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Updated: Nov 9, 2025
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A Two-interval Forced-choice Task for Multisensory Comparisons
Published on: November 9, 2018
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Stimulus-dependent relationships between behavioral choice and sensory neural responses
Daniel Chicharro1,2, Stefano Panzeri1, Ralf M Haefner3
1Neural Computation Laboratory, Center for Neuroscience and Cognitive Systems@UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy.
Elife
|April 7, 2021
Summary
Researchers developed new methods to analyze how neural activity relates to choices, revealing stimulus-dependent choice probabilities (CPs) in perceptual decision-making. This advances understanding of neural signals driving behavior.
Area of Science:
- Neuroscience
- Computational Neuroscience
- Decision Neuroscience
Background:
- Perceptual decision-making links sensory neural activity to behavioral choices.
- Choice probability (CP) quantifies activity-choice covariations in two-choice tasks but often overlooks stimulus level effects.
- Existing methods lack the granularity to capture stimulus-dependent neural signal variations influencing choices.
Purpose of the Study:
- To theoretically predict and empirically validate stimulus dependencies in activity-choice covariations.
- To develop novel analytical tools for dissecting stimulus- and choice-driven neural signals.
- To characterize stimulus-dependent patterns of choice-related signals in neural populations.
Main Methods:
- Developed a general decision-threshold model incorporating feedforward/feedback processing and stimulus-modulated covariance.
- Derived analytical predictions for stimulus-dependent choice probabilities (CPs).
- Introduced refined CP analyses and generalized linear models with stimulus-choice interactions.
Main Results:
- Analytically predicted a general, previously unreported stimulus dependence of CPs under specific model assumptions.
- Developed and applied new analytical tools to assess stimulus- or choice-driven signals per neuron.
- Preliminary analysis of macaque MT neurons in a motion discrimination task showed evidence supporting stimulus-dependent choice signals.
Conclusions:
- Choice probabilities (CPs) exhibit stimulus-dependent variations, challenging previous assumptions of uniformity.
- New analytical methods accurately characterize stimulus-dependent choice-related neural signals.
- Findings encourage further investigation into stimulus dependencies of choice signals across broader datasets.
Keywords:
choice probabilityneural codingneuroscienceperceptual decision-makingrhesus macaquesensory neuronsMore Related Videos
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