Authors: Buscema, Massimo; Grossi, Enzo; Snowdon, Dave; Antuono, Piero

Source: Current Alzheimer Research, Volume 5, Number 5, October 2008 , pp. 481-498(18)

Publisher: Bentham Science Publishers

Abstract:

This article presents a new paradigm of Artificial Neural Networks (ANNs): the Auto-Contractive Maps (Auto- CM). The Auto-CM differ from the traditional ANNs under many viewpoints: the Auto-CM start their learning task without a random initialization of their weights, they meet their convergence criterion when all their output nodes become null, their weights matrix develops a data driven warping of the original Euclidean space, they show suitable topological properties, etc. Further two new algorithms, theoretically linked to Auto-CM are presented: the first one is useful to evaluate the complexity and the topological information of any kind of connected graph: the H Function is the index to measure the global hubness of the graph generated by the Auto-CM weights matrix. The second one is named Maximally Regular Graph (MRG) and it is an development of the traditionally Minimum Spanning Tree (MST). Finally, Auto-CM and MRG, with the support of the H Function, are applied to a real complex dataset about Alzheimer disease: this data come from the very known Nuns Study, where variables measuring the abilities of normal and Alzheimer subject during their lifespan and variables measuring the number of the plaques and of the tangles in their brain after their death.

The example of the Alzheimer data base is extremely useful to figure out how this new approach can help to re design bottom-up the overall structure of factors related to a complex disease like this.

Keywords: Artificial neural networks; contractive maps; artificial adaptive systems; theory of graph; minimum spanning tree; Alzheimer disease; nun study

Document Type: Research article

DOI: http://dx.doi.org/10.2174/156720508785908928

Publication date: 2008-10-01

More about this publication?

• Current Alzheimer Research publishes peer-reviewed frontier review and research articles on all areas of Alzheimer's disease. This multidisciplinary journal will help in understanding the neurobiology, genetics, pathogenesis, and treatment strategies of Alzheimer's disease. The journal publishes objective reviews written by experts and leaders actively engaged in research using cellular, molecular, and animal models. The journal also covers original articles on recent research in fast emerging areas of molecular diagnostics, brain imaging, drug development and discovery, and clinical aspects of Alzheimer's disease. Manuscripts are encouraged that relate to the synergistic mechanism of Alzheimer's disease with other dementia and neurodegenerative disorders. Book reviews, meeting reports and letters-to-the-editor are also published. The journal is essential reading for researchers, educators and physicians with interest in age-related dementia and Alzheimer's disease. Current Alzheimer Research provides a comprehensive 'bird's-eye view' of the current state of Alzheimer's research for neuroscientists, clinicians, health science planners, granting, caregivers and families of this devastating disease.

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