Abstract
Objectives
Laryngeal dystonia (LD) is a voice motor disorder involving multilevel central networks. Existing LD functional magnetic resonance imaging (fMRI) studies use heterogeneous region-of-interest (ROI) definitions and parcellation schemes, limiting comparability and reproducibility. To provide a more consistent framework for ROI definition and whole-brain network-level analysis, we aimed to develop and technically validate a standardized, small-structure-preserving whole-brain ROI atlas for LD fMRI research.Methods
We integrated Automated Anatomical Labeling version 1 (AAL1)-derived cerebral and selected subcortical regions, the Spatially Unbiased Infratentorial Template (SUIT) cerebellar atlas, the Najdenovska thalamic nuclei atlas, and Brainstem Navigator-derived diencephalic and brainstem regions. Atlases were harmonized to Montreal Neurological Institute (MNI) space with nearest-neighbor interpolation and small-structure-prioritized merging, generating a 1-mm reference atlas (LD-208) and a 2-mm fMRI-ready atlas (LD-205). Quality control included ROI continuity, zero-voxel checks, voxel counts, connected components, and source tracing. LD-205 was tested in resting-state fMRI data from 10 healthy participants.Results
LD-208 and LD-205 contained 208 and 205 ROIs, respectively. Compared with LD-208, LD-205 did not retain three extremely small brainstem ROIs on the 2-mm grid. Both atlases had continuous ROI numbering and no zero-voxel ROIs. All LD-205 ROIs yielded valid voxels, mean blood oxygen level-dependent (BOLD) time series, and complete 205 × 205 connectivity matrices in every participant.Conclusions
LD-208 and LD-205 provide traceable and quality-controlled whole-brain ROI frameworks for LD-oriented fMRI research. The technical validation demonstrates the feasibility of applying LD-205 to conventional resting-state fMRI data and supports its use as a standardized ROI framework for future disease-specific studies.