Bøger i Springer Series in Cognitive and Neural Systems serien

Here is a unified view of how the time domain can be effectively employed in neural network models. Covers synchronization, phase-locking behavior, image processing, temporal pattern analysis, fMRI analyis, network topology and synchronizability and more.

The study of the brain and behavior is illuminated with the discovery of invariances. Experimental brain research uncovers constancies amidst variation, with respect to interventions and transformations prescribed by experimental paradigms. Place cells, mirror neurons, event related potentials and areas differentially active in fMRI, all illustrate the pervasive role of invariances in neural systems in relation to their function.

This book focuses on our current understanding of brain dynamics in various brain disorders (e.g. epilepsy, Alzheimer¿s and Parkinson¿s disease) and how the multi-scale, multi-level tools of computational neuroscience can enhance this understanding.In recent years, there have been significant advances in the study of the dynamics of the disordered brain at both the microscopic and the macroscopic levels. This understanding can be furthered by the application of multi-scale computational models as integrative principles that may link single neuron dynamics and the dynamics of local and distant brain regions observed using human EEG, ERPs, MEG, LFPs and fMRI.Focusing on the computational models that are used to study movement, memory and cognitive disorders as well as epilepsy and consciousness related diseases, the book brings together physiologists and anatomists investigating cortical circuits; cognitive neuroscientists studying brain dynamics and behaviorby means of EEG and functional magnetic resonance imaging (fMRI); and computational neuroscientists using neural modeling techniques to explore local and large-scale disordered brain dynamics.Covering topics that have a significant impact on the field of medicine, neuroscience and computer science, the book appeals to a diverse group of investigators.

This both accessible and exhaustive book will help to improve modeling of attention and to inspire innovations in industry. Those working in the field as engineers will benefit from this book's introduction to the psychological and biological approaches to attention, and neuroscientists can learn about engineering work on attention.

This book focuses on our current understanding of brain dynamics in various brain disorders (e.g. epilepsy, Alzheimer¿s and Parkinson¿s disease) and how the multi-scale, multi-level tools of computational neuroscience can enhance this understanding.In recent years, there have been significant advances in the study of the dynamics of the disordered brain at both the microscopic and the macroscopic levels. This understanding can be furthered by the application of multi-scale computational models as integrative principles that may link single neuron dynamics and the dynamics of local and distant brain regions observed using human EEG, ERPs, MEG, LFPs and fMRI.Focusing on the computational models that are used to study movement, memory and cognitive disorders as well as epilepsy and consciousness related diseases, the book brings together physiologists and anatomists investigating cortical circuits; cognitive neuroscientists studying brain dynamics and behavior by means of EEG and functional magnetic resonance imaging (fMRI); and computational neuroscientists using neural modeling techniques to explore local and large-scale disordered brain dynamics.Covering topics that have a significant impact on the field of medicine, neuroscience and computer science, the book appeals to a diverse group of investigators.

This book covers recent advances in the understanding of brain structure, function and disorders based on the fundamental principles of physics. It provides novel insights into the devastating brain disorders of the mind such as schizophrenia, dementia, autism, aging or addictions, as well as into the new devices for brain repair.

This edited volume is about how unprejudiced approaches to real human cognition can improve the design of AI. It covers many aspects of human cognition and across 12 chapters the reader can explore multiple approaches about the complexities of human cognitive skills and reasoning, always guided by experts from different but complimentary academic fields.A central concept is explained: blended cognition, the natural skill of human beings for combining constantly different heuristics during their several task-solving activities. Something that was sometimes observed like a problem as "bad reasoning", is now the central key for the understanding of the richness, adaptability and creativity of human cognition. The topic of this book connects in a significant way with the disciplines of psychology, neurology, anthropology, philosophy, logics, engineering, logics, and AI. In a nutshell: understanding better humans for designing better machines.Any person with interests on natural and artificial reasoning should read this book as a primary source of inspiration and a way to achieve a critical thinking on these topics.

The possibility of gathering prominent scientists in the heart of the Silicon Valley given by the 2011 International Joint Conference on Neural Networks held in San Jose, CA, has offered us the unique opportunity of organizing a series of special events on the present status and future perspectives in neuromorphic memristor science.

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.

This book covers recent advances in the understanding of brain structure, function and disorders based on the fundamental principles of physics. It provides novel insights into the devastating brain disorders of the mind such as schizophrenia, dementia, autism, aging or addictions, as well as into the new devices for brain repair.

This both accessible and exhaustive book will help to improve modeling of attention and to inspire innovations in industry. Those working in the field as engineers will benefit from this book's introduction to the psychological and biological approaches to attention, and neuroscientists can learn about engineering work on attention.

This book presents how the Corollary Discharge of Attention Movement (CODAM) neural network model allows for a scientific understanding of consciousness as well as provides a solution to the mind-body problem.

This book advances understanding of brain function by defining a framework for representation based on category theory. Brings mathematical formalism into the domain of neural representation of physical spaces, as a basis for a theory of mental representation.

This book examines proposals involving electron tunneling between synapses, and quantum computations within neurons. It features clear explanations of neural pulses with reference to physical circuitry.

Here is a unified view of how the time domain can be effectively employed in neural network models. Covers synchronization, phase-locking behavior, image processing, temporal pattern analysis, fMRI analyis, network topology and synchronizability and more.

The study of the brain and behavior is illuminated with the discovery of invariances. Experimental brain research uncovers constancies amidst variation, with respect to interventions and transformations prescribed by experimental paradigms.

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.

The possibility of gathering prominent scientists in the heart of the Silicon Valley given by the 2011 International Joint Conference on Neural Networks held in San Jose, CA, has offered us the unique opportunity of organizing a series of special events on the present status and future perspectives in neuromorphic memristor science.

These techniques create hierarchies of information process based descriptions on different levels of detail, where higher levels contain less information and can therefore describe complete cognitive phenomena, but are more approximate.