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Unconscious biases in neural populations coding multiple stimuli

Keemink, Sander W.; Tailor, Dharmesh V.; van Rossum, Mark C.W.


Sander W. Keemink

Dharmesh V. Tailor

Chair and Director/Neuralcomputation Research Group


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.


Keemink, S. W., Tailor, D. V., & van Rossum, M. C. (2018). Unconscious biases in neural populations coding multiple stimuli. Neural Computation, 30(12), 3168–3188.

Journal Article Type Article
Acceptance Date Jul 6, 2018
Online Publication Date Sep 14, 2018
Publication Date 2018-12
Deposit Date Jul 11, 2018
Publicly Available Date Sep 14, 2018
Journal Neural Computation
Print ISSN 0899-7667
Electronic ISSN 1530-888X
Publisher Massachusetts Institute of Technology Press
Peer Reviewed Peer Reviewed
Volume 30
Issue 12
Pages 3168–3188
Public URL
Publisher URL
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingh.../end_user_agreement.pdf


NECO-05-18-3161-Source.pdf (953 Kb)

Copyright Statement
Copyright information regarding this work can be found at the following address:

neco_a_01130 (558 Kb)

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