AIMC Topic: Brain

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Functional connectivity in multiple sclerosis after robotic rehabilitative treatment: A case report.

Medicine
RATIONALE: Multiple sclerosis (MS) is an inflammatory demyelinating disease of central nervous system and it is associated with an impaired motor function status. The efficacy of rehabilitation in promoting functional recovery and increasing quality ...

Neural network models and deep learning.

Current biology : CB
Originally inspired by neurobiology, deep neural network models have become a powerful tool of machine learning and artificial intelligence. They can approximate functions and dynamics by learning from examples. Here we give a brief introduction to n...

The Residual Center of Mass: An Image Descriptor for the Diagnosis of Alzheimer Disease.

Neuroinformatics
A crucial quest in neuroimaging is the discovery of image features (biomarkers) associated with neurodegenerative disorders. Recent works show that such biomarkers can be obtained by image analysis techniques. However, these techniques cannot be dire...

Intracerebral EEG Artifact Identification Using Convolutional Neural Networks.

Neuroinformatics
Manual and semi-automatic identification of artifacts and unwanted physiological signals in large intracerebral electroencephalographic (iEEG) recordings is time consuming and inaccurate. To date, unsupervised methods to accurately detect iEEG artifa...

ME-Class2 reveals context dependent regulatory roles for 5-hydroxymethylcytosine.

Nucleic acids research
Since the discovery of 5-hydroxymethylcytosine (5hmC) as a prominent DNA modification found in mammalian genomes, an emergent question has been what role this mark plays in gene regulation. 5hmC is hypothesized to function as an intermediate in the d...

Machine learning-based prediction of clinical pain using multimodal neuroimaging and autonomic metrics.

Pain
Although self-report pain ratings are the gold standard in clinical pain assessment, they are inherently subjective in nature and significantly influenced by multidimensional contextual variables. Although objective biomarkers for pain could substant...

Whole-brain structural magnetic resonance imaging-based classification of primary dysmenorrhea in pain-free phase: a machine learning study.

Pain
To develop a machine learning model to investigate the discriminative power of whole-brain gray-matter (GM) images derived from primary dysmenorrhea (PDM) women and healthy controls (HCs) during the pain-free phase and further evaluate the predictive...

Stability properties of neural networks with non-instantaneous impulses.

Mathematical biosciences and engineering : MBE
In this paper, we consider neural networks in the case when the neurons are subject to a certain impulsive state displacement at fixed moments and the duration of this displacement is not negligible small (these are known as non-instantaneous impulse...