Biology subjects

Ukharova, E.

Publications and source records attributed to Ukharova, E..

3 recordsLinked to original sources

bioRxiv2025

Predictive modeling of TMS-evoked responses: Unraveling instantaneous excitability states

Transcranial magnetic stimulation (TMS) combined with electroencephalography (EEG) and electromyography (EMG) provides a unique window into instantaneous cortical and corticospinal excitability states. We investigated 50 healthy participants to determine how fluctuations in pre-stimulus brain activity influence single-trial TMS-evoked potentials (TEPs) and motor-evoked potentials (MEPs). We developed a novel automated source-level TEP extraction method using individualized spatiotemporal priors that is robust against poor single-trial signal-to-noise ratios (SNRs) and ongoing oscillations. TEP and MEP amplitudes were predicted with linear mixed-effects models based on pre-stimulation EEG band-powers (theta to gamma), while accounting for temporal drifts (within-session trends), coil control, and inter-subject differences. We found that higher pre-stimulus sensorimotor alpha, beta, and gamma power were each associated with larger TEPs, indicating a more excitable cortical state. Increases in alpha and gamma power immediately before stimulation specifically predicted larger MEPs, reflecting increased corticospinal excitability. These results reveal relationships between ongoing oscillatory brain states and TMS response amplitudes, identifying EEG biomarkers of high- and low-excitability states. In conclusion, our study demonstrates the feasibility of single-trial source-level TMS-EEG analysis and shows that spontaneous alpha-, beta-, and gamma-band oscillations modulate motor cortical and corticospinal responsiveness. These findings pave the way for EEG-informed, brain-state-dependent TMS protocols to optimize neuromodulatory interventions in clinical and research applications.

neuroscience↗

bioRxiv2024

Optimization of TMS target engagement: novel evidence based on combined TMS-EEG and dMRI tractography of brain circuitry

Neuromodulation is based on the principle that brain stimulation produces plastic changes in cerebral circuitry. Given the intersubject structural and functional variability, neuromodulation has a personalized effect in the brain. Moreover, because of cerebral dominance and interhemispheric functional and structural differences in the same individual, the characterization of specific brain circuitries involved is currently not feasible. This notion is extremely important for neuromodulation treatments applied in neuropsychiatry. Specifically, the efficacy of the neuromodulation treatments is critically dependent on the anatomical precision of the brain target and the circuitry which has been affected. However, a complete understanding of how the brain behaves under stimulation needs a combined characterization of its neurophysiological response. This can be achieved by TMS-EEG guided by current multimodal neuroimaging techniques in real time. Herein, we present novel data based on dMRI tractography-guided TMS-EEG on one healthy young adult volunteer.

neuroscience↗

bioRxiv2024

The FinnBrain Multimodal Neonatal Template and Atlas Collection: T1, T2, and DTI brain templates, and accompanying cortical and subcortical atlases

The accurate processing of neonatal and infant brain MRI data is crucially important for developmental neuroscience, but presents challenges that child and adult data do not. Tissue segmentation and image coregistration accuracy can be improved by optimizing template images and / or related segmentation procedures. Here, we describe the construction of the FinnBrain Neonate (FBN-125) template; a multi-contrast template with T1- and T2-weighted as well as diffusion tensor imaging derived fractional anisotropy and mean diffusivity images. The template is symmetric and aligned to the Talairach-like MNI 152 template and has high spatial resolution (0.5 mm3). In addition, we provide atlas labels, constructed from manual segmentations, for cortical grey matter, white matter, cerebrospinal fluid, brainstem, and cerebellum as well as the bilateral hippocampi, amygdalae, caudate nuclei, putamina, globi pallidi, and thalami. We provide this multi-contrast template along with the labelled atlases for the use of the neuroscience community in the hope that it will prove useful in advancing developmental neuroscience, for example, by helping to achieve reliable means for spatial normalization and measures of neonate brain structure via automated computational methods. Additionally, we provide standard co-registration files that will enable investigators to reliably transform their statistical maps to the adult MNI space, which has the potential to improve the consistency and comparability of neonatal studies or the use of adult MNI space atlases in neonatal neuroimaging.

neuroscience↗