An Iterative Framework for EEG-based Image Search: Robust Retrieval with Weak Classifiers

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The brain mechanism of embodiment in a virtual body has grown a scientific interest recently, with a particular focus on providing optimal virtual reality (VR) experiences. Disruptions from an embodied state to a less- or non-embodied state, denominated Br ...

Recent years have seen considerable progress in understanding brain function, and in modulating it through real-time fMRI neurofeedback (NF). Inspired by these advances, paired with the unique possibility of inducing the clinically relevant Presence Halluc ...

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 ...

Implanted brain electrodes provide a unique way of electrically interfacing with individual neurons in vivo. However, chronic recording or stimulating capabilities of neural implants are often impaired by a strong immune response resulting in a fibrous sca ...

Exosuits typically provide limited mechanical support and rely on a user's residual functional ability. However, people with neurological impairments often suffer from both motor and sensory deficits that limit the assistance an exosuit can provide. To ove ...

Recent years have seen growing interest in leveraging deep learning models for monitoring epilepsy patients based on electroencephalographic (EEG) signals. However, these approaches often exhibit poor generalization when applied outside of the setting in w ...

The use of TMS-EEG coupling as a neuroimaging tool for the functional exploration of the human brain recently gained strong interest. If this tool directly inherits the fine temporal resolution from EEG, its spatial counterpart remains unknown. In this stu ...

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 ...

An automatic seizure detection method from high-resolution intracranial-EEG (iEEG) signals is presented to minimize the computational complexity and realize real-time accurate seizure detection for biomedical implants. Complex signal processing on a large ...

Objective Long-term automatic detection of focal seizures remains one of the major challenges in epilepsy due to the unacceptably high number of false alarms from state-of-the-art methods. Our aim was to investigate to what extent a new patient-specific ap ...

An Iterative Framework for EEG-based Image Search: Robust Retrieval with Weak Classifiers

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EEG signature of breaks in embodiment in VR

Neuroengineering of hallucinations through fMRI neurofeedback: Understanding and modulating neural dynamics for the control of hallucinations in health and disease

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Sensory-Motor Neurostimulation to Enhance Exosuit Performance

M2D2: Maximum-Mean-Discrepancy Decoder for Temporal Localization of Epileptic Brain Activities

Exploring the spatial resolution of TMS-EEG coupling on the sensorimotor region

Breathing is coupled with voluntary initiation of mental imagery

Computation Complexity Reduction Technique for Accurate Seizure Detection Implants

Personalized seizure signature: An interpretable approach to false alarm reduction for long‐term epileptic seizure detection