Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Neurochemistry --- Nervous System Physiological Phenomena --- Cognitive Science --- Neurosciences --- Neurochemistry. --- Nervous System Physiological Phenomena. --- Neurochemistries --- Chemistry --- Nervous System Physiological Concepts --- Nervous System Physiological Phenomenon --- Nervous System Physiological Process --- Physiology, Nervous System --- Nervous System Physiologic Processes --- Nervous System Physiological Processes --- Nervous System Physiology --- System Physiology, Nervous --- Nervous System --- physiology --- Neural sciences --- Neurological sciences --- Neuroscience --- Medical sciences --- Nervous system

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This third edition of the standard reference on the nervous system of the rat is a complete and updated revision of the 1994 second edition. All chapters have been extensively updated, and new chapters added covering early segmentation, growth factors, and glia. The book is now aligned with the data available in the Rat Brain in Stereotaxic Coordinates, making it an excellent companion to this bestselling atlas. Physiological data, functional concepts, and correlates to human anatomy and function round out the new edition.*Designed to be used in conjunction with the bestselling

Animal psychology and neurophysiology --- Mammals --- Rats --- Brain --- Anatomy --- Nervous system --- Rat --- Muridae --- Nervous system. --- Anatomy. --- Rats - Anatomy --- Brain - Anatomy --- Rats - Nervous system

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Neurons in the brain communicate by short electrical pulses, the so-called action potentials or spikes. How can we understand the process of spike generation? How can we understand information transmission by neurons? What happens if thousands of neurons are coupled together in a seemingly random network? How does the network connectivity determine the activity patterns? And, vice versa, how does the spike activity influence the connectivity pattern? These questions are addressed in this 2002 introduction to spiking neurons aimed at those taking courses in computational neuroscience, theoretical biology, biophysics, or neural networks. The approach will suit students of physics, mathematics, or computer science; it will also be useful for biologists who are interested in mathematical modelling. The text is enhanced by many worked examples and illustrations. There are no mathematical prerequisites beyond what the audience would meet as undergraduates: more advanced techniques are introduced in an elementary, concrete fashion when needed.

Computational neuroscience. --- Neural networks (Neurobiology). --- Neurons. --- Neuroplasticity. --- Neurons --- Neuronal Plasticity --- Nerve Net --- Models, Neurological --- Nervous System Physiological Processes --- Models, Biological --- Nervous System --- Cells --- Models, Theoretical --- Anatomy --- Nervous System Physiological Phenomena --- Musculoskeletal and Neural Physiological Phenomena --- Investigative Techniques --- Phenomena and Processes --- Analytical, Diagnostic and Therapeutic Techniques and Equipment --- Neuroscience --- Human Anatomy & Physiology --- Health & Biological Sciences --- Investigative Technics --- Investigative Technic --- Investigative Technique --- Technic, Investigative --- Technics, Investigative --- Technique, Investigative --- Techniques, Investigative --- Musculoskeletal and Neural Physiological Concepts --- Musculoskeletal and Neural Physiological Phenomenon --- Musculoskeletal and Neural Physiology --- Neural Networks (Anatomic) --- Nerve Nets --- Net, Nerve --- Nets, Nerve --- Network, Neural (Anatomic) --- Networks, Neural (Anatomic) --- Neural Network (Anatomic) --- Axon Pruning --- Axonal Pruning --- Dendrite Arborization --- Dendrite Pruning --- Dendritic Arborization --- Dendritic Pruning --- Dendritic Remodeling --- Neural Plasticity --- Neurite Pruning --- Neuronal Arborization --- Neuronal Network Remodeling --- Neuronal Pruning --- Neuronal Remodeling --- Neuroplasticity --- Synaptic Plasticity --- Synaptic Pruning --- Brain Plasticity --- Plasticity, Neuronal --- Arborization, Dendrite --- Arborization, Dendritic --- Arborization, Neuronal --- Arborizations, Dendrite --- Arborizations, Dendritic --- Arborizations, Neuronal --- Axon Prunings --- Axonal Prunings --- Brain Plasticities --- Dendrite Arborizations --- Dendrite Prunings --- Dendritic Arborizations --- Dendritic Prunings --- Dendritic Remodelings --- Network Remodeling, Neuronal --- Network Remodelings, Neuronal --- Neural Plasticities --- Neurite Prunings --- Neuronal Arborizations --- Neuronal Network Remodelings --- Neuronal Plasticities --- Neuronal Prunings --- Neuronal Remodelings --- Neuroplasticities --- Plasticities, Brain --- Plasticities, Neural --- Plasticities, Neuronal --- Plasticities, Synaptic --- Plasticity, Brain --- Plasticity, Neural --- Plasticity, Synaptic --- Pruning, Axon --- Pruning, Axonal --- Pruning, Dendrite --- Pruning, Dendritic --- Pruning, Neurite --- Pruning, Neuronal --- Pruning, Synaptic --- Prunings, Axon --- Prunings, Axonal --- Prunings, Dendrite --- Prunings, Dendritic --- Prunings, Neurite --- Prunings, Neuronal --- Prunings, Synaptic --- Remodeling, Dendritic --- Remodeling, Neuronal --- Remodeling, Neuronal Network --- Remodelings, Dendritic --- Remodelings, Neuronal --- Remodelings, Neuronal Network --- Synaptic Plasticities --- Synaptic Prunings --- Cell Plasticity --- Nervous System Physiological Concepts --- Nervous System Physiological Phenomenon --- Nervous System Physiological Process --- Physiology, Nervous System --- Nervous System Physiologic Processes --- Nervous System Physiology --- System Physiology, Nervous --- Anatomies --- Experimental Model --- Experimental Models --- Mathematical Model --- Model, Experimental --- Models (Theoretical) --- Models, Experimental --- Models, Theoretic --- Theoretical Study --- Mathematical Models --- Model (Theoretical) --- Model, Mathematical --- Model, Theoretical --- Models, Mathematical --- Studies, Theoretical --- Study, Theoretical --- Theoretical Model --- Theoretical Models --- Theoretical Studies --- Computer Simulation --- Systems Theory --- Cell --- Cell Biology --- Nervous Systems --- System, Nervous --- Systems, Nervous --- Biological Model --- Biological Models --- Model, Biological --- Models, Biologic --- Biologic Model --- Biologic Models --- Model, Biologic --- Model, Neurological --- Neurologic Model --- Neurological Model --- Neurological Models --- Neurologic Models --- Model, Neurologic --- Models, Neurologic --- Nerve Cells --- Cell, Nerve --- Cells, Nerve --- Nerve Cell --- Neuron --- physiology --- Computational neuroscience --- Neural networks (Neurobiology) --- 681.3*I51 --- Nervous system plasticity --- Neural adaptation --- Neural plasticity --- Neuronal adaptation --- Neuronal plasticity --- Plasticity, Nervous system --- Soft-wired nervous system --- Synaptic plasticity --- Adaptation (Physiology) --- Neurophysiology --- Developmental neurobiology --- Nerve cells --- Neurocytes --- Nervous system --- Biological neural networks --- Nets, Neural (Neurobiology) --- Networks, Neural (Neurobiology) --- Neural nets (Neurobiology) --- Cognitive neuroscience --- Neurobiology --- Neural circuitry --- Computational neurosciences --- Computational biology --- Neurosciences --- 681.3*I51 Models: deterministic; fuzzy set; geometric; statistical; structural (Patternrecognition) --- Models: deterministic; fuzzy set; geometric; statistical; structural (Patternrecognition)

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

In this volume, Koch shows how individual nerve cells can multiply, integrate, or delay synaptic inputs, and how information is encoded in the voltage across the membrane, in the intracellular calcium concentration, or in the timing of individual spikes.

Computational neuroscience. --- Neurons. --- Neural networks (Neurobiology) --- Action potentials (Electrophysiology) --- Neural conduction. --- Conduction, Neural --- Nerve conduction --- Neurophysiology --- Electrophysiology --- Biological neural networks --- Nets, Neural (Neurobiology) --- Networks, Neural (Neurobiology) --- Neural nets (Neurobiology) --- Cognitive neuroscience --- Neurobiology --- Neural circuitry --- Nerve cells --- Neurocytes --- Cells --- Nervous system --- Computational neurosciences --- Computational biology --- Neurosciences --- Computational neuroscience --- Neural conduction --- Neurons

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Explains the relationship of electrophysiology, nonlinear dynamics, and the computational properties of neurons, with each concept presented in terms of both neuroscience and mathematics and illustrated using geometrical intuition. In order to model neuronal behavior or to interpret the results of modeling studies, neuroscientists must call upon methods of nonlinear dynamics. This book offers an introduction to nonlinear dynamical systems theory for researchers and graduate students in neuroscience. It also provides an overview of neuroscience for mathematicians who want to learn the basic facts of electrophysiology. Dynamical Systems in Neuroscience presents a systematic study of the relationship of electrophysiology, nonlinear dynamics, and computational properties of neurons. It emphasizes that information processing in the brain depends not only on the electrophysiological properties of neurons but also on their dynamical properties. The book introduces dynamical systems, starting with one- and two-dimensional Hodgkin-Huxley-type models and continuing to a description of bursting systems. Each chapter proceeds from the simple to the complex, and provides sample problems at the end. The book explains all necessary mathematical concepts using geometrical intuition; it includes many figures and few equations, making it especially suitable for non-mathematicians. Each concept is presented in terms of both neuroscience and mathematics, providing a link between the two disciplines. Nonlinear dynamical systems theory is at the core of computational neuroscience research, but it is not a standard part of the graduate neuroscience curriculum--or taught by math or physics department in a way that is suitable for students of biology. This book offers neuroscience students and researchers a comprehensive account of concepts and methods increasingly used in computational neuroscience. An additional chapter on synchronization, with more advanced material, can be found at the author's website, www.izhikevich.com.

Differentiable dynamical systems. --- Neurology. --- Neurons. --- Neurosciences. --- Models, Neurological --- Neurons --- Neurosciences --- Models, Neurological. --- Differential dynamical systems --- Dynamical systems, Differentiable --- Dynamics, Differentiable --- Nerve cells --- Neurocytes --- Neural sciences --- Neurological sciences --- Neuroscience --- Differential equations --- Global analysis (Mathematics) --- Topological dynamics --- Cells --- Nervous system --- Medicine --- Neuropsychiatry --- Medical sciences --- Diseases --- Differentiable dynamical systems --- Neurology --- NEUROSCIENCE/General --- Neurologia --- Electrofisiologia --- Sistemes dinàmics diferenciables --- Electricitat animal --- Electrobiologia --- Fisiologia --- Anestèsia elèctrica --- Circuit neuronal --- Electrocardiografia --- Electroencefalografia --- Músculs --- Potencials evocats (Electrofisiologia) --- Medicina --- Inhibició --- Neurocirurgia --- Neurooftalmologia --- Neuroimmunologia --- Neurologia pediàtrica --- Neurologia geriàtrica --- Neurologia veterinària --- Psicofisiologia --- Psicopatologia --- Urgències en neurologia --- Neuròlegs --- Dinàmica diferencial --- Exponents de Lyapunov --- Fluxos (Sistemes dinàmics diferenciables) --- Sistemes dinàmics aleatoris --- Sistemes dinàmics complexos --- Sistemes dinàmics hiperbòlics --- Sistemes hamiltonians --- Teoria de la bifurcació --- Dinàmica topològica --- Dinàmica combinatòria