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Neural Signature Accumulated Evidence

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Seminar✓ Recording AvailableNeuroscience

Neural signature for accumulated evidence underlying temporal decisions

Nir Ofir

The Hebrew University of Jerusalem

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Wednesday, December 15, 2021

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Wednesday, December 15, 2021

10:00 AM America/New_York

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Host: Timing Research Forum

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Timing Research Forum

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Abstract

Cognitive models of timing often include a pacemaker analogue whose ticks are accumulated to form an internal representation of time, and a threshold that determines when a target duration has elapsed. However, clear EEG manifestations of these abstract components have not yet been identified. We measured the EEG of subjects while they performed a temporal bisection task in which they were requested to categorize visual stimuli as short or long in duration. We report an ERP component whose amplitude depends monotonically on the stimulus duration. The relation of the ERP amplitude and stimulus duration can be captured by a simple model, adapted from a known drift-diffusion model for time perception. It includes a noisy accumulator that starts with the stimulus onset and a threshold. If the threshold is reached during stimulus presentation, the stimulus is categorized as "long", otherwise the stimulus is categorized as "short". At the stimulus offset, a response proportional to the distance to the threshold is emitted. This simple model has two parameters that fit both the behavior and ERP amplitudes recorded in the task. Two subsequent experiments replicate and extend this finding to another modality (touch) as well as to different time ranges (subsecond and suprasecond), establishing the described ERP component as a useful handle on the cognitive processes involved in temporal decisions.

Topics

EEGERP componentaccumulatordrift-diffusion modelsensory modalitiesstimulus durationtemporal bisectiontemporal bisection tasktemporal decisionsthresholdtime perception

About the Speaker

Nir Ofir

The Hebrew University of Jerusalem

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Personal Website

www.landaulab.com/nir-ofir.html

@nirofir

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