Biology subjects

Gogulski, J.

Publications and source records attributed to Gogulski, J..

9 recordsLinked to original sources

bioRxiv2026

Aperiodic neural activity predicts cortical excitability in TMS-EEG

Background: Fluctuating cortical excitability states are inherent to and critical for brain function. They can be probed non-invasively using transcranial magnetic stimulation (TMS) combined with electroencephalography (EEG) by measuring early local TMS-evoked potentials (EL-TEPs). Pre-stimulus periodic neural activity can predict fluctuating excitability states. To what extent aperiodic neural activity represents a marker of cortical excitability has not been explored. Objectives: We investigated the relationship between pre-stimulus aperiodic and periodic neural activity and EL-TEP amplitude in both the primary motor cortex (M1) and dorsolateral prefrontal cortex (DLPFC). Methods: Single-pulse TMS was delivered to the left M1 or left DLPFC in 29 and 11 healthy adults, respectively, while EEG was recorded simultaneously. Pre-stimulus EEG was parameterized into aperiodic and periodic components to extract the aperiodic exponent (slope of 1/f-like activity), alpha power (8-13 Hz), and beta power (13-30 Hz). EL-TEP peak-to-peak amplitudes were extracted from approximately 20-65 ms after the TMS pulse. Results: Aperiodic exponent showed a strong negative relationship with EL-TEP amplitude in both M1 and DLPFC, with steeper 1/f-like slopes associated with smaller EL-TEP amplitudes. Inconsistent relationships were found between alpha and beta power with EL-TEP amplitude across the two regions. Conclusions: These findings indicate that pre-stimulus aperiodic neural activity influences cortical excitability in both motor and prefrontal areas. Notably, the aperiodic exponent exhibited stronger associations with cortical excitability compared to periodic alpha or beta power. Brain-state-dependent protocols may benefit from real-time extraction of aperiodic exponent as a target feature to improve the precision and efficacy of TMS.

neuroscience↗

bioRxiv2026

MEG-informed navigated TMS for individualized speech cortical mapping

Speech cortical mapping by means of navigated repetitive transcranial magnetic stimulation (SCM nrTMS) provides neurosurgeons with noninvasive prior information about individuals cortical speech network. Individualized mapping is required, since the exact locations and activation patterns of speech production show high variability between individuals. We hypothesized that magnetoencephalography (MEG) data of an individuals speech production could guide the SCM TMS process temporally and spatially, leading to higher error rates at MEG-defined locations with TMS pulse timings coinciding with MEG activity. 13 healthy subjects participated in MEG and TMS measurements, where the timing of the TMS pulse (PTI; picture-to-TMS interval) was adjusted based on the individuals MEG activation in a picture naming task. At the group level, significant correlations were observed between the latency of the peak MEG activation and the PTI that produced the highest speech error rate. The MEG peak preceded the best PTI by 132 ms (R=0.713, p=0.006) across the entire stimulation area in the lateral left hemisphere, and by 103 ms (R=0.673, p=0.012) in the left frontal regions. We found 17 combinations of PTI and stimulation area in which the subjects speech error rate increased significantly compared to their average error rate. Our findings suggest that optimal PTIs are highly individual, and that individualizing the PTI according to MEG activation provides a straightforward method for accounting individual variability in speech function and may increase the sensitivity and utility of SCM TMS.

neuroscience↗

bioRxiv2026

Cognitive load modulates cortical excitability in the human prefrontal cortex

The prefrontal cortex dynamically adjusts its excitability to meet changing cognitive demands, yet our understanding of how these rapid state changes unfold in real time remains limited. Existing evidence relies predominantly on correlational neuroimaging and invasive electrophysiology in clinical populations, neither of which affords causal measurement in healthy humans. Here, using concurrent single-pulse TMS-EEG during a parametric cognitive multi-source interference task (MSIT) in 27 healthy participants, we causally probed left prefrontal excitability across conditions spanning a range of cognitive interference levels. Prefrontal excitability scaled systematically with cognitive load, peaking at intermediate incongruency levels where trial-type uncertainty was greatest, and differentiating high-from low-conflict trials at the single-subject level. Critically, prefrontal excitability and midfrontal theta power showed parallel state dependency patterns, linking causal perturbation of prefrontal circuit responsiveness to an established oscillatory marker of cognitive control. The observed excitability modulation was selective to the left prefrontal cortex: stimulation of right dlPFC, pre-SMA, and vertex in a separate control cohort (N=5) produced no load-dependent effects. These results position prefrontal excitability as a real-time, regionally selective physiological readout of how the human prefrontal cortex adapts to cognitive demand. HighlightsO_LIWe evaluated the links between cognitive interference, prefrontal excitability, and intrinsic theta activity during a multi-source interference task C_LIO_LICognitive load, estimated based on behavioral performance, was greatest at at intermediate interference levels (33% congruent), where trial-type uncertainty was maximal C_LIO_LIPrefrontal excitability, measured via single-pulse TMS-evoked potentials, scaled with cognitive load C_LIO_LIEffects were observed at the single subject level and were specific to prefrontal stimulation C_LIO_LIPrefrontal excitability changes and midfrontal theta power showed parallel scaling with cognitive load, linking causal probing to established oscillatory markers C_LIO_LIThis noninvasive technique provides causal measurement of prefrontal engagement during cognitive processing C_LIO_LIThe methodology demonstrates potential for tracking brain state dynamics in both healthy cognition and neuropsychiatric disorders C_LI

neuroscience↗

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

Noninvasive profiling of input-output excitability curves in human prefrontal cortex

Abstract.O_ST_ABSBackgroundC_ST_ABSThe prefrontal cortex plays a critical role in cognitive control and behavior, and its dysfunction has been linked to numerous psychiatric and neurological disorders. However, noninvasive measurement of prefrontal activity remains challenging, limiting our understanding of how to optimize prefrontal treatments. Input-output relationships reveal how neural circuits respond to different inputs and are essential for determining optimal treatment parameters and understanding individual variability in treatment response, yet systematic investigation of prefrontal input-output relationships has been lacking. ObjectiveTo characterize human prefrontal excitability with input-output (I/O) curves. MethodsWe employed transcranial magnetic stimulation (TMS) with electroencephalography in a randomized mixed-block design with 28 healthy participants receiving single-pulse TMS to left dorsolateral prefrontal cortex (dlPFC) across 12 stimulation intensities (60-140% of resting motor threshold). We quantified prefrontal excitability using early local TMS-evoked potentials (EL-TEPs), cortical responses measured locally 20-60 ms post-stimulus. ResultsWe observed a strong effect of TMS intensity on prefrontal EL-TEP amplitudes. Sigmoidal EL-TEP I/O curves were observed in 57% of participants, with the sigmoidality partially explained by EL-TEP signal quality. Correlations were observed between EL-TEP and motor-evoked potential curve parameters, but intensity parameterization approaches did not significantly differ in explaining inter-individual EL-TEP response variability. Reliable EL-TEPs could be obtained using fewer TMS pulses at high intensities, and test- retest assessments revealed robust I/O curve profiles. ConclusionsThese findings provide a systematic noninvasive characterization of prefrontal input-output physiology, establishing a framework for estimating prefrontal excitability. The comparison of various intensity parameterizations motivates the need for enhanced models and individualized measurement of stimulation responses. HighlightsO_LIWe present noninvasive input-output curves for prefrontal TMS. C_LIO_LIEL-TEPs exhibit robust dose-dependent responses to TMS intensity. C_LIO_LISigmoidal I/O curves observed in 57% of participants, with a strong dependence on signal quality. C_LIO_LICorrelations observed between MEP and prefrontal EL-TEP curve parameters. C_LIO_LIHigh test-retest reliability and rapid protocols at [≥]110% rMT C_LI

neuroscience↗

bioRxiv2025

Sensory Entrained TMS (seTMS) enhances motor cortex plasticity

Neural excitability fluctuates with sensory events, creating windows of opportunity to enhance brain stimulation. Repetitive transcranial magnetic stimulation (TMS), including intermittent theta burst stimulation (iTBS), is a promising treatment for neurological and psychiatric disorders, but does not account for fluctuations in neural excitability, likely contributing to variable outcomes. Sensory Entrained TMS (seTMS) leverages sensorimotor oscillations to enhance corticospinal responses, but the sustained effects as a repetitive protocol are unknown. We extended seTMS to iTBS measuring motor-evoked potentials (MEPs) as a physiological readout in a randomized crossover study comparing standard iTBS with sensory entrained iTBS (se-iTBS, n=20). se-iTBS more than doubled the MEP effect (55% vs. 26% MEP enhancement) and persisted for at least 30 minutes. Notably, more than 80% of participants showed larger responses with se-iTBS at all time points. se-iTBS may provide a robust and practical framework for optimizing TMS that bridges electrophysiological mechanisms and clinical applications.

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

Real-time optimization to enhance noninvasive cortical excitability assessment in the human dorsolateral prefrontal cortex

ObjectiveWe currently lack a robust noninvasive method to measure prefrontal excitability in humans. Concurrent TMS and EEG in the prefrontal cortex is usually confounded by artifacts. Here we asked if real-time optimization could reduce artifacts and enhance a TMS-EEG measure of left prefrontal excitability. MethodsThis closed-loop optimization procedure adjusts left dlPFC TMS coil location, angle, and intensity in real-time based on the EEG response to TMS. Our outcome measure was the left prefrontal early (20-60 ms) and local TMS-evoked potential (EL-TEP). ResultsIn 18 healthy participants, this optimization of coil angle and brain target significantly reduced artifacts by 63% and, when combined with an increase in intensity, increased EL-TEP magnitude by 75% compared to a non-optimized approach. ConclusionsReal-time optimization of TMS parameters during dlPFC stimulation can enhance the EL-TEP. SignificanceEnhancing our ability to measure prefrontal excitability is important for monitoring pathological states and treatment response. HighlightsO_LIWe developed a real-time closed-loop optimization procedure to obtain high amplitude early local TEPs (EL-TEPs) from dlPFC TMS. C_LIO_LISequential optimization of coil angle and brain target reduced artifacts by 63%. C_LIO_LISequential optimization of coil angle, brain target, and intensity increased EL-TEP amplitude by 75%. C_LI

neuroscience↗

bioRxiv2023

Mapping cortical excitability in the human dorsolateral prefrontal cortex

ObjectiveTo characterize early TEPs anatomically and temporally (20-50 ms) close to the TMS pulse (EL-TEPs), as well as associated muscle artifacts (<20 ms), across the dlPFC. We hypothesized that TMS location and angle influence EL-TEPs, and that EL-TEP amplitude is inversely related to muscle artifact. Additionally, we sought to determine an optimal group-level TMS target and angle, while investigating the potential benefits of a personalized approach. MethodsIn 16 healthy participants, we applied single-pulse TMS to six targets within the dlPFC at two coil angles and measured EEG responses. ResultsStimulation location significantly influenced EL-TEPs, with posterior and medial targets yielding larger EL-TEPs. Regions with high EL-TEP amplitude had less muscle artifact, and vice versa. The best group-level target yielded 102% larger EL-TEP responses compared to other dlPFC targets. Optimal dlPFC target differed across subjects, suggesting that a personalized targeting approach might boost the EL-TEP by an additional 36%. SignificanceEarly local TMS-evoked potentials (EL-TEPs) can be probed without significant muscle-related confounds in posterior-medial regions of the dlPFC. The identification of an optimal group-level target and the potential for further refinement through personalized targeting hold significant implications for optimizing depression treatment protocols. HighlightsO_LIEarly local TMS-evoked potentials (EL-TEPs) varied significantly across the dlPFC as a function of TMS target. C_LIO_LITMS targets with less muscle artifact had significantly larger EL-TEPs. C_LIO_LISelection of a postero-medial target increased EL-TEPs by 102% compared to anterior targets. C_LI

neuroscience↗