Unconscious biases in neural populations coding multiple stimuli

Throughout the nervous system information is commonly coded in activity distributed over populations of neurons. In idealized situations where a single, continuous stimulus is encoded in a homogeneous population code, the value of the encoded stimulus can be read out without bias. However in many si...

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Main Authors: Keemink, Sander W., Tailor, Dharmesh V., van Rossum, Mark C.W.
Format: Article
Published: MIT Press 2018
Online Access:https://eprints.nottingham.ac.uk/52884/
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author Keemink, Sander W.
Tailor, Dharmesh V.
van Rossum, Mark C.W.
author_facet Keemink, Sander W.
Tailor, Dharmesh V.
van Rossum, Mark C.W.
author_sort Keemink, Sander W.
building Nottingham Research Data Repository
collection Online Access
description Throughout the nervous system information is commonly coded in activity distributed over populations of neurons. In idealized situations where a single, continuous stimulus is encoded in a homogeneous population code, the value of the encoded stimulus can be read out without bias. However in many situations multiple stimuli are simultaneously present, for example, multiple motion patterns might overlap. Here we find that when multiple stimuli that overlap in their neural representation are simultaneously encoded in the population, biases in the read-out emerge. Although the bias disappears in the absence of noise, the bias is remarkably persistent at low noise levels. The bias can be reduced by competitive encoding schemes or by employing complex decoders. To study the origin of the bias, we develop a novel general framework based on Gaussian processes that allows for an accurate calculation of the estimate distributions of maximum likelihood decoders, and reveals that the distribution of estimates is bimodal for overlapping stimuli. The results have implications for neural coding and behavioural experiments on, for instance, overlapping motion patterns.
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spelling nottingham-528842020-05-04T19:45:29Z https://eprints.nottingham.ac.uk/52884/ Unconscious biases in neural populations coding multiple stimuli Keemink, Sander W. Tailor, Dharmesh V. van Rossum, Mark C.W. Throughout the nervous system information is commonly coded in activity distributed over populations of neurons. In idealized situations where a single, continuous stimulus is encoded in a homogeneous population code, the value of the encoded stimulus can be read out without bias. However in many situations multiple stimuli are simultaneously present, for example, multiple motion patterns might overlap. Here we find that when multiple stimuli that overlap in their neural representation are simultaneously encoded in the population, biases in the read-out emerge. Although the bias disappears in the absence of noise, the bias is remarkably persistent at low noise levels. The bias can be reduced by competitive encoding schemes or by employing complex decoders. To study the origin of the bias, we develop a novel general framework based on Gaussian processes that allows for an accurate calculation of the estimate distributions of maximum likelihood decoders, and reveals that the distribution of estimates is bimodal for overlapping stimuli. The results have implications for neural coding and behavioural experiments on, for instance, overlapping motion patterns. MIT Press 2018-07-06 Article PeerReviewed Keemink, Sander W., Tailor, Dharmesh V. and van Rossum, Mark C.W. (2018) Unconscious biases in neural populations coding multiple stimuli. Neural Computation . ISSN 1530-888X (In Press) https://www.mitpressjournals.org/doi/abs/10.1162/neco_a_01130 doi:10.1162/neco_a_01130 doi:10.1162/neco_a_01130
spellingShingle Keemink, Sander W.
Tailor, Dharmesh V.
van Rossum, Mark C.W.
Unconscious biases in neural populations coding multiple stimuli
title Unconscious biases in neural populations coding multiple stimuli
title_full Unconscious biases in neural populations coding multiple stimuli
title_fullStr Unconscious biases in neural populations coding multiple stimuli
title_full_unstemmed Unconscious biases in neural populations coding multiple stimuli
title_short Unconscious biases in neural populations coding multiple stimuli
title_sort unconscious biases in neural populations coding multiple stimuli
url https://eprints.nottingham.ac.uk/52884/
https://eprints.nottingham.ac.uk/52884/
https://eprints.nottingham.ac.uk/52884/