This book presents a flexible Bayesian framework for combining neural and cognitive models. Traditionally, studies in cognition and cognitive sciences have been done by either observing behavior (e.g., response times, percentage correct, etc.) or by observing neural activity (e.g., the BOLD response). These two types of observations have traditionally supported two separate lines of study, which are led by two different cognitive modelers. Joining neuroimaging and computational modeling in a single hierarchical framework allows the neural data to influence the parameters of the cognitive model and allows behavioral data to constrain the neural model. This Bayesian approach can be used to reveal interactions between behavioral and neural parameters, and ultimately, between neural activity and cognitive mechanisms. Chapters demonstrate the utility of this Bayesian model with a variety of applications, and feature a tutorial chapter where the methods can be applied to an example problem. The book also discusses other joint modeling approaches and future directions. Joint Models of Neural and Behavioral Data will be of interest to advanced graduate students and postdoctoral candidates in an academic setting as well as researchers in the fields of cognitive psychology and neuroscience.
Rigorously researched and accessibly written, Cognitive Psychology: A Student’s Handbook is widely regarded as the leading undergraduate textbook in the field. The book is clearly organised, and offers comprehensive coverage of all the key areas of cognitive psychology. With a strong focus on considering human cognition in context, the book has been designed to help students develop a thorough understanding of the fundamentals of cognitive psychology, providing them with detailed knowledge of the very latest advances in the field. New to this edition: Thoroughly revised throughout to include the latest research and developments in the field Extended coverage of cognitive neuroscience Additional content on computational cognitive science New and updated case studies demonstrating real life applications of cognitive psychology Fully updated companion website Cognitive Psychology: A Student’s Handbook will be essential reading for all undergraduate students of psychology. Those taking courses in computer science, education, linguistics, physiology, and medicine will also find it an invaluable resource.
Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches. Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research. Please visit the book companion website at https://www.cs.waikato.ac.nz/~ml/weka/book.html. It contains - Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book - Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book - Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc. - Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects - Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods - Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface - Includes open-access online courses that introduce practical applications of the material in the book
The advent of increasingly large consumer collections of audio (e.g., iTunes), imagery (e.g., Flickr), and video (e.g., YouTube) is driving a need not only for multimedia retrieval but also information extraction from and across media. Furthermore, industrial and government collections fuel requirements for stock media access, media preservation, broadcast news retrieval, identity management, and video surveillance. While significant advances have been made in language processing for information extraction from unstructured multilingual text and extraction of objects from imagery and video, these advances have been explored in largely independent research communities who have addressed extracting information from single media (e.g., text, imagery, audio). And yet users need to search for concepts across individual media, author multimedia artifacts, and perform multimedia analysis in many domains. This collection is intended to serve several purposes, including reporting the current state of the art, stimulating novel research, and encouraging cross-fertilization of distinct research disciplines. The collection and integration of a common base of intellectual material will provide an invaluable service from which to teach a future generation of cross disciplinary media scientists and engineers.
The book explores the claim that English local government exists in one of the most centralised relationships with national government. Such a position fundamentally undermines any notion of local self-government and makes the term ‘government’ in local government a misnomer. The book will examine how the erosion of the autonomy, powers, roles, functions and responsibilities of English local government came about, the arguments of centralisers and localisers to support their view of the constitutional status of local government, and its overall role in the government of England. The book offers an antidote to the onward march of centralisation by offering a new vision of local government which emphasises both ‘local’ and ‘government’.
Introduces the main algorithms and ideas that underpin machine learning techniques and applications Keeps mathematical prerequisites to a minimum, providing mathematical explanations in comment boxes and highlighting important equations Covers modern machine learning research and techniques Includes three new chapters on Markov Chain Monte Carlo techniques, Classification and Regression with Gaussian Processes, and Dirichlet Process models Offers Python, R, and MATLAB code on accompanying website: http://www.dcs.gla.ac.uk/~srogers/firstcourseml/
Physics of Biological Action and Perception helps researchers interested in exploring biological motor control from a physics or alternative viewpoint perspective. The book introduces the idea of parametric control as a distinguishing feature of living systems. Sections cover how the CNS creates stable percepts based on fuzzy and continuously changing signals from numerous receptors and the variable processes related to ongoing actions. The author also develops the idea of control with referent coordinates to stability of salient variables in fields typically united under the label of "cognition." Examples of this include communication (how the gist of a message is preserved despite variability of phrases), thought processes (how one can solve a mental problem via different logical routes), and playing chess (how one selects an optimal move given a position on the board). The book is written for researchers, instructors, clinicians and other professionals in all the fields related to biological movement and perception. - Presents a unifying theory of motor control based on physics - Encompasses action, perception and cognition - Discusses referent coordinates, kinesthetic perception and stability of actions - Identifies the importance of the CNS over computational brain function
This book aims to synthesize different directions in knowledge studies into a unified theory of knowledge and knowledge processes. It explicates important relations between knowledge and information. It provides the readers with understanding of the essence and structure of knowledge, explicating operations and process that are based on knowledge and vital for society.The book also highlights how the theory of knowledge paves the way for more advanced design and utilization of computers and networks.
This book presents a flexible Bayesian framework for combining neural and cognitive models. Traditionally, studies in cognition and cognitive sciences have been done by either observing behavior (e.g., response times, percentage correct, etc.) or by observing neural activity (e.g., the BOLD response). These two types of observations have traditionally supported two separate lines of study, which are led by two different cognitive modelers. Joining neuroimaging and computational modeling in a single hierarchical framework allows the neural data to influence the parameters of the cognitive model and allows behavioral data to constrain the neural model. This Bayesian approach can be used to reveal interactions between behavioral and neural parameters, and ultimately, between neural activity and cognitive mechanisms. Chapters demonstrate the utility of this Bayesian model with a variety of applications, and feature a tutorial chapter where the methods can be applied to an example problem. The book also discusses other joint modeling approaches and future directions. Joint Models of Neural and Behavioral Data will be of interest to advanced graduate students and postdoctoral candidates in an academic setting as well as researchers in the fields of cognitive psychology and neuroscience.
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