scholarly journals Contribution of sensory encoding to measured bias

2018 ◽  
Author(s):  
Miaomiao Jin ◽  
Lindsey L. Glickfeld
Keyword(s):  
Decision Making ◽  
Neuronal Response ◽  
Decision Criterion ◽  
Neuronal Firing ◽  
Mathematical Framework ◽  
Perceptual Decision Making ◽  
Stimulus Interval ◽  
Perceptual Decision ◽  
Behavioral Bias ◽  
Sensory Encoding

AbstractPerceptual decision-making is a complex process that involves sensory integration followed by application of a cognitive threshold. Signal detection theory (SDT) provides a mathematical framework for attributing the underlying neurobiological processes to these distinct phases of perceptual decision-making. In particular, SDT reveals the sensitivity (d’) of the neuronal response distributions and the bias (c) of the decision criterion, which are commonly thought to reflect sensory and cognitive processes, respectively. However, neuronal representations of bias have been observed in sensory areas, suggesting that some changes in bias are due to effects on sensory encoding. To directly test whether sensory encoding can influence bias, we optogenetically manipulated neuronal excitability in primary visual cortex (V1) during a detection task. Increasing excitability in V1 significantly decreased behavioral bias, while decreasing excitability had the opposite effect. To determine whether this change in bias is consistent with the effects on sensory encoding, we made extracellular recordings from V1 neurons in passively viewing mice. Indeed, we found that optogenetic manipulation of excitability shifted the neuronal bias in the same direction as the behavioral bias, despite using a fixed artificial decision criterion to predict hit and false alarm rates from the neuronal firing rates. To test the generality these effects, we also manipulated the quality of V1 encoding by changing stimulus contrast or inter-stimulus interval. These stimulus manipulations also resulted in consistent changes in bias measured both behaviorally and neuronally. Thus, changes in sensory encoding are sufficient to drive changes in bias measured using SDT.

scholarly journals Autistic Traits in the Neurotypical Population do not Predict Increased Response Conservativeness in Perceptual Decision Making

Perception ◽  
2018 ◽  
Vol 47 (10-11) ◽  
pp. 1081-1096 ◽  
Author(s):  
Angelo Pirrone ◽  
Wen Wen ◽  
Sheng Li ◽  
Daniel H. Baker ◽  
Elizabeth Milne
Keyword(s):  
Decision Making ◽  
Autistic Traits ◽  
Decision Criterion ◽  
Autism Spectrum ◽  
Coherent Motion ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
The United Kingdom ◽  
Perceptual Differences ◽  
Adults And Children

Recent research has shown that adults and children with autism spectrum disorders have a more conservative decision criterion in perceptual decision making compared to neurotypical individuals, meaning that autistic participants prioritise accuracy over speed of a decision. Here, we test whether autistic traits in the neurotypical population correlate with increased response conservativeness. We employed three different tasks; for two tasks we recruited participants from China ( N = 39) and for one task from the United Kingdom ( N = 37). Our results show that autistic traits in the neurotypical population do not predict variation in response criterion. We also failed to replicate previous work showing a relationship between autistic traits and sensitivity to coherent motion and static orientation. Following the argument proposed by Gregory and Plaisted-Grant, we discuss why perceptual differences between autistic and neurotypical participants do not necessarily predict perceptual differences between neurotypical participants with high and low autistic traits.

scholarly journals Re-thinking the fixed-criterion model of perceptual decision-making

2021 ◽  
Author(s):  
Jennifer Laura Lee ◽  
Rachel N. Denison ◽  
Wei Ji Ma
Keyword(s):  
Decision Making ◽  
Probabilistic Reasoning ◽  
Sensory Information ◽  
Feature Space ◽  
Decision Criterion ◽  
Decision Variable ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Response Variance ◽  
Sensory Uncertainty

Perceptual decision-making is often conceptualized as the process of comparing an internal decision variable to a categorical boundary, or criterion. How the mind sets such a criterion has been studied from at least two perspectives. First, researchers interested in consciousness have proposed that criterion-crossing determines whether a stimulus is consciously perceived. Second, researchers interested in decision-making have studied how the criterion depends on a range of stimulus and task variables. Both communities have considered the question of how the criterion behaves when sensory information is weak or uncertain. Interestingly, however, they have arrived at different conclusions. Consciousness researchers investigating a phenomenon called "subjective inflation" – a form of metacognitive mismatch in which observers overestimate the quality of their sensory representations in the periphery or at an unattended location – have proposed that the criterion governing subjective visibility is fixed. That is, it does not adjust to changes in sensory uncertainty. Decision-making researchers, on the other hand, have concluded that the criterion does adjust to account for sensory uncertainty, including under inattention. Here, we mathematically demonstrate that previous empirical findings supporting subjective inflation are consistent with either a fixed or a flexible decision criterion. We further show that specific experimental task requirements are necessary to make inferences about the flexibility of the criterion: 1) a clear mapping from decision variable space to stimulus feature space, and 2) a task incentive for observers to adjust their decision criterion as response variance increases. We conclude that the fixed-criterion model of subjective inflation requires re-thinking in light of new evidence from the probabilistic reasoning literature that decision criteria flexibly adjust according to response variance.

scholarly journals Prestimulus alpha power predicts fidelity of sensory encoding in perceptual decision making

NeuroImage ◽  
2014 ◽  
Vol 87 ◽  
pp. 242-251 ◽  
Author(s):  
Bin Lou ◽  
Yun Li ◽  
Marios G. Philiastides ◽  
Paul Sajda
Keyword(s):  
Decision Making ◽  
Alpha Power ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Sensory Encoding

scholarly journals The interplay between multisensory integration and perceptual decision making

2019 ◽  
Author(s):  
Manuel R. Mercier ◽  
Celine Cappe
Keyword(s):  
Decision Making ◽  
Multisensory Integration ◽  
Multisensory Processing ◽  
Optimal Decision ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Human Participants ◽  
Sensory Encoding ◽  
Optimal Decision Making ◽  
The Brain

AbstractFacing perceptual uncertainty, the brain combines information from different senses to shape optimal decision making and to guide behavior. Despite overlapping neural networks underlying multisensory integration and perceptual decision making, the process chain of decision formation has been studied mostly in unimodal contexts and is thought to be supramodal. To reveal whether and how multisensory processing interplay with perceptual decision making, we devised a paradigm mimicking naturalistic situations where human participants were exposed to continuous cacophonous audiovisual inputs containing an unpredictable relevant signal cue in one or two modalities. Using multivariate pattern analysis on concurrently recorded EEG, we decoded the neural signatures of sensory encoding and decision formation stages. Generalization analyses across conditions and time revealed that multisensory signal cues were processed faster during both processing stages. We further established that acceleration of neural dynamics was directly linked to two distinct multisensory integration processes and associated with multisensory benefit. Our results, substantiated in both detection and categorization tasks, provide evidence that the brain integrates signals from different modalities at both the sensory encoding and the decision formation stages.

Discarding optimality: Throwing out the baby with the bathwater?

2018 ◽  
Vol 41 ◽  
Author(s):  
Patrick Simen ◽  
Fuat Balcı
Keyword(s):  
Decision Making ◽  
Perceptual Decision Making ◽  
Reward Rate ◽  
Perceptual Decision ◽  
Standard Observer ◽  
Rate Maximization ◽  
Reward Rate Maximization ◽  
Descriptive Standard ◽  
Observer Model

AbstractRahnev & Denison (R&D) argue against normative theories and in favor of a more descriptive “standard observer model” of perceptual decision making. We agree with the authors in many respects, but we argue that optimality (specifically, reward-rate maximization) has proved demonstrably useful as a hypothesis, contrary to the authors’ claims.

LPCD framework: Analytical tool or psychological model?

2018 ◽  
Vol 41 ◽  
Author(s):  
David Danks
Keyword(s):  
Decision Making ◽  
Analytical Tool ◽  
Mathematical Framework ◽  
Bayesian Decision ◽  
Perceptual Decision Making ◽  
Psychological Model ◽  
Psychological Reality ◽  
Psychological Theories ◽  
Target Article ◽  
Bayesian Decision Making

AbstractThe target article uses a mathematical framework derived from Bayesian decision making to demonstrate suboptimal decision making but then attributes psychological reality to the framework components. Rahnev & Denison's (R&D) positive proposal thus risks ignoring plausible psychological theories that could implement complex perceptual decision making. We must be careful not to slide from success with an analytical tool to the reality of the tool components.

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.

Effects of a Brief Mindfulness-Based Attentional Intervention on Threat-Related Perceptual Decision-Making

Mindfulness ◽  
2021 ◽  
Author(s):  
Sungjin Im ◽  
Maya A. Marder ◽  
Gabriella Imbriano ◽  
Tamara J. Sussman ◽  
Aprajita Mohanty
Keyword(s):  
Decision Making ◽  
Perceptual Decision Making ◽  
Perceptual Decision
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