Evidence map›Paper›PMID 42016557›Full record

ArticleImaging neuroscience (Cambridge, Mass.)

All spectral frequencies of neural activity reveal semantic representation in the human anterior ventral temporal cortex.

Saskia L Frisby, Ajay D Halai, Christopher R Cox, Alex Clarke, Akihiro Shimotake, Takayuki Kikuchi, Takeharu Kuneida, Yoshiki Arakawa, Ryosuke Takahashi, Akio Ikeda and 3 more

Abstract read
In one paragraph

Article in Imaging neuroscience (Cambridge, Mass.). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

13 authors.

Saskia L FrisbyMRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom.ORCID https://orcid.org/0000-0002-5786-6900
Ajay D HalaiMRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom.ORCID https://orcid.org/0000-0003-1725-7948
Christopher R CoxDepartment of Psychology, Louisiana State University, Baton Rouge, LA, United States.ORCID https://orcid.org/0000-0001-8287-3865
Alex ClarkeDepartment of Psychology, University of Warwick, Warwick, United Kingdom.
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 KuneidaDepartment of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Yoshiki ArakawaDepartment 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 of Medicine, Kyoto, Japan.
Riki MatsumotoDepartment of Neurology, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Timothy T RogersDepartment of Psychology, University of Wisconsin-Madison, Madison, WI, United States.
Matthew A Lambon RalphMRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Intracranial electrophysiology offers a unique insight into the nature of information representation in the brain-it can be used to disentangle information encoded in gamma and high gamma frequencies from information encoded in lower frequencies. We used regularised logistic regression to decode animacy from time-frequency power and phase extracted from electrocorticography (ECoG) grid electrode data recorded on the surface of human ventral anterior temporal lobe (vATL). Power in gamma (30-60 Hz) and high gamma (60-200 Hz) produced reliable decoding, indicating that semantic information is, indeed, expressed by local populations in vATL. However, power from a wide range of frequencies (4-200 Hz) produced significantly higher decoding accuracy and also exhibited the same rapidly-changing dynamic code previously observed when decoding voltage. These findings support the theory that semantic information is encoded by a local vATL "hub" that interacts with distributed cortical "spokes".

Indexed as

decodingelectrocorticographyintracranial electrophysiologymultivariate pattern analysissemantic representationtime-frequency analysis

Identifiers

PMID42016557
PMCPMC13094022

What OpenQuestion holds

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Registered trials

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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.