Evidence map›Paper›PMID 39423801›Full record

ReviewCell2024

Decoding the brain: From neural representations to mechanistic models.

Mackenzie Weygandt Mathis, Adriana Perez Rotondo, Edward F Chang, Andreas S Tolias, Alexander Mathis

Abstract readReview
In one paragraph

Review in Cell, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Review
  12. Article
  13. Article
  14. Review
  15. Article
  16. Review
  17. Review
  18. Sensory processing reformats odor coding around valence and dynamics.bioRxiv : the preprint server for biology · 2025
    Article
  19. Review
  20. 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

5 authors.

Mackenzie Weygandt MathisBrain Mind Institute, École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland; Neuro-X Institute, École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland. Electronic address: mackenzie.mathis@epfl.ch.
Adriana Perez RotondoBrain Mind Institute, École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland; Neuro-X Institute, École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland.
Edward F ChangDepartment of Neurological Surgery, UCSF, San Francisco, CA, USA.
Andreas S ToliasDepartment of Ophthalmology, Byers Eye Institute, Stanford University, Stanford, CA, USA; Department of Electrical Engineering, Stanford University, Stanford, CA, USA; Stanford BioX, Stanford University, Stanford, CA, USA; Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA.
Alexander MathisBrain Mind Institute, École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland; Neuro-X Institute, École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland.

Funding

A Pilot Clinical Trial for Speech NeuroprosthesisU01DC018671 · NIDCD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI CHANG, EDWARD · 2021 to 2025
$5.6M
Computational foundations of active visual sensingUF1NS126566 · NINDS · STANFORD UNIVERSITY · PI MATHIS, MACKENZIE WEYGANDT, NIELL, CRISTOPHER M · 2022 to 2022
$4.8M
NIDCD NIH HHS U01 DC018671NINDS NIH HHS UF1 NS126566
6 · The paper itself

Abstract

A central principle in neuroscience is that neurons within the brain act in concert to produce perception, cognition, and adaptive behavior. Neurons are organized into specialized brain areas, dedicated to different functions to varying extents, and their function relies on distributed circuits to continuously encode relevant environmental and body-state features, enabling other areas to decode (interpret) these representations for computing meaningful decisions and executing precise movements. Thus, the distributed brain can be thought of as a series of computations that act to encode and decode information. In this perspective, we detail important concepts of neural encoding and decoding and highlight the mathematical tools used to measure them, including deep learning methods. We provide case studies where decoding concepts enable foundational and translational science in motor, visual, and language processing.

Indexed as

BrainModels, NeurologicalNeuronsAnimalsHumansBCIsdata-drivendecodingdeep learningencodinglanguagenormative models

Identifiers

PMID39423801
PMCPMC11637322

What Socratic holds

Textmetadata
LicenceTDM
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 Socratic graph.