AIMC Topic: Brain

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A loop-based neural architecture for structured behavior encoding and decoding.

Neural networks : the official journal of the International Neural Network Society
We present a new type of artificial neural network that generalizes on anatomical and dynamical aspects of the mammal brain. Its main novelty lies in its topological structure which is built as an array of interacting elementary motifs shaped like lo...

An Improved Pathological Brain Detection System Based on Two-Dimensional PCA and Evolutionary Extreme Learning Machine.

Journal of medical systems
Pathological brain detection has made notable stride in the past years, as a consequence many pathological brain detection systems (PBDSs) have been proposed. But, the accuracy of these systems still needs significant improvement in order to meet the...

Support vector machine-based classification of first episode drug-naïve schizophrenia patients and healthy controls using structural MRI.

Schizophrenia research
Although regional brain deficits have been demonstrated in schizophrenia patients by structural MRI studies, one important question that remains largely unanswered is whether the complex and subtle deficits revealed by MRI could be used as objective ...

Predict, then simplify.

NeuroImage
The desire to understand a given phenomenon is at the core of a scientist's mission. Yet what is meant by "understanding"? As soon as we try to operationalize this concept, I argue that understanding amounts to building models of a set of related emp...

A novel fuzzy rough selection of non-linearly extracted features for schizophrenia diagnosis using fMRI.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Schizophrenia is a severe brain disorder primarily diagnosed through externally observed behavioural symptoms due to the dearth of established clinical tests. Functional magnetic resonance imaging (fMRI) can capture the dis...

Exploring the Organization of Semantic Memory through Unsupervised Analysis of Event-related Potentials.

Journal of cognitive neuroscience
Modern multivariate methods have enabled the application of unsupervised techniques to analyze neurophysiological data without strict adherence to predefined experimental conditions. We demonstrate a multivariate method that leverages priming effects...

Branching into brains.

eLife
What can artificial intelligence learn from neuroscience, and vice versa?

Multi-class parkinsonian disorders classification with quantitative MR markers and graph-based features using support vector machines.

Parkinsonism & related disorders
BACKGROUND AND PURPOSE: In this study we attempt to automatically classify individual patients with different parkinsonian disorders, making use of pattern recognition techniques to distinguish among several forms of parkinsonisms (multi-class classi...

Early Diagnosis of Alzheimer's Disease Based on Resting-State Brain Networks and Deep Learning.

IEEE/ACM transactions on computational biology and bioinformatics
Computerized healthcare has undergone rapid development thanks to the advances in medical imaging and machine learning technologies. Especially, recent progress on deep learning opens a new era for multimedia based clinical decision support. In this ...