Activelets: Wavelets for sparse representation of hemodynamic responses

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Background. Latencies of motor evoked potentials (MEPs) can provide insights into the motor neuronal pathways activated by transcranial magnetic stimulation. Notwithstanding its clinical relevance, accurate, unbiased methods to automatize latency detection ...

Purpose: Simultaneous scalp electroencephalography and functional magnetic resonance imaging (EEG-fMRI) enable noninvasive assessment of brain function with high spatial and temporal resolution. However, at ultra-high field, the data quality of both modali ...

Background: Functional connectivity quantifies the statistical dependencies between the activity of brain regions, measured using neuroimaging data such as functional magnetic resonance imaging (fMRI) blood-oxygenation-level dependent time series. The netw ...

Research on schizophrenia typically focuses on one paradigm for which clear-cut differences between patients and controls are established. Great efforts are made to understand the underlying genetical, neurophysiological, and cognitive mechanisms, which ev ...

In this thesis, timing is everything. In the first part, we mean this literally, as we tackle systems that encode information using timing alone. In the second part, we adopt the standard, metaphoric interpretation of this saying and show the importance of ...

Highly energy-efficient wireless sensor nodes are a prerequisite for a sustainable operation of the Internet of things. Therefore, classical approaches for system design based on digital signal processing are not a viable solution, but system design has to ...

Previous research has suggested that bodily signals from internal organs are associated with diverse cortical and subcortical processes involved in sensory-motor functions, beyond homeostatic reflexes. For instance, a recent study demonstrated that the pre ...

Understanding how neural circuits remodel and adapt to animal behavior is a central theme in the field of Neuroscience. One strategy to reach this goal is to repeatedly record the same animal's neural circuits and observe how they adapt when facing differe ...

Community structure in graph-modeled data appears in a range of disciplines that comprise network science. Its importance relies on the influence it bears on other properties of graphs such as resilience, or prediction of missing connections. Nevertheless, ...

Bottom-up models of functionally relevant patterns of neural activity provide an explicit link between neuronal dynamics and computation. A prime example of functional activity patterns are propagating bursts of place-cell activities called hippocampal rep ...

Activelets: Wavelets for sparse representation of hemodynamic responses

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An automatized method to determine latencies of motor-evoked potentials under physiological and pathophysiological conditions

Segmenting electroencephalography wires reduces radiofrequency shielding artifacts in simultaneous electroencephalography and functional magnetic resonance imaging at 7 T

Improving Functional Connectome Fingerprinting with Degree-Normalization

The EEG multiverse of schizophrenia

Timing is Everything

Spike-Based Sensing and Communication for Highly Energy-Efficient Sensor Edge Nodes

Breathing is coupled with voluntary initiation of mental imagery

Methods for acute and long-term imaging of the ventral nerve cord in behaving adult Drosophila

Graph signal processing tailored for subgraph focus and community structure

Mesoscopic description of hippocampal replay and metastability in spiking neural networks with short-term plasticity