Evidence map›Paper›PMID 37738297›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2023

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

Jing Shuang Li, Anish A Sarma, Terrence J Sejnowski, John C Doyle

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
4.9field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 28 citations in OpenAlex.

  1. Article
  2. Article
  3. Temporal Dynamics of EEG Reflect Continuous Error Correction during Force Control.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
    Article
  4. Online supervised learning of temporal patterns in biological neural networks under feedback control.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. The neuron as a direct data-driven controller.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  12. Optimal reaching subject to computational and physical constraints reveals structure of the sensorimotor control system.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Jing Shuang Li *Control and Dynamical Systems, Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA 91125.ORCID 0000-0003-4931-8709
Anish A Sarma *Control and Dynamical Systems, Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA 91125.
Terrence J SejnowskiDepartment of Neurobiology, Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037.ORCID 0000-0002-0622-7391
John C DoyleControl and Dynamical Systems, Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA 91125.ORCID 0000-0002-1828-2486
California Institute of Technology · USSalk Institute for Biological Studies · US

Funding

Stability and Robustness of Hippocampal Representations of SpaceR01NS121918 · NINDS · CALIFORNIA INSTITUTE OF TECHNOLOGY · PI DOYLE, JOHN C, LOIS, CARLOS · 2021 to 2025
$5.0M
NINDS NIH HHS R01 NS121918
6 · The paper itself

Abstract

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.

Indexed as

Behavior Observation TechniquesSensory Receptor CellsAnimalsEfferent PathwaysFeedbackHumansPerceptioninternal feedbackoptimal controlsensorimotor controlspeed–accuracy trade-off

Identifiers

PMID37738297
PMCPMC10523540
OpenAlexW4386953665

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.