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1 online resource.
  • Meeting Emerging Challenges and Opportunities in Psychiatry Through Computational Neuroscience Section I. Applying Circuit Modeling to Understand Psychiatric Symptoms 1. Cortical Circuit Models in Psychiatry: Linking Disrupted Excitation-Inhibition Balance to Cognitive Deficits Associated with Schizophrenia 2. Serotonergic Modulation of Cognition in Prefrontal Cortical Circuits in Major Depression 3. Dopaminergic Neurons in the Ventral Tegmental Area and their Dysregulation in Nicotine Addiction Section II. Modeling Neural System Disruptions in Psychiatric Illness 4. Computational Models of Dysconnectivity in Large-Scale Resting-State Networks 5. Dynamic Causal Modelling and its Application to Psychiatric Disorders 6. Systems Level Modeling of Cognitive Control in Psychiatric Disorders: A focus on schizophrenia 7. Computational Psychiatry: Mathematical Modeling of Mental Illness Section III: Characterizing Complex Psychiatric Symptoms via Mathematical Models 8. A Case Study in Computational Psychiatry: Addiction as Failure Modes of the Decision-Making System 9. Modeling Negative Symptoms in Schizophrenia 10. Bayesian Approaches to Learning and Decision Making 11. Computational Phenotypes Revealed by Interactive Economic Games.
  • (source: Nielsen Book Data)9780128098257 20171017
Computational Psychiatry: Mathematical Modeling of Mental Illness is the first systematic effort to bring together leading scholars in the fields of psychiatry and computational neuroscience who have conducted the most impactful research and scholarship in this area. It includes an introduction outlining the challenges and opportunities facing the field of psychiatry that is followed by a detailed treatment of computational methods used in the service of understanding neuropsychiatric symptoms, improving diagnosis and guiding treatments. This book provides a vital resource for the clinical neuroscience community with an in-depth treatment of various computational neuroscience approaches geared towards understanding psychiatric phenomena. Its most valuable feature is a comprehensive survey of work from leaders in this field.
(source: Nielsen Book Data)9780128098257 20171017
1 online resource ( 272 pages) :
  • Cover; Half Title; Title; Copyright; Contents; Introduction; 1. Interferences: Philosophy, Science, Art, and Capitalism; PART I: What Can Be Done to a Brain?; 2. Neurolabor: Digital Work and Consumption; 3. Control and Dystopia; PART II: What Can a Brain Do?; 4. Sense Making and Assemblages; 5. Relationality, Care, and the Rhythmic Brain; CODA: Taking Care of the Not-Self; Acknowledgments; Notes; Index; A; B; C; D; E; F; G; H; I; J; K; L; M; N; O; P; Q; R; S; T; U; V; W; Y; Z.
1 online resource.
EBSCOhost Access limited to 1 user
1 online resource (213 p.) : ill. (some col.)
"Our age is characterized by global access to information, places and cultures: we can gain more and more knowledge about "the others": other people and their cultures by "indirect knowledge" — learning about them via the global information net assisted by electronic and other high-tech communication channels, as well as by "direct knowledge": personally visiting various parts of the world and meeting local people in their own natural and social environments. East and West, two major worlds of aspirations, cultures, world-views, theoretical and practical approaches to life and death, have come closer by personal experiences of both Westerners and Easterners. But do we really understand the similarities and differences between the cultural-cognitive-behavioural-emotional patterns of the East and the West, with special regard to their neurobiological underpinnings in the human brain? The contents of this book focus on cultural patterns and cognitive patterns in the East and West, with special regard to those patterns which are determined by our natural-genetic endownments in contrast to those patterns which are influenced by our cultural ("East–West") influences, and within this context a unique flavour is given to the "good life" aspects of adapting to this global community."--Publisher's website.
1 online resource.
  • 1. How to Build a human brain 2. Time to start the day! How our Senses Help Us Wake Up! 3. 6:35 AM Time to Run! I run so I don't kill people. 4. 9:00 AM Lions and Tigers and Bears, oh my! Oh wait, no, it's just work! 5. 10:00 AM - Staff Meeting about the new thing and how we have to learn it to do our job! 6. 11:30 AM Hanger: (n) hunger induced anger. 7. 3:30 PM My Mood Ring is Blue Right Now. 8. 10:00 PM Counting Sheep.
  • (source: Nielsen Book Data)9780128110164 20170710
Neuroscience Basics: A Guide to the Brain's Involvement in Everyday Activities examines how our brain works in everyday activities like sleeping, eating, love, and exercise. Many want to better understand how the brain works, but the terminology and jargon of books can be overwhelming. The book covers the basics taught in an introductory neurobiology course designed for anyone new to the neuroscience field, including non-neuroscientists. While each of the chapters explore the brain in a normal state, Neuroscience Basics also discusses disruptions of the normal state-psychosis, Alzheimer's, Parkinson's, autism, learning disorders, etc. This book breaks down the topics into language that is more accessible while making the neuroscience topics fun and relevant.
(source: Nielsen Book Data)9780128110164 20170710
1 online resource.
  • Part 1. Cocaine, Behavior, and Psychopathological EffectsPart 2. Effects of Cocaine Misuse on Neurological Function and FeaturesPart 3. Pharmacology and NeuropharmacologyPart 4. Withdrawal and Abstinence Part 5. Cocaine as a Component of Dual-Use and Polydrug Use or Poly AddictionsPart 6. Cellular Effects and Molecular Biology of Cocaine Part 7. Treatments for Cocaine Misuse and Dependency and Related Features.
  • (source: Nielsen Book Data)9780128037508 20170710
The Neuroscience of Cocaine: Mechanisms and Treatment explores the complex effects of this drug, addressing the neurobiology behind cocaine use and the psychosocial and behavioral factors that impact cocaine use and abuse. This book provides researchers with an up-to-date understanding of the mechanisms behind cocaine use, and aids them in deriving new pharmacological compounds and therapeutic regimens to treat dependency and withdrawal symptoms. Cocaine is one of the most highly abused illicit drugs worldwide and is frequently associated with other forms of drug addiction and misuse, but researchers are still struggling to understand cocaine's neuropharmacological profile and the mechanisms of its effects and manifestations at the cognitive level. Cessation of cocaine use can lead to numerous adverse withdrawal conditions, from the cellular and molecular level to the behavioral level of the individual user. Written by worldwide experts in cocaine addiction, this book assists neuroscientists and other addiction researchers in unraveling the many complex facets of cocaine use and abuse.
(source: Nielsen Book Data)9780128037508 20170710
VIII, 237 p. : online resource. Digital: text file; PDF.
  • Determining and Understanding N-H Bond Strengths in Synthetic Nitrogen Fixation Cycles.- Dinitrogen Fixation by Transition Metal Hydride Complexes.- Reactivity of Group 5 Element Dinitrogen Complexes and N2-Derived Nitrides.- Functionalization of N2 by Mid to Late Transition Metals via N-N Bond Cleavage.- Synthetic Nitrogen Fixation with Mononuclear Molybdenum(0) Phosphine Complexes: Occupying the trans-Position of Coordinated N2.- Catalytic Nitrogen Fixation Using Molybdenum-Dinitrogen Complexes as Catalysts.- Computational Approach to Nitrogen Fixation on Molybdenum-Dinitrogen Complexes.- Sulfur-Supported Iron Complexes for Understanding N2 Reduction.- Catalytic Transformations of Molecular Dinitrogen by Iron and Cobalt-Dinitrogen Complexes as Catalysts.
  • (source: Nielsen Book Data)9783319577135 20171211
This volume presents a review of recent developments in nitrogen fixation using transition metal-dinitrogen complexes in the last decade. The authors are international experts in the corresponding field and each chapter discusses their latest achievements in the preparation of various transition metal-dinitrogen complexes and their reactivity. This volume will be helpful to researchers, teachers, and students who are interested in innovative and sustainable chemistry.
(source: Nielsen Book Data)9783319577135 20171211
1 online resource.
  • Frontmatter
  • Preface
  • Contents
  • List of Figures
  • 1. Introduction
  • Part I: Stage Setting
  • 2. Braining Up Psychology
  • 3. The Life of Mechanisms
  • 4. The Interventionist View
  • 5. Intermezzo: What's at Stake?
  • Part II: Puzzles
  • 6. The Unsuccessful Marriage
  • 7. Causation vs. Constitution
  • 8. Beyond Mutual Manipulability
  • 9. Interventionism's Short-Sightedness
  • 10. Intermezzo: Well Then?
  • Part III: Shopping for Solutions
  • 11. Fixing Interventionism
  • 12. Mere Interactions
  • 13. Excursus: A Perspectival View
  • 14. Mere Interactions at Work: A Catalog of Experiments
  • 15. Conclusions
  • References
  • Key Terms
  • Index
1 online resource (205 p.) : ill. (some col.).
"This book was developed to help students and researchers in the fields of economics, finance, law and other social science areas to understand and apply neuroscience. With the use of neuroscience technologies, it is now possible to understand how people make decisions in practice, using friendly and ecological experimental setups. The first half of the book studies the decision-making process and explains how the brain is organized. It presents the brain as a distributed processing system, shows how to record brain activities, and how to combine neurosciences and statistical tools to design experiments. In the last chapters, experiments on stock market decision, dilemma judgment, vote decision and understanding of media propaganda are described and discussed."--Publisher's website.
1 online resource (290 pages) : illustrations.
  • Perceptual processes and multisensoriality: understanding multimodal art from neuroscientific concepts / Rosangella Leote
  • Inside/out: looking back into the future / Maria Manuela Lopes
  • Cells, organisms, and the living brain as new media for art: a pursuit in art research / Marta Menezes
  • Neuroesthetics: perspectives and reflections / Fernando Fogliano, Hosana Celeste Oliveira
  • A study on the interface between arts and sciences: neuroesthetics and cognitive neuroscience of art / Alexandre Siqueira de Freitas
  • Neuroaesthetics: insights into the aesthetic experience of visual art / Ana Teresa Contier, Laila Torres
  • Understanding the Interdisciplinary Meaning of beauty to neuroscience: designing beauty to neuroscience / Bruno H.S. Araujo, Ibrahim Elias Nasseh
  • Design and emotion: contributions to the emotional design / Paula da Cruz Landim
  • Qualia and extended field of contemporary design / Leila Reinert
  • Conceptual experiments in automated designing / Petr Ivanovich Sosnin
  • Can we induce a cognitive representation of a prosthetic arm by means of crossmodal stimuli? / Mateus Franco [and 3 others]
  • Cognitive processes in fashion design: designing of modelling projects for the visually handicapped / Geraldo Coelho Lima Júnior
  • Cognitive processes in the reception of interactive short film script: mental representations by audiovisual specialists / Patricia Bieging, Raul Inácio Busarello
  • Understanding how the mind works: the neuroscience of perception, behavior, and creativity / Claudia Feitosa-Santana.
Recent advances in neuroscience suggest that the human brain is particularly well-suited to design things: concepts, tools, languages and places. Current research even indicates that the human brain may indeed have evolved to be creative, to imagine new ideas, to put them into practice, and to critically analyze their results. Projective Processes and Neuroscience in Art and Design provides a forum for discussion relating to the intersection of projective processes and cognitive neuroscience. This innovative publication offers a neuroscientific perspective on the roles and responsibilities of designers, artists, and architects, with relation to the products they design. Expanding on current research in the areas of sensor-perception, cognition, creativity, and behavioral processes, this publication is designed for use by researchers, professionals, and graduate-level students working and studying the fields of design, art, architecture, neuroscience, and computer science.
(source: Nielsen Book Data)9781522505105 20161213
1 PDF (xxv, 215 pages).
  • Part I. Introduction to space-time computing and temporal neural networks
  • 1. Introduction
  • 1.1 Basics of neuron operation
  • 1.2 Space-time communication and computation
  • 1.2.1 Communication
  • 1.2.2 Computation
  • 1.2.3 Discussion
  • 1.3 Background: neural network models
  • 1.3.1 Rate coding
  • 1.3.2 Temporal coding
  • 1.3.3 Rate processing
  • 1.3.4 Spike processing
  • 1.3.5 Summary and taxonomy
  • 1.4 Background: machine learning
  • 1.5 Approach: interaction of computer engineering and neuroscience
  • 1.6 Bottom-up analysis: a guiding analogy
  • 1.7 Overview
  • 2. Space-time computing
  • 2.1 Definition of terms
  • 2.2 Feedforward computing networks
  • 2.3 General TNN model
  • 2.4 Space-time computing systems
  • 2.5 Implications of invariance
  • 2.6 TNN system architecture
  • 2.6.1 Training
  • 2.6.2 Computation (evaluation)
  • 2.6.3 Encoding
  • 2.6.4 Decoding
  • 2.7 Summary: meta-architecture
  • 2.7.1 Simulation
  • 2.7.2 Implied functions
  • 2.8 Special case: feedforward McCulloch-Pitts networks
  • 2.9 Race logic
  • 3. Biological overview
  • 3.1 Overall brain structure (very brief )
  • 3.2 Neurons
  • 3.2.1 Synapses
  • 3.2.2 Synaptic plasticity
  • 3.2.3 Frequency-current relationship
  • 3.2.4 Inhibition
  • 3.3 Hierarchy and columnar organization
  • 3.3.1 Neurons
  • 3.3.2 Columns (micro-columns)
  • 3.3.3 Macro-columns
  • 3.3.4 Regions
  • 3.3.5 Lobes
  • 3.3.6 Uniformity
  • 3.4 Inter-neuron connections
  • 3.4.1 Path distances
  • 3.4.2 Propagation velocities
  • 3.4.3 Transmission delays
  • 3.4.4 Numbers of connections
  • 3.4.5 Attenuation of excitatory responses
  • 3.4.6 Connections summary
  • 3.5 Sensory processing
  • 3.5.1 Receptive fields
  • 3.5.2 Saccades and whisks
  • 3.5.3 Vision pathway
  • 3.5.4 Waves of spikes
  • 3.5.5 Feedforward processing path
  • 3.5.6 Precision
  • 3.5.7 Information content
  • 3.5.8 Neural processing
  • 3.6 Oscillations
  • 3.6.1 Theta oscillations
  • 3.6.2 Gamma oscillations
  • Part II. Modeling temporal neural networks
  • 4. Connecting TNNs with biology
  • 4.1 Communication via voltage spikes
  • 4.2 Columns and spike bundles
  • 4.3 Spike synchronization
  • 4.3.1 Aperiodic synchronization: saccades, whisks, and sniffs
  • 4.3.2 Periodic synchronization
  • 4.4 First spikes carry information
  • 4.5 Feedforward processing
  • 4.6 Simplifications summary
  • 4.7 Plasticity and training
  • 4.8 Fault tolerance and temporal stability
  • 4.8.1 Interwoven fault tolerance
  • 4.8.2 Temporal stability
  • 4.8.3 Noise (or lack thereof )
  • 4.9 Discussion: reconciling biological complexity with model simplicity
  • 4.10 Prototype architecture overview
  • 5. Neuron modeling
  • 5.1 Basic models
  • 5.1.1 Hodgkin Huxley neuron model
  • 5.1.2 Derivation of the leaky integrate and fire (LIF) model
  • 5.1.3 Spike response model (SRM0)
  • 5.2 Modeling synaptic connections
  • 5.3 Excitatory neuron implementation
  • 5.4 The menagerie of LIF neurons
  • 5.4.1 Synaptic conductance model
  • 5.4.2 Biexponential SRM0 model
  • 5.4.3 Single stage SRM0
  • 5.4.4 Linear leak integrate and fire (LLIF)
  • 5.5 Other neuron models
  • 5.5.1 Alpha function
  • 5.5.2 Quadratic integrate-and-fire
  • 5.6 Synaptic plasticity and training
  • 6. Computing with excitatory neurons
  • 6.1 Single neuron clustering
  • 6.1.1 Definitions
  • 6.1.2 Excitatory neuron function, approximate description
  • 6.1.3 Looking ahead
  • 6.2 Spike coding
  • 6.2.1 Volleys
  • 6.2.2 Nonlinear mappings
  • 6.2.3 Distance functions
  • 6.3 Prior work: radial basis function (RBF) neurons
  • 6.4 Excitatory neuron I: training mode
  • 6.4.1 Modeling excitatory response functions
  • 6.4.2 Training set
  • 6.4.3 STDP update rule
  • 6.4.4 Weight stabilization
  • 6.5 Excitatory neuron I: compound response functions
  • 6.6 Excitatory neuron model II
  • 6.6.1 Neuron model derivation
  • 6.6.2 Training mode
  • 6.6.3 Evaluation mode
  • 6.7 Attenuation of excitatory responses
  • 6.8 Threshold detection
  • 6.9 Excitatory neuron model II summary
  • 7. System architecture
  • 7.1 Overview
  • 7.2 Interconnection structure
  • 7.3 Input encoding
  • 7.4 Excitatory column operation
  • 7.4.1 Evaluation
  • 7.4.2 Training
  • 7.4.3 Unsupervised synaptic weight training
  • 7.4.4 Supervised weight training
  • 7.5 Inhibition
  • 7.5.1 Feedback inhibition
  • 7.5.2 Lateral inhibition
  • 7.5.3 Feedforward inhibition
  • 7.6 Volley decoding and analysis
  • 7.6.1 Temporal flattening
  • 7.6.2 Decoding to estimate clustering quality
  • 7.6.3 Decoding for classification
  • 7.7 Training inhibition
  • 7.7.1 FFI: establishing tF and kF
  • 7.7.2 LI: establishing tL and kL
  • 7.7.3 Excitatory neuron training in the presence of inhibition
  • Part III: extended design study: clustering the MNIST dataset
  • 8. Simulator implementation
  • 8.1 Simulator overview
  • 8.2 Inter-unit communication
  • 8.3 Simulating time
  • 8.4 Synaptic weight training
  • 8.5 Evaluation
  • 8.5.1 EC block
  • 8.5.2 IC block
  • 8.5.3 VA block
  • 8.6 Design methodology
  • 9. Clustering the MNIST dataset
  • 9.1 MNIST workload
  • 9.2 Prototype clustering architecture
  • 9.3 OnOff encoding
  • 9.4 Intra-CC network
  • 9.5 Excitatory column (EC)
  • 9.6 Lateral inhibition
  • 9.7 144 RFs
  • 9.8 Feedforward inhibition
  • 9.9 Layer 1 result summary
  • 9.10 Related work
  • 9.11 Considering layer 2
  • 10. Summary and conclusions
  • References
  • Author biography.
Understanding and implementing the brain's computational paradigm is the one true grand challenge facing computer researchers. Not only are the brain's computational capabilities far beyond those of conventional computers, its energy efficiency is truly remarkable. This book, written from the perspective of a computer designer and targeted at computer researchers, is intended to give both background and lay out a course of action for studying the brain's computational paradigm. It contains a mix of concepts and ideas drawn from computational neuroscience, combined with those of the author. As background, relevant biological features are described in terms of their computational and communication properties. The brain's neocortex is constructed of massively interconnected neurons that compute and communicate via voltage spikes, and a strong argument can be made that precise spike timing is an essential element of the paradigm. Drawing from the biological features, a mathematics-based computational paradigm is constructed. The key feature is spiking neurons that perform communication and processing in space-time, with emphasis on time. In these paradigms, time is used as a freely available resource for both communication and computation. Neuron models are first discussed in general, and one is chosen for detailed development. Using the model, single-neuron computation is first explored. Neuron inputs are encoded as spike patterns, and the neuron is trained to identify input pattern similarities. Individual neurons are building blocks for constructing larger ensembles, referred to as "columns". These columns are trained in an unsupervised manner and operate collectively to perform the basic cognitive function of pattern clustering. Similar input patterns are mapped to a much smaller set of similar output patterns, thereby dividing the input patterns into identifiable clusters. Larger cognitive systems are formed by combining columns into a hierarchical architecture. These higher level architectures are the subject of ongoing study, and progress to date is described in detail in later chapters. Simulation plays a major role in model development, and the simulation infrastructure developed by the author is described.
Sound recording
1 sound file : digital Digital: audio file.
Business Library
1 online resource (V, 239 p. 96 ill., 79 illus. in color.) : online resource. Digital: text file; PDF.
  • Spinal dural arteriovenous fistula - A review.- Intracranial Meningiomas-a 30 year experience and literature review.- Arteries and veins of the Sylvian fissure and Insula.- Hearing outcomes after stereotactic radiosurgery for vestibular schwannomas: Mechanism of hearing loss and how to preserve hearing.- Merits and Limits of various Tractography Techniques for the Un-initiated.- ALA guided surgery of high grade gliomas.- Clinical relevance of prognostic and predictive molecular markers in gliomas.
  • (source: Nielsen Book Data)9783319213583 20160619
This volume reviews standard treatments for spinal dural arteriovenous fistulas, examining the anatomy of arteries and veins of the sylvian fissure, as well as microsurgical advances and the development of modern therapeutic strategies in intracranial meningiomas. The advances section presents a strategy for minimizing hearing loss after stereotactic radiosurgery for vestibular schwannomas, as well as a description of the mode of action and biology of ALA, including its interaction with tumor cells and the limits of this method. A dedicated chapter addresses the essential question of the limits (and merits) of various tractography techniques and of their importance for non-specialists, who may be tempted to use them uncritically. A further chapter examines molecular markers, which have become standard in neuropathological reports on intracranial tumors, reviewing the prognostic and predictive value of these modern molecular markers in gliomas. Additional chapters round out the coverage, offering a comprehensive overview of standard and advanced techniques.
(source: Nielsen Book Data)9783319213583 20160619
The cleaned bench testing reconstructions for the gold166 datasets have been put online at github https://github.com/BigNeuron/Events-and-News/wiki/BigNeuron-Even ts-and-News https://github.com/BigNeuron/Data/releases/tag/gold166_bt_v1.0 The respective image datasets were released a while ago from other sites (major pointer is available at github as well https://github.com/BigNeuron/Data/releases/tag/Gold166_v1 but since the files were big, the actual downloading was distributed at 3 continents separately)
1 online resource (xxii, 585 pages) : illustrations (some color). Digital: text file; PDF.
  • Part I. Introduction to Fractal Geometry and its Applications to Neurosciences
  • The Fractal Geometry of the Brain: An Overview
  • 2. Box-Counting Fractal Analysis: A Primer for the Clinician
  • Tenets and Methods of Fractal Analysis (1/f noise)
  • 4. Tenets, Methods and Applications of Multifractal Analysis in Neurosciences
  • Part II. Fractals in Neuroanatomy and Basic Neurosciences
  • Fractals in Neuroanatomy and Basic Neurosciences: An Overview
  • Morphology and Fractal-Based Classifications of Neurons and Microglia
  • The Morphology of the Brain Neurons: Box-counting Method in Quantitative Analysis of 2D Image
  • Neuronal Fractal Dynamics
  • Does a Self-Similarity Logic Shape the Organization of the Nervous System?
  • Fractality of Cranial Sutures
  • The Fractal Geometry of the Human Brain: An Evolutionary Perspective
  • Part III. Fractals in Clinical Neurosciences
  • Fractal Analysis in Clinical Neurosciences: An Overview
  • Fractal Analysis in Neurological Diseases
  • Fractal Dimension Studies of the Brain Shape in Aging and Neurodegenerative Diseases
  • Fractal Analysis in Neurodegenerative Diseases
  • Fractal Analysis of the Cerebrovascular System Physiopathology
  • Fractal and Chaos in the Hemodynamics of Intracranial Aneurysms
  • Fractal-based Analysis of Arteriovenous Malformations (AVMs)
  • Fractals in Neuroimaging
  • Computational Fractal-Based Analysis of MR Susceptibility Weighted Imaging (SWI) in Neuro-oncology and neurotraumatology
  • Texture Estimation for Abnormal Tissue Segmentation in Brain MRI
  • Tumor Growth in the Brain: Complexity and Fractality
  • Histological Fractal-based Classification of Brain Tumors
  • Computational Fractal-based Analysis of the Brain Tumors Microvascular Networks
  • Fractal analysis of electroencephalographic time-series (EEG-signals)
  • On Multiscaling of Parkinsonian Rest Tremor Signals and Their Classification
  • Fractals and Electromyograms
  • Fractal analysis in Neuro-ophthalmology
  • Fractals in Affective and Anxiety Disorders
  • Fractal Fluency: An Intimate Relationship Between the Brain and Processing of Fractal Stimuli
  • Part IV. Computational Fractal-Based Neurosciences
  • Computational Fractal-based Neurosciences: An Overview
  • ImageJ in Computational Fractal-based Neuroscience: Pattern Extraction and Translational Research
  • Fractal Analysis in MATLAB: A Tutorial for Neuroscientists
  • Methodology to Increase the Computational Speed to Obtain the Fractal Dimension Using GPU Programming
  • Fractal Electronics as a Generic Interface to Neurons
  • Fractal Geometry meets Computational Intelligence: Future Perspectives.
Reviews the most intriguing applications of fractal analysis in neuroscience with a focus on current and future potential, limits, advantages, and disadvantages. Will bring an understanding of fractals to clinicians and researchers also if they do not have a mathematical background, and will serve as a good tool for teaching the translational applications of computational models to students and scholars of different disciplines. This comprehensive collection is organized in four parts: (1) Basics of fractal analysis; (2) Applications of fractals to the basic neurosciences; (3) Applications of fractals to the clinical neurosciences; (4) Analysis software, modeling and methodology.
1 online resource (Article No. 11313 ) : digital, PDF file.
Persistent neurogenesis in the dentate gyrus produces immature neurons with high intrinsic excitability and low levels of inhibition that are predicted to be more broadly responsive to afferent activity than mature neurons. Mounting evidence suggests that these immature neurons are necessary for generating distinct neural representations of similar contexts, but it is unclear how broadly responsive neurons help distinguish between similar patterns of afferent activity. Here we show that stimulation of the entorhinal cortex in mouse brain slices paradoxically generates spiking of mature neurons in the absence of immature neuron spiking. Immature neurons with high intrinsic excitability fail to spike due to insufficient excitatory drive that results from low innervation rather than silent synapses or low release probability. Here, our results suggest that low synaptic connectivity prevents immature neurons from responding broadly to cortical activity, potentially enabling excitable immature neurons to contribute to sparse and orthogonal dentate representations.
x, 224 pages : illustrations ; 24 cm
  • Table of Contents Dedication Acknowledgments Introduction Chapter I: Educational Neuroscience for All Chapter II: A Formative Assessment Chapter III: The Top Twelve Research Informed Strategies Every Teacher Should Be Doing With Every Student Chapter IV: How Much Do We Need to Know About the Brain? Chapter V: A Mindset for the Future of Teaching and Learning Chapter VI: "My Best (Research Informed) Class Ever" Chapter VII: "I Love Your Amygdala!" Chapter VIII: Memory + Attention + Engagement = Learning Chapter IX: Assessment 360 Chapter X: Homework, Sleep, and the Learning Brain Chapter XI: Technology and a Student's Second Brain Chapter XII: Teachers Are Researchers Chapter XIII: From Research to Practice: A Mind, Brain, and Education Science Professional Growth Framework for You and Your School Conclusion: What's Next - The 10% Challenge Appendix I: Readings, Research, and Resources Appendix II: Self-Reflection Tool: A Personal MBE Science Research-Informed Strategies Checklist About the Authors Index Join the Neuroteach Network.
  • (source: Nielsen Book Data)9781475825350 20161108
Teachers are brain changers. Thus it would seem obvious that an understanding of the brain - the organ of learning - would be critical to a teacher's readiness to work with students. Unfortunately, in traditional public, public-charter, private, parochial, and home schools across the country, most teachers lack an understanding of how the brain receives, filters, consolidates, and applies learning for both the short and long term. Neuroteach was therefore written to help solve the problem teachers and school leaders have in knowing how to bring the growing body of educational neuroscience research into the design of their schools, classrooms, and work with each individual student. It is our hope, that Neuroteach will help ensure that one day, every student -regardless of zip code or school type-will learn and develop with the guidance of a teacher who knows the research behind how his or her brain works and learns.
(source: Nielsen Book Data)9781475825350 20161108
Green Library
1 online resource.
  • Introduction
  • Bio-electronics Interfaces
  • Organic Devices for Electrophysiological Applications
  • The Micro Organic Charge Modulated FET Array
  • Experimental Results.-Conclusions.
This thesis reports on the Micro OCMFET Array, a novel, reference-less system for extracellular recordings of action potentials. The book provides readers with a full description of the system, together with an extensive report of the successful experimental trials carried out on both cardiac and nerve cells. Moreover, it offers a concise yet comprehensive overview of both bioelectronic interfaces, such as Micro Electrode Arrays (MEAs) and Field Effect Devices (FEDs), and organic sensors for electro- physiological applications, including Organic Charge-Modulated FETs (OCMFET), Electrolyte-Gated Organic FETs (EGOFETs), and Organic Electrochemical Transistors (OECTs).
1 online resource (444 p.)
  • Preface Acknowledgement Introduction Rapid Unsupervised Effective Causal Learning A General Noological Framework Conceptual Grounding and Operational Representation Causal Rules, Problem Solving, and Operational Representation The Causal Role of Sensory Information. Application to the StarCraft Game Environment A Grand Challenge for Noology and Computational Intelligence Affect Driven Noological Processes Summary and Beyond Appendix A: Causal vs Reinforcement Learning Appendix B: Rapid Effective Causal Learning Algorithm Index.
  • (source: Nielsen Book Data)9783319321110 20160815
The idea of this book is to establish a new scientific discipline, "noology, " under which a set of fundamental principles are proposed for the characterization of both naturally occurring and artificial intelligent systems. The methodology adopted in Principles of Noology for the characterization of intelligent systems, or "noological systems, " is a computational one, much like that of AI. Many AI devices such as predicate logic representations, search mechanisms, heuristics, and computational learning mechanisms are employed but they are recast in a totally new framework for the characterization of noological systems. The computational approach in this book provides a quantitative and high resolution understanding of noological processes, and at the same time the principles and methodologies formulated are directly implementable in AI systems. In contrast to traditional AI that ignores motivational and affective processes, under the paradigm of noology, motivational and affective processes are central to the functioning of noological systems and their roles in noological processes are elucidated in detailed computational terms. In addition, a number of novel representational and learning mechanisms are proposed, and ample examples and computer simulations are provided to show their applications. These include rapid effective causal learning (a novel learning mechanism that allows an AI/noological system to learn causality with a small number of training instances), learning of scripts that enables knowledge chunking and rapid problem solving, and learning of heuristics that further accelerates problem solving. Semantic grounding allows an AI/noological system to "truly understand" the meaning of the knowledge it encodes. This issue is extensively explored. This is a highly informative book providing novel and deep insights into intelligent systems which is particularly relevant to both researchers and students of AI and the cognitive sciences.
(source: Nielsen Book Data)9783319321110 20160815