Predictions In The Brain

When one is immersed in the fascinating world of neuroscience findings, the brain might start to seem like a collection of "modules," each specializes in a specific mental feat. But just like in other domains of Nature, it is possible that much of the brain and mind's operation can be explained with a small set of universal principles. Given exciting recent developments in theory, empirical findings and computational studies, it seems that the generation of predictions might be one strong candidate for such a universal principle. This is the focus of Predictions in the brain. From the predictions required when a rat navigates a maze to food-caching in scrub-jays; from predictions essential in decision-making to social interactions; from predictions in the retina to the prefrontal cortex; and from predictions in early development to foresight in non-humans. The perspectives represented in this collection span a spectrum from the cellular underpinnings to the computational principles underlying future-related mental processes, and from systems neuroscience to cognition and emotion. In spite of this diversity, they share some core elements. Memory, for instance, is critical in any framework that explains predictions. In asking "what is next?" our brains have to refer to memory and experience on the way to simulating our mental future. But as much as this collection offers answers to important questions, it raises and emphasizes outstanding ones. How are experiences coded optimally to afford using them for predictions? How do we construct a new simulation from separate memories? How specific in detail are future-oriented thoughts, and when do they rely on imagery, concepts or language? Therefore, in addition to presenting the state-of-the-art of research and ideas about predictions as a universal principle in mind and brain, it is hoped that this collection will stimulate important new research into the foundations of our mental lives.

An accessible and engaging account of the mind and its connection to the brain. The mind encompasses everything we experience, and these experiences are created by the brain--often without our awareness. Experience is private; we can't know the minds of others. But we also don't know what is happening in our own minds. In this book, E. Bruce Goldstein offers an accessible and engaging account of the mind and its connection to the brain. He takes as his starting point two central questions--what is the mind? and what is consciousness?--and leads readers through topics that range from conceptions of the mind in popular culture to the wiring system of the brain. Throughout, he draws on the latest research, explaining its significance and relevance.

This title brings together work on embodiment, action, and the predictive mind. At the core is the vision of human minds as prediction machines - devices that constantly try to stay one step ahead of the breaking waves of sensory stimulation, by actively predicting the incoming flow. In every situation we encounter, that complex prediction machinery is already buzzing, proactively trying to anticipate the sensory barrage. The book shows in detail how this strange but potent strategy of self-anticipation ushers perception, understanding, and imagination simultaneously onto the cognitive stage.

A new theory is taking hold in neuroscience. It is the theory that the brain is essentially a hypothesis-testing mechanism, one that attempts to minimise the error of its predictions about the sensory input it receives from the world. It is an attractive theory because powerful theoretical arguments support it, and yet it is at heart stunningly simple. Jakob Hohwy explains and explores this theory from the perspective of cognitive science and philosophy. The key argument throughout The Predictive Mind is that the mechanism explains the rich, deep, and multifaceted character of our conscious perception. It also gives a unified account of how perception is sculpted by attention, and how it depends on action. The mind is revealed as having a fragile and indirect relation to the world. Though we are deeply in tune with the world we are also strangely distanced from it. The first part of the book sets out how the theory enables rich, layered perception. The theory's probabilistic and statistical foundations are explained using examples from empirical research and analogies to different forms of inference. The second part uses the simple mechanism in an explanation of problematic cases of how we manage to represent, and sometimes misrepresent, the world in health as well as in mental illness. The third part looks into the mind, and shows how the theory accounts for attention, conscious unity, introspection, self and the privacy of our mental world.

When one is immersed in the fascinating world of neuroscience findings, the brain might start to seem like a collection of "modules," each specializes in a specific mental feat. But just like in other domains of Nature, it is possible that much of the brain and mind's operation can be explained with a small set of universal principles. Given exciting recent developments in theory, empirical findings and computational studies, it seems that the generation of predictions might be one strong candidate for such a universal principle. This is the focus of Predictions in the brain. From the predictions required when a rat navigates a maze to food-caching in scrub-jays; from predictions essential in decision-making to social interactions; from predictions in the retina to the prefrontal cortex; and from predictions in early development to foresight in non-humans. The perspectives represented in this collection span a spectrum from the cellular underpinnings to the computational principles underlying future-related mental processes, and from systems neuroscience to cognition and emotion. In spite of this diversity, they share some core elements. Memory, for instance, is critical in any framework that explains predictions. In asking "what is next?" our brains have to refer to memory and experience on the way to simulating our mental future. But as much as this collection offers answers to important questions, it raises and emphasizes outstanding ones. How are experiences coded optimally to afford using them for predictions? How do we construct a new simulation from separate memories? How specific in detail are future-oriented thoughts, and when do they rely on imagery, concepts or language? Therefore, in addition to presenting the state-of-the-art of research and ideas about predictions as a universal principle in mind and brain, it is hoped that this collection will stimulate important new research into the foundations of our mental lives.

From the author of How Emotions Are Made, a myth-busting primer on the brain, in the tradition of Seven Brief Lessons on Physics and Astrophysics for People in a Hurry

Theoretical reflections on memory and prediction, linking these concepts to the role of the cerebellum in higher cognition. What is memory? What is memory for? Where is memory in the brain? Although memory is probably the most studied function in cognition, these fundamental questions remain challenging. We can try to answer the question of memory's purpose by defining the function of memory as remembering the past. And yet this definition is not consistent with the many errors that characterize our memory, or with the phylogenetic and ontogenetic origin of memory. In this book, Tomaso Vecchi and Daniele Gatti argue that the purpose of memory is not to remember the past but to predict the future. Vecchi and Gatti link memory and prediction to the role of the cerebellum in higher cognition, relying on recent empirical data to support theoretical reflections. They propose a new model of memory functions that comprises a system devoted to prediction, based in the cerebellum and mediated by the hippocampus, and a parallel system with a major role for cortical structures and mediated by the amygdala. Although memory is often conceived as a kind of storehouse, this storehouse is constantly changing, integrating new information in a continual process of modification. In order to explain these characteristics, Vecchi and Gatti argue, we must change our interpretation of the nature and functions of the memory system.

From the inventor of the PalmPilot comes a new and compelling theory of intelligence, brain function, and the future of intelligent machines Jeff Hawkins, the man who created the PalmPilot, Treo smart phone, and other handheld devices, has reshaped our relationship to computers. Now he stands ready to revolutionize both neuroscience and computing in one stroke, with a new understanding of intelligence itself. Hawkins develops a powerful theory of how the human brain works, explaining why computers are not intelligent and how, based on this new theory, we can finally build intelligent machines. The brain is not a computer, but a memory system that stores experiences in a way that reflects the true structure of the world, remembering sequences of events and their nested relationships and making predictions based on those memories. It is this memory-prediction system that forms the basis of intelligence, perception, creativity, and even consciousness. In an engaging style that will captivate audiences from the merely curious to the professional scientist, Hawkins shows how a clear understanding of how the brain works will make it possible for us to build intelligent machines, in silicon, that will exceed our human ability in surprising ways. Written with acclaimed science writer Sandra Blakeslee, On Intelligence promises to completely transfigure the possibilities of the technology age. It is a landmark book in its scope and clarity.

In the burdened scenes of everyday life, our brains must select from among many competing inputs for perceptual synthesis - so that only the most relevant receive full attention and irrelevant (distracting) information is suppressed. At the same time, we must remain responsive to salient events outside our current focus of attention - and balancing these two processing modes is a fundamental task our brain constantly needs to solve. Both the physical saliency of a stimulus, as well as top-down predictions about imminent sensations crucially influence attentional selection and consequently the response to unexpected events. Research over recent decades has identified two separate brain networks involved in predictive top-down control and reorientation to unattended events (or oddball stimuli): the dorsal and ventral fronto-parietal attention systems of the human brain. Moreover, specific electrophysiological brain responses are known to characterize attentional orienting as well as the processing of deviant stimuli. However, many key questions are outstanding. What are the exact functional differences between these cortical attention systems? How are they lateralised in the two hemispheres? How do top-down and bottom-up signals interact to enable flexible attentional control? How does structural damage to one system affect the functionality of the other in brain damaged patients? Are there sensory-specific and supra-modal attentional systems in the brain? In addition to these questions, it is now accepted that brain responses are not only affected by the saliency of external stimuli, but also by our expectations about sensory inputs. How these two influences are balanced, and how predictions are formed in cortical networks, or generated on the basis of experience-dependent learning, are intriguing issues. In this Research Topic, we aim to collect innovative contributions that shed further light on the (cortical) mechanisms of attentional control in the human brain. In particular, we would like to encourage submissions that investigate the behavioural correlates, functional anatomy or electrophysiological markers of attentional selection and reorientation. Special emphasis will be given to studies investigating the context-sensitivity of these attentional processes in relation to prior expectations, trial history, contextual cues or physical saliency. We would like to encourage submissions employing different research methods (psychophysical recordings, neuroimaging techniques such as fMRI, MEG, EEG or ECoG, as well as neurostimulation methods such as TMS or tDCS) in healthy volunteers or neurological patients. Computational models and animal studies are also welcome. Finally, we also welcome submission of meta-analyses and reviews articles that provide new insights into, or conclusions about recent work in the field.

Publisher Description