Evidence map›Paper›PMID 42735843›Full record

ArticleNeuroImage2026

Whole-brain millisecond-scale effective connectivity of auditory and visual naming.

Ryuzaburo Kochi, Aya Kanno, Hiroshi Uda, Keisuke Hatano, Masaki Sonoda, Hidenori Endo, Michael Cools, Robert Rothermel, Aimee F Luat, Eishi Asano

Abstract read
In one paragraph

Article in NeuroImage, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

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No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Ryuzaburo KochiDepartment of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit Medical Center, Detroit, MI, 48201, USA; Department of Neurosurgery, Tohoku University, Sendai, 9808575, Japan.
Aya KannoDepartment of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit Medical Center, Detroit, MI, 48201, USA; Department of Neurosurgery, Sapporo Medical University, Sapporo, Hokkaido, 0608543, Japan.
Hiroshi UdaDepartment of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit Medical Center, Detroit, MI, 48201, USA; Department of Neurosurgery, Osaka Metropolitan University Graduate School of Medicine, Osaka, 5458585, Japan.
Keisuke HatanoDepartment of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit Medical Center, Detroit, MI, 48201, USA.
Masaki SonodaDepartment of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit Medical Center, Detroit, MI, 48201, USA; Department of Neurosurgery, Yokohama City University Graduate School of Medicine, Yokohama, 2360004, Japan.
Hidenori EndoDepartment of Neurosurgery, Tohoku University, Sendai, 9808575, Japan.
Michael CoolsDepartment of Neurosurgery, Children's Hospital of Michigan, Detroit Medical Center, Detroit, MI, 48201, USA.
Robert RothermelDepartment of Psychiatry, Children's Hospital of Michigan, Wayne State University, Detroit Medical Center, Detroit, MI, 48201, USA; Department of Pediatrics, Central Michigan University, Mt. Pleasant, MI, 48858, USA.
Aimee F LuatDepartment of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit Medical Center, Detroit, MI, 48201, USA; Department of Pediatrics, Central Michigan University, Mt. Pleasant, MI, 48858, USA; Department of Neurology, Children's Hospital of Michigan, Wayne State University, Detroit Medical Center, Detroit, MI, 48201, USA.
Eishi AsanoDepartment of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit Medical Center, Detroit, MI, 48201, USA; Department of Pediatrics, Central Michigan University, Mt. Pleasant, MI, 48858, USA; Department of Neurology, Children's Hospital of Michigan, Wayne State University, Detroit Medical Center, Detroit, MI, 48201, USA. Electronic address: easano@med.wayne.edu.

Funding

Functional brain mapping in pediatric neurosurgeryR01NS064033 · NINDS · WAYNE STATE UNIVERSITY · PI EISHI ASANO · 2009 to 2026
$5.7M
NINDS NIH HHS R01 NS064033
6 · The paper itself

Abstract

objectiveClinical mapping studies in epilepsy and brain tumor surgery have informed neurobiological models of speech. However, a comprehensive model requires clarification of when, for how long, and in what directions cortical regions transmit information to support processes ranging from perception and comprehension to lexical retrieval and articulation. We aimed to characterize whole-brain patterns of directional neural information flow during auditory and visual naming.

methodsWe studied 127 patients who performed auditory and picture naming tasks during intracranial EEG recordings, analyzing 9526 artifact-free nonepileptic recording sites. We applied transfer entropy-based effective connectivity analysis to estimate information flow between brain regions. Information flow was classified as accelerating when increases in group-level high-gamma amplitude in one region predicted subsequent increases in another region connected by white matter, and decelerating when decreases predicted subsequent decreases in the downstream region. The functional relevance of these information flow patterns was evaluated using electrical stimulation mapping and behavioral response times.

resultsFollowing stimulus onset, accelerating flows emerged from modality-specific sensory cortices and propagated to higher-order regions before becoming bidirectional. These transient accelerating flows were typically followed by decelerating phases, during which new accelerating flows arose. Stronger accelerating flows at specific time points predicted a higher probability of stimulation-induced symptoms (Spearman's rho: 0.54-0.81; p < 0.00,001). During auditory naming, faster responses were associated with stronger accelerating flows within left perisylvian pathways, whereas during visual naming faster responses were associated with stronger accelerating flows within bilateral basal temporal pathways. DISCUSSION: Strong accelerating flows, followed rapidly by decelerating flows, predicted stimulation-induced symptoms and faster behavioral responses, indicating that information transfer through white matter supports sequential transitions from perception to lexical retrieval and articulation. By resolving the direction of neural propagation through white matter pathways, this study provides a whole-brain model of temporally precise, anatomically specific, and directional network interactions underlying human speech.

Indexed as

Auditory PerceptionBrainNerve NetVisual PerceptionAdolescentAdultBrain MappingElectrocorticographyEpilepsyFemaleHumansMaleMiddle AgedYoung AdultDynamic causal tractography atlasEpilepsy surgeryLanguage organization

Identifiers

PMID42735843
PMCPMC13659335

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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.