Function of the auditory cortex characterized by its intrinsic dynamic coactivation patterns estimated in individuals

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Authors: Maria Hakonen, Kaisu Lankinen, Parker L. Kotlarz, Jon̈athan R. Polimeni, Tori Turpin, Jianxun Ren, Danhong Wang, Hesheng Liu, Jyrki Ahveninen
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References: 103

Abstract

Determining the functional organization of the auditory cortex (AC) has been difficult with conventional task-based approaches due to the broad responsiveness of auditory subregions to various acoustic properties. Moreover, most studies have investigated functional organization of AC with static methods, although the brain has shown to be organized into dynamic networks. Here, we investigated dynamically varying coactivation patterns of the local networks in the auditory cortex (AC) determined from 7T fMRI data. Dynamic AC patterns successfully captured interindividual variability, as indicated by significantly higher variability between than within individuals for the AC pattern occurrence rates and spatial topographies. The coactivation patterns shared similarities between resting-state and auditory-task data, as indicated by the group-level similarity of 0.84 and individual-level similarity of 0.71 in the spatial topographies. Furthermore, the occurrence rates of AC patterns identified in the task data, using pattern templates derived from resting-state data, correlated with specific task contrast regressors. Our results suggest that the AC function can be characterized by a set of dynamically varying coactivation patterns. These patterns are consistently observed during resting state and auditory stimulation, and they become synchronized with auditory inputs. These findings enhance our understanding of the relationship between spontaneous and stimulus-driven activity in the AC and support the development of more time-efficient paradigms for studying its functional organization.

Fields of Study & Subjects

Functional Brain Connectivity Studies Neuroscience and Music Perception Neural dynamics and brain function

Publication details

Journal / source
Imaging Neuroscience
Volume
4
Publication date
1 January 2026
Language
EN