The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Transfer of coded information from sensory to motor networks
Open accessAbstract
During sensory-guided motor tasks, information must be transferred from arrays of neurons coding target location to motor networks that generate and control movement. We address two basic questions about this information transfer. First, what mechanisms assure that the different neural representations align properly so that activity in the sensory network representing target location evokes a motor response generating accurate movement toward the target? Coordinate transformations may be needed to put the sensory data into a form appropriate for use by the motor system. For example, in visually guided reaching the location of a target relative to the body is determined by a combination of the position of its image on the retina and the direction of gaze. What assures that the motor network responds to the appropriate combination of sensory inputs corresponding to target position in body- or arm-centered coordinates? To answer these questions, we model a sensory network coding target position and use it to drive a similarly modeled motor network. To determine the actual motor response we use decoding methods that have been developed and verified in experimental work. We derive a general set of conditions on the sensory-to-motor synaptic connections that assure a properly aligned and transformed response. The accuracy of the response for different numbers of coding cells is computed. We show that development of the synaptic weights needed to generate the correct motor response can occur spontaneously through the observation of random movements and correlation-based synaptic modification. No error signal or external teaching is needed during this process. We also discuss nonlinear coordinate transformations and the presence of both shifting and nonshifting receptive fields in sensory/motor systems.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Fukushima, K. (1980) · Biological Cybernetics · doi:10.1007/bf00344251 · Cited by 5,759
Correlated neuronal discharge rate and its implications for psychophysical performance
Zohary, E., Shadlen, M. N., & Newsome, W. T. (1994) · Nature · doi:10.1038/370140a0 · Cited by 1,237
Olshausen, B., Anderson, C., & Van Essen, D. (1993) · The Journal of Neuroscience · doi:10.1523/jneurosci.13-11-04700.1993 · Cited by 908
Visual and Eye Movement Functions of the Posterior Parietal Cortex
Andersen, R. A. (1989) · Annual Review of Neuroscience · doi:10.1146/annurev.ne.12.030189.002113 · Cited by 382
Cited by
Intentional Maps in Posterior Parietal Cortex
Andersen, R. A., & Buneo, C. A. (2002) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.25.112701.142922 · Cited by 1,294
Gain Modulation from Background Synaptic Input
Chance, F. S., Abbott, L. F., & Reyes, A. D. (2002) · Neuron · doi:10.1016/s0896-6273(02)00820-6 · Cited by 1,012
Self-citationConfidence and certainty: Distinct probabilistic quantities for different goals
Pouget, A., Drugowitsch, J., & Kepecs, A. (2016) · Nature Neuroscience · doi:10.1038/nn.4240 · Cited by 528
Visuospatial properties of ventral premotor cortex
Graziano, M. S. A., Hu, X. T., & Gross, C. G. (1997) · Journal of Neurophysiology · doi:10.1152/jn.1997.77.5.2268 · Cited by 603
Spatial Cognition and the Brain
Burgess, N. (2008) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1440.002 · Cited by 614
Metadata
- Authors
- Salinas, E., & Abbott, L.
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 1995-10-01
- Volume
- 15
- Issue
- 10
- Pages
- 6461-6474
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- OpenAlex
- W2138667780
- Cited by
- 295
- References
- 4
- FWCI
- 7.89
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Transfer of coded information from sensory to motor networks. https://app.cochat.ai/papers/10.1523/jneurosci.15-10-06461.1995
- The paper
- Salinas, E., & Abbott, L. (1995). Transfer of coded information from sensory to motor networks. The Journal of Neuroscience. https://doi.org/10.1523/jneurosci.15-10-06461.1995
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.