Dynamic Control of Response Criterion in Premotor Cortex during Perceptual Detection under Temporal Uncertainty
Under uncertainty, the brain uses previous knowledge to transform sensory inputs into the percepts on which decisions are based. When the uncertainty lies in the timing of sensory evidence, however, the mechanism underlying the use of previously acquired temporal information remains unknown. We stud...
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          | Published in | Neuron (Cambridge, Mass.) Vol. 86; no. 4; pp. 1067 - 1077 | 
|---|---|
| Main Authors | , , , , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
        United States
          Elsevier Inc
    
        20.05.2015
     Elsevier Limited  | 
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| Online Access | Get full text | 
| ISSN | 0896-6273 1097-4199 1097-4199  | 
| DOI | 10.1016/j.neuron.2015.04.014 | 
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| Abstract | Under uncertainty, the brain uses previous knowledge to transform sensory inputs into the percepts on which decisions are based. When the uncertainty lies in the timing of sensory evidence, however, the mechanism underlying the use of previously acquired temporal information remains unknown. We study this issue in monkeys performing a detection task with variable stimulation times. We use the neural correlates of false alarms to infer the subject’s response criterion and find that it modulates over the course of a trial. Analysis of premotor cortex activity shows that this modulation is represented by the dynamics of population responses. A trained recurrent network model reproduces the experimental findings and demonstrates a neural mechanism to benefit from temporal expectations in perceptual detection. Previous knowledge about the probability of stimulation over time can be intrinsically encoded in the neural population dynamics, allowing a flexible control of the response criterion over time.
•A template-matching algorithm detects neural correlates of false alarm events•The subject’s response criterion modulates over the course of a trial•The response criterion is represented by the dynamics of a neural population•A trained recurrent network unveils a mechanism for flexible response criterion
Carnevale et al. explore how monkeys exploit previous knowledge to cope with temporal uncertainty in a perceptual detection task. The study demonstrates a neural mechanism by which prior information is intrinsically encoded in the dynamics of a neural population. | 
    
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| AbstractList | Under uncertainty, the brain uses previous knowledge to transform sensory inputs into the percepts on which decisions are based. When the uncertainty lies in the timing of sensory evidence, however, the mechanism underlying the use of previously acquired temporal information remains unknown. We study this issue in monkeys performing a detection task with variable stimulation times. We use the neural correlates of false alarms to infer the subject's response criterion and find that it modulates over the course of a trial. Analysis of premotor cortex activity shows that this modulation is represented by the dynamics of population responses. A trained recurrent network model reproduces the experimental findings and demonstrates a neural mechanism to benefit from temporal expectations in perceptual detection. Previous knowledge about the probability of stimulation over time can be intrinsically encoded in the neural population dynamics, allowing a flexible control of the response criterion over time.Under uncertainty, the brain uses previous knowledge to transform sensory inputs into the percepts on which decisions are based. When the uncertainty lies in the timing of sensory evidence, however, the mechanism underlying the use of previously acquired temporal information remains unknown. We study this issue in monkeys performing a detection task with variable stimulation times. We use the neural correlates of false alarms to infer the subject's response criterion and find that it modulates over the course of a trial. Analysis of premotor cortex activity shows that this modulation is represented by the dynamics of population responses. A trained recurrent network model reproduces the experimental findings and demonstrates a neural mechanism to benefit from temporal expectations in perceptual detection. Previous knowledge about the probability of stimulation over time can be intrinsically encoded in the neural population dynamics, allowing a flexible control of the response criterion over time. Under uncertainty, the brain uses previous knowledge to transform sensory inputs into the percepts on which decisions are based. When the uncertainty lies in the timing of sensory evidence, however, the mechanism underlying the use of previously acquired temporal information remains unknown. We study this issue in monkeys performing a detection task with variable stimulation times. We use the neural correlates of false alarms to infer the subject's response criterion and find that it modulates over the course of a trial. Analysis of premotor cortex activity shows that this modulation is represented by the dynamics of population responses. A trained recurrent network model reproduces the experimental findings and demonstrates a neural mechanism to benefit from temporal expectations in perceptual detection. Previous knowledge about the probability of stimulation over time can be intrinsically encoded in the neural population dynamics, allowing a flexible control of the response criterion over time. Under uncertainty, the brain uses previous knowledge to transform sensory inputs into the percepts on which decisions are based. When the uncertainty lies in the timing of sensory evidence, however, the mechanism underlying the use of previously acquired temporal information remains unknown. We study this issue in monkeys performing a detection task with variable stimulation times. We use the neural correlates of false alarms to infer the subject’s response criterion and find that it modulates over the course of a trial. Analysis of premotor cortex activity shows that this modulation is represented by the dynamics of population responses. A trained recurrent network model reproduces the experimental findings and demonstrates a neural mechanism to benefit from temporal expectations in perceptual detection. Previous knowledge about the probability of stimulation over time can be intrinsically encoded in the neural population dynamics, allowing a flexible control of the response criterion over time. •A template-matching algorithm detects neural correlates of false alarm events•The subject’s response criterion modulates over the course of a trial•The response criterion is represented by the dynamics of a neural population•A trained recurrent network unveils a mechanism for flexible response criterion Carnevale et al. explore how monkeys exploit previous knowledge to cope with temporal uncertainty in a perceptual detection task. The study demonstrates a neural mechanism by which prior information is intrinsically encoded in the dynamics of a neural population.  | 
    
| Author | Carnevale, Federico Barak, Omri de Lafuente, Victor Parga, Néstor Romo, Ranulfo  | 
    
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| SubjectTerms | Algorithms Animals Attention - physiology Behavior Behavior, Animal Choice Behavior - physiology Decision making Haplorhini Motion Perception - physiology Motor Cortex - physiology Photic Stimulation - methods Reaction Time Uncertainty Visual Perception - physiology  | 
    
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| Title | Dynamic Control of Response Criterion in Premotor Cortex during Perceptual Detection under Temporal Uncertainty | 
    
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