bioRxivNeurosciencePreprint
Exploring the properties of the left angular gyrus using TMS-evoked potentials
Dominika ŠulcováiD, Yasmine SalmaniD, Adrian Ivanoiu, André MourauxiD
Abstract
The angular gyrus (AG) is involved in multiple cognitive processes and its structural alterations are commonly observed in many neuropsychiatric syndromes. Since changes in excitability may precede structural changes and clinical symptoms, there is a need for diagnostic tools assessing the functional state of hub brain regions like the AG. The combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) can provide such functional readouts by probing the brain response to direct stimulation. This study aimed to characterize TMS-evoked potentials (TEP) elicited by AG stimulation, determine optimal stimulation parameters, and identify TEP biomarkers of AG function. We recorded AG-TEPs in 19 subjects using four TMS orientations and three intensities and compared TEP spatiotemporal features using topographic dissimilarity and microstate analyses. Additionally, we explored the relationship between AG-TEP topography and TMS-evoked muscular activity. Our results showed topographic variability in AG-TEP components P25, N45, and N75. The P25 topography was sensitive to TMS orientation, while the topography of N45 and N75 was highly dependent on both coil orientation and intensity. Interestingly, we found that TMS-evoked muscular activity was also dependent on both these parameters and strongly related to the occurrence of a specific topographic pattern, which therefore possibly corresponds to the somatosensory brain response to muscle contraction. We conclude that the early AG-TEP component P25 likely reflects neural processes triggered by direct AG activation and could provide an index of local excitability. Later components N45 and N75 must be interpreted with caution as they may primarily reflect peripherally evoked activity.
- organism: human
- assay: electronic health records
- research focus: cell type annotation
- approach: statistical model
- Citations
- 1
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