Principles of Neurocomputing for Science and Engineering
Principles of Neurocomputing for Science and Engineering
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
A quantitative comparison of functional MRI cluster analysis
Artificial Intelligence in Medicine
Node merging in Kohonen's self-organizing mapping of fMRI data
Artificial Intelligence in Medicine
A novel, direct spatio-temporal approach for analyzing fMRI experiments
Artificial Intelligence in Medicine
An evaluation of methods for detecting brain activations from functional neuroimages
Artificial Intelligence in Medicine
Fuzzy cluster analysis of high-field functional MRI data
Artificial Intelligence in Medicine
Fuzzy-based dialectical non-supervised image classification and clustering
International Journal of Hybrid Intelligent Systems
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One of the major challenges at the field of cognitive sciences is mapping the regions of the brain responsible for the motor and behavioural functions. The acquisition of functional magnetic resonance images is an important non-invasive technique to study the neural activity in the human brain. The dialectical conception of reality is a kind of philosophical investigative method for analysing processes present in nature and in human societies. The dialectical method is a tool for studying systems by considering the dynamics of their contradictions, as dynamic processes with intertwined phases of evolution and revolutionary crisis. It has inspired us to conceive a dialectical classifier able to solve classification problems. This work presents a new approach for the detection of activated brain regions: the composition and analysis of synthetic multi and monospectral images using statistical methods and proposing a non-parametrical method based on Kohonen self-organised networks and in objective dialectical classifiers.