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In networked control systems, communication is a shared and therefore scarce resource. Event-triggered control (ETC) can achieve high performance control with a significantly reduced amount of samples compared to classical, periodic control…
Epilepsy is a disorder characterised by spontaneous, recurrent seizures. Both local and network abnormalities have been associated with epilepsy, and the exact processes generating seizures are thought to be heterogeneous and…
The computational underpinnings of positive psychotic symptoms have recently received significant attention. Candidate mechanisms include some combination of maladaptive priors and reduced updating of these priors during perception. A…
Emotion regulation plays a key role in human behavior and overall well-being. Neurofeedback is a non-invasive self-brain training technique used for emotion regulation to enhance brain function and treatment of mental disorders through…
Social isolation (SI) in older adults has emerged as a critical mental health concern, with established links to cognitive decline. While depression is hypothesized to mediate this relationship, the longitudinal mechanisms remain unclear.…
Emotion recognition has significant potential in healthcare and affect-sensitive systems such as brain-computer interfaces (BCIs). However, challenges such as the high cost of labeled data and variability in electroencephalogram (EEG)…
Event-triggered control (ETC) is claimed to provide enormous reductions in sampling frequency when compared to periodic sampling, but little is formally known about its generated traffic. This work shows that ETC can exhibit very complex,…
Understanding and predicting the emotional trajectory in multi-party multi-turn conversations is of great significance. Such information can be used, for example, to generate empathetic response in human-machine interaction or to inform…
Controllability scores provide principled information on where intervention should be applied in large-scale network systems when explicit control design is difficult. Two representative controllability scores are the volumetric…
Behavioral health interventions, such as trainings or incentives, are implemented in settings where individuals are interconnected, and the intervention assigned to some individuals may also affect others within their network. Evaluating…
Biophysical models of human brain represent the latter as a graph of inter-connected neural regions. Building from the model by Naskar et al. (Network Neuroscience 2021), our motivation was to understand how these brain regions can be…
Neuronal dynamics are fundamentally constrained by the underlying structural network architecture, yet much of the details of this synaptic connectivity are still unknown even in neuronal cultures in vitro. Here we extend a previous…
Coronary angiography remains the gold standard for diagnosing Acute Coronary Syndrome (ACS). However, its resource-intensive and invasive nature can expose patients to procedural risks and diagnostic delays, leading to postponed treatment…
Analyzing neural data such as Electroencephalography (EEG) data often involves dealing with high-dimensional datasets, where not all channels provide equally meaningful informa- tion. Selecting the most relevant channels is crucial for…
Diagnosis of major depressive disorder (MDD) primarily relies on the patient's self-reported symptoms and a clinical evaluation. Effective connectivity (EC) from resting-state functional magnetic resonance imaging (rs-fMRI) analysis can…
Objective. Personalized transcranial electrical stimulation (tES) has gained growing attention due to the substantial inter-individual variability in brain anatomy and physiology. While previous reviews have discussed the physiological…
Background. Clinical parameters measured from gated single-photon emission computed tomography myocardial perfusion imaging (SPECT MPI) have value in predicting cardiac resynchronization therapy (CRT) patient outcomes, but still show…
We introduce the target controllability score (TCS), a concept for evaluating node importance under actuator constraints and designated target objectives, formulated within a virtual system setting. The TCS consists of the target volumetric…
Hypergraphs provide an effective abstraction for modeling multi-way group interactions among nodes, where each hyperedge can connect any number of nodes. Different from most existing studies which leverage statistical dependencies, we study…
Stress has emerged as a critical global health issue, contributing to cardiovascular disorders, depression, and several other long-term illnesses. Consequently, accurate and reliable stress monitoring systems are of growing importance. In…