In order to understand how the brain works, it is essential to know what is computed by different brain systems, and how those computations are performed.
Brain Computations: What and How elucidates what is computed in different brain systems and describes current computational approaches and models of how each of these brain systems computes.
This approach has enormous potential for helping us understand ourselves better in health. Potential applications of this understanding are to the treatment of the brain in disease, as well as to artificial intelligence, which will benefit from knowledge of how the brain performs many of its extraordinarily impressive functions.
Pioneering in its approach, Brain Computations: What and How will be of interest to all scientists interested in brain function and how the brain works, whether they are from neuroscience, or from medical sciences including neurology and psychiatry, or from the area of computational science including machine learning and artificial intelligence, or from areas such as theoretical physics.
Rezensionen / Stimmen
This neuronal network approach stands in contrast to connectionist approaches and also focuses exclusively on higher primate and human modeling. Helpful chapter highlights and several practical appendixes are provided, and the bibliography is excellent. * H. Storl, Augustana College (IL), CHOICE * This "bottom-up" approach to data-driven neuroscientific discovery serves as the perfect primer for those who study brain sciences, cognitive sciences, artificial intelligence, neuro-engineering, neuropsychology, and empirically oriented philosophy. * H. Storl, CHOICE * Brain Computations is the first complete attempt to summarize our current knowledge about computation in the brain, at a level a graduate can understand. ... This is a biologically grounded, full systems neuroscience textbook-which makes it one of a kind. ... Hippocampal memories, action selection in the striatum, orbitofrontal reward representations, emotion in the limbic system, cerebellar motor control, parietal spatial coordinate transforms, place fields, and posterior visual object recognition-all these can emerge from relatively simple rules. This is Rolls' unspoken but substantial grand unifying theory. (full review https://doi.org/10.1093/brain/awab477) * Brain * He concludes with 13 principles about how information in encoded in neural networks. This is almost the Holy Grail of neuroscience, the language of neurons, what makes us what we are. Yet, these ideas are presented in a simple unassuming scientific language ... * Nikolaos C. Aggelopoulos, Neurosurgery *
Sprache
Verlagsort
Zielgruppe
Produkt-Hinweis
Fadenheftung
Gewebe-Einband
Maße
Höhe: 249 mm
Breite: 175 mm
Dicke: 43 mm
Gewicht
ISBN-13
978-0-19-887110-1 (9780198871101)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Professor Edmund T. Rolls performs full-time research at the Oxford Centre for Computational Neuroscience, and at the University of Warwick, and has performed research and teaching for many years as Professor of Experimental Psychology at the University of Oxford, and as Fellow and Tutor of Corpus Christi College, Oxford. His research links computational neuroscience approaches to neurophysiological, human functional neuroimaging and neuropsychological studies in order to provide a fundamental basis for understanding human brain function and its disorders.
Autor*in
Professor in the Department of Computer ScienceProfessor in the Department of Computer Science, University of Warwick and Oxford Centre for Computational Neuroscience
1: Introduction
2: The ventral visual system
3: The dorsal visual system
4: The taste and flavour system
5: The olfactory system
6: The somatosensory system
7: The auditory system
8: The temporal cortex
9: The hippocampus, memory, and spatial function
10: The parietal cortex, spatial functions, and navigation
11: The orbitofrontal cortex, amygdala, reward value, and emotion
12: The cingulate cortex
13: The motor cortical areas
14: The basal ganglia
15: Cerebellar cortex
16: The prefrontal cortex
17: Language and syntax in the brain
18: Noise in the cortex, stability, psychiatric disease, and aging
19: Computations by different types of brain, and by artificial neural systems
Appendix A: Introduction to linear algebra for neural networks
Appendix B: Neuronal network models
Appendix C: Information theory, and neuronal encoding
Appendix D: Simulation software for neuronal network models, and information analysis of neuronal encoding
