Evidence map›Paper›PMID 38293021›Full record

ArticlebioRxiv : the preprint server for biology2024

Individual connectivity-based parcellations reflect functional properties of human auditory cortex.

M Hakonen, L Dahmani, K Lankinen, J Ren, J Barbaro, A Blazejewska, W Cui, P Kotlarz, M Li, J R Polimeni and 5 more

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

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

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

15 authors.

M HakonenAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, MA, USA.ORCID 0000-0002-0322-4347
L DahmaniAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, MA, USA.ORCID 0000-0003-1335-6340
K LankinenAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, MA, USA.ORCID 0000-0003-2210-2385
J RenDivision of Brain Sciences, Changping Laboratory, Beijing, China.ORCID 0000-0002-7885-4546
J BarbaroAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, MA, USA.
A BlazejewskaAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, MA, USA.ORCID 0000-0002-2944-1147
W CuiDivision of Brain Sciences, Changping Laboratory, Beijing, China.
P KotlarzAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, MA, USA.ORCID 0000-0003-3667-8908
M LiDivision of Brain Sciences, Changping Laboratory, Beijing, China.
J R PolimeniAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, MA, USA.ORCID 0000-0002-1348-1179
T TurpinAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, MA, USA.ORCID 0000-0003-1751-2283
I UluçAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, MA, USA.
D WangAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, MA, USA.
H LiuDivision of Brain Sciences, Changping Laboratory, Beijing, China.ORCID 0000-0002-7233-1509
J AhveninenAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, MA, USA.ORCID 0000-0001-9058-8669

Funding

Project 4U19NS123717 · NINDS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI LINNINGER, ANDREAS A · 2021 to 2025
$13.4M
Training and Dissemination CoreP41EB030006 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI BRUCE R ROSEN · 2020 to 2026
$10.9M
Project 4P41EB015896 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI ROSEN, BRUCE R · 2012 to 2018
$9.8M
Mapping the intrinsic functional organization of auditory cortex in individual subjects using 7T MRIR01DC017991 · NIDCD · MASSACHUSETTS GENERAL HOSPITAL · PI AHVENINEN, JYRKI · 2019 to 2023
$4.0M
Decoding parametric attributes of auditory working memories from human brain activityR01DC016915 · NIDCD · MASSACHUSETTS GENERAL HOSPITAL · PI AHVENINEN, JYRKI · 2018 to 2022
$3.0M
Non-invasive measures of multisensory cortical feedforward and feedback influencesR01DC016765 · NIDCD · MASSACHUSETTS GENERAL HOSPITAL · PI AHLFORS, SEPPO PENTTI, AHVENINEN, JYRKI · 2018 to 2022
$2.7M
System Upgrade for Siemens 7T Human MRI SystemS10OD023637 · OD · MASSACHUSETTS GENERAL HOSPITAL · PI WALD, LAWRENCE L · 2017 to 2017
$2.0M
Relating functional MRI to neuronal activity: accounting for effects of microarchitectureR00MH120054 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI BLAZEJEWSKA, ANNA I · 2022 to 2024
$722k
NIBIB NIH HHS P41 EB015896NIBIB NIH HHS P41 EB030006NIDCD NIH HHS R01 DC016765NIDCD NIH HHS R01 DC016915NIDCD NIH HHS R01 DC017991NIH HHS S10 OD023637NIMH NIH HHS R00 MH120054NINDS NIH HHS U19 NS123717
6 · The paper itself

Abstract

Neuroimaging studies of the functional organization of human auditory cortex have focused on group-level analyses to identify tendencies that represent the typical brain. Here, we mapped auditory areas of the human superior temporal cortex (STC) in 30 participants by combining functional network analysis and 1-mm isotropic resolution 7T functional magnetic resonance imaging (fMRI). Two resting-state fMRI sessions, and one or two auditory and audiovisual speech localizer sessions, were collected on 3-4 separate days. We generated a set of functional network-based parcellations from these data. Solutions with 4, 6, and 11 networks were selected for closer examination based on local maxima of Dice and Silhouette values. The resulting parcellation of auditory cortices showed high intraindividual reproducibility both between resting state sessions (Dice coefficient: 69-78%) and between resting state and task sessions (Dice coefficient: 62-73%). This demonstrates that auditory areas in STC can be reliably segmented into functional subareas. The interindividual variability was significantly larger than intraindividual variability (Dice coefficient: 57%-68%, p<0.001), indicating that the parcellations also captured meaningful interindividual variability. The individual-specific parcellations yielded the highest alignment with task response topographies, suggesting that individual variability in parcellations reflects individual variability in auditory function. Connectional homogeneity within networks was also highest for the individual-specific parcellations. Furthermore, the similarity in the functional parcellations was not explainable by the similarity of macroanatomical properties of auditory cortex. Our findings suggest that individual-level parcellations capture meaningful idiosyncrasies in auditory cortex organization.

Indexed as

7T fMRIauditory cortexfunctional connectivityhumanindividual differencesparcellation

Identifiers

PMID38293021
PMCPMC10827228

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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.