AIMC Topic: Brain

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Directional Clustering Through Matrix Factorization.

IEEE transactions on neural networks and learning systems
This paper deals with a clustering problem where feature vectors are clustered depending on the angle between feature vectors, that is, feature vectors are grouped together if they point roughly in the same direction. This directional distance measur...

Relationship Induced Multi-Template Learning for Diagnosis of Alzheimer's Disease and Mild Cognitive Impairment.

IEEE transactions on medical imaging
As shown in the literature, methods based on multiple templates usually achieve better performance, compared with those using only a single template for processing medical images. However, most existing multi-template based methods simply average or ...

The Athlete's Brain: Cross-Sectional Evidence for Neural Efficiency during Cycling Exercise.

Neural plasticity
The "neural efficiency" hypothesis suggests that experts are characterized by a more efficient cortical function in cognitive tests. Although this hypothesis has been extended to a variety of movement-related tasks within the last years, it is unclea...

A Fuzzy Integral Ensemble Method in Visual P300 Brain-Computer Interface.

Computational intelligence and neuroscience
We evaluate the possibility of application of combination of classifiers using fuzzy measures and integrals to Brain-Computer Interface (BCI) based on electroencephalography. In particular, we present an ensemble method that can be applied to a varie...

Brain-inspired cheminformatics of drug-target brain interactome, synthesis, and assay of TVP1022 derivatives.

Neuropharmacology
The use of Cheminformatics tools is gaining importance in the field of translational research from Medicinal Chemistry to Neuropharmacology. In particular, we need it for the analysis of chemical information on large datasets of bioactive compounds. ...

Memory Stacking in Hierarchical Networks.

Neural computation
Robust representations of sounds with a complex spectrotemporal structure are thought to emerge in hierarchically organized auditory cortex, but the computational advantage of this hierarchy remains unknown. Here, we used computational models to stud...

Decoding intracranial EEG data with multiple kernel learning method.

Journal of neuroscience methods
BACKGROUND: Machine learning models have been successfully applied to neuroimaging data to make predictions about behavioral and cognitive states of interest. While these multivariate methods have greatly advanced the field of neuroimaging, their app...

Neuroplasticity in dynamic neural networks comprised of neurons attached to adaptive base plate.

Neural networks : the official journal of the International Neural Network Society
In this paper, a learning algorithm is developed for Dynamic Plastic Continuous Neural Networks (DPCNNs) to improve their learning of highly nonlinear time dependent problems. A DPCNN is comprised of a base medium, which is nonlinear and plastic, and...

Predicting healthy older adult's brain age based on structural connectivity networks using artificial neural networks.

Computer methods and programs in biomedicine
Brain ageing is followed by changes of the connectivity of white matter (WM) and changes of the grey matter (GM) concentration. Neurodegenerative disease is more vulnerable to an accelerated brain ageing, which is associated with prospective cognitiv...