Evidence map›Paper›PMID 40791209›Full record

ArticleImaging neuroscience (Cambridge, Mass.)2025

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

Maria Hakonen, Louisa Dahmani, Kaisu Lankinen, Jianxun Ren, Julianna Barbaro, Anna Blazejewska, Weigang Cui, Parker Kotlarz, Meiling Li, Jonathan R Polimeni and 5 more

Abstract read
In one paragraph

Article in Imaging neuroscience (Cambridge, Mass.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors.

Maria HakonenAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, Boston, MA, United States.
Louisa DahmaniAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, Boston, MA, United States.
Kaisu LankinenAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, Boston, MA, United States.
Jianxun RenDivision of Brain Sciences, Changping Laboratory, Beijing, China.
Julianna BarbaroAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, Boston, MA, United States.
Anna BlazejewskaAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, Boston, MA, United States.
Weigang CuiDivision of Brain Sciences, Changping Laboratory, Beijing, China.
Parker KotlarzAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, Boston, MA, United States.
Meiling LiDivision of Brain Sciences, Changping Laboratory, Beijing, China.
Jonathan R PolimeniAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, Boston, MA, United States.
Tori TurpinAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, Boston, MA, United States.
Işıl UluçAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, Boston, MA, United States.
Danhong WangAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, Boston, MA, United States.
Hesheng LiuDivision of Brain Sciences, Changping Laboratory, Beijing, China.
Jyrki AhveninenAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital Charlestown, Boston, MA, United States.

Funding

Training and Dissemination CoreP41EB030006 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI Susie Yi Huang · 2020 to 2026
$10.9M
Project 4P41EB015896 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI ROSEN, BRUCE R · 2012 to 2018
$9.8M
fMRI Technologies for Imaging at the Limit of Biological Spatiotemporal Resolution: Administrative SupplementR01EB019437 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI POLIMENI, JONATHAN RIZZO, SETSOMPOP, KAWIN · 2015 to 2024
$5.5M
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
Subtyping tinnitus based on fMRI dynamic functional connectivityK99DC022305 · NIDCD · MASSACHUSETTS GENERAL HOSPITAL · PI Maria Hakonen · 2025 to 2026
$269k
NIBIB NIH HHS P41 EB015896NIBIB NIH HHS P41 EB030006NIBIB NIH HHS R01 EB019437NIDCD NIH HHS K99 DC022305NIDCD NIH HHS R01 DC016765NIDCD NIH HHS R01 DC016915NIDCD NIH HHS R01 DC017991NIH HHS S10 OD023637
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 (15 women) 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 the Dice coefficients and Silhouette values. The resulting parcellation of auditory cortices showed intraindividual reproducibility of 69-78% between resting-state sessions and 62-73% between resting-state and task sessions, indicating moderate reproducibility. 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 the auditory cortex. Together, our results show that auditory areas in STC can be segmented into functional subareas based on functional connectivity. Our findings also suggest that individual-level parcellations capture meaningful idiosyncrasies in auditory cortex organization.

Indexed as

7T fMRIauditory cortexfunctional connectivityhumanindividual differencesparcellation

Identifiers

PMID40791209
PMCPMC12319797

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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.