Igor Aleksander

Vassilis Cutsuridis

Amir Hussain

Allan Kardec Barros

Leslie S. Smith

Ron Chrisley

Brain Inspired Cognitive Systems 2008 (June 24-27, 2008; São Luís, Brazil) brought together leading scientists and engineers who use analytic, syntactic and computational methods both to understand the prodigious processing properties of biological systems and, specifically, of the brain, and to exploit such knowledge to advance computational methods towards ever higher levels of cognitive competence. This book includes the papers presented at four major symposia: Part I - Cognitive Neuroscience Part II - Biologically Inspired Systems Part III - Neural Computation Part IV - Models of Consciousness.

Brain Inspired Cognitive Systems 2008

Stuart Cobb

Imre Vida

Bruce P. Graham

This is the 2nd edition of a very well received and popular book that reflects the current state-of-the-art of the ongoing research avenues concerning the hippocampus and processing units bridging the gap between single cell activity, network activity and global brain function. It aims to provide a methodology to anyone interested in developing microcircuit level models of the hippocampus. The book is divided into two thematic areas: (I) Experimental background and (II) Computational analysis. In part I, leading experimental neuroscientists discuss the morphological, physiological and molecular characteristics as well as the connectivity and synaptic properties of the various cell types found in the hippocampus. Behaviour-related ensemble activity patterns of morphologically identified neurons in anesthetized and freely moving animals provide insights on the function of the hippocampal areas. In part II, computational neuroscientists present models of the hippocampal microcircuits at various levels of detail (e.g. single cell level, network level, etc.). Synaptomics and connectomics models of hippocampal structures are initially discussed. Then, network models of memory, rhythm generation and spatial navigation are presented, followed by abstract and biophysical models of synaptic plasticity. Network models of hippocampal implicated disorders (epilepsy and schizophrenia) are then detailed and how their network topologies, connectivities and activities change in these diseases. Finally, two chapters are dedicated to describing simulator environments of single neurons and networks currently used by computational neuroscientists in developing their models and modelling tools to parametrically constrain them. This engaging volume is invaluable to experimental and computational neuroscientists, electrical engineers, physicists, mathematicians and others interested in developing microcircuit models of the hippocampus. Graduate level students and trainees in all of these fields can find this book a significant source of information.

A Computational Modeler's Resource Book

Hippocampal Microcircuits

Bruce Graham

Rich in detail, Hippocampal Microcircuits: A Computational Modeler’s Resource Book provides succinct and focused reviews of experimental results. It is an unparalleled resource of data and methodology that will be invaluable to anyone wishing to develop computational models of the microcircuits of the hippocampus. The editors have divided the material into two thematic areas. Covering the subject’s experimental background, leading neuroscientists discuss the morphological, physiological and molecular characteristics as well as the connectivity and synaptic properties of the various cell types found in the hippocampus. Here, ensemble activity, related to behavior, on the part of morphologically identified neurons in anesthetized and freely moving animals, lead to insights into the functions of hippocampal areas. In the second section, on computational analysis, computational neuroscientists present models of hippocampal microcircuits at various levels of detail, including single-cell and network levels. A full chapter is devoted to the single-neuron and network simulation environments currently used by computational neuroscientists in developing their models. In addition to the above, the chapters also identify outstanding questions and areas in need of further clarification that will guide future research by computational neuroscientists.

John G. Taylor

The perception-action cycle is the circular flow of information that takes place between the organism and its environment in the course of a sensory-guided sequence of behaviour towards a goal. Each action causes changes in the environment that are analyzed bottom-up through the perceptual hierarchy and lead to the processing of further action, top-down through the executive hierarchy, toward motor effectors. These actions cause new changes that are analyzed and lead to new action, and so the cycle continues. The Perception-action cycle: Models, architectures and hardware book provides focused and easily accessible reviews of various aspects of the perception-action cycle. It is an unparalleled resource of information that will be an invaluable companion to anyone in constructing and developing models, algorithms and hardware implementations of autonomous machines empowered with cognitive capabilities. The book is divided into three main parts. In the first part, leading computational neuroscientists present brain-inspired models of perception, attention, cognitive control, decision making, conflict resolution and monitoring, knowledge representation and reasoning, learning and memory, planning and action, and consciousness grounded on experimental data. In the second part, architectures, algorithms, and systems with cognitive capabilities and minimal guidance from the brain, are discussed. These architectures, algorithms, and systems are inspired from the areas of cognitive science, computer vision, robotics, information theory, machine learning, computer agents and artificial intelligence. In the third part, the analysis, design and implementation of hardware systems with robust cognitive abilities from the areas of mechatronics, sensing technology, sensor fusion, smart sensor networks, control rules, controllability, stability, model/knowledge representation, and reasoning are discussed.

Models, Architectures, and Hardware

Perception-Action Cycle

Vassilis Cutsuridis

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