Within our knowledge, the series of the International Conference on Cognitive Neurodynamics (ICCN) is the only conference series dedicating to cognitive neurodynamis. This volume is the proceedings of the 3rd International Conference on Cognitive Neurodynamics held in 2011, which reviews the progress in this field since the 1st ICCN - 2007. The topics include: Neural coding and realistic neural network dynamics, Neural population dynamics, Firing Oscillations and Patterns in Neuronal Networks, Brain imaging, EEG, MEG, Sensory and Motor Dynamics, Global cognitive function, Multi-scalar Neurodynamics - from Physiology to Systems Theory, Neural computing, Emerging Technologies for Brain Computer Interfaces, Neural dynamics of brain disorders.

Within our knowledge, the series of the International Conference on Cognitive Neurodynamics (ICCN) is the only conference series dedicating to cognitive neurodynamics. This volume is the proceedings of the 2nd International Conference on Cognitive Neurodynamics held in 2009, which reviews the progress in this field since the 1st ICCN -2007. The topics include: Neural coding and realistic neural network dynamics, Neural population dynamics, Firing Oscillations and Patterns in Neuronal Networks, Brain imaging, EEG, MEG, Sensory and Motor Dynamics, Global cognitive function, Multi-scalar Neurodynamics - from Physiology to Systems Theory, Neural computing, Emerging Technologies for Brain Computer Interfaces, Neural dynamics of brain disorders.

This book contains original articles submitted to the Seventh International Conference on Cognitive Neurodynamics (ICCN 2019). The brain is an endless case study of a complex system characterized by multiple levels of integration, multiple time scales of activity, and multiple coding and decoding properties. The contribution of several disciplines, mathematics, physics, computer science, neurobiology, pharmacology, physiology, and behavioral and clinical sciences, is necessary in order to cope with such seemingly unattainable complexity that transforms the experimental information into a tricky puzzle which hides the correspondence with model predictions. This conference gathered active participants to discuss ideas and pose new questions from different viewpoints, ranging from single neurons and neural networks to animal/human behavior in theoretical and experimental studies. The conference is organized with plenary lectures, mini-symposia, interdisciplinary round tables, and oral and poster sessions.

Fifty years ago, enthused by successes in creating digital computers and the DNA model of heredity, scientists were con?dent that solutions to the problems of und- standing biological intelligence and creating machine intelligence were within their grasp. Progress at ?rst seemed rapid. Giant ‘brains’ that ?lled air-conditioned rooms were shrunk into briefcases. The speed of computation doubled every two years. What these advances revealed is not the solutions but the dif?culties of the pr- lems. We are like the geographers who ‘discovered’ America, not as a collection of islands but as continents seen only at shores and demanding exploration. We are astounded less by the magnitude of our discoveries about how brains cogitate than by the enormity of the tasks we have undertaken, to explain and replicate the higher functions of brains. Five decades of brain research have led to the emergence of a new ?eld, which spans the entire range of brain cognition from quantum ?elds to social interactions, and which is combined by the conceptions of nonlinear neurodynamics operating simultaneously at and across all levels. A new breed of scientists has emerged, schooled in multiple academic disciplines, comfortable in working with data from different levels, and conversant with the mathematical tools that are essential to cross boundaries.

This proceedings contains articles submitted to the fifth International Conference on Cognitive Neurodynamics (ICCN2015). In ICCN2015, twelve invited plenary lectures were presented by the leading scientists in their respective research fields. More than 15 mini-symposiums are organized by specialists with topics covering: motor control and learning, dynamic coding in distributed neural circuits, dynamics of firing patterns and synchronization in neuronal systems, information and signal processing techniques in neurotechnology, neural oscillations and synaptic plasticity in the hippocampus, new perspective on model-based vs. model-free brain process, neural mechanisms of internal switching, neuroinformation computation, neural model and dynamics, imaging human cognitive networks, neuroinformatics, neuroergonomics & neuroengineering, dynamic brain for communication, visual information processing and functional imaging and neural mechanisms of language processing. All articles are peer-reviewed. The ICCN is a series conference held every two years since 2007.

This book constitutes the refereed proceedings of the Third International Conference on Geometric Science of Information, GSI 2017, held in Paris, France, in November 2017. The 101 full papers presented were carefully reviewed and selected from 113 submissions and are organized into the following subjects: statistics on non-linear data; shape space; optimal transport and applications: image processing; optimal transport and applications: signal processing; statistical manifold and hessian information geometry; monotone embedding in information geometry; information structure in neuroscience; geometric robotics and tracking; geometric mechanics and robotics; stochastic geometric mechanics and Lie group thermodynamics; probability on Riemannian manifolds; divergence geometry; non-parametric information geometry; optimization on manifold; computational information geometry; probability density estimation; session geometry of tensor-valued data; geodesic methods with constraints; applications of distance geometry.

The book is a compendium of the aforementioned subclass of models of Basal Ganglia, which presents some the key existent theories of Basal Ganglia function. The book presents computational models of basal ganglia-related disorders, including Parkinson’s disease, schizophrenia, and addiction. Importantly, it highlights the applications of understanding the role of the basal ganglia to treat neurological and psychiatric disorders. The purpose of the present book is to amend and expand on James Houk’s book (MIT press; ASIN: B010BF4U9K) by providing a comprehensive overview on computational models of the basal ganglia. This book caters to researchers and academics from the area of computational cognitive neuroscience.

This volume provides new insight into motivation theory by integrating noteworthy neuroscience research findings on motivation. This volume is dedicated to advancing our understanding of brain mechanisms of underlying motivational phenomena, including reward, approach, autonomy, intrinsic motivation, learning, effort, curiosity, and self-control.

A field of theory and research is evolving around the question highlighted in the Uncanny Valley Hypothesis: How does high realism in anthropomorphic design influence human experience and behaviour? The Uncanny Valley Hypothesis posits that a very humanlike character or object (e.g., robot, prosthetic limb, doll) can evoke a negative affective (i.e., uncanny) state. Recent advances in robotic and computer-graphic technologies in simulating aspects of human appearance, behaviour and interaction have been accompanied, therefore, by theorising and research on the meaning and relevance of the Uncanny Valley Hypothesis for anthropomorphic design. Current understanding of the "uncanny" idea is still fragmentary and further original research is needed. However, the emerging picture indicates that the relationship between humanlike realism and subjective experience and behaviour may not be as straightforward as the Uncanny Valley Hypothesis suggests. This Research Topic brings together researchers from traditionally separate domains (including robotics, computer graphics, cognitive science, psychology and neuroscience) to provide a snapshot of current work in this field. A diversity of issues and questions are addressed in contributions that include original research, review, theory, and opinion papers.

A classical view of neural computation is that it can be characterized in terms of convergence to attractor states or sequential transitions among states in a noisy background. After over three decades, is this still a valid model of how brain dynamics implements cognition? This book provides a comprehensive collection of recent theoretical and experimental contributions addressing the question of stable versus transient neural population dynamics from complementary angles. These studies showcase recent efforts for designing a framework that encompasses the multiple facets of metastability in neural responses, one of the most exciting topics currently in systems and computational neuroscience.