Evidence map›Paper›PMID 38352422›Full record

ArticlebioRxiv : the preprint server for biology2024

Frontal-Auditory Cortical Interactions and Sensory Prediction During Vocal Production in Marmoset Monkeys.

Joji Tsunada, Steven J Eliades

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Joji TsunadaChinese Institute for Brain Research, Beijing, China.
Steven J EliadesDepartment of Head and Neck Surgery & Communication Sciences, Duke University School of Medicine, Durham, NC 27710, USA.

Funding

Sensory Prediction in the Auditory Cortex during Vocal ProductionR01DC018525 · NIDCD · UNIVERSITY OF PENNSYLVANIA · PI ELIADES, STEVEN J · 2020 to 2024
$2.0M
Cortical Mechanisms of Auditory-Vocal InteractionK08DC014299 · NIDCD · UNIVERSITY OF PENNSYLVANIA · PI ELIADES, STEVEN J · 2015 to 2019
$1.2M
NIDCD NIH HHS K08 DC014299NIDCD NIH HHS R01 DC018525
6 · The paper itself

Abstract

The control of speech and vocal production involves the calculation of error between the intended vocal output and the resulting auditory feedback. Consistent with this model, recent evidence has demonstrated that the auditory cortex is suppressed immediately before and during vocal production, yet is still sensitive to differences between vocal output and altered auditory feedback. This suppression has been suggested to be the result of top-down signals containing information about the intended vocal output, potentially originating from motor or other frontal cortical areas. However, whether such frontal areas are the source of suppressive and predictive signaling to the auditory cortex during vocalization is unknown. Here, we simultaneously recorded neural activity from both the auditory and frontal cortices of marmoset monkeys while they produced self-initiated vocalizations. We found increases in neural activity in both brain areas preceding the onset of vocal production, notably changes in both multi-unit activity and local field potential theta-band power. Connectivity analysis using Granger causality demonstrated that frontal cortex sends directed signaling to the auditory cortex during this pre-vocal period. Importantly, this pre-vocal activity predicted both vocalization-induced suppression of the auditory cortex as well as the acoustics of subsequent vocalizations. These results suggest that frontal cortical areas communicate with the auditory cortex preceding vocal production, with frontal-auditory signals that may reflect the transmission of sensory prediction information. This interaction between frontal and auditory cortices may contribute to mechanisms that calculate errors between intended and actual vocal outputs during vocal communication.

Identifiers

PMID38352422
PMCPMC10862695

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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.