Computational Methods for Translational Brain-Behavior Analysis
| Author | : Rong Chen |
| Publisher | : Frontiers Media SA |
| Total Pages | : 147 |
| Release | : 2021-06-24 |
| Genre | : Science |
| ISBN | : 2889668975 |
Computational Methods For Translational Brain Behavior Analysis
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Artificial Intelligence for Neurological Disorders
| Author | : Ajith Abraham |
| Publisher | : Academic Press |
| Total Pages | : 434 |
| Release | : 2022-09-23 |
| Genre | : Medical |
| ISBN | : 0323902782 |
Artificial Intelligence for Neurological Disorders provides a comprehensive resource of state-of-the-art approaches for AI, big data analytics and machine learning-based neurological research. The book discusses many machine learning techniques to detect neurological diseases at the cellular level, as well as other applications such as image segmentation, classification and image indexing, neural networks and image processing methods. Chapters include AI techniques for the early detection of neurological disease and deep learning applications using brain imaging methods like EEG, MEG, fMRI, fNIRS and PET for seizure prediction or neuromuscular rehabilitation. The goal of this book is to provide readers with broad coverage of these methods to encourage an even wider adoption of AI, Machine Learning and Big Data Analytics for problem-solving and stimulating neurological research and therapy advances. Discusses various AI and ML methods to apply for neurological research Explores Deep Learning techniques for brain MRI images Covers AI techniques for the early detection of neurological diseases and seizure prediction Examines cognitive therapies using AI and Deep Learning methods
Brain-inspired Machine Learning and Computation for Brain-Behavior Analysis
| Author | : Rong Chen |
| Publisher | : Frontiers Media SA |
| Total Pages | : 290 |
| Release | : 2021-04-16 |
| Genre | : Science |
| ISBN | : 2889666832 |
Big Behavioral Data Analysis : Computational Methods for the Study of Continuous Recordings Behavior
| Author | : José Espinosa-Carrasco |
| Publisher | : |
| Total Pages | : 155 |
| Release | : 2018 |
| Genre | : |
| ISBN | : |
New high-throughput behavioral systems enable the recording of continuous behavioral sequences with an unprecedented richness of signals and a deep temporal resolution. Automated systems offer neuroscience the opportunity to tackle in a new way the old question of how the brain orchestrates behavior and ultimately understand brain function itself, however, they accumulate large amounts of data leading to what is being termed Big Behavioral Data. The manipulation, analysis and contextualization of these data to obtain useful biological insights is not a trivial problem. This thesis presents Pergola, a computational framework to comprehensively analyze spontaneous longitudinal behaviors. Pergola provides access to a large set of mature genomic bioinformatics tools for the analysis and visualization of continuous behavioral recordings. I also explored multidimensional analysis techniques to help reducing the huge spatio-temporal dimensionality derived from behavioral recordings, and the high variability associated to all behavioral paradigms. This problem is addressed adapting Principal Component Analysis (PCA) for statistical inference on complex behaviors such as the recognition of learning strategies.
Translational brain-computer interfaces: From research labs to the market and back
| Author | : Davide Valeriani |
| Publisher | : Frontiers Media SA |
| Total Pages | : 136 |
| Release | : 2023-03-16 |
| Genre | : Science |
| ISBN | : 2832517641 |
Computational Techniques in Neuroscience
| Author | : Kamal Malik |
| Publisher | : CRC Press |
| Total Pages | : 186 |
| Release | : 2023-11-14 |
| Genre | : Technology & Engineering |
| ISBN | : 100099421X |
The text discusses the techniques of deep learning and machine learning in the field of neuroscience, engineering approaches to study the brain structure and dynamics, convolutional networks for fast, energy-efficient neuromorphic computing, and reinforcement learning in feedback control. It showcases case studies in neural data analysis. Features: Focuses on neuron modeling, development, and direction of neural circuits to explain perception, behavior, and biologically inspired intelligent agents for decision making Showcases important aspects such as human behavior prediction using smart technologies and understanding the modeling of nervous systems Discusses nature-inspired algorithms such as swarm intelligence, ant colony optimization, and multi-agent systems Presents information-theoretic, control-theoretic, and decision-theoretic approaches in neuroscience. Includes case studies in functional magnetic resonance imaging (fMRI) and neural data analysis This reference text addresses different applications of computational neuro-sciences using artificial intelligence, deep learning, and other machine learning techniques to fine-tune the models, thereby solving the real-life problems prominently. It will further discuss important topics such as neural rehabili-tation, brain-computer interfacing, neural control, neural system analysis, and neurobiologically inspired self-monitoring systems. It will serve as an ideal reference text for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, information technology, and biomedical engineering.
Computer Analysis of Human Behavior
| Author | : Albert Ali Salah |
| Publisher | : Springer |
| Total Pages | : 412 |
| Release | : 2013-11-30 |
| Genre | : Computers |
| ISBN | : 9781447159490 |
This book provides a broad survey of advanced pattern recognition techniques for human behavior analysis. Clearly structured, the book begins with concise coverage of the major concepts, before introducing the most frequently used techniques and algorithms in detail, and then discussing examples of real applications. Features: contains contributions from an international selection of experts in the field; presents a thorough introduction to the fundamental topics of human behavior analysis; investigates methods for activity recognition, including gait and posture analysis, hand gesture analysis, and semantics of human behavior in image sequences; provides an accessible psychological treatise on social signals for the analysis of social behaviors; discusses voice and speech analysis, combined audiovisual cues, and social interactions and group dynamics; examines applications in different research fields; each chapter concludes with review questions, a summary of the topics covered, and a glossary.
The Sage Handbook of Cognitive and Systems Neuroscience
| Author | : Gregory J. Boyle |
| Publisher | : SAGE Publications Limited |
| Total Pages | : 742 |
| Release | : 2023-11-15 |
| Genre | : Psychology |
| ISBN | : 152961662X |
Cognitive neuroscience is the interdisciplinary study of how cognitive and intellectual functions are processed and represented within the brain, which is critical to building understanding of core psychological and behavioural processes such as learning, memory, behaviour, perception, and consciousness. Understanding these processes not only offers relevant fundamental insights into brain-behavioural relations, but may also lead to actionable knowledge that can be applied in the clinical treatment of patients with various brain-related disabilities. This Handbook examines complex cognitive systems through the lens of neuroscience, as well as providing an overview of development and applications within cognitive and systems neuroscience research and beyond. Containing 35 original, state of the art contributions from leading experts in the field, this Handbook is essential reading for researchers and students of cognitive psychology, as well as scholars across the fields of neuroscientific, behavioural and health sciences. Part 1: Attention, Learning and Memory Part 2: Language and Communication Part 3: Emotion and Motivation Part 4: Social Cognition Part 5: Cognitive Control and Decision Making Part 6: Intelligence
Biosignal Processing and Computational Methods to Enhance Sensory Motor Neuroprosthetics
| Author | : Mitsuhiro Hayashibe |
| Publisher | : Frontiers Media SA |
| Total Pages | : 230 |
| Release | : 2016-01-22 |
| Genre | : Biosignal processing |
| ISBN | : 2889197182 |
Though there have been many developments in sensory/motor prosthetics, they have not yet reached the level of standard and worldwide use like pacemakers and cochlear implants. One challenging issue in motor prosthetics is the large variety of patient situations, which depending on the type of neurological disorder. To improve neuroprosthetic performance beyond the current limited use of such systems, robust bio-signal processing and model-based control involving actual sensory motor state (with biosignal feedback) would bring about new modalities and applications, and could be a breakthrough toward adaptive neuroprosthetics. Recent advances of Brain Computer Interfaces (BCI) now enable patients to transmit their intention of movement. However, the functionality and controllability of motor prosthetics itself can be further improved to take advantage of BCI interfaces. In this Research Topic we welcome contribution of original research articles, computational and experimental studies, review articles, and methodological advances related to biosignal processing that may enhance the functionality of sensory motor neuroprosthetics. The scope of this topic includes, but is not limited to, studies aimed at enhancing: 1) computational biosignal processing in EMG (Electromyography), EEG (Electroencephalography), and other modalities of biofeedback information; 2) the computational method in modeling and control of sensory motor neuroprosthetics; 3) the systematic functionality aiming to provide solutions for specific pathological movement disorders; 4) human interfaces such as BCI - but in the case of BCI study, manuscripts should be experimental studies which are applied to sensory/motor neuroprosthetics in patients with motor disabilities.
Behavior Analysis and Learning
| Author | : W. David Pierce |
| Publisher | : Taylor & Francis |
| Total Pages | : 622 |
| Release | : 2017-06-14 |
| Genre | : Psychology |
| ISBN | : 135177980X |
Using a consistent Skinnerian perspective, Behavior Analysis and Learning: A Biobehavioral Approach, Sixth Edition provides an advanced introduction to the principles of behavior analysis and learned behaviors, covering a full range of principles from basic respondent and operant conditioning through applied behavior analysis into cultural design. The textbook uses Darwinian, neurophysiological, and biological theories and research to inform B. F. Skinner’s philosophy of radical behaviorism. The sixth edition expands focus on neurophysiological mechanisms and their relation to the experimental analysis of behavior, providing updated studies and references to reflect current expansions and changes in the field of behavior analysis. By bringing together ideas from behavior analysis, neuroscience, and epigenetics under a selectionist framework, this textbook facilitates understanding of behavior at environmental, genetic, and neurophysiological levels. This "grand synthesis" of behavior, neuroscience, and neurobiology roots behavior firmly in biology. The book includes special sections, "New Directions," "Focus On," "Note On," "On the Applied Side," and "Advanced Section," which enhance student learning and provide greater insight on specific topics. This book is a valuable resource for advanced undergraduate and graduate students in psychology or other behavior-based disciplines, especially behavioral neuroscience. For additional resources to use alongside the textbook, consult the Companion Website at www.routledge.com/cw/pierce.
