Vocalization localizer with high-resolution functional data in macaques (v1)
Year: 2026
Type: dataset
Abstract: This dataset provides high-resolution functional MRI (fMRI) contrast maps investigating the brain networks involved in processing auditory stimuli in macaques. The data originate from an auditory localizer task conducted at KU Leuven, involving two adult rhesus macaques (Macaca mulatta). The shared dataset consists of group-level statistical maps combining data from both subjects, fully normalized to the standard MEBRAIN macaque template space. Specifically, it includes spatial T-maps representing three main functional contrasts: vocalizations versus silence, non-vocalizations versus silence, and vocalizations versus non-vocalizations. Methodologically, these statistical maps were generated using a General Linear Model (GLM) applied to high-resolution functional scans acquired while the subjects were passively exposed to the auditory stimuli. The provided maps are thresholded at an uncorrected p < 0.001 (T-score > 3.09) with a minimum cluster size of 10 voxels. These maps can be reused by the neuroimaging community to define robust auditory and vocalization-selective regions of interest (ROIs) in the macaque brain. Furthermore, being registered to the MEBRAIN space, they can be directly integrated into comparative MRI studies or used as functional priors for future neurophysiological targeted recordings.
Source: EBRAINS
DOI: 10.25493/hgzh-ba0
Authors: Froesel, Mathilda, Zhu, Qi, Vanduffel, Wim
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7202175703