scholarly journals Regulation of evidence accumulation by pupil-linked arousal processes

2018 ◽  
Author(s):  
Waitsang Keung ◽  
Todd A. Hagen ◽  
Robert C. Wilson
Keyword(s):  
Decision Making ◽  
Individual Differences ◽  
Large Body ◽  
Order Effects ◽  
Auditory Information ◽  
Perceptual Decision Making ◽  
Pupil Response ◽  
Evidence Accumulation ◽  
Integration Kernel ◽  
Over Time

AbstractIntegrating evidence over time is crucial for effective decision making. For simple perceptual decisions, a large body of work suggests that humans and animals are capable of integrating evidence over time fairly well, but that their performance is far from optimal. This suboptimality is thought to arise from a number of different sources including: (1) noise in sensory and motor systems, (2) unequal weighting of evidence over time, (3) order effects from previous trials and (4) irrational side biases for one choice over another. In this work we investigated these di.erent sources of suboptimality and how they are related to pupil dilation, a putative correlate of norepinephrine tone. In particular, we measured pupil response in humans making a series of decisions based on rapidly-presented auditory information in an evidence accumulation task. We found that people exhibited all four types of suboptimality, and that some of these suboptimalities covaried with each other across participants. Pupillometry showed that only noise and the uneven weighting of evidence over time, the ‘integration kernel’, were related to the change in pupil response during the stimulus. Moreover, these two different suboptimalities were related to different aspects of the pupil signal, with the individual differences in pupil response associated with individual differences in integration kernel, while trial-by-trial fluctuations in pupil response were associated with trial-by-trial fluctuations in noise. These results suggest that di.erent sources of suboptimality in human perceptual decision making are related to distinct pupil-linked processes possibly related to tonic and phasic norepinephrine activity.

scholarly journals A divisive model of evidence accumulation explains uneven weighting of evidence over time

2019 ◽  
Author(s):  
Waitsang Keung ◽  
Todd A. Hagen ◽  
Robert C. Wilson
Keyword(s):  
Decision Making ◽  
Total Activity ◽  
Neural System ◽  
Perceptual Decision Making ◽  
Evidence Accumulation ◽  
Integration Kernel ◽  
Neural Processes ◽  
Divisive Normalization ◽  
Human Participants ◽  
Over Time

SummaryDivisive normalization has long been used to account for computations in various neural processes and behaviours. The model proposes that inputs into a neural system are divisively normalized by the total activity of the system. More recently, dynamical versions of divisive normalization have been shown to account for how neural activity evolves over time in value-based decision making. Despite its ubiquity, divisive normalization has not been studied in decisions that require evidence to be integrated over time. Such decisions are important when we do not have all the information available at once. A key feature of such decisions is how evidence is weighted over time, known as the integration ‘kernel’. Here we provide a formal expression for the integration kernel in divisive normalization, and show that divisive normalization can quantitatively account for the perceptual decision making behaviour of 133 human participants, performing as well as the state-of-the-art Drift Diffusion Model, the predominant model for perceptual evidence accumulation.

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 Finding the key to successful L2 learning in groups and individuals

2017 ◽  
Vol 7 (1) ◽  
pp. 127-148 ◽  
Author(s):  
Wander Lowie ◽  
Marijn Van Dijk ◽  
Huiping Chan ◽  
Marjolijn Verspoor
Keyword(s):  
Second Language ◽  
Individual Differences ◽  
Language Development ◽  
Language Learning ◽  
Second Language Learning ◽  
Large Body ◽  
Individual Characteristics ◽  
Learner Characteristics ◽  
Complex Dynamic ◽  
Over Time

A large body studies into individual differences in second language learning has shown that success in second language learning is strongly affected by a set of relevant learner characteristics ranging from the age of onset to motivation, aptitude, and personality. Most studies have concentrated on a limited number of learner characteristics and have argued for the relative importance of some of these factors. Clearly, some learners are more successful than others, and it is tempting to try to find the factor or combination of factors that can crack the code to success. However, isolating one or several global individual characteristics can only give a partial explanation of success in second language learning. The limitation of this approach is that it only reflects on rather general personality characteristics of learners at one point in time, while both language development and the factors affecting it are instances of complex dynamic processes that develop over time. Factors that have been labelled as “individual differences” as well as the development of proficiency are characterized by nonlinear relationships in the time domain, due to which the rate of success cannot be simply deduced from a combination of factors. Moreover, in complex dynamic systems theory (CDST) literature it has been argued that a generalization about the interaction of variables across individuals is not warranted when we acknowledge that language development is essentially an individual process (Molenaar, 2015). In this paper, the viability of these generalizations is investigated by exploring the L2 development over time for two identical twins in Taiwan who can be expected to be highly similar in all respects, from their environment to their level of English proficiency, to their exposure to English, and to their individual differences. In spite of the striking similarities between these learners, the development of their L2 English over time was very different. Developmental patterns for spoken and written language even showed opposite tendencies. These observations underline the individual nature of the process of second language development.

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 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 Brain Areas Consistently Linked to Individual Differences in Perceptual Decision-making in Younger as well as Older Adults before and after Training

2011 ◽  
Vol 23 (9) ◽  
pp. 2147-2158 ◽  
Author(s):  
Simone Kühn ◽  
Florian Schmiedek ◽  
Björn Schott ◽  
Roger Ratcliff ◽  
Hans-Jochen Heinze ◽  
...  
Keyword(s):  
Older Adults ◽  
Decision Making ◽  
Individual Differences ◽  
Drift Rate ◽  
Parietal Lobe ◽  
Perceptual Decision Making ◽  
Inferior Parietal Lobe ◽  
Perceptual Decision ◽  
Boundary Separation ◽  
Before And After

Perceptual decision-making performance depends on several cognitive and neural processes. Here, we fit Ratcliff's diffusion model to accuracy data and reaction-time distributions from one numerical and one verbal two-choice perceptual-decision task to deconstruct these performance measures into the rate of evidence accumulation (i.e., drift rate), response criterion setting (i.e., boundary separation), and peripheral aspects of performance (i.e., nondecision time). These theoretical processes are then related to individual differences in brain activation by means of multiple regression. The sample consisted of 24 younger and 15 older adults performing the task in fMRI before and after 100 daily 1-hr behavioral training sessions in a multitude of cognitive tasks. Results showed that individual differences in boundary separation were related to striatal activity, whereas differences in drift rate were related to activity in the inferior parietal lobe. These associations were not significantly modified by adult age or perceptual expertise. We conclude that the striatum is involved in regulating response thresholds, whereas the inferior parietal lobe might represent decision-making evidence related to letters and numbers.

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 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.

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