Evidence map›Paper›PMID 25420067›Full record

ArticleNature neuroscience2015

A learning-based approach to artificial sensory feedback leads to optimal integration.

Maria C Dadarlat, Joseph E O'Doherty, Philip N Sabes

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 96 papers.

0numbers the graph read from it
0cells of the map it votes in
96citing papers in PubMed
–field-weighted citation impact
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

96 citing papers in PubMed.

  1. Trial
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  3. Integration of learned artificial sensation with vision during freely moving navigation.Proceedings of the National Academy of Sciences of the United States of America · 2026
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  17. From Multisensory Integration to Multisensory Decision-Making.Advances in experimental medicine and biology · 2024
    Review
  18. Article
  19. Article
  20. Article

36 more citing papers are in PubMed but not listed here.

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

3 authors.

Maria C Dadarlat1] Department of Physiology, University of California, San Francisco, California, USA. [2] Center for Integrative Neuroscience, University of California, San Francisco, California, USA. [3] UC Berkeley-UCSF Center for Neural Engineering and Prosthetics, University of California, San Francisco, California, USA. [4] UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco, California, USA.
Joseph E O'Doherty1] Department of Physiology, University of California, San Francisco, California, USA. [2] Center for Integrative Neuroscience, University of California, San Francisco, California, USA. [3] UC Berkeley-UCSF Center for Neural Engineering and Prosthetics, University of California, San Francisco, California, USA.ORCID 0000000181755699
Philip N Sabes1] Department of Physiology, University of California, San Francisco, California, USA. [2] Center for Integrative Neuroscience, University of California, San Francisco, California, USA. [3] UC Berkeley-UCSF Center for Neural Engineering and Prosthetics, University of California, San Francisco, California, USA. [4] UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco, California, USA.ORCID 0000000183976225

Funding

Training Program for the Visual SciencesT32EY007120 · NEI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI COPENHAGEN, DAVID RICHARD · 1990 to 2015
$2.9M
Visuomotor adaptation in reachingR01EY015679 · NEI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI SABES, PHILIP N · 2004 to 2012
$2.4M
NEI NIH HHS EY007120NEI NIH HHS EY015679NEI NIH HHS R01 EY015679NEI NIH HHS T32 EY007120
6 · The paper itself

Abstract

Proprioception-the sense of the body's position in space-is important to natural movement planning and execution and will likewise be necessary for successful motor prostheses and brain-machine interfaces (BMIs). Here we demonstrate that monkeys were able to learn to use an initially unfamiliar multichannel intracortical microstimulation signal, which provided continuous information about hand position relative to an unseen target, to complete accurate reaches. Furthermore, monkeys combined this artificial signal with vision to form an optimal, minimum-variance estimate of relative hand position. These results demonstrate that a learning-based approach can be used to provide a rich artificial sensory feedback signal, suggesting a new strategy for restoring proprioception to patients using BMIs, as well as a powerful new tool for studying the adaptive mechanisms of sensory integration.

Indexed as

AnimalsBehavior, AnimalBrain-Computer InterfacesConditioning, OperantFeedback, PsychologicalLearningMacaca mulattaMalePhotic StimulationPsychomotor PerformanceSensationSomatosensory CortexVisual Perception

Identifiers

PMID25420067
PMCPMC4282864

What OpenQuestion holds

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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.