Perceptual decision-making in patients with Parkinson’s disease

2014 ◽  
Vol 28 (12) ◽  
pp. 1149-1154 ◽  
Author(s):  
Atbin Djamshidian ◽  
Sean S O’Sullivan ◽  
Andrew D Lawrence ◽  
Thomas Foltynie ◽  
Iciar Aviles-Olmos ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Decision Making ◽  
Parkinson's Disease ◽  
Perceptual Decision Making ◽  
Perceptual Decision

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.

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

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

Sensors ◽  
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).

scholarly journals Risky decision-making and affective features of impulse control disorders in Parkinson’s disease

2017 ◽  
Vol 125 (2) ◽  
pp. 131-143 ◽  
Author(s):  
Alice Martini ◽  
Simon J. Ellis ◽  
James A. Grange ◽  
Stefano Tamburin ◽  
Denise Dal Lago ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Decision Making ◽  
Parkinson's Disease ◽  
Impulse Control ◽  
Impulse Control Disorders ◽  
Risky Decision Making ◽  
Risky Decision

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 Multiple brain networks contribute to the acquisition of bias in perceptual decision-making

2015 ◽  
Vol 9 ◽  
Author(s):  
Mei-Yen Chen ◽  
Koji Jimura ◽  
Corey N. White ◽  
W. Todd Maddox ◽  
Russell A. Poldrack
Keyword(s):  
Decision Making ◽  
Brain Networks ◽  
Perceptual Decision Making ◽  
Perceptual Decision
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