Spatio-temporal filtering for EEG error related potentials

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Objective. A key challenge of virtual reality (VR) applications is to maintain a reliable human-avatar mapping. Users may lose the sense of controlling (sense of agency), owning (sense of body ownership), or being located (sense of self-location) inside th ...

Traditionally, studies in schizophrenia research employ a single experimental paradigm. The results typically demonstrate a significant difference between patients and controls. Subsequent studies aim to describe the underlying abnormal mechanism at the ge ...

Reinforcement learning (RL) is crucial for learning to adapt to new environments. In RL, the prediction error is an important component that compares the expected and actual rewards. Dopamine plays a critical role in encoding these prediction errors. In my ...

The analysis of motor evoked potentials (MEPs) generated by transcranial magnetic stimulation (TMS) is crucial in research and clinical medical practice. MEPs are characterized by their latency and the treatment of a single patient may require the characte ...

During reaching actions, the human central nerve system (CNS) generates the trajectories that optimize effort and time. When there is an obstacle in the path, we make sure that our arm passes the obstacle with a sufficient margin. This comfort margin varie ...

Electroencephalography (EEG) data entail a complex spatiotemporal structure that reflects ongoing organi-zation of brain activity. Characterization of the spatial patterns is an indispensable step in numerous EEG processing pipelines. We present a novel me ...

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 ...

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: Mirror therapy is thought to drive interhemispheric communication, resulting in a balanced activation. We hypothesized that embodied virtual mirror visual feedback (VR-MVF) presented on a computer screen may produce a similar activation. In thi ...

While Deep Learning (DL) is often considered the state-of-the art for Artificial Intelligence-based medical decision support, it remains sparsely implemented in clinical practice and poorly trusted by clinicians due to insufficient interpretability of neur ...

Objective: Markup of generalized interictal epileptiform discharges (IEDs) on EEG is an important step in the diagnosis and characterization of epilepsy. However, manual EEG markup is a time-consuming, subjective, and the specialized task where the human r ...

Visual backward masking (VBM) deficits are candidate endophenotypes of schizophrenia indexing genetic liability of the disorder. In VBM, a target is followed by a mask that deteriorates target perception. Schizophrenia patients and, to a lesser extent, the ...

Objective. Event Related Potentials (ERPs) reflecting cognitive response to external stimuli, are widely used in brain computer interfaces. ERP waveforms are characterized by a series of components of particular latency and amplitude. The classical ERP dec ...

Voluntary action is a fundamental element of self-consciousness. The readiness potential (RP), a slow drift of neural activity preceding self-initiated movement, has been suggested to reflect neural processes underlying the preparation of voluntary action; ...

Objective: We employed dual-site TMS to test whether ipsilateral functional premotor-motor connectivity is altered in relapsing-remitting Multiple Sclerosis (RR-MS) and is related to central fatigue. ...

Decoding visual cognition from non-invasive measurements of brain activity has shown valuable applications. Vision-based Brain-Computer Interfaces (BCI) systems extend from spellers to database search and spatial navigation. Despite the high performance of ...

Epileptic networks, defined as brain regions involved in epileptic brain activity, have been mapped by functional connectivity in simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI) recordings. This technique allows to ...

In this thesis, I focus on monitoring of patients suffering from cardiovascular and neurological diseases through the use of wearable devices. The main diseases considered in this thesis are atrial fibrillation (AF), myocardial infarction (MI), and epileps ...

Altered states of embodiment are fundamental to the scientific understanding of bodily self consciousness. The feeling of disembodiment during everyday activities is common to clinical conditions; however, the direct study of disembodiment in experimental ...

Decoding the subjective perception of task difficulty may help improve operator performance, i.e., automatically optimize the task difficulty level. Here, we aim to decode a compound of cognitive states that covaries with the task difficulty level. We desi ...

Spatio-temporal filtering for EEG error related potentials

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Customizing the human-avatar mapping based on EEG error related potentials during avatar-based interaction

Variability is the rule: Neurophysiology and contextual visual processing in schizophrenia

Unveiling the complexity of learning and decision-making

DELMEP: a deep learning algorithm for automated annotation of motor evoked potential latencies

Inferring individual evaluation criteria for reaching trajectories with obstacle avoidance from EEG signals

Spectral representation of EEG data using learned graphs with application to motor imagery decoding

Breathing is coupled with voluntary initiation of mental imagery

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

Movement-Related Cortical Potentials in Embodied Virtual Mirror Visual Feedback

Interpreting deep learning models for epileptic seizure detection on EEG signals

Automatic detection of generalized paroxysmal fast activity in interictal EEG using time-frequency analysis

Neural Compensation Mechanisms of Siblings of Schizophrenia Patients as Revealed by High-Density EEG

Spatial covariance improves BCI performance for late ERPs components with high temporal variability

Breathing is coupled with voluntary action and the cortical readiness potential

Probing Context-Dependent Modulations of Ipsilateral Premotor-Motor Connectivity in Relapsing-Remitting Multiple Sclerosis

Towards everyday brain-computer interfacing through decoding visual cognition

Modulation of epileptic networks by transient interictal epileptic activity: A dynamic approach to simultaneous EEG-fMRI

Monitoring of Cardiovascular and Neurological Diseases Using Wearable Devices

Psychometrics of Disembodiment and Its Differential Modulation by Visuomotor and Visuotactile Mismatches

EEG Correlates of Difficulty Levels in Dynamical Transitions of Simulated Flying and Mapping Tasks