The results show that the interpretability of extracellular signals depends critically on neuronal morphology and synchronization state, and provide a mechanistic framework for the use of STN LFPs as biomarkers in adaptive deep brain stimulation for Parkinson’s disease.
A major challenge in systems neuroscience is understanding how external perturbations interact with ongoing brain activity. Transcranial magnetic stimulation (TMS), increasingly used in both basic and clinical neuroscience and often combined with electroencephalography (EEG), provides a unique opportunity to probe this interaction. However, how intrinsic dynamics constrain the propagation of TMS-evoked activity remains poorly understood. In particular, effective connectivity (EC)—capturing directed, state-dependent interactions between brain regions—is thought to critically shape perturbational spread, yet remains difficult to estimate at the whole-brain EEG level. Here we introduce an analytically tractable, generative whole-brain model that links spontaneous EEG activity to cortical responses under perturbation. By deriving a closed-form expression for the model’s cross-spectral density, we directly fit empirical resting-state EEG spectra and infer biophysically interpretable local dynamical parameters without time-domain simulations. We then estimate stimulation-site-specific EC using only a small fraction of the TMS–EEG trials. The resulting model accurately predicts the spatiotemporal structure of TMS-evoked potentials (TEPs) in unseen trials. Moreover, even without subject-specific refitting, group-level EC templates capture canonical site-specific propagation motifs underlying single-subject early TMS responses. Together, our results establish an analytical framework for individualized whole-brain modeling of TMS-EEG with potential applicability to model-based neuromodulation.
Andrea Veronese, D. Momi, S. Sarasso et al.· bioRxiv· 0 citations
Beta oscillations (13–35 Hz) in the subthalamic nucleus (STN) are a hallmark of Parkinson’s disease (PD), yet little is known about their spatial dynamics. Since traveling waves (spatially propagating oscillations) have been observed in cortical and subcortical structures at different frequencies, we hypothesized that beta oscillations propagate as traveling waves in the STN, likely originating from the motor region of the nucleus. We leveraged multi-contact local field potential recordings from PD patients to estimate pairwise delays between contacts, and asked whether these delays could be accounted for by a simple spherical traveling wave model. Using statistical controls to safeguard against overfitting, we found evidence for spherical traveling beta waves in 11 out of 20 hemispheres, on average during 16% of the recording duration. We further demonstrated that sources are most likely located in the dorsal portion of the motor STN at the group level, and observed a positive correlation between propagation speed and residual motor impairment. Our results suggest that parkinsonian STN beta activity can organise into mesoscopic traveling waves, which has important implications for the pathophysiology of PD and the improvement of sensing-guided DBS.
Parsa Nilchian, A. Averna, H. Cagnan et al.· bioRxiv· 0 citations
A computational model was developed in which GPe neurons are represented as coupled phase oscillators influenced by experimentally derived phase-response curves and extrinsic inputs, showing that while the model captures general trends, discrepancies exist in peak amplitude and decay rates, suggesting that key biological details of the GPe are not represented in the model.
Functional-connectivity analyses often treat signals sampled from nearby cortical positions as interchangeable, despite anatomical and hemodynamic transitions at the gray-white boundary. We tested whether sampling position constitutes a state-sensitive dimension of macroscale functional organization. In 176 Human Connectome Project young adults with four 7 T resting-state and four movie-watching runs, BOLD time series were sampled from subject-specific midthickness and gray-white-boundary surfaces, summarized across 400 cortical parcels, and embedded in a common functional-gradient space. Movie viewing reduced principal-gradient separation between surfaces, but this effect was spatially heterogeneous: Visual, Limbic and Default networks converged, whereas Salience/ventral-attention cortex differentiated. Shapley decomposition and counterfactual analyses showed that the state change reflected coordinated reconfiguration of both surface representations rather than one surface approaching the other. Changes in the original connectivity profiles tracked gradient changes, indicating that the result was not solely introduced by embedding. Both surfaces also exhibited stimulus-locked intersubject functional connectivity during movies. However, stimulus-shared separation captured only part of movie-state organization and did not explain the movie-minus-rest change. Finally, in 172 matched participants, resting-state separation maps generalized from 7 T to 3 T, whereas absolute magnitude and cross-field individual ranking were less stable. These findings establish cortical sampling position as an interpretable measurement dimension of functional-connectivity geometry. Its spatial organization is reproducible across acquisitions, but its magnitude and state dependence vary, emphasizing that where BOLD signals are sampled relative to the cortical boundary can shape conclusions about macroscale brain organization.
Muwei Li, Z. Ding, John C. Gore· bioRxiv· 0 citations
Resting-state hemodynamic fluctuations take place over broad temporal scales and are reported to be closely linked to gamma-band neural activity, yet whether specific cell types drive these fluctuations remains unclear. Given the established contribution of parvalbumin (PV) neurons in generating gamma oscillations, they are prime candidates. Using chemogenetic tools in awake PV-Cre mice, we modulated PV interneuron activity and measured effects on neural network activity, EEG, and hemodynamics. Two-photon calcium imaging confirmed their modulation of excitatory neurons as well as local vascular changes. PV chemogenetic suppression reduced EEG gamma power, increased low-frequency EEG activity, and elevated basal CBF. Two-photon imaging under control conditions showed increased basal arterial diameter and significantly greater vascular fluctuation in deeper cortical layers enriched with PV cells, but not in superficial layers. Importantly, PV suppression significantly weakened the correlation between the EEG gamma power and CBF. These findings provide evidence that PV interneuron contribute to spontaneous neurovascular dynamics and to the link between gamma oscillations and resting-state hemodynamic signals, pointing to a significant role in neurovascular changes during non-task-engaged brain states.
Adiya Rakymzhan, Mitsuhiro Fukuda, Alberto L Vazquez· Journal of Cerebral Blood Fl...· 0 citations
Amyotrophic Lateral Sclerosis (ALS) is an incurable neurodegenerative disease characterized by the selective loss of spinal motor neurons (MN). Trans-spinal direct current stimulation (tsDCS) has emerged as a promising noninvasive neuromodulation technique that could provide neuroprotection and slow down disease progression. However, the mechanisms by which tsDCS affects individual MNs remain poorly understood. This study uses computational modeling to explore how low-intensity extracellular electric fields (EEFs), generated by tsDCS, influence the electrophysiological behavior of MNs. Morphologically realistic, multi-compartment models of neonate mouse alpha-MNs were developed in the NEURON simulation environment. Simulations were conducted under different EEF magnitudes, polarities and orientations. At the population level, consistent directional effects on excitability-related properties were limited and depended on stimulation condition. However, analyses of response magnitude showed that EEFs could modulate several properties, including resting membrane potential and rheobase, even when the direction of change varied across neurons. This heterogeneity was associated with neuronal morphology and its alignment with the applied field, with dendritic length and asymmetry affecting sensitivity. Overall, the results suggest that low-intensity EEFs produce modest, morphology-dependent modulation of MN electrophysiological properties, and that variability in neuronal structure and orientation may help explain discrepancies across previous experimental and modeling studies.
Marta Krumina, S. Fernandes, B. Vilne et al.· IEEE transactions on neural...· 0 citations
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