Cognitive Phase Transitions In The Cerebral Cortex Enhancing The Neuron Doctrine By Modeling Neural Fields
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Cognitive Phase Transitions in the Cerebral Cortex - Enhancing the Neuron Doctrine by Modeling Neural Fields
This intriguing book was born out of the many discussions the authors had in the past 10 years about the role of scale-free structure and dynamics in producing intelligent behavior in brains. The microscopic dynamics of neural networks is well described by the prevailing paradigm based in a narrow interpretation of the neuron doctrine. This book broadens the doctrine by incorporating the dynamics of neural fields, as first revealed by modeling with differential equations (K-sets). The book broadens that approach by application of random graph theory (neuropercolation). The book concludes with diverse commentaries that exemplify the wide range of mathematical/conceptual approaches to neural fields. This book is intended for researchers, postdocs, and graduate students, who see the limitations of network theory and seek a beachhead from which to embark on mesoscopic and macroscopic neurodynamics.
Artificial Intelligence in the Age of Neural Networks and Brain Computing
Artificial Intelligence in the Age of Neural Networks and Brain Computing, Second Edition demonstrates that present disruptive implications and applications of AI is a development of the unique attributes of neural networks, mainly machine learning, distributed architectures, massive parallel processing, black-box inference, intrinsic nonlinearity, and smart autonomous search engines. The book covers the major basic ideas of "brain-like computing" behind AI, provides a framework to deep learning, and launches novel and intriguing paradigms as possible future alternatives. The present success of AI-based commercial products proposed by top industry leaders, such as Google, IBM, Microsoft, Intel, and Amazon, can be interpreted using the perspective presented in this book by viewing the co-existence of a successful synergism among what is referred to as computational intelligence, natural intelligence, brain computing, and neural engineering. The new edition has been updated to include major new advances in the field, including many new chapters. - Developed from the 30th anniversary of the International Neural Network Society (INNS) and the 2017 International Joint Conference on Neural Networks (IJCNN - Authored by top experts, global field pioneers, and researchers working on cutting-edge applications in signal processing, speech recognition, games, adaptive control and decision-making - Edited by high-level academics and researchers in intelligent systems and neural networks - Includes all new chapters, including topics such as Frontiers in Recurrent Neural Network Research; Big Science, Team Science, Open Science for Neuroscience; A Model-Based Approach for Bridging Scales of Cortical Activity; A Cognitive Architecture for Object Recognition in Video; How Brain Architecture Leads to Abstract Thought; Deep Learning-Based Speech Separation and Advances in AI, Neural Networks
Temporal Sampling and Representation Updating
Temporal Sampling and Representation Updating, Volume 236, addresses the gap between laboratory studies using static or predictable stimuli and the more complex change that is a characteristic of the real world. Topics in this new volume include a section on Unfolding the time course of emotion perception, Temporal sampling and representation updating for action in interception and grasping tasks, The influence of Cognitive Control and Attention on Temporal Sampling: Lessons from the Attentional Blink, Synchronizing tracking eye movements with the motion of a visual target, and Sampling feature distributions with visual search in heterogeneous displays. - Contains contributions from experts in diverse fields relating to temporal sampling and representation updating - Addresses the way in which we update our representations of the world when it is more unpredictable - Bridges the gap between laboratory studies using static or predictable stimuli and the more complex change that is a characteristic of the real world as it unfolds over time