Neurology

Spiking Neural Network Modelling Approach Reveals How Mindfulness Training Rewires the Brain.

There has been substantial interest in Mindfulness Training (MT) to understand how it can benefit healthy individuals as well as people with a broad range of health conditions. Research has begun to delineate associated changes in brain function. However, whether measures of brain function can be used to identify individuals who are more likely to respond to MT remains unclear. The present study a...

Deep Residual Inception Encoder-Decoder Network for Medical Imaging Synthesis.

Image synthesis is a novel solution in precision medicine for scenarios where important medical imaging is not otherwise available. The convolutional neural network (CNN) is an ideal model for this task because of its powerful learning capabilities through the large number of layers and trainable parameters. In this research, we propose a new architecture of residual inception encoder-decoder neur...

EIQ: EEG based IQ test using wavelet packet transform and hierarchical extreme learning machine.

BACKGROUND: The use of electroencephalography has been perpetually incrementing and has numerous applications such as clinical and psychiatric studies...

SPINDLE: End-to-end learning from EEG/EMG to extrapolate animal sleep scoring across experimental settings, labs and species.

Understanding sleep and its perturbation by environment, mutation, or medication remains a central problem in biomedical research. Its examination in ...

Refining humane endpoints in mouse models of disease by systematic review and machine learning-based endpoint definition.

Ideally, humane endpoints allow for early termination of experiments by minimizing an animal's discomfort, distress and pain, while ensuring that scie...

Open-source pipeline for multi-class segmentation of the spinal cord with deep learning.

This paper presents an open-source pipeline to train neural networks to segment structures of interest from MRI data. The pipeline is tailored towards...

Systems Pharmacological Approach to Investigate the Mechanism of for Application to Alzheimer's Disease.

(OC)-a traditional Chinese medicine (TCM)-has been reported to have large numbers of flavonoids, alkaloids, and triterpenoids. The previous studies o...

Machine learning approaches to studying the role of cognitive reserve in conversion from mild cognitive impairment to dementia.

OBJECTIVES: The overall aim of the present study was to explore the role of cognitive reserve (CR) in the conversion from mild cognitive impairment (M...

Anticancer Drug Affects Metabolomic Profiles in Multicellular Spheroids: Studies Using Mass Spectrometry Imaging Combined with Machine Learning.

Multicellular spheroids (hereinafter referred to as spheroids) are 3D biological models. The metabolomic profiles inside spheroids provide crucial inf...

Machine Learning for Diagnosis of Hematologic Diseases in Magnetic Resonance Imaging of Lumbar Spines.

We aimed to assess feasibility of a support vector machine (SVM) texture classifier to discriminate pathologic infiltration patterns from the normal b...

Machine Learning Analysis of Matricellular Proteins and Clinical Variables for Early Prediction of Delayed Cerebral Ischemia After Aneurysmal Subarachnoid Hemorrhage.

Although delayed cerebral ischemia (DCI) is a well-known complication after subarachnoid hemorrhage (SAH), there are no reliable biomarkers to predict...

Hidden Bursting Firings and Bifurcation Mechanisms in Memristive Neuron Model With Threshold Electromagnetic Induction.

Memristors can be employed to mimic biological neural synapses or to describe electromagnetic induction effects. To exhibit the threshold effect of el...

Differential diagnosis of multiple system atrophy with predominant parkinsonism and Parkinson's disease using neural networks.

Differential diagnosis between Parkinson's disease (PD) and atypical parkinsonism, such as multiple system atrophy (MSA), can be difficult, especially...

Hand Extension Robot Orthosis (HERO) Glove: Development and Testing With Stroke Survivors With Severe Hand Impairment.

The hand extension robot orthosis (HERO) glove was iteratively designed with occupational therapists and stroke survivors to enable stroke survivors w...

Feasible Classified Models for Parkinson Disease from Tc-TRODAT-1 SPECT Imaging.

The neuroimaging techniques such as dopaminergic imaging using Single Photon Emission Computed Tomography (SPECT) with Tc-TRODAT-1 have been employed ...

Application of Artificial Neural Networks to Identify Alzheimer's Disease Using Cerebral Perfusion SPECT Data.

The aim of this study was to demonstrate the usefulness of artificial neural networks in Alzheimer disease diagnosis (AD) using data of brain single p...

Influence of New Technologies on Post-Stroke Rehabilitation: A Comparison of Armeo Spring to the Kinect System.

BACKGROUND: New technologies to improve post-stroke rehabilitation outcomes are of great interest and have a positive impact on functional, motor, and...

Deep-learning for seizure forecasting in canines with epilepsy.

OBJECTIVE: This paper introduces a fully automated, subject-specific deep-learning convolutional neural network (CNN) system for forecasting seizures ...

Upper limb robot-assisted rehabilitation versus physical therapy on subacute stroke patients: A follow-up study.

This study aims to analyse the long-term effects (6 months follow-up) of upper limb Robot-assisted Therapy (RT) compared to Traditional physical Thera...

A simulation-based approach to improve decoded neurofeedback performance.

The neural correlates of specific brain functions such as visual orientation tuning and individual finger movements can be revealed using multivoxel p...