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Published September 26, 2023 | Published
Journal Article Open

Internal feedback in the cortical perception–action loop enables fast and accurate behavior

  • 1. ROR icon California Institute of Technology


Animals move smoothly and reliably in unpredictable environments. Models of sensorimotor control, drawing on control theory, have assumed that sensory information from the environment leads to actions, which then act back on the environment, creating a single, unidirectional perception–action loop. However, the sensorimotor loop contains internal delays in sensory and motor pathways, which can lead to unstable control. We show here that these delays can be compensated by internal feedback signals that flow backward, from motor toward sensory areas. This internal feedback is ubiquitous in neural sensorimotor systems, and we show how internal feedback compensates internal delays. This is accomplished by filtering out self-generated and other predictable changes so that unpredicted, actionable information can be rapidly transmitted toward action by the fastest components, effectively compressing the sensory input to more efficiently use feedforward pathways: Tracts of fast, giant neurons necessarily convey less accurate signals than tracts with many smaller neurons, but they are crucial for fast and accurate behavior. We use a mathematically tractable control model to show that internal feedback has an indispensable role in achieving state estimation, localization of function (how different parts of the cortex control different parts of the body), and attention, all of which are crucial for effective sensorimotor control. This control model can explain anatomical, physiological, and behavioral observations, including motor signals in the visual cortex, heterogeneous kinetics of sensory receptors, and the presence of giant cells in the cortex of humans as well as internal feedback patterns and unexplained heterogeneity in neural systems.

Copyright and License

© 2023 the Author(s). Published by PNAS. This article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).


Stephen Lisberger helped clarify our discussion on the oculomotor system. J.C.D. and T.J.S. were supported by NSF NCS-FO 1735004. J.C.D. was supported by NIH NS121918. T.J.S. was supported by ONR N00014-16-1-282. J.S.L. was in part supported by NSERC PGSD3-557385-2021. This paper is based on the doctoral research of A.A.S. and J.S.L.


J.S.L., A.A.S., T.J.S., and J.C.D. designed research; performed research; and wrote the paper.

Data Availability

There are no data underlying this work.

Conflict of Interest

The authors declare no competing interest.



Additional details

November 2, 2023
November 2, 2023