Hoc

Assessing one's confidence in one's choices is of paramount importance to making adaptive decisions, and it is thus no surprise that humans excel in this ability. However, standard models of decision-making, such as the drift-diffusion model (DDM), treat confidence assessment as a post-hoc or parallel process that does not directly influence the choice -- the latter depends only on accumulated evidence. Here, we pursue the alternative hypothesis that what is accumulated during a decision is confidence (that the to-be selected option is the best) rather than raw evidence. Accumulating confidence has the appealing consequence that the decision threshold corresponds to a desired level of confidence for the choice, and that confidence improvements can be traded off against the resources required to secure them. We show that most previous findings on perceptual and value-based decisions traditionally interpreted from an evidence-accumulation perspective can be explained more parsimoniously from our novel confidence-driven perspective. Furthermore, we show that our novel confidence-driven DDM (cDDM) naturally generalizes to any number of decisions -- which is notoriously extemporaneous using traditional DDM or related models. Finally, we discuss future empirical evidence that could be useful in adjudicating between these alternatives.

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.

scholarly journals The latency of a visual evoked potential tracks the onset of decision making

2018 ◽  
Author(s):  
Michael D. Nunez ◽  
Aishwarya Gosai ◽  
Joachim Vandekerckhove ◽  
Ramesh Srinivasan
Keyword(s):  
Decision Making ◽  
Response Time ◽  
Response Times ◽  
Stimulus Presentation ◽  
Sensory Stimulus ◽  
Visual Noise ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Evidence Accumulation ◽  
Visual Encoding

AbstractEncoding of a sensory stimulus is believed to be the first step in perceptual decision making. Previous research has shown that electrical signals recorded from the human brain track evidence accumulation during perceptual decision making (Gold and Shadlen, 2007; O’Connell et al., 2012; Philiastides et al., 2014). In this study we directly tested the hypothesis that the latency of the N200 recorded by EEG (a negative peak occurring between 150 and 275 ms after stimulus presentation in human participants) reflects the visual encoding time (VET) required for completion of figure-ground segregation before evidence accumulation. We show that N200 latencies vary across individuals, are modulated by external visual noise, and increase response time by x milliseconds when they increase by x milliseconds, reflecting a linear regression slope of 1. Simulations of cognitive decision-making theory show that variation in human response times not related to evidence accumulation (including VET) are tracked by the fastest response times. A relationship with a slope of 1 between N200 latencies and VET was found by fitting a linear model between trial-averaged N200 latencies and the 10th percentiles of response times. A slope of 1 was also found between single-trial N200 latencies and response times. Fitting a novel neuro-cognitive model of decision-making also yielded a slope of 1 between N200 latency and non-decision time in multiple visual noise conditions, indicating that N200 latencies track the completion of visual encoding and the onset of evidence accumulation. The N200 waveforms were localized to the cortical surface at distributed temporal and extrastriate locations, consistent with a distributed network engaged in figure-ground segregation of the target stimulus.Significance StatementEncoding of a sensory stimulus is believed to be the first step in perceptual decision making. In this study, we report evidence that visual evoked potentials (EPs) around 200 ms after stimulus presentation track the time of visual figure-ground segregation before the onset of evidence accumulation during decision making. These EP latencies vary across individuals, are modulated by external visual noise, and increase response time by x milliseconds when they increase by x milliseconds. Hierarchical Bayesian model-fitting was also used to relate these EPs to a specific cognitive parameter that tracks time related to visual encoding in a decision-making model of response time. This work adds to the growing literature that suggests that EEG signals can track the component cognitive processes of 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

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 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 Foraging as an evidence accumulation process

2018 ◽  
Author(s):  
Jacob D. Davidson ◽  
Ahmed El Hady
Keyword(s):  
Decision Making ◽  
Diffusion Processes ◽  
Optimal Strategies ◽  
Theoretical Work ◽  
Decision Threshold ◽  
Residence Times ◽  
Marginal Value ◽  
Evidence Accumulation ◽  
Current Resource ◽  
Noisy Measurements

AbstractA canonical foraging task is the patch-leaving problem, in which a forager must decide to leave a current resource in search for another. Theoretical work has derived optimal strategies for when to leave a patch, and experiments have tested for conditions where animals do or do not follow an optimal strategy. Nevertheless, models of patch-leaving decisions do not consider the imperfect and noisy sampling process through which an animal gathers information, and how this process is constrained by neurobiological mechanisms. In this theoretical study, we formulate an evidence accumulation model of patch-leaving decisions where the animal averages over noisy measurements to estimate the state of the current patch and the overall environment. Evidence accumulation models belong to the class of drift diffusion processes and have been used to model decision making in different contexts especially in cognitive and systems neuroscience. We solve the model for conditions where foraging decisions are optimal and equivalent to the marginal value theorem, and perform simulations to analyze deviations from optimal when these conditions are not met. By adjusting the drift rate and decision threshold, the model can represent different “strategies”, for example an increment-decrement or counting strategy. These strategies yield identical decisions in the limiting case but differ in how patch residence times adapt when the foraging environment is uncertain. To account for sub-optimal decisions, we introduce an energy-dependent utility function that predicts longer than optimal patch residence times when food is plentiful. Our model provides a quantitative connection between ecological models of foraging behavior and evidence accumulation models of decision making. Moreover, it provides a theoretical framework for potential experiments which seek to identify neural circuits underlying patch leaving decisions.

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