Biology subjects

Grano, I.

Publications and source records attributed to Grano, I..

5 recordsLinked to original sources

bioRxiv2026

Distinct cortical excitability and connectivity profiles within the human SMA complex

Introduction and aimUnderstanding brain functions increasingly relies on a network-based perspective, emphasizing interactions across distributed regions. High-order cognitive functions, like language and executive processes, engage such networks rather than isolated cortical areas, yet mapping their dynamics in humans remains challenging. The supplementary motor area (SMA) complex serves as a crucial hub, functioning as an interface between cognitive and sensorimotor processing. Navigated transcranial magnetic stimulation combined with electroencephalography (TMS-EEG) enables causal, time-resolved assessment of cortical excitability and connectivity with high temporal and spatial precision. Extending prior proof-of-concept work, this study aims to provide normative neurophysiological signatures of the SMA complex (pre-SMA and SMA). MethodsTwenty-one healthy subjects underwent a TMS-EEG session where six stimulation targets over the SMA complex (three in pre-SMA, one in the border between pre-SMA and SMA, two in SMA) were recorded. Global cortical excitability via global mean field power (GMFP) was computed over three time-windows (10-50, 50-100, and 100-200 ms) and compared across targets. Normalized power in different frequency bands (, {beta}1, {beta}2, {gamma}) and natural frequency (NF) were also computed and compared across stimulation sites. Then, we calculated tractography-derived connectivity metrics to examine corticothalamic projections from each stimulation site. Apparent fiber density (AFD)-derived connection strength quantified intra-axonal fibre volume along pathways to the whole thalamus, whereas fibre bundle capacity (FBC) assessed the aggregate intra-axonal cross-sectional area at pathway endpoints, providing an estimate of information transmission capacity to each of the 23 thalamic nuclei. ResultsCortical excitability and oscillatory properties varied significantly across TMS targets. A gradient in cortical excitability was observed, where anterior and middle portions of pre-SMA exhibited significantly lower GMFP in the early post-stimulus phase (i.e., 10-50 ms) than SMA portions; interestingly, these differences were clearly dampened in a later time-window (50-100 ms) and disappeared after this period. Furthermore, higher and lower {beta}2 power were observed in anterior pre-SMA than posterior pre-SMA portions. No differences were observed in NF. Crucially, we also observed significant differences in whole- and single-nuclei thalamic structural connectivity. DiscussionThese findings provide direct human in vivo evidence for distinct neurophysiological and structural connectivity profiles of the pre-SMA and SMA, possibly reflecting their different cytoarchitectonic, myeloarchitectonic and connectivity properties. Variations in cortical excitability, oscillatory dynamics, and FBC along the rostro-caudal axis may mirror functional specialization, with pre-SMA supporting cognitive control processes and SMA engaging motor-related thalamocortical networks. Together, the results demonstrate the sensitivity of TMS-EEG and diffusion-weighted connectomics to measure fine-grained neurophysiological differences of corticothalamic projections, which can lead to individualized neuromodulation targeting.

neuroscience↗

bioRxiv2025

The dependency of TMS-evoked potentials on electric-field orientation in the cortex

Transcranial magnetic stimulation (TMS) stimulates the brain by electromagnetic induction. The outcome depends on multiple stimulation parameters such as the induced electric-field pattern (in particular, the location of the peak field and its orientation), intensity and timing. However, it is not clear how the TMS-evoked responses are affected by all the stimulation parameters. This study elucidates the dependency of the TMS-evoked electroencephalography (EEG) responses on the orientation of the stimulating electric field. To achieve this, we analysed a dataset from six subjects who were given pulses with 36 stimulus orientations to the pre-supplementary motor area (pre-SMA). The TMS-evoked potentials (TEPs) and induced oscillations were analysed with cluster-based statistics. Source estimation was performed to assess the effects of stimulus orientation on the TMS-evoked signal propagation. The amplitudes of the early peaks (20 and 40 ms after the TMS pulse) strongly depended on the electric field orientation. Our analysis suggested orientation dependency up to 100 ms post-stimulus in most subjects, indicating changes in stimulation efficacy and potential changes in signal propagation from the stimulated site. These results suggest that different orientations may perturb different networks. Thus, the orientation is a crucial parameter for the stimulation outcome and should be adjusted according to the cortical network under investigation.

neuroscience↗

bioRxiv2024

Test-retest reliability of TMS-evoked potentials over fMRI-based definitions of non-motor cortical targets

ObjectiveThis study assessed the test-retest reliability of TMS-evoked potentials (TEPs) across two cortical regions--dorsolateral prefrontal cortex (DLPFC), and angular gyrus-- in comparison to motor cortex (M1), using individualized and literature-based targeting approaches. The study compared the reliability of single-pulse TMS, short-interval intracortical inhibition (SICI), and long-interval intracortical inhibition (LICI) protocols to evaluate TEP consistency in these regions. MethodsSeventeen healthy participants underwent two TMS-EEG sessions spaced by at least one week, with targets for DLPFC and angular gyrus identified using resting-state functional connectivity (RS) and Neurosynth-based functional overlays. Motor cortex was targeted using resting motor threshold (RMT). Early TEPs were quantified as peak-to-peak amplitude, in dBV. Test-retest reliability of early TEPs was calculated using the concordance correlation coefficient (CCC) for each region and protocol. ResultsM1 demonstrated the highest TEP reliability (CCCmean = 0.59), while DLPFC (CCCmean = 0.40) and angular gyrus (CCCmean = 0.45) showed lower reliability, particularly for anterior DLPFC targets. Neurosynth-based DLPFC targets exhibited slightly higher CCC values (mean CCC = 0.57) compared to RS-based targets (mean CCC = 0.30), but the difference was not statistically significant. No significant differences in reliability were found across single pulse and paired pulse protocols. Lateral targets, DLPFC and angular gyrus, showed lower reliability in comparison to motor cortex which might have been caused by muscle artifacts. ConclusionWhile individualized functional targeting methods provide advantages in engaging specific brain networks, their reliability for TEP measurements remains lower than the RMT-based approach for motor cortex. Future studies should integrate neuroimaging-based targeting with real-time TEP monitoring to enhance reliability in non-motor regions. This approach could enhance the precision of TMS-EEG protocols, especially for clinical applications targeting cortical regions like the DLPFC and angular gyrus.

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↗

bioRxiv2021

Local brain-state dependency of effective connectivity: evidence from TMS-EEG

BackgroundSpontaneous cortical oscillations have been shown to modulate cortical responses to transcranial magnetic stimulation (TMS). If not controlled for, they might increase variability in responses and mask meaningful changes in the signals of interest when studying the brain with TMS combined with electroencephalography (TMS-EEG). To address this challenge in future closed-loop stimulation paradigms, we need to understand how spontaneous oscillations affect TMS-evoked responses. ObjectiveTo describe the effect of the pre-stimulus phase of cortical mu (8-13 Hz) and beta (13-30 Hz) oscillations on TMS-induced effective connectivity patterns. MethodsWe applied TMS to the left primary motor cortex and right pre-supplementary motor area of three subjects while recording EEG. We classified trials off-line into positive- and negative-phase classes according to the mu and beta rhythms. We calculated differences in the global mean-field amplitude (GMFA) and compared the cortical spreading of the TMS-evoked activity between the two classes. ResultsPhase had significant effects on the GMFA in 11 out of 12 datasets (3 subjects x 2 stimulation sites x 2 frequency bands). Seven of the datasets showed significant differences in the time range 15-50 ms, nine in 50-150 ms, and eight after 150 ms post-stimulus. Source estimates showed complex spatial differences between the classes in the cortical spreading of the TMS-evoked activity. ConclusionsTMS-evoked effective connectivity appears to depend on the phase of local cortical oscillations at the stimulated site. This may be crucial for efficient design of future brain-state-dependent and closed-loop stimulation paradigms.

neuroscience↗