Evidence map›Paper›PMID 35558420›Full record

ArticleFrontiers in psychiatry2022

Prediction-Related Frontal-Temporal Network for Omission Mismatch Activity in the Macaque Monkey.

Yuki Suda, Mariko Tada, Takeshi Matsuo, Keisuke Kawasaki, Takeshi Saigusa, Maho Ishida, Tetsuo Mitsui, Hironori Kumano, Kenji Kirihara, Takafumi Suzuki and 4 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in psychiatry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.9field-weighted citation impact, top 15% 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

11 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
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  5. Different Subregions of Monkey Lateral Prefrontal Cortex Respond to Abstract Sequences and Their Components.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024
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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

14 authors at 6 institutions in 1 country.

Yuki SudaDepartment of Integrative Physiology, Graduate School of Medicine, University of Yamanashi, Chuo, Japan.
Mariko TadaDepartment of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Bunkyo, Japan.
Takeshi MatsuoDepartment of Neurosurgery, Tokyo Metropolitan Neurological Hospital, Fuchu, Japan.
Keisuke KawasakiDepartment of Physiology, Niigata University School of Medicine, Chuo, Japan.
Takeshi SaigusaDepartment of Integrative Physiology, Graduate School of Medicine, University of Yamanashi, Chuo, Japan.
Maho IshidaDepartment of Integrative Physiology, Graduate School of Medicine, University of Yamanashi, Chuo, Japan.
Tetsuo MitsuiDepartment of Integrative Physiology, Graduate School of Medicine, University of Yamanashi, Chuo, Japan.
Hironori KumanoDepartment of Integrative Physiology, Graduate School of Medicine, University of Yamanashi, Chuo, Japan.
Kenji KiriharaDepartment of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Bunkyo, Japan.
Takafumi SuzukiCenter for Information and Neural Networks, National Institute of Information and Communications Technology, Suita, Japan.
Kenji MatsumotoBrain Science Institute, Tamagawa University, Machida, Japan.
Isao HasegawaDepartment of Physiology, Niigata University School of Medicine, Chuo, Japan.
Kiyoto KasaiDepartment of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Bunkyo, Japan.
Takanori UkaDepartment of Integrative Physiology, Graduate School of Medicine, University of Yamanashi, Chuo, Japan.
University of Yamanashi · JPThe University of Tokyo · JPNiigata University · JPTamagawa University · JPNational Institute of Information and Communications Technology · JPTokyo Metropolitan Neurological Hospital · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sensory prediction is considered an important element of mismatch negativity (MMN) whose reduction is well known in patients with schizophrenia. Omission MMN is a variant of the MMN which is elicited by the absence of a tone previously sequentially presented. Omission MMN can eliminate the effects of sound differences in typical oddball paradigms and affords the opportunity to identify prediction-related signals in the brain. Auditory predictions are thought to reflect bottom-up and top-down processing within hierarchically organized auditory areas. However, the communications between the various subregions of the auditory cortex and the prefrontal cortex that generate and communicate sensory prediction-related signals remain poorly understood. To explore how the frontal and temporal cortices communicate for the generation and propagation of such signals, we investigated the response in the omission paradigm using electrocorticogram (ECoG) electrodes implanted in the temporal, lateral prefrontal, and orbitofrontal cortices of macaque monkeys. We recorded ECoG data from three monkeys during the omission paradigm and examined the functional connectivity between the temporal and frontal cortices by calculating phase-locking values (PLVs). This revealed that theta- (4-8 Hz), alpha- (8-12 Hz), and low-beta- (12-25 Hz) band synchronization increased at tone onset between the higher auditory cortex and the frontal pole where an early omission response was observed in the event-related potential (ERP). These synchronizations were absent when the tone was omitted. Conversely, low-beta-band (12-25 Hz) oscillation then became stronger for tone omission than for tone presentation approximately 200 ms after tone onset. The results suggest that auditory input is propagated to the frontal pole

Indexed as

electrocorticogram (ECoG)macaquemismatch negativity (MMN)predictionschizophrenia

Identifiers

PMID35558420
PMCPMC9086590
OpenAlexW4280605489

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.