scholarly journals The impact of learning on perceptual decisions and its implication for speed-accuracy tradeoffs

2018 ◽  
Author(s):  
André G. Mendonça ◽  
Jan Drugowitsch ◽  
M. Inês Vicente ◽  
Eric DeWitt ◽  
Alexandre Pouget ◽  
...  
Keyword(s):  
Decision Making ◽  
Learning Strategy ◽  
Primary Source ◽  
Critical Factor ◽  
Specific Pattern ◽  
Perceptual Decision Making ◽  
History Effects ◽  
Sensory Evidence ◽  
The Impact ◽  
Speed Accuracy

SUMMARYIn standard models of perceptual decision-making, noisy sensory evidence is considered to be the primary source of choice errors and the accumulation of evidence needed to overcome this noise gives rise to speed-accuracy tradeoffs. Here, we investigated how the history of recent choices and their outcomes interacts with these processes using a combination of theory and experiment. We found that the speed and accuracy of performance of rats on olfactory decision tasks could be best explained by a Bayesian model that combines reinforcement-based learning with accumulation of uncertain sensory evidence. This model predicted the specific pattern of trial history effects that were found in the data. The results suggest that learning is a critical factor contributing to speed-accuracy tradeoffs in decision-making and that task history effects are not simply biases but rather the signatures of an optimal learning strategy.

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 Transient neuronal suppression for exploitation of new sensory evidence

2022 ◽  
Vol 13 (1) ◽  
Author(s):  
Maxwell Shinn ◽  
Daeyeol Lee ◽  
John D. Murray ◽  
Hyojung Seo
Keyword(s):  
Decision Making ◽  
Neural Activity ◽  
Temporal Integration ◽  
Motor Preparation ◽  
Stimulus Onset ◽  
Frontal Eye Field ◽  
Perceptual Decision Making ◽  
Behavioral Studies ◽  
The Face ◽  
Sensory Evidence

AbstractIn noisy but stationary environments, decisions should be based on the temporal integration of sequentially sampled evidence. This strategy has been supported by many behavioral studies and is qualitatively consistent with neural activity in multiple brain areas. By contrast, decision-making in the face of non-stationary sensory evidence remains poorly understood. Here, we trained monkeys to identify and respond via saccade to the dominant color of a dynamically refreshed bicolor patch that becomes informative after a variable delay. Animals’ behavioral responses were briefly suppressed after evidence changes, and many neurons in the frontal eye field displayed a corresponding dip in activity at this time, similar to that frequently observed after stimulus onset but sensitive to stimulus strength. Generalized drift-diffusion models revealed consistency of behavior and neural activity with brief suppression of motor output, but not with pausing or resetting of evidence accumulation. These results suggest that momentary arrest of motor preparation is important for dynamic perceptual decision making.

scholarly journals A Diffusion Model Approach for Understanding the Impact of 17 Interventions on the Race Implicit Association Test

2020 ◽  
Author(s):  
Jessica Röhner ◽  
Calvin K. Lai
Keyword(s):  
Decision Making ◽  
Implicit Association Test ◽  
Association Test ◽  
Implicit Measure ◽  
Implicit Association ◽  
Implicit Measures ◽  
Long Term Effects ◽  
Sham Intervention ◽  
The Impact ◽  
Speed Accuracy

<p>Performance on implicit measures reflects construct-specific and non-construct-specific processes. This creates an interpretive issue for understanding interventions to change implicit measures: change in performance could reflect changes in the constructs-of-interest or changes in other mental processes. We re-analyzed data from six studies (<i>N</i> = 23,342) to examine the process-level effects of 17 interventions and one sham intervention to change race Implicit Association Test (IAT) performance. Diffusion models decompose overall IAT performance (<i>D</i>-scores) into construct-specific (ease of decision-making), and non-construct-specific processes (speed-accuracy tradeoffs, non-decision-related processes like motor execution). Interventions that effectively reduced <i>D-</i>scores changed ease of decision-making on compatible and incompatible trials. They also eliminated differences in speed-accuracy tradeoffs between compatible and incompatible trials. Non-decision-related processes were impacted by two interventions only. There was little evidence that interventions had any long-term effects. These findings highlight the value of diffusion modeling for understanding the mechanisms by which interventions affect implicit measure performance.</p>

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.

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 The impact of MRI scanner environment on perceptual decision-making

2015 ◽  
Vol 48 (1) ◽  
pp. 184-200 ◽  
Author(s):  
Leendert van Maanen ◽  
Birte U. Forstmann ◽  
Max C. Keuken ◽  
Eric-Jan Wagenmakers ◽  
Andrew Heathcote
Keyword(s):  
Decision Making ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
The Impact

Rats and Humans Can Optimally Accumulate Evidence for Decision-Making

Science ◽  
2013 ◽  
Vol 340 (6128) ◽  
pp. 95-98 ◽  
Author(s):  
Bingni W. Brunton ◽  
Matthew M. Botvinick ◽  
Carlos D. Brody
Keyword(s):  
Decision Making ◽  
Primary Source ◽  
Powerful Method ◽  
Fundamental Component ◽  
Modeling Approach ◽  
Pulse Timing ◽  
Decision Making Processes ◽  
Sensory Evidence ◽  
Internal Properties

The gradual and noisy accumulation of evidence is a fundamental component of decision-making, with noise playing a key role as the source of variability and errors. However, the origins of this noise have never been determined. We developed decision-making tasks in which sensory evidence is delivered in randomly timed pulses, and analyzed the resulting data with models that use the richly detailed information of each trial’s pulse timing to distinguish between different decision-making mechanisms. This analysis allowed measurement of the magnitude of noise in the accumulator’s memory, separately from noise associated with incoming sensory evidence. In our tasks, the accumulator’s memory was noiseless, for both rats and humans. In contrast, the addition of new sensory evidence was the primary source of variability. We suggest our task and modeling approach as a powerful method for revealing internal properties of decision-making processes.

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.

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