Tena Dubcek

Last Name

Dubcek

First Name

Tena

ORCID

0000-0003-3636-3201

Organisational unit

03963 - Wenderoth, Nicole / Wenderoth, Nicole

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Publications 1 - 10 of 10

Functional network dynamics in photosensitive epilepsy depend on stimulation frequency and photoparoxysmal electroencephalographic response
Timar, Lili; Deplazes, Sina; Bothmann, Julia; et al. (2025)
Epilepsia
ObjectivePhotosensitive epilepsy (PSE) is a reflex epilepsy, where abnormal electroencephalographic (EEG) responses are induced by photic stimulation. Photosensitivity is classified into four types based on the propagation of the brain's response to visual stimuli. Here, we aimed to describe the underlying dynamical mechanisms of PSE and different photosensitivity types.MethodsThis retrospective study included healthy controls (HC), PSE patients, and non-PSE patients with epilepsy (PWE). All participants were stimulated with flickering white light (1-60 Hz) under 10-20 EEG monitoring.ResultsWe observed significantly higher occipital photoparoxysmal response (PPR) power in PSE patients compared to HC for stimulation frequencies between 10 and 20 Hz. However, the excitability of the visual cortex, investigated by the occipital transient (P100) and steady-state visual evoked potentials (ssVEP), remained unchanged in most PSE types compared to HC and to PWE. The ssVEP power only increased significantly in PSE type 4 compared to HC. Instead, PSE patients exhibited notable differences in functional connectivity for stimulation frequencies of 10-20 Hz in the PPR band (3-4 Hz) relative to HC, characterized by centroparietal and centrofrontopolar hypoconnectivity. Additionally, for the same stimulation frequencies, PSE patients with PPR propagation showed occipitofrontocentral hyperconnectivity compared to both HC and PWE.SignificanceOur results provide novel evidence that altered network dynamics in PSE patients are likely a prerequisite for the propagation of the PPR and type-specific responses. PSE is a network effect modulated by anterior and anteroposterior hyperconnectivity, supported by a hyperexcitable visual cortex.
Functional network dynamics between the anterior thalamus and the cortex in deep brain stimulation for epilepsy
Aiello, Giovanna; Ledergerber, Debora; Dubcek, Tena; et al. (2023)
Brain: A Journal of Neurology
Owing to its unique connectivity profile with cortical brain regions, and its suggested role in the subcortical propagation of seizures, the anterior nucleus of the thalamus (ANT) has been proposed as a key deep brain stimulation (DBS) target in drug-resistant epilepsy. However, the spatio-temporal interaction dynamics of this brain structure, and the functional mechanisms underlying ANT DBS in epilepsy remain unknown. Here, we study how the ANT interacts with the neocortex in vivo in humans and provide a detailed neurofunctional characterization of mechanisms underlying the effectiveness of ANT DBS, aiming at defining intraoperative neural biomarkers of responsiveness to therapy, assessed at 6 months post-implantation as the reduction in seizure frequency. A cohort of 15 patients with drug-resistant epilepsy (n = 6 males, age = 41.6 ± 13.79 years) underwent bilateral ANT DBS implantation. Using intraoperative cortical and ANT simultaneous electrophysiological recordings, we found that the ANT is characterized by high amplitude θ (4–8 Hz) oscillations, mostly in its superior part. The strongest functional connectivity between the ANT and the scalp EEG was also found in the θ band in ipsilateral centro-frontal regions. Upon intraoperative stimulation in the ANT, we found a decrease in higher EEG frequencies (20–70 Hz) and a generalized increase in scalp-to-scalp connectivity. Crucially, we observed that responders to ANT DBS treatment were characterized by higher EEG θ oscillations, higher θ power in the ANT, and stronger ANT-to-scalp θ connectivity, highlighting the crucial role of θ oscillations in the dynamical network characterization of these structures. Our study provides a comprehensive characterization of the interaction dynamic between the ANT and the cortex, delivering crucial information to optimize and predict clinical DBS response in patients with drug-resistant epilepsy.
Binary classification of spoken words with passive elastic metastructures
Dubcek, Tena; Moreno-Garcia, Daniel; Haag, Thomas; et al. (2021)
arXiv
Many electronic devices spend most of their time waiting for a wake-up event: pacemakers waiting for an anomalous heartbeat, security systems on alert to detect an intruder, smartphones listening for the user to say a wake-up phrase. These devices continuously convert physical signals into electrical currents that are then analyzed on a digital computer -- leading to power consumption even when no event is taking place. Solving this problem requires the ability to passively distinguish relevant from irrelevant events (e.g. tell a wake-up phrase from a regular conversation). Here, we experimentally demonstrate an elastic metastructure, consisting of a network of coupled silicon resonators, that passively discriminates between pairs of spoken words -- solving the wake-up problem for scenarios where only two classes of events are possible. This passive speech recognition is demonstrated on a dataset from speakers with significant gender and accent diversity. The geometry of the metastructure is determined during the design process, in which the network of resonators ('mechanical neurones') learns to selectively respond to spoken words. Training is facilitated by a machine learning model that reduces the number of computationally expensive three-dimensional elastic wave simulations. By embedding event detection in the structural dynamics, mechanical neural networks thus enable novel classes of always-on smart devices with no standby power consumption.
Elastic structures you can talk to: Speech classification with mechanical neural networks
Dubcek, Tena; Moreno-Garcia, Daniel; Villanueva, Luis Guillermo; et al. (2022)
META Proceedings ~ META 2022 Torremolinos - Spain
Electroencephalography-driven brain-network models for personalized interpretation and prediction of neural oscillations
Dubcek, Tena; Ledergerber, Debora; Thomann, Jana; et al. (2025)
Clinical Neurophysiology
Objective: Develop an encephalography (EEG)-driven method that integrates interpretability, predictiveness, and personalization to assess the dynamics of the brain network, with a focus on pathological conditions such as pharmacoresistant epilepsy. Methods: We propose a method to identify dominant coherent oscillations from EEG recordings. It relies on the Koopman operator theory to achieve individualized EEG prediction and electrophysiological interpretability. We extend it with concepts from adiabatic theory to address the nonstationary and noisy EEG signals. Results: By simultaneously capturing the local spectral and connectivity aspects of patient-specific oscillatory dynamics, we are able to clarify the underlying dynamical mechanism. We use it to construct the corresponding generative models of the brain network. We demonstrate the proposed approach on recordings of patients in status epilepticus. Conclusions: The proposed EEG-driven method opens new perspectives on integrating interpretability, predictiveness, and personalization within a unified framework. It provides a quantitative approach for assessing EEG recordings, crucial for understanding and modulating pathological brain activity. Significance: This work bridges theoretical neuroscience and clinical practice, offering a novel framework for understanding and predicting brain network dynamics. The resulting approach paves the way for data-driven insights into brain network mechanisms and the design of personalized neuromodulation therapies.
Exact solutions of a model for synthetic anyons in a noninteracting system
Lunic, Frane; Todoric, Marija; Klajn, Bruno; et al. (2020)
Physical Review B
Phases, instabilities and excitations in a two-component lattice model with photon-mediated interactions
Carl, Leon; Rosa-Medina Pimentel, Rodrigo Felipe; Huber, Sebastian; et al. (2023)
Physical Review Research
Engineering long-range interacting spin systems with ultracold atoms offers the possibility to explore exotic magnetically ordered phases in strongly-correlated scenarios. Quantum gases in optical cavities provide a versatile experimental platform to further engineer photon-mediated interactions and access the underlying microscopic processes by probing the cavity field. Here, we study a two-component spin Bose-Hubbard system with cavity-mediated interactions. We provide a comprehensive overview of its phase diagram and transitions in experimentally relevant regimes. The interplay of different energy scales yields a rich phase diagram with superfluid and insulating phases exhibiting density modulation or spin ordering. In particular, the combined effect of contact and global-range interactions gives rise to an antiferromagnetically ordered phase for arbitrarily small spin-dependent light-matter coupling, while global-range and inter-spin contact interactions introduce regions of instability and phase separation in the phase diagram. We further study the low energy excitations above the antiferromagnetic phase. Besides particle-hole branches, it hosts spin-exchange excitations with a tunable energy gap. The studied lattice model can be readily realized in cold-atom experiments with optical cavities.
Discovery of topological metamaterials by symmetry relaxation and smooth topological indicators
Bösch, Cyrill; Dubcek, Tena; Schindler, Frank; et al. (2020)
Physical Review B
Physical properties of a topological origin are known to be robust against small perturbations. This robustness is both a source of theoretical interest and a driver for technological applications, but presents a challenge when looking for new topological systems: Small perturbations cannot be used to identify the global direction of change in the topological indices. Here, we overcome this limitation by breaking the symmetries protecting the topology. The introduction of symmetry-breaking terms causes the topological indices to become smooth, nonquantized functions of the system parameters, which are amenable to efficient design algorithms based on gradient methods. We demonstrate this capability by designing discrete and continuous phononic systems realizing conventional and higher-order topological insulators. © 2020 American Physical Society.
In‐Sensor Passive Speech Classification with Phononic Metamaterials
Dubcek, Tena; Moreno-Garcia, Daniel; Haag, Thomas; et al. (2024)
Advanced Functional Materials
Mitigating the energy requirements of artificial intelligence requires novel physical substrates for computation. Phononic metamaterials have vanishingly low power dissipation and hence are a prime candidate for green, always-on computers. However, their use in machine learning applications has not been explored due to the complexity of their design process. Current phononic metamaterials are restricted to simple geometries (e.g., periodic and tapered) and hence do not possess sufficient expressivity to encode machine learning tasks. A non-periodic phononic metamaterial, directly from data samples, that can distinguish between pairs of spoken words in the presence of a simple readout nonlinearity is designed and fabricated, hence demonstrating that phononic metamaterials are a viable avenue towards zero-power smart devices.
Weyl orbits without an external magnetic field
Peri, Valerio; Dubcek, Tena; Valenti, Agnes; et al. (2020)
Physical Review B
Weyl semimetals in a magnetic field give rise to interesting nonlocal electronic orbits: the ballistic transport through the bulk enabled by the chiral Landau levels is combined with a momentum-space sliding along the surface Fermi-arc driven by the Lorentz force. Bulk chiral Landau levels can also be induced by axial fields whose sign depends on the chirality of the Weyl point. However, the microscopic perturbations that give rise to them can be described in terms of gauge fields only in the low-energy sectors around the Weyl points. In addition, since pseudofields are intrinsic, there is no apparent reason for a Lorentz force that causes sliding along the Fermi arcs. Therefore, the existence of nonlocal orbits driven exclusively by pseudofields is not obvious. Here we show that for systems with at least four Weyl points in the bulk spectrum, nonlocal orbits can be induced by axial fields alone. We discuss the underlying mechanisms by a combination of analytical semiclassical theory, the microscopic numerical study of wave-packet dynamics, and a surface Green's function analysis.

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Tena Dubcek

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