Dissociating Sensory and Cognitive Biases in Human Perceptual Decision-Making: A Re-evaluation of Evidence From Reference Repulsion

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.

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Confirmation bias in decision making for fingerprints, DNA and eyewitness evidence cannot be explained by cognitive style or thinking dispositions.

10.31234/osf.io/59tzd ◽

2019 ◽

Author(s):

Daniel Edgcumbe

Keyword(s):

Decision Making ◽

Cognitive Style ◽

Cognitive Biases ◽

Confirmation Bias ◽

Criminal Case ◽

Court Cases ◽

Legal Proceedings ◽

Thinking Dispositions ◽

Evaluation Of Evidence ◽

Facial Composite

Pre-existing beliefs about the background or guilt of a suspect can bias the subsequent evaluation of evidence for forensic examiners and lay people alike. This biasing effect, called the confirmation bias, has influenced legal proceedings in prominent court cases such as that of Brandon Mayfield. Today many forensic providers attempt to train their examiners against these cognitive biases. Nine hundred and forty-two participants read a fictional criminal case and received either neutral, incriminating or exonerating evidence (fingerprint, eyewitness, or DNA) before providing an initial rating of guilt. Participants then viewed ambiguous evidence (alibi, facial composite, handwriting sample or informant statement) before providing a final rating of guilt. Final guilt ratings were higher for all evidence conditions (neutral, incriminating or exonerating) following exposure to the ambiguous evidence. This provides evidence that the confirmation bias influences the evaluation of evidence.

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Mesoscale cortical dynamics reflect the interaction of sensory evidence and temporal expectation during perceptual decision-making

Neuron ◽

10.1016/j.neuron.2021.03.031 ◽

2021 ◽

Author(s):

Ivana Orsolic ◽

Maxime Rio ◽

Thomas D. Mrsic-Flogel ◽

Petr Znamenskiy

Keyword(s):

Decision Making ◽

Perceptual Decision Making ◽

Cortical Dynamics ◽

Perceptual Decision ◽

Temporal Expectation ◽

Sensory Evidence

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Flexible categorization in perceptual decision making

Nature Communications ◽

10.1038/s41467-021-21501-z ◽

2021 ◽

Vol 12 (1) ◽

Cited By ~ 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.

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

Mindfulness ◽

10.1007/s12671-020-01562-9 ◽

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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Sensor-Level Wavelet Analysis Reveals EEG Biomarkers of Perceptual Decision-Making

Sensors ◽

10.3390/s21072461 ◽

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).

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