Cognitive Systems Monographs – serie

This book provides an overview of model-based environmental visual perception for humanoid robots. The visual perception of a humanoid robot creates a bidirectional bridge connecting sensor signals with internal representations of environmental objects. The objective of such perception systems is to answer two fundamental questions: What & where is it? To answer these questions using a sensor-to-representation bridge, coordinated processes are conducted to extract and exploit cues matching robot’s mental representations to physical entities. These include sensor & actuator modeling, calibration, filtering, and feature extraction for state estimation. This book discusses the following topics in depth: •     Active Sensing: Robust probabilistic methods for optimal, high dynamic range image acquisition are suitable for use with inexpensive cameras. This enables ideal sensing in arbitrary environmental conditions encountered in human-centric spaces. The book quantitatively shows the importance of equipping robots with dependable visual sensing. •     Feature Extraction & Recognition: Parameter-free, edge extraction methods based on structural graphs enable the representation of geometric primitives effectively and efficiently. This is done by eccentricity segmentation providing excellent recognition even on noisy & low-resolution images. Stereoscopic vision, Euclidean metric and graph-shape descriptors are shown to be powerful mechanisms for difficult recognition tasks. •     Global Self-Localization & Depth Uncertainty Learning: Simultaneous feature matching for global localization and 6D self-pose estimation are addressed by a novel geometric and probabilistic concept using intersection of Gaussian spheres. The path from intuition to the closed-form optimal solution determining the robot location is described, including a supervised learning method for uncertainty depth modeling based on extensive ground-truth training data from a motion capture system.The methods and experiments are presented in self-contained chapters with comparisons and the state of the art. The algorithms were implemented and empirically evaluated on two humanoid robots: ARMAR III-A & B. The excellent robustness, performance and derived results received an award at the IEEE conference on humanoid robots and the contributions have been utilized for numerous visual manipulation tasks with demonstration at distinguished venues such as ICRA, CeBIT, IAS, and Automatica.

This book focuses on a critical issue in the study of physical agents, whether natural or artificial: the quantitative modelling of sensory–motor coordination.Adopting a novel approach, it defines a common scientific framework for both the intelligent systems designed by engineers and those that have evolved naturally. As such it contributes to the widespread adoption of a rigorous quantitative and refutable approach in the scientific study of ‘embodied’ intelligence and cognition. More than 70 years after Norbert Wiener’s famous book Cybernetics: or Control and Communication in the Animal and the Machine (1948), robotics, AI and life sciences seem to be converging towards a common model of what we can call the ‘science of embodied intelligent/cognitive agents’. This book is interesting for an interdisciplinary community of researchers, technologists and entrepreneurs working at the frontiers of robotics and AI, neuroscience and general life and brain sciences.

This book describes how robots can make sense of motion in their surroundings and use the patterns they observe to blend in better in dynamic environments shared with humans.The world around us is constantly changing. Nonetheless, we can find our way and aren’t overwhelmed by all the buzz, since motion often follows discernible patterns. Just like humans, robots need to understand the patterns behind the dynamics in their surroundings to be able to efficiently operate e.g. in a busy airport. Yet robotic mapping has traditionally been based on the static world assumption, which disregards motion altogether. In this book, the authors describe how robots can instead explicitly learn patterns of dynamic change from observations, store those patterns in Maps of Dynamics (MoDs), and use MoDs to plan less intrusive, safer and more efficient paths. The authors discuss the pros and cons of recently introduced MoDs and approaches to MoD-informed motion planning, and provide an outlook on future work in this emerging, fascinating field.

This book describes how robots can make sense of motion in their surroundings and use the patterns they observe to blend in better in dynamic environments shared with humans.The world around us is constantly changing. Nonetheless, we can find our way and aren’t overwhelmed by all the buzz, since motion often follows discernible patterns. Just like humans, robots need to understand the patterns behind the dynamics in their surroundings to be able to efficiently operate e.g. in a busy airport. Yet robotic mapping has traditionally been based on the static world assumption, which disregards motion altogether. In this book, the authors describe how robots can instead explicitly learn patterns of dynamic change from observations, store those patterns in Maps of Dynamics (MoDs), and use MoDs to plan less intrusive, safer and more efficient paths. The authors discuss the pros and cons of recently introduced MoDs and approaches to MoD-informed motion planning, and provide an outlook on future work in this emerging, fascinating field.

This book presents a theoretical critical appraisal of the Mechanistic Theory of Human Cognition (MTHC), which is one of the most popular major theories in the contemporary field of cognitive science. It analyses and evaluates whether MTHC provides a unifying account of human cognition and its explanation. The book presents a systematic investigation of the internal and external consistency of the theory, as well as a systematic comparison with other contemporary major theories in the field. In this sense, it provides a fresh look at more recent major theoretical debates in this area of scientific research and a rigorous analysis of one of its most central major theories. Rigorous theoretical work is integrated with objective consideration of relevant empirical evidence, making the discussions robust and clear. As a result, the book shows that MTHC provides a significant theoretical contribution for the field of cognitive science. The content is useful for those interested in theoretical and empirical issues concerning major theories in the contemporary field of cognitive science.

This book presents a theoretical critical appraisal of the Mechanistic Theory of Human Cognition (MTHC), which is one of the most popular major theories in the contemporary field of cognitive science. It analyses and evaluates whether MTHC provides a unifying account of human cognition and its explanation. The book presents a systematic investigation of the internal and external consistency of the theory, as well as a systematic comparison with other contemporary major theories in the field. In this sense, it provides a fresh look at more recent major theoretical debates in this area of scientific research and a rigorous analysis of one of its most central major theories. Rigorous theoretical work is integrated with objective consideration of relevant empirical evidence, making the discussions robust and clear. As a result, the book shows that MTHC provides a significant theoretical contribution for the field of cognitive science. The content is useful for those interested in theoretical and empirical issues concerning major theories in the contemporary field of cognitive science.

This book explores the psychological impact of advanced forms of artificial intelligence. How will it be to live with a superior intelligence? How will the exposure to highly developed artificial intelligence (AI) systems change human well-being? With a review of recent advancements in brain–computer interfaces, military AI, Explainable AI (XAI) and digital clones as a foundation, the experience of living with a hyperintelligence is discussed from the viewpoint of a clinical psychologist. The theory of universal solicitation is introduced, i.e. the demand character of a technology that wants to be used in all aspects of life. With a focus on human experience, and to a lesser extent on technology, the book is written for a general readership with an interest in psychology, technology and the future of our human condition. With its unique focus on psychological topics, the book offers contributions to a discussion on the future of human life beyond purely technological considerations.

This book explores the psychological impact of advanced forms of artificial intelligence. How will it be to live with a superior intelligence? How will the exposure to highly developed artificial intelligence (AI) systems change human well-being? With a review of recent advancements in brain–computer interfaces, military AI, Explainable AI (XAI) and digital clones as a foundation, the experience of living with a hyperintelligence is discussed from the viewpoint of a clinical psychologist. The theory of universal solicitation is introduced, i.e. the demand character of a technology that wants to be used in all aspects of life. With a focus on human experience, and to a lesser extent on technology, the book is written for a general readership with an interest in psychology, technology and the future of our human condition. With its unique focus on psychological topics, the book offers contributions to a discussion on the future of human life beyond purely technological considerations.

This book mainly focuses on the widely distributed nature of computational tools, models, and methods, ultimately related to the current importance of computational machines as mediators of cognition. An entirely new eco-cognitive approach to computation is offered, to underline the question of the overwhelming cognitive domestication of ignorant entities, which is persistently at work in our current societies. Eco-cognitive computationalism does not aim at furnishing an ultimate and static definition of the concepts of information, cognition, and computation, instead, it intends, by respecting their historical and dynamical character, to propose an intellectual framework that depicts how we can understand their forms of “emergence” and the modification of their meanings, also dealing with impressive unconventional non-digital cases. The new proposed perspective also leads to a clear description of the divergence between weak and strong levels of creative “abductive” hypothetical cognition: weak accomplishments are related to “locked abductive strategies”, typical of computational machines, and deep creativity is instead related to “unlocked abductive strategies”, which characterize human cognizers, who benefit from the so-called “eco-cognitive openness”.

This book mainly focuses on the widely distributed nature of computational tools, models, and methods, ultimately related to the current importance of computational machines as mediators of cognition. An entirely new eco-cognitive approach to computation is offered, to underline the question of the overwhelming cognitive domestication of ignorant entities, which is persistently at work in our current societies. Eco-cognitive computationalism does not aim at furnishing an ultimate and static definition of the concepts of information, cognition, and computation, instead, it intends, by respecting their historical and dynamical character, to propose an intellectual framework that depicts how we can understand their forms of “emergence” and the modification of their meanings, also dealing with impressive unconventional non-digital cases. The new proposed perspective also leads to a clear description of the divergence between weak and strong levels of creative “abductive” hypothetical cognition: weak accomplishments are related to “locked abductive strategies”, typical of computational machines, and deep creativity is instead related to “unlocked abductive strategies”, which characterize human cognizers, who benefit from the so-called “eco-cognitive openness”.

This book helps transform the awareness of the anticipatory perspective into actionable methods for practitioners of medicine. It provides guidance for those who design new means and methods inspired by epigenetics, in particular to those who advance sustainable alternatives.

This book helps transform the awareness of the anticipatory perspective into actionable methods for practitioners of medicine. It provides guidance for those who design new means and methods inspired by epigenetics, in particular to those who advance sustainable alternatives.

This book explores the transformative roles of human-computer interaction (HCI) and augmented intelligence (AI) in shaping intelligent systems. HCI focuses on designing interactive systems that enhance human-technology relationships, while AI empowers users with adaptive, data-driven tools that complement decision-making. Together, these fields drive innovation, creating systems that are efficient, intuitive, and inclusive, addressing diverse user needs across various domains.Central to this work is the paradigm of interactive machine learning (IML), which builds on HCI and AI principles to create adaptive systems capable of evolving in real-time. The book highlights the application of IML in educational software, demonstrating how dynamic, personalized, and responsive learning environments can enhance student engagement and success. It provides detailed case studies and practical examples that showcase how IML aligns educational content, feedback, and interactions with learner behaviors and preferences. Additionally, it includes numerous Python code implementations and actionable design strategies, making these concepts accessible to practitioners and researchers alike.Key topics include leveraging cognitive and communication styles to shape adaptive systems, integrating learning models to enhance personalization, and addressing ethical considerations such as data privacy and algorithmic fairness. Readers will also discover discussions on creating personalized tutoring systems, collaborative platforms, and immersive environments that redefine educational technology.This book is a valuable resource for researchers, software developers, educators, instructional designers, and technologists at the intersection of human-computer interaction, augmented intelligence, and educational innovation. With its comprehensive framework and practical insights, it offers the tools to design adaptive, inclusive, and impactful learning systems for the future.

This book explores the transformative roles of human-computer interaction (HCI) and augmented intelligence (AI) in shaping intelligent systems. HCI focuses on designing interactive systems that enhance human-technology relationships, while AI empowers users with adaptive, data-driven tools that complement decision-making. Together, these fields drive innovation, creating systems that are efficient, intuitive, and inclusive, addressing diverse user needs across various domains.Central to this work is the paradigm of interactive machine learning (IML), which builds on HCI and AI principles to create adaptive systems capable of evolving in real-time. The book highlights the application of IML in educational software, demonstrating how dynamic, personalized, and responsive learning environments can enhance student engagement and success. It provides detailed case studies and practical examples that showcase how IML aligns educational content, feedback, and interactions with learner behaviors and preferences. Additionally, it includes numerous Python code implementations and actionable design strategies, making these concepts accessible to practitioners and researchers alike.Key topics include leveraging cognitive and communication styles to shape adaptive systems, integrating learning models to enhance personalization, and addressing ethical considerations such as data privacy and algorithmic fairness. Readers will also discover discussions on creating personalized tutoring systems, collaborative platforms, and immersive environments that redefine educational technology.This book is a valuable resource for researchers, software developers, educators, instructional designers, and technologists at the intersection of human-computer interaction, augmented intelligence, and educational innovation. With its comprehensive framework and practical insights, it offers the tools to design adaptive, inclusive, and impactful learning systems for the future.

This book provides an in-depth exploration of how generative AI is transforming the diagnosis, treatment planning, and future of cognitive healthcare. By integrating cutting-edge artificial intelligence with medical science, it highlights how AI-driven innovations are enhancing early detection, intervention strategies, and personalized treatment for neurological disorders such as Alzheimer’s, Parkinson’s, and dementia.Cognitive diseases pose significant challenges due to late-stage diagnoses, limited treatment efficacy, and the complexity of neurological disorders. This book addresses these critical issues by showcasing the role of AI-generated medical imaging, synthetic data, and biomarker discovery in improving diagnostic accuracy and advancing research. It introduces AI-powered digital twins, neuro rehabilitation, and cognitive therapy, demonstrating how machine learning models can predict disease progression and optimize patient care.Readers will gain insights into how AI is reshaping healthcare workflows, from GANs, VAEs, and diffusion models in medical imaging to AI-assisted patient monitoring and rehabilitation programs. Ethical considerations, such as bias in AI models, patient privacy, and regulatory frameworks, are also discussed, ensuring a balanced perspective on AI adoption in healthcare.Designed for an interdisciplinary audience, this book serves as both an academic reference and a practical guide for medical professionals, AI researchers, healthcare innovators, and policymakers. Whether you are a clinician looking to integrate AI into your practice, a researcher exploring AI applications in medicine, or a technology leader shaping the future of healthcare, this book equips you with the knowledge to harness generative AI for improved cognitive disease management.

The human hand and its dexterity in grasping and manipulating objects are some of the hallmarks of the human species. For years, anatomic and biomechanical studies have deepened the understanding of the human hand’s functioning and, in parallel, the robotics community has been working on the design of robotic hands capable of manipulating objects with a performance similar to that of the human hand. However, although many researchers have partially studied various aspects, to date there has been no comprehensive characterization of the human hand’s function for grasping and manipulation of everyday life objects.This monograph explores the hypothesis that the confluence of both scientific fields, the biomechanical study of the human hand and the analysis of robotic manipulation of objects, would greatly benefit and advance both disciplines through simulation. Therefore, in this book, the current knowledge of robotics and biomechanics guides the design and implementation of a simulation framework focused on manipulation interactions that allows the study of the grasp through simulation. As a result, a valuable framework for the study of the grasp, with relevant applications in several fields such as robotics, biomechanics, ergonomics, rehabilitation and medicine, has been made available to these communities.

This book presents the result of a joint effort from different European Institutions within the framework of the EU funded project called SPARK II, devoted to device an insect brain computational model, useful to be embedded into autonomous robotic agents.Part I reports the biological background on Drosophila melanogaster with particular attention to the main centers which are used as building blocks for the implementation of the insect brain computational model.Part II reports the mathematical approach to model the Central Pattern Generator used for the gait generation in a six-legged robot. Also the Reaction-diffusion principles in non-linear lattices are exploited to develop a compact internal representation of a dynamically changing environment for behavioral planning. In Part III a software/hardware framework, developed to integrate the insect brain computational model in a simulated/real robotic platform, is illustrated. The different robots used for the experiments are also described. Moreover the problems related to the vision system were addressed proposing robust solutions for object identification and feature extraction.Part IV includes the relevant scenarios used in the experiments to test the capabilities of the insect brain-inspired architecture taking as comparison the biological case. Experimental results are finally reported, whose multimedia can be found in the SPARK II web page: www.spark2.diees.unict.it

Cognitive Science is a discipline that brings together research in natural and artificial systems and this is clearly reflected in the diverse contributions to From Animals to Robots and Back.In tribute to Aaron Sloman and his pioneering work in Cognitive Science and Artificial Intelligence, the editors have collected a unique collection of cross-disciplinary papers that include work on:·        intelligent robotics;·        philosophy of cognitive science;·        emotional research·        computational vision;·        comparative psychology; and·        human-computer interaction.Key themes such as the importance of taking an architectural view in approaching cognition, run through the text. Drawing on the expertize of leading international researchers, contemporary debates in the study of natural and artificial cognition are addressed from complementary and contrasting perspectives with key issues being outlined at various levels of abstraction.From Animals to Robots and Back, will give readers with backgrounds in the study of both natural and artificial cognition an important window on the state of the art in cognitive systems research.

This volume presents the work of leading scientists from Russia, Georgia, Estonia, Lithuania, Israel and the USA, revealing major insights long unknown to the scientific community. Without any doubt their work will provide a springboard for further research in anticipation. Until recently, Robert Rosen (Anticipatory Systems) and Mihai Nadin (MIND – Anticipation and Chaos) were deemed forerunners in this still new knowledge domain.The distinguished neurobiologist, Steven Rose, pointed to the fact that Soviet neuropsychological theories have not on the whole been well received by Western science. These earlier insights as presented in this volume make an important contribution to the foundation of the science of anticipation. It is shown that the daring hypotheses and rich experimental evidence produced by Bernstein, Beritashvili, Ukhtomsky, Anokhin and Uznadze, among others—extend foundational work to aspects of neuroscience, physiology, motorics, education.

In this fundamental book the authors devise a framework that describes the working of the brain as a whole. It presents a comprehensive introduction to the principles of Neural Information Processing as well as recent and authoritative research. The books´ guiding principles are the main purpose of neural activity, namely, to organize behavior to ensure survival, as well as the understanding of the evolutionary genesis of the brain. Among the developed principles and strategies belong self-organization of neural systems, flexibility, the active interpretation of the world by means of construction and prediction as well as their embedding into the world, all of which form the framework of the presented description. Since, in brains, their partial self-organization, the lifelong adaptation and their use of various methods of processing incoming information are all interconnected, the authors have chosen not only neurobiology and evolution theory as a basis for the elaboration of sucha framework but also systems and signal theory.The most important message of the book and authors is: brains are evolved as a whole and a description of parts although necessary lets one miss the wood for the trees.

This book presents interdisciplinary research that pursues the mutual enrichment of neuroscience and robotics. Building on experimental work, and on the wealth of literature regarding the two cortical pathways of visual processing - the dorsal and ventral streams - we define and implement, computationally and on a real robot, a functional model of the brain areas involved in vision-based grasping actions.Grasping in robotics is largely an unsolved problem, and we show how the bio-inspired approach is successful in dealing with some fundamental issues of the task. Our robotic system can safely perform grasping actions on different unmodeled objects, denoting especially reliable visual and visuomotor skills.The computational model and the robotic experiments help in validating theories on the mechanisms employed by the brain areas more directly involved in grasping actions. This book offers new insights and research hypotheses regarding such mechanisms, especially for what concerns the interaction between the dorsal and ventral streams. Moreover, it helps in establishing a common research framework for neuroscientists and roboticists regarding research on brain functions.

This book clarifies the role and relevance of the body in social interaction and cognition from an embodied cognitive science perspective. Theories of embodied cognition have during the last decades offered a radical shift in explanations of the human mind, from traditional computationalism, to emphasizing the way cognition is shaped by the body and its sensorimotor interaction with the surrounding social and material world.This book presents a theoretical framework for the relational nature of embodied social cognition, which is based on an interdisciplinary approach that ranges historically in time and across different disciplines. It includes work in cognitive science, artificial intelligence, phenomenology, ethology, developmental psychology, neuroscience, social psychology, linguistics, communication and gesture studies.The theoretical framework is illustrated by empirical work that provides some detailed observational fieldwork on embodied actions captured in three different episodes of spontaneous social interaction and cognition in situ.Furthermore, the theoretical contributions and implications of the study of embodied social cognition are discussed and summed up. Finally, the issue what it would take for an artificial system to be socially embodied is addressed and discussed, as well as the practical relevance for applications to artificial intelligence (AI) and socially interactive technology.

Never before was anticipation more relevant to the life and activity of humankind than it is today. “It is no overstatement to suggest that humanity’s future will be shaped by its capacity to anticipate….” (Research Agenda for the 21st Century, National Science Foundation). The sciences and the humanities can no longer risk explaining away the complexity and interactivity that lie at the foundation of life and living. The perspective of the world that anticipation opens justifies the descriptor “the post-Cartesian Revolution.”If anticipation is a valid research domain, what practical relevance can we await? Indeed, anticipation is more than just the latest catch-word in marketing the apps developed by the digital technology industry. Due to spectacular advances in the study of the living, anticipation can claim a legitimate place in current investigations and applications in the sciences and the humanities. Biology, genetics, medicine, as well as politics and cognitive, behavioral, and social sciences, provide rich evidence of anticipatory processes at work. Readers seeking a foundation for anticipation will find in these pages recent outcomes pertinent to plant life, political anticipation, cognitive science, architecture, computation. The authors contributing to this volume frame experimental data in language that can be shared among experts from all fields of endeavor. The major characteristic is the inference from the richness of data to principles and practical consequences.

This book presents state-of-the-art computationalattention models that have been successfully tested in diverse applicationareas and can build the foundation for artificial systems to efficientlyexplore, analyze, and understand natural scenes. It gives a comprehensive overview of the most recentcomputational attention models for processing visual and acoustic input. Itcovers the biological background of visual and auditory attention, as well as bottom-up and top-down attentionalmechanisms and discusses various applications. In the first part new approachesfor bottom-up visual and acoustic saliency models are presented and applied tothe task of audio-visual scene exploration of a robot. In the second part theinfluence of top-down cues for attention modeling is investigated.

This book presents the result of a joint effort from different European Institutions within the framework of the EU funded project called SPARK II, devoted to device an insect brain computational model, useful to be embedded into autonomous robotic agents.Part I reports the biological background on Drosophila melanogaster with particular attention to the main centers which are used as building blocks for the implementation of the insect brain computational model.Part II reports the mathematical approach to model the Central Pattern Generator used for the gait generation in a six-legged robot. Also the Reaction-diffusion principles in non-linear lattices are exploited to develop a compact internal representation of a dynamically changing environment for behavioral planning. In Part III a software/hardware framework, developed to integrate the insect brain computational model in a simulated/real robotic platform, is illustrated. The different robots used for the experiments are also described. Moreover the problems related to the vision system were addressed proposing robust solutions for object identification and feature extraction.Part IV includes the relevant scenarios used in the experiments to test the capabilities of the insect brain-inspired architecture taking as comparison the biological case. Experimental results are finally reported, whose multimedia can be found in the SPARK II web page: www.spark2.diees.unict.it

The human hand and its dexterity in grasping and manipulating objects are some of the hallmarks of the human species. For years, anatomic and biomechanical studies have deepened the understanding of the human hand’s functioning and, in parallel, the robotics community has been working on the design of robotic hands capable of manipulating objects with a performance similar to that of the human hand. However, although many researchers have partially studied various aspects, to date there has been no comprehensive characterization of the human hand’s function for grasping and manipulation of everyday life objects.This monograph explores the hypothesis that the confluence of both scientific fields, the biomechanical study of the human hand and the analysis of robotic manipulation of objects, would greatly benefit and advance both disciplines through simulation. Therefore, in this book, the current knowledge of robotics and biomechanics guides the design and implementation of a simulation framework focused on manipulation interactions that allows the study of the grasp through simulation. As a result, a valuable framework for the study of the grasp, with relevant applications in several fields such as robotics, biomechanics, ergonomics, rehabilitation and medicine, has been made available to these communities.

Never before was anticipation more relevant to the life and activity of humankind than it is today. “It is no overstatement to suggest that humanity’s future will be shaped by its capacity to anticipate….” (Research Agenda for the 21st Century, National Science Foundation). The sciences and the humanities can no longer risk explaining away the complexity and interactivity that lie at the foundation of life and living. The perspective of the world that anticipation opens justifies the descriptor “the post-Cartesian Revolution.”If anticipation is a valid research domain, what practical relevance can we await? Indeed, anticipation is more than just the latest catch-word in marketing the apps developed by the digital technology industry. Due to spectacular advances in the study of the living, anticipation can claim a legitimate place in current investigations and applications in the sciences and the humanities. Biology, genetics, medicine, as well as politics and cognitive, behavioral, and social sciences, provide rich evidence of anticipatory processes at work. Readers seeking a foundation for anticipation will find in these pages recent outcomes pertinent to plant life, political anticipation, cognitive science, architecture, computation. The authors contributing to this volume frame experimental data in language that can be shared among experts from all fields of endeavor. The major characteristic is the inference from the richness of data to principles and practical consequences.

This volume presents the work of leading scientists from Russia, Georgia, Estonia, Lithuania, Israel and the USA, revealing major insights long unknown to the scientific community. Without any doubt their work will provide a springboard for further research in anticipation. Until recently, Robert Rosen (Anticipatory Systems) and Mihai Nadin (MIND – Anticipation and Chaos) were deemed forerunners in this still new knowledge domain.The distinguished neurobiologist, Steven Rose, pointed to the fact that Soviet neuropsychological theories have not on the whole been well received by Western science. These earlier insights as presented in this volume make an important contribution to the foundation of the science of anticipation. It is shown that the daring hypotheses and rich experimental evidence produced by Bernstein, Beritashvili, Ukhtomsky, Anokhin and Uznadze, among others—extend foundational work to aspects of neuroscience, physiology, motorics, education.

In this fundamental book the authors devise a framework that describes the working of the brain as a whole. It presents a comprehensive introduction to the principles of Neural Information Processing as well as recent and authoritative research. The books´ guiding principles are the main purpose of neural activity, namely, to organize behavior to ensure survival, as well as the understanding of the evolutionary genesis of the brain. Among the developed principles and strategies belong self-organization of neural systems, flexibility, the active interpretation of the world by means of construction and prediction as well as their embedding into the world, all of which form the framework of the presented description. Since, in brains, their partial self-organization, the lifelong adaptation and their use of various methods of processing incoming information are all interconnected, the authors have chosen not only neurobiology and evolution theory as a basis for the elaboration of sucha framework but also systems and signal theory.The most important message of the book and authors is: brains are evolved as a whole and a description of parts although necessary lets one miss the wood for the trees.