scholarly journals Neural Correlates of Multidimensional Perceptual Decision Making in Macaque Frontal Eye Field

2020 ◽  
Vol 20 (11) ◽  
pp. 123
Author(s):  
Kaleb A. Lowe ◽  
Thomas R. Reppert ◽  
Jeffrey D. Schall
2020 ◽  
Vol 30 (10) ◽  
pp. 5471-5483
Author(s):  
Y Yau ◽  
M Dadar ◽  
M Taylor ◽  
Y Zeighami ◽  
L K Fellows ◽  
...  

Abstract Current models of decision-making assume that the brain gradually accumulates evidence and drifts toward a threshold that, once crossed, results in a choice selection. These models have been especially successful in primate research; however, transposing them to human fMRI paradigms has proved it to be challenging. Here, we exploit the face-selective visual system and test whether decoded emotional facial features from multivariate fMRI signals during a dynamic perceptual decision-making task are related to the parameters of computational models of decision-making. We show that trial-by-trial variations in the pattern of neural activity in the fusiform gyrus reflect facial emotional information and modulate drift rates during deliberation. We also observed an inverse-urgency signal based in the caudate nucleus that was independent of sensory information but appeared to slow decisions, particularly when information in the task was ambiguous. Taken together, our results characterize how decision parameters from a computational model (i.e., drift rate and urgency signal) are involved in perceptual decision-making and reflected in the activity of the human brain.


Author(s):  
Jacobo Fernandez-Vargas ◽  
Christoph Tremmel ◽  
Davide Valeriani ◽  
Saugat Bhattacharyya ◽  
Caterina Cinel ◽  
...  

2013 ◽  
Author(s):  
Martijn J. Mulder ◽  
Eric-Jan Wagenmakers ◽  
Roger Ratcliff ◽  
Wouter Boekel ◽  
Birte U. Forstmann

2011 ◽  
Vol 106 (5) ◽  
pp. 2383-2398 ◽  
Author(s):  
Taosheng Liu ◽  
Timothy J. Pleskac

Sequential sampling models provide a useful framework for understanding human decision making. A key component of these models is an evidence accumulation process in which information is accrued over time to a threshold, at which point a choice is made. Previous neurophysiological studies on perceptual decision making have suggested accumulation occurs only in sensorimotor areas involved in making the action for the choice. Here we investigated the neural correlates of evidence accumulation in the human brain using functional magnetic resonance imaging (fMRI) while manipulating the quality of sensory evidence, the response modality, and the foreknowledge of the response modality. We trained subjects to perform a random dot motion direction discrimination task by either moving their eyes or pressing buttons to make their responses. In addition, they were cued about the response modality either in advance of the stimulus or after a delay. We isolated fMRI responses for perceptual decisions in both independently defined sensorimotor areas and task-defined nonsensorimotor areas. We found neural signatures of evidence accumulation, a higher fMRI response on low coherence trials than high coherence trials, primarily in saccade-related sensorimotor areas (frontal eye field and intraparietal sulcus) and nonsensorimotor areas in anterior insula and inferior frontal sulcus. Critically, such neural signatures did not depend on response modality or foreknowledge. These results help establish human brain areas involved in evidence accumulation and suggest that the neural mechanism for evidence accumulation is not specific to effectors. Instead, the neural system might accumulate evidence for particular stimulus features relevant to a perceptual task.


2019 ◽  
Author(s):  
Y. Yau ◽  
M. Dadar ◽  
M. Taylor ◽  
Y. Zeighami ◽  
L.K. Fellows ◽  
...  

AbstractCurrent models of decision-making assume that the brain gradually accumulates evidence and drifts towards a threshold which, once crossed, results in a choice selection. These models have been especially successful in primate research, however transposing them to human fMRI paradigms has proved challenging. Here, we exploit the face-selective visual system and test whether decoded emotional facial features from multivariate fMRI signals during a dynamic perceptual decision-making task are related to the parameters of computational models of decision-making. We show that trial-by-trial variations in the pattern of neural activity in the fusiform gyrus reflect facial emotional information and modulate drift rates during deliberation. We also observed an inverse-urgency signal based in the caudate nucleus that was independent of sensory information but appeared to slow decisions, particularly when information in the task was ambiguous. Taken together, our results characterize how decision parameters from a computational model (i.e., drift rate and urgency signal) are involved in perceptual decision-making and reflected in the activity of the human brain.


Author(s):  
Thomas J. Palmeri ◽  
Jeffrey D. Schall ◽  
Gordon D. Logan

Mathematical psychology and systems neuroscience have converged on stochastic accumulator models to explain decision making. We examined saccade decisions in monkeys while neurophysiological recordings were made within their frontal eye field. Accumulator models were tested on how well they fit response probabilities and distributions of response times to make saccades. We connected these models with neurophysiology. To test the hypothesis that visually responsive neurons represented perceptual evidence driving accumulation, we replaced perceptual processing time and drift rate parameters with recorded neurophysiology from those neurons. To test the hypothesis that movement related neurons instantiated the accumulator, we compared measures of neural dynamics with predicted measures of accumulator dynamics. Thus, neurophysiology both provides a constraint on model assumptions and data for model selection. We highlight a gated accumulator model that accounts for saccade behavior during visual search, predicts neurophysiology during search, and provides insights into the locus of cognitive control over decisions.


Sign in / Sign up

Export Citation Format

Share Document