EEG signature of breaks in embodiment in VR

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The researchers used a machine-learning classification approach to better understand neurological features associated with periods of wayfinding uncertainty. The participants (n = 30) were asked to complete wayfinding tasks of varying difficulty in a virtu ...

This study presents a methodology developed for estimating effective connectivity in brain networks (BNs) using multichannel scalp EEG recordings. The methodology uses transfer entropy as an information transfer measure to detect pair-wise directed informa ...

This study presents a new methodology for obtaining functional brain networks (FBNs) using multichannel scalp EEG recordings. The developed methodology extracts pair-wise phase synchrony between EEG electrodes to obtain FBNs at delta, theta, and alpha-band ...

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 ...

Understanding memory requires an explanation for how information can be stored in the brain in a stable state. The change in the brain that accounts for a given memory is referred to as an engram. In recent years, the term engram has been operationalized a ...

Both electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) are non-invasive methods that show complementary aspects of human brain activity. Despite measuring different proxies of brain activity, both the measured blood-oxygenation ...

In visual backward masking (VBM), a target is followed by a mask that decreases target discriminability. Schizophrenia patients (SZ) show strong and reproducible masking impairments, which are associated with reduced EEG amplitudes. Patients with bipolar d ...

Brain lesions caused by cerebral ischemia lead to network disturbances in both hemispheres, causing a subsequent reorganization of functional connectivity both locally and remotely with respect to the injury. Quantitative electroencephalography (qEEG) meth ...

Recent advances in virtual reality and robotic technologies have allowed researchers to explore the mechanisms underlying bodily aspects of self-consciousness which are largely attributed to the multisensory and sensorimotor processing of bodily signals (b ...

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 ...

EEG signature of breaks in embodiment in VR

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Identifying uncertainty states during wayfinding in indoor environments: An EEG classification Study

Effective connectivity in brain networks estimated using EEG signals is altered in children with ADHD

An EEG-based methodology for the estimation of functional brain connectivity networks: Application to the analysis of newborn EEG seizure

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

Engram cell connectivity: an evolving substrate for information storage

The relationship between EEG and fMRI connectomes is reproducible across simultaneous EEG-fMRI studies from 1.5T to 7T

Electrophysiological correlates of visual backward masking in patients with bipolar disorder

Connectivity Measures Differentiate Cortical and Subcortical Sub-Acute Ischemic Stroke Patients

Cogno-Vest: A Torso-Worn, Force Display to Experimentally Induce Specific Hallucinations and Related Bodily Sensations

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