The behaviorist credo that animals are devices for translating sensory input into appropriate responses dies hard. The thesis of this pathbreaking book is that the brain is innately constructed to initiate behaviors likely to promote the survival of the species, and to sensitize sensory systems to stimuli required for those behaviors. Animals attend innately to vital stimuli (reinforcers) and the more advanced animals learn to attend to related stimuli as well. Thus, the centrifugal attentional components of sensory systems are as important for learned behavior as the more conventional paths. It is hypothesized that the basal ganglia are an important source of response plans and attentional signals. This reversal of traditional learning theory, along with the rapid expansion of knowledge about the brain, especially that acquired by improved techniques for recording neural activity in behaving animals and people, makes it possible to re-examine some long standing psychological problems. One such problem is how the intention to perform an act selects sensory input from relevant objects and ensures that it alone is delivered to the motor system to control the intended response. This is an aspect of what is sometimes known as the binding problem: how the different features of an observed object are integrated into a unified percept. Another problem that has never been satisfactorily addressed is how the brain stores information concerning temporal order, a requirement for the production of most learned responses, including pronouncing and writing words. A fundamental process, the association between brain activities representing external events, is surprisingly poorly understood at the neural level. Most concepts have multiple associations but the concept is not unduly corrupted by them, and usually only a single appropriate association is aroused at a time. Furthermore, any arbitrary pair of concepts can be instantly associated, apparently requiring an impossibly high degree of neural interconnection. The author suggests a substitute for the reverberating closed neuronal loop as an explanation for the engram (active memory trace or working memory), which may go some way to resolving these difficulties. Shedding new light on enduring questions, The Autonomous Brain will be welcomed by a broad audience of behavioral and brain scientists.

The behaviorist credo that animals are devices for translating sensory input into appropriate responses dies hard. The thesis of this pathbreaking book is that the brain is innately constructed to initiate behaviors likely to promote the survival of the species, and to sensitize sensory systems to stimuli required for those behaviors. Animals attend innately to vital stimuli (reinforcers) and the more advanced animals learn to attend to related stimuli as well. Thus, the centrifugal attentional components of sensory systems are as important for learned behavior as the more conventional paths. It is hypothesized that the basal ganglia are an important source of response plans and attentional signals. This reversal of traditional learning theory, along with the rapid expansion of knowledge about the brain, especially that acquired by improved techniques for recording neural activity in behaving animals and people, makes it possible to re-examine some long standing psychological problems. One such problem is how the intention to perform an act selects sensory input from relevant objects and ensures that it alone is delivered to the motor system to control the intended response. This is an aspect of what is sometimes known as the binding problem: how the different features of an observed object are integrated into a unified percept. Another problem that has never been satisfactorily addressed is how the brain stores information concerning temporal order, a requirement for the production of most learned responses, including pronouncing and writing words. A fundamental process, the association between brain activities representing external events, is surprisingly poorly understood at the neural level. Most concepts have multiple associations but the concept is not unduly corrupted by them, and usually only a single appropriate association is aroused at a time. Furthermore, any arbitrary pair of concepts can be instantly associated, apparently requiring an impossibly high degree of neural interconnection. The author suggests a substitute for the reverberating closed neuronal loop as an explanation for the engram (active memory trace or working memory), which may go some way to resolving these difficulties. Shedding new light on enduring questions, The Autonomous Brain will be welcomed by a broad audience of behavioral and brain scientists.

"In this book, Peter Robin Hiesinger explores historical and contemporary attempts to understand the information needed to make biological and artificial neural networks. Developmental neurobiologists and computer scientists with an interest in artificial intelligence - driven by the promise and resources of biomedical research on the one hand, and by the promise and advances of computer technology on the other - are trying to understand the fundamental principles that guide the generation of an intelligent system. Yet, though researchers in these disciplines share a common interest, their perspectives and approaches are often quite different. The book makes the case that "the information problem" underlies both fields, driving the questions that are driving forward the frontiers, and aims to encourage cross-disciplinary communication and understanding, to help both fields make progress. The questions that challenge researchers in these fields include the following. How does genetic information unfold during the years-long process of human brain development, and can this be a short-cut to create human-level artificial intelligence? Is the biological brain just messy hardware that can be improved upon by running learning algorithms in computers? Can artificial intelligence bypass evolutionary programming of "grown" networks? These questions are tightly linked, and answering them requires an understanding of how information unfolds algorithmically to generate functional neural networks. Via a series of closely linked "discussions" (fictional dialogues between researchers in different disciplines) and pedagogical "seminars," the author explores the different challenges facing researchers working on neural networks, their different perspectives and approaches, as well as the common ground and understanding to be found amongst those sharing an interest in the development of biological brains and artificial intelligent systems"--

A user-friendly guide to ASMR—the stress-reducing, sleep-inducing, tingly sensation you have to try!— featuring step-by-step instructions on ASMR best practices for home and professional use alike. The calming feeling when someone gently brushes your hair. The deep comfort and connection you feel when a friend whispers in your ear. The tingly sensation experienced from the personal attention of a hairdresser, a clinician, or even watching and listening to Bob Ross… That feeling has a name! ASMR, or autonomous sensory meridian response (a deeply relaxing sensation with delightful head tingles that typically begin on the scalp and move down the spine) feels so good that some refer to it as a “brain-gasm.” ASMR videos on YouTube have millions of subscribers and billions of views. ASMR is truly everywhere—from ad campaigns to celebrities to millions of regular people looking for a moment of “ahhhh.” With Brain Tingles, it’s now possible to stimulate—and even share—those feel-good tingles every day, and in real life! ASMRUniversity.com founder Craig Richard, PhD, explains what ASMR is, why it happens, and how to trigger it at home. No special training or fancy equipment required! Inside, you’ll learn the most common auditory, visual, and tactile triggers and how to create person-to-person ASMR scenarios (from a mock eye exam to a pretend manicure) with a partner, client, or friend. The end result? That calming, tingly euphoria that can be used for comfort, relaxation, restfulness, or even to set the tone for sleep—on demand! With a textured cover you can rub, stroke, or scratch to use as a tactile trigger, Brain Tingles is the ultimate ASMR tool, inside and out.

How does your mind work? How does your brain give rise to your mind? These are questions that all of us have wondered about at some point in our lives, if only because everything that we know is experienced in our minds. They are also very hard questions to answer. After all, how can a mind understand itself? How can you understand something as complex as the tool that is being used to understand it? This book provides an introductory and self-contained description of some of the exciting answers to these questions that modern theories of mind and brain have recently proposed. Stephen Grossberg is broadly acknowledged to be the most important pioneer and current research leader who has, for the past 50 years, modelled how brains give rise to minds, notably how neural circuits in multiple brain regions interact together to generate psychological functions. This research has led to a unified understanding of how, where, and why our brains can consciously see, hear, feel, and know about the world, and effectively plan and act within it. The work embodies revolutionary Principia of Mind that clarify how autonomous adaptive intelligence is achieved. It provides mechanistic explanations of multiple mental disorders, including symptoms of Alzheimer's disease, autism, amnesia, and sleep disorders; biological bases of morality and religion, including why our brains are biased towards the good so that values are not purely relative; perplexing aspects of the human condition, including why many decisions are irrational and self-defeating despite evolution's selection of adaptive behaviors; and solutions to large-scale problems in machine learning, technology, and Artificial Intelligence that provide a blueprint for autonomously intelligent algorithms and robots. Because brains embody a universal developmental code, unifying insights also emerge about shared laws that are found in all living cellular tissues, from the most primitive to the most advanced, notably how the laws governing networks of interacting cells support developmental and learning processes in all species. The fundamental brain design principles of complementarity, uncertainty, and resonance that Grossberg has discovered also reflect laws of the physical world with which our brains ceaselessly interact, and which enable our brains to incrementally learn to understand those laws, thereby enabling humans to understand the world scientifically. Accessibly written, and lavishly illustrated, Conscious Mind/Resonant Brain is the magnum opus of one of the most influential scientists of the past 50 years, and will appeal to a broad readership across the sciences and humanities.

"When anything can be owned, how can we be free? Earth, 2144. Jack is an anti-patent scientist turned drug pirate, a pharmaceutical Robin Hood traversing the world in a submarine, fabricating cheap scrips for poor people who can't otherwise afford them. But her latest drug hack leaves a trail of lethal overdoses as people become addicted to their work, repeating job tasks until they become insane. Hot on her trail, an unlikely pair: Eliasz, a brooding military agent, and his partner, Paladin, a young indentured robot. As they race to stop information about the hacked drugs at their source, they form an uncommonly close relationship that neither of them fully understands, and Paladin begins to question their connection - and a society that profits from indentured robots" --

Early rules-based artificial intelligence demonstrated intriguing decision-making capabilities but lacked perception and didn't learn. AI today, primed with machine learning perception and deep reinforcement learning capabilities, can perform superhuman decision-making for specific tasks. This book shows you how to combine the practicality of early AI with deep learning capabilities and industrial control technologies to make robust decisions in the real world. Using concrete examples, minimal theory, and a proven architectural framework, author Kence Anderson demonstrates how to teach autonomous AI explicit skills and strategies. You'll learn when and how to use and combine various AI architecture design patterns, as well as how to design advanced AI without needing to manipulate neural networks or machine learning algorithms. Students, process operators, data scientists, machine learning algorithm experts, and engineers who own and manage industrial processes can use the methodology in this book to design autonomous AI. This book examines: Differences between and limitations of automated, autonomous, and human decision-making Unique advantages of autonomous AI for real-time decision-making, with use cases How to design an autonomous AI from modular components and document your designs