Evidence map›Paper›PMID 36408645›Full record

ArticleCerebral cortex (New York, N.Y. : 1991)2023

The dynamics of cortical interactions in visual recognition of object category: living versus nonliving.

Kiyohide Usami, Riki Matsumoto, Anna Korzeniewska, Akihiro Shimotake, Masao Matsuhashi, Takuro Nakae, Takayuki Kikuchi, Kazumichi Yoshida, Takeharu Kunieda, Ryosuke Takahashi and 2 more

Open access · greenAbstract read
In one paragraph

Article in Cerebral cortex (New York, N.Y. : 1991), 2023. 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
0.2field-weighted citation impact, top 49% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  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

12 authors at 5 institutions in 2 countries.

Kiyohide UsamiDepartment of Epilepsy, Movement Disorders and Physiology, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan.ORCID 0000-0003-2257-8279
Riki MatsumotoDivision of Neurology, Kobe University Graduate School of Medicine, Kobe 650-0017, Japan.ORCID 0000-0003-3985-9210
Anna KorzeniewskaDepartment of Neurology, Johns Hopkins University School of Medicine, MD 21287, United States.ORCID 0000-0002-9453-7751
Akihiro ShimotakeDepartment of Neurology, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan.ORCID 0000-0003-3777-685X
Masao MatsuhashiDepartment of Epilepsy, Movement Disorders and Physiology, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan.ORCID 0000-0003-2385-1265
Takuro NakaeDepartment of Neurosurgery, Shiga General Hospital, Moriyama 524-8524, Japan.ORCID 0000-0002-3574-1744
Takayuki KikuchiDepartment of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan.ORCID 0000-0002-6295-5510
Kazumichi YoshidaDepartment of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan.ORCID 0000-0002-8898-079X
Takeharu KuniedaDepartment of Neurosurgery, Ehime University Graduate School of Medicine, Toon 791-0295, Japan.ORCID 0000-0001-8653-0763
Ryosuke TakahashiDepartment of Neurology, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan.ORCID 0000-0002-1407-9640
Nathan E CroneDepartment of Neurology, Johns Hopkins University School of Medicine, MD 21287, United States.ORCID 0000-0001-7950-2617
Akio IkedaDepartment of Epilepsy, Movement Disorders and Physiology, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan.ORCID 0000-0002-0790-2598
Kyoto University · JPJohns Hopkins University · USEhime University · JPKobe University · JPShiga Medical Center · JP

Funding

Diagnostic validity and safety of high-gamma language mapping with intracranial EEGR01NS115929 · NINDS · JOHNS HOPKINS UNIVERSITY · PI Ravindra Arya, NATHAN E CRONE · 2020 to 2026
$3.9M
Temporal-spatial mapping of cortical networks important for human cognitionR01NS091139 · NINDS · JOHNS HOPKINS UNIVERSITY · PI CRONE, NATHAN E · 2015 to 2019
$1.8M
NINDS NIH HHS R01 NS091139NINDS NIH HHS R01 NS115929
6 · The paper itself

Abstract

Noninvasive brain imaging studies have shown that higher visual processing of objects occurs in neural populations that are separable along broad semantic categories, particularly living versus nonliving objects. However, because of their limited temporal resolution, these studies have not been able to determine whether broad semantic categories are also reflected in the dynamics of neural interactions within cortical networks. We investigated the time course of neural propagation among cortical areas activated during object naming in 12 patients implanted with subdural electrode grids prior to epilepsy surgery, with a special focus on the visual recognition phase of the task. Analysis of event-related causality revealed significantly stronger neural propagation among sites within ventral temporal lobe (VTL) at early latencies, around 250 ms, for living objects compared to nonliving objects. Differences in other features, including familiarity, visual complexity, and age of acquisition, did not significantly change the patterns of neural propagation. Our findings suggest that the visual processing of living objects relies on stronger causal interactions among sites within VTL, perhaps reflecting greater integration of visual feature processing. In turn, this may help explain the fragility of naming living objects in neurological diseases affecting VTL.

Indexed as

Brain MappingRecognition, PsychologyBrainHumansPattern Recognition, VisualSemanticsTemporal Lobecausal interactionevent-related causalityhigh-gamma activitypicture naming

Identifiers

PMID36408645
PMCPMC10152084
OpenAlexW4309506281

What OpenQuestion holds

Textmetadata
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.