PT  - JOURNAL ARTICLE
AU  - Seth W. Egger
AU  - Stephen G. Lisberger
TI  - Neural structure of a sensory decoder for motor control
AID  - 10.1101/2020.10.22.350371
DP  - 2020 Jan 01
TA  - bioRxiv
PG  - 2020.10.22.350371
4099  - http://biorxiv.org/content/early/2020/10/22/2020.10.22.350371.short
4100  - http://biorxiv.org/content/early/2020/10/22/2020.10.22.350371.full
AB  - We seek to understand the neural mechanisms that perform sensory decoding for motor behavior, advancing the field by designing decoders based on neural circuits. A simple experiment produced a surprising result that shapes our approach. Changing the size of a target for smooth pursuit eye movements changes the relationship between the variance and mean of the evoked behavior in a way that contradicts the regime of “signal-dependent noise” and defies traditional decoding approaches. A theoretical analysis leads us to conclude that sensory decoding circuits for pursuit include multiple parallel pathways and multiple sources of variation. Behavioral and neural responses with biomimetic statistics emerge from a biologically-motivated circuit model with noise in the pathway that is dedicated to flexibly adjusting the strength of visual-motor transmission. Flexible adjustment of transmission strength applies much more broadly to issues in sensory-motor control such as Bayesian integration and control strategies to optimize motor behavior.Competing Interest StatementThe authors have declared no competing interest.