Neural computation arises from the capacity of nervous tissue to process information and accumulate knowledge in an intelligent manner. Conventional computational machines have encountered enormous difficulties in duplicatingsuch functionalities. This has given rise to the development of Artificial Neural Networks where computation is distributed over a great number of local processing elements with a high degree of connectivityand in which external programming is replaced with supervised and unsupervised learning. The papers presented in this volume are carefully reviewed versions of the talks delivered at the International Workshop on Artificial Neural Networks (IWANN '93) organized by the Universities of Catalonia and the Spanish Open University at Madrid and held at Barcelona, Spain, in June 1993. The 111 papers are organized in seven sections: biological perspectives, mathematical models, learning, self-organizing networks, neural software, hardware implementation, and applications (in five subsections: signal processing and pattern recognition, communications, artificial vision, control and robotics, and other applications).
Computational Retinal Image Analysis: Tools, Applications and Perspectives gives an overview of contemporary retinal image analysis (RIA) in the context of healthcare informatics and artificial intelligence. Specifically, it provides a history of the field, the clinical motivation for RIA, technical foundations (image acquisition modalities, instruments), computational techniques for essential operations, lesion detection (e.g. optic disc in glaucoma, microaneurysms in diabetes) and validation, as well as insights into current investigations drawing from artificial intelligence and big data. This comprehensive reference is ideal for researchers and graduate students in retinal image analysis, computational ophthalmology, artificial intelligence, biomedical engineering, health informatics, and more. Provides a unique, well-structured and integrated overview of retinal image analysis Gives insights into future areas, such as large-scale screening programs, precision medicine, and computer-assisted eye care Includes plans and aspirations of companies and professional bodies
|Author||: José Manuel Ferrández Vicente,José Ramón Álvarez-Sánchez,Félix de la Paz López,Javier Toledo Moreo,Hojjat Adeli|
|Release Date||: 2017-06-10|
|ISBN 10||: 331959740X|
|Pages||: 476 pages|
The two volumes LNCS 10337 and 10338 constitute the proceedings of the International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2017, held in Corunna, Spain, in June 2017. The total of 102 full papers was carefully reviewed and selected from 194 submissions during two rounds of reviewing and improvement. The papers are organized in two volumes, one on natural and artificial computation for biomedicine and neuroscience, addressing topics such as theoretical neural computation; models; natural computing in bioinformatics; physiological computing in affective smart environments; emotions; as well as signal processing and machine learning applied to biomedical and neuroscience applications. The second volume deals with biomedical applications, based on natural and artificial computing and addresses topics such as biomedical applications; mobile brain computer interaction; human robot interaction; deep learning; machine learning applied to big data analysis; computational intelligence in data coding and transmission; and applications.
When one is immersed in the fascinating world of neuroscience findings, the brain might start to seem like a collection of "modules," each specializes in a specific mental feat. But just like in other domains of Nature, it is possible that much of the brain and mind's operation can be explained with a small set of universal principles. Given exciting recent developments in theory, empirical findings and computational studies, it seems that the generation of predictions might be one strong candidate for such a universal principle. This is the focus of Predictions in the brain. From the predictions required when a rat navigates a maze to food-caching in scrub-jays; from predictions essential in decision-making to social interactions; from predictions in the retina to the prefrontal cortex; and from predictions in early development to foresight in non-humans. The perspectives represented in this collection span a spectrum from the cellular underpinnings to the computational principles underlying future-related mental processes, and from systems neuroscience to cognition and emotion. In spite of this diversity, they share some core elements. Memory, for instance, is critical in any framework that explains predictions. In asking "what is next?" our brains have to refer to memory and experience on the way to simulating our mental future. But as much as this collection offers answers to important questions, it raises and emphasizes outstanding ones. How are experiences coded optimally to afford using them for predictions? How do we construct a new simulation from separate memories? How specific in detail are future-oriented thoughts, and when do they rely on imagery, concepts or language? Therefore, in addition to presenting the state-of-the-art of research and ideas about predictions as a universal principle in mind and brain, it is hoped that this collection will stimulate important new research into the foundations of our mental lives.
|Author||: Qiang Chen|
|Release Date||: 2018|
|ISBN 10||: 9780438756236|
|Pages||: 153 pages|
We rely on visual information to navigate through the natural environment. The extraction of visual features by the nervous system first arises in the retina. The retina sends processed visual information to cortical and sub-cortical brain regions through 20-40 types of retinal ganglion cells (RGCs), each encodes specific aspect of the visual scene. One of the most prominent visual processing in the retina is the computation of motion direction, implemented by retinal direction selective circuit. While our notions about retinal direction circuit have come from the usage of simple parametric stimuli, natural scenes are rarely homogeneous but full of competing signals. This thesis focuses on understanding the underlying mechanisms of noise resilience of retinal direction computation. In chapter 1, we review the recent understanding of the dynamic engagement of circuitry and synaptic mechanisms for robust retinal directional selectivity under various visual conditions. Chapter 2 described the protocol we developed for recording and functional imaging of retinal neurons under two-photon microscopy in the laboratory. In chapter 3, we used synapse-specific genetic manipulation to dissect the role of distinct sets of inhibitory motifs for motion processing. We found that the functional circuitries that process bright versus dark moving objects are not mirrored symmetric. Furthermore, Lateral inhibitory motifs in retinal direction selective circuit are only recruited in the noisy visual condition in On pathway. Based upon findings in chapter 3, chapter 4 further investigated the mechanistic implementation of noise resilience by lateral inhibition motif. We found that one particular form of lateral inhibition, the mutual inhibition of lateral inhibition, prevents use-dependent synaptic suppression triggered by competing signals, thus maintains the strength and fidelity of synaptic transmission in the circuitry. Since feature selectivity, including direction selectivity, relies on the veto of spiking activities to "null" stimuli. This silencing of neuronal spiking requires timely cancellation of excitation by inhibition. In chapter 5, we investigated how retinal direction selective circuit maintains the ms time-scale covariation of inhibition and excitation for robust direction selectivity.
|Author||: John A: Bullinaria,David W. Glasspool|
|Release Date||: 1998|
|Pages||: 342 pages|
This volume contains a collection of papers presented at the 4th Neural Computation and Psychology Workshop, held in London from 7-11 April 1997. The theme of the workshop was: Connectionist Representations: Theory and Practice which covers many importan t issues ranging from the philosophical (such as the grounding problem), and the physiological (what can connectionist representations tell us about the real neural system?), to the technical (what is needed in order to get specific models to work?). The topic is one of increasing importance within Neural Computing and covers issues of interest to researchers from a wide range of backgrounds including: artificial intelligence, applied mathematics, cognitive science, computer science, neurobiology, phi losophy and psychology. In providing a comprehensive overview of this topic it provides an invaluable contribution to the Perspectives in Neural Computing series.
|Author||: Mihail C. Roco,Carlo D. Montemagno|
|Release Date||: 2004|
|Pages||: 259 pages|
The convergence of nanoscience, biotechnology, information technology, and cognitive science (NBIC) offers immense opportunities for the improvement of human abilities, social outcomes, the nation's productivity, and its quality of life; it also represents a major new frontier in research and development. This conclusion was reached at a December 2001 workshop held by the National Science Foundation and the Department of Commerce in which leading experts from government, the academic research community and the private sector explored the nature and size of the potential opportunities in NBIC convergence. The report that resulted from this workshop, asserting that NBIC convergence is a broad, cross-cutting, emerging and timely opportunity of interest to individuals, society and humanity in the long term, recommended that an R&D initiative focusing on enhancing human performance (while governed by respect for human welfare and dignity) should become a national priority. The NBIC Convergence 2003 conference was organized as a first step in realizing the vision of this report. In this volume, a panel of nationally recognized experts analyzes the opportunities NBIC convergence prese
|Release Date||: 2000|
|Pages||: 329 pages|