Neurology

An algorithmic information theory of consciousness.

Providing objective metrics of conscious state is of great interest across multiple research and clinical fields-from neurology to artificial intelligence. Here we approach this challenge by proposing plausible mechanisms for the phenomenon of structured experience. In earlier work, we argued that the experience we call reality is a mental construct derived from information compression. Here we sh...

Fuzzy neuronal model of motor control inspired by cerebellar pathways to online and gradually learn inverse biomechanical functions in the presence of delay.

Contrary to forward biomechanical functions, which are deterministic, inverse biomechanical functions are generally not. Calculating an inverse biomechanical function is an ill-posed problem, which has no unique solution for a manipulator with several degrees of freedom. Studies of the command and control of biological movements suggest that the cerebellum takes part in the computation of approxim...

A brain-computer interface based on functional transcranial doppler ultrasound using wavelet transform and support vector machines.

BACKGROUND: Functional transcranial Doppler (fTCD) is an ultrasound based neuroimaging technique used to assess neural activation that occurs during a...

Improving the Accuracy and Training Speed of Motor Imagery Brain-Computer Interfaces Using Wavelet-Based Combined Feature Vectors and Gaussian Mixture Model-Supervectors.

In this paper, we propose a set of wavelet-based combined feature vectors and a Gaussian mixture model (GMM)-supervector to enhance training speed and...

Nonlinearity-aware based dimensionality reduction and over-sampling for AD/MCI classification from MRI measures.

Alzheimer's disease (AD) has been not only a substantial financial burden to the health care system but also an emotional burden to patients and their...

Alzheimer's disease and driving: review of the literature and consensus guideline from Belgian dementia experts and the Belgian road safety institute endorsed by the Belgian Medical Association.

Alzheimer's disease (AD) is a highly prevalent condition and its prevalence is expected to further increase due to the aging of the general population...

Support vector machine-based classification of neuroimages in Alzheimer's disease: direct comparison of FDG-PET, rCBF-SPECT and MRI data acquired from the same individuals.

OBJECTIVE: To conduct the first support vector machine (SVM)-based study comparing the diagnostic accuracy of T1-weighted magnetic resonance imaging (...

Automated diagnosis of temporal lobe epilepsy in the absence of interictal spikes.

OBJECTIVE: To diagnose and lateralise temporal lobe epilepsy (TLE) by building a classification system that uses directed functional connectivity patt...

Deep convolutional neural network for the automated detection and diagnosis of seizure using EEG signals.

An encephalogram (EEG) is a commonly used ancillary test to aide in the diagnosis of epilepsy. The EEG signal contains information about the electrica...

Deep learning guided stroke management: a review of clinical applications.

Stroke is a leading cause of long-term disability, and outcome is directly related to timely intervention. Not all patients benefit from rapid interve...

Delineation of the ischemic stroke lesion based on watershed and relative fuzzy connectedness in brain MRI.

Precise segmentation of stroke lesions from brain magnetic resonance (MR) images poses a challenging task in automated diagnosis. In this paper, we pr...

Long-term stability of gentamicin sulfate-ethylenediaminetetraacetic acid disodium salt (EDTA-Na) solution for catheter locks.

A lock solution composed of gentamicin sulfate (5 mg/mL) and ethylenediaminetetraacetic acid disodium salt (EDTA-Na, 30 mg/mL) could fully eradicate i...

Ethical Design of Intelligent Assistive Technologies for Dementia: A Descriptive Review.

The use of Intelligent Assistive Technology (IAT) in dementia care opens the prospects of reducing the global burden of dementia and enabling novel op...

Stimulus-induced transitions between spike-wave discharges and spindles with the modulation of thalamic reticular nucleus.

It is believed that thalamic reticular nucleus (TRN) controls spindles and spike-wave discharges (SWD) in seizure or sleeping processes. The dynamical...

Detection of Interictal Discharges With Convolutional Neural Networks Using Discrete Ordered Multichannel Intracranial EEG.

Detection algorithms for electroencephalography (EEG) data, especially in the field of interictal epileptiform discharge (IED) detection, have traditi...

Type 2 Diabetes Mellitus Is Associated with Social Recognition Memory Deficit and Altered Dopaminergic Neurotransmission in the Amygdala.

OBJECTIVE: Diabetic neuropathy is a chronic and often disabling condition that affects a significant number of individuals with diabetes mellitus (DM)...

Using artificial neural networks to select the parameters for the prognostic of mild cognitive impairment and dementia in elderly individuals.

BACKGROUND AND OBJECTIVES: A huge number of solutions based on computational systems have been recently developed for the classification of cognitive ...

Fusion of Facial Expressions and EEG for Multimodal Emotion Recognition.

This paper proposes two multimodal fusion methods between brain and peripheral signals for emotion recognition. The input signals are electroencephalo...

Synchrony measure for a neuron driven by excitatory and inhibitory inputs and its adaptation to experimentally-recorded data.

The aim of the current work is twofold: firstly to adapt an existing method measuring the input synchrony of a neuron driven only by excitatory inputs...

The Combined Effects of Adaptive Control and Virtual Reality on Robot-Assisted Fine Hand Motion Rehabilitation in Chronic Stroke Patients: A Case Study.

Robot-assisted therapy is regarded as an effective and reliable method for the delivery of highly repetitive training that is needed to trigger neurop...