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Zusammenfassung:
Objective: Microstructural mapping indicates multiple sub-areas within Broca’s region which constitutes a core node in the language network. Connectivity based parcellations of white matter fiber tractograms have been shown to correlate with cytoarchitectonic mapping. More recently, navigated transcranial magnetic stimulation (TMS) language mapping at high spatial resolution revealed a focus of TMS impact close to the inferior frontal junction area. Here, we correlate a novel connectivity-based structural parcellation approach with TMS language mapping results.
Methods: Twelve healthy, left-dominant native German speakers underwent both diffusion tensor magnetic resonance imaging and high-resolution TMS language mapping with a previously described focus of TMS susceptibility in the inferior frontal junction area. Diffusion-weighted images were acquired at 3 Tesla and were isotopic distributed along 64 directions (b-value = 1000 s/mm2). Data were analyzed using the FMRIB Software Library (FSL) Diffusion Toolbox FDT with standard preprocessing. Probabilistic tractography was performed based on 30 seed volumes originating from TMS stimulation sites systematically covering Broca’s region. Linear registration to the MNI template was performed for normalization. A multi-session temporal concatenation independent component analysis (ICA; FSL Toolbox MELODIC) was applied to the series of tractograms. Four independent components and thus four clusters of stimulation sites were specified. This parcellation of Broca’s area was correlated to TMS results and probabilistic cytoarchitectonic maps.
Results: The dorso-posterior cluster corresponded clearly to the inferior frontal junction area and the focus of TMS susceptibility in naming. Medial clusters were arranged along the border of cytoarchitectonic areas 44 and 45, while the anterior cluster was restricted to area 45.
Conclusion: Parcellation of Broca’s region according to an ICA of structural connectivity data appears to converge with functional clustering of high-resolution TMS language mapping. This correspondence will lead to a more detailed understanding of the structure-function relationships within the language network and might have clinical impact in pre-surgical planning.
