Evidence map›Paper›PMID 34704935›Full record

ArticleeLife2021

Evidence for a deep, distributed and dynamic code for animacy in human ventral anterior temporal cortex.

Timothy T Rogers, Christopher R Cox, Qihong Lu, Akihiro Shimotake, Takayuki Kikuchi, Takeharu Kunieda, Susumu Miyamoto, Ryosuke Takahashi, Akio Ikeda, Riki Matsumoto and 1 more

Open access · goldAbstract read
In one paragraph

Article in eLife, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
4.7field-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

26 citing papers in PubMed, 54 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  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

11 authors at 5 institutions in 3 countries.

Timothy T RogersDepartment of Psychology, University of Wisconsin- Madison, Madison, United States.ORCID 0000-0001-6304-755X
Christopher R CoxDepartment of Psychology, Louisiana State University, Baton Rouge, United States.ORCID 0000-0001-8287-3865
Qihong LuDepartment of Psychology, Princeton University, Princeton, United States.
Akihiro ShimotakeDepartment of Neurology, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Takayuki KikuchiDepartment of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Takeharu KuniedaDepartment of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Susumu MiyamotoDepartment of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Ryosuke TakahashiDepartment of Neurology, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Akio IkedaDepartment of Epilepsy, Movement Disorders and Physiology, Kyoto University Graduate School ofMedicine, Kyoto, Japan.
Riki MatsumotoDepartment of Neurology, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Matthew A Lambon RalphMRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0001-5907-2488
Kyoto University · JPLouisiana State University · USMRC Cognition and Brain Sciences Unit · GBPrinceton University · USUniversity of Wisconsin–Madison · US

Funding

Medical Research Council MC_UU_00005/18Medical Research Council MR/J004146/1Medical Research Council MR/R023883/1
6 · The paper itself

Abstract

How does the human brain encode semantic information about objects? This paper reconciles two seemingly contradictory views. The first proposes that local neural populations independently encode semantic features; the second, that semantic representations arise as a dynamic distributed code that changes radically with stimulus processing. Combining simulations with a well-known neural network model of semantic memory, multivariate pattern classification, and human electrocorticography, we find that both views are partially correct: information about the animacy of a depicted stimulus is distributed across ventral temporal cortex in a dynamic code possessing feature-like elements posteriorly but with elements that change rapidly and nonlinearly in anterior regions. This pattern is consistent with the view that anterior temporal lobes serve as a deep cross-modal 'hub' in an interactive semantic network, and more generally suggests that tertiary association cortices may adopt dynamic distributed codes difficult to detect with common brain imaging methods.

Indexed as

AdolescentAdultBrain MappingElectrocorticographyFemaleHumansMaleMemoryNeural Networks, ComputerTemporal LobeYoung AdultcognitionECOGhumanmvpaneural networksneurosciencesemantic memorytemporal lobe

Identifiers

PMID34704935
PMCPMC8550752
OpenAlexW3208303043

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.