The computing dendrite : from structure to function /
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| Imprint: | New York : Springer, 2014. |
|---|---|
| Description: | 1 online resource (350 pages). |
| Language: | English |
| Series: | Springer series in computational neuroscience ; volume 11 Springer series in computational neuroscience ; volume 11. |
| Subject: | |
| Format: | E-Resource Book |
| URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/11081824 |
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| 245 | 0 | 4 | |a The computing dendrite : |b from structure to function / |c Hermann Cuntz, Michiel W. Remme, Benjamin Torben-Nielsen, editors. |
| 264 | 1 | |a New York : |b Springer, |c 2014. | |
| 300 | |a 1 online resource (350 pages). | ||
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| 490 | 1 | |a Springer series in computational neuroscience ; |v volume 11 | |
| 505 | 0 | 0 | |g Part I. |t Dendritic Morphology -- |t Introduction to Dendritic Morphology / |r Benjamin Torben-Nielsen and Hermann Cuntz -- |t The Cell Biology of Dendrite Differentiation / |r Gaia Tavosanis -- |t Archetypes and Outliers in the Neuromorphological Space / |r Cesar H. Comin, Julian Tejada, Matheus P. Viana, Antonio C. Roque and Luciano da F. Costa -- |t Neuronal Arborizations, Spatial Innervation, and Emergent Network Connectivity / |r Jaap van Pelt, Harry B. M. Uylings and Arjen van Ooyen -- |t Shaping of Neurons by Environmental Interaction / |r Artur Luczak -- |t Modelling Dendrite Shape from Wiring Principles / |r Hermann Cuntz -- |t A Statistical Theory of Dendritic Morphology / |r Quan Wen -- |t Reverse Engineering the 3D Structure and Sensory-Evoked Signal Flow of Rat Vibrissal Cortex / |r Robert Egger, Vincent J. Dercksen, Christiaan P. J. de Kock and Marcel Oberlaender -- |t Optimized Dendritic Morphologies for Noisy Inputs / |r Klaus M. Stiefel and Benjamin Torben-Nielsen -- |g Part II. |t Dendritic Computation -- |t Introduction to Dendritic Computation / |r Michiel W. H. Remme and Benjamin Torben-Nielsen -- |t Noisy Dendrites: Models of Dendritic Integration In Vivo / |r Alain Destexhe and Michelle Rudolph-Lilith -- |t Distributed Parallel Processing in Retinal Amacrine Cells / |r Jeffrey S. Diamond and William N. Grimes -- |t Dendritic Computation of Direction in Retinal Neurons / |r Robert G. Smith and W. Rowland Taylor -- |t Rapid Integration Across Tonotopy by Individual Auditory Brainstem Octopus Cells / |r Matthew J. McGinley -- |t Computing Temporal Sequence with Dendrites / |r Tiago Branco -- |t Modelling the Cellular Mechanisms of Fly Optic Flow Processing / |r Hermann Cuntz, Juergen Haag and Alexander Borst -- |t Biophysical Mechanisms of Computation in a Looming Sensitive Neuron / |r Simon P. Peron -- |t Biophysics of Synaptic Inhibition in Dendrites / |r Albert Gidon -- |t Role of Non-uniform Dendrite Properties on Input Processing by GABAergic Interneurons / |r Anja Matthiä, Marlene Bartos and Imre Vida -- |t Subthreshold Resonance and Membrane Potential Oscillations in a Neuron with Nonuniform Active Dendritic Properties / |r Ekaterina Zhuchkova, Michiel W. H. Remme and Susanne Schreiber -- |t A Trade-Off Between Dendritic Democracy and Independence in Neurons with Intrinsic Subthreshold Membrane Potential Oscillations / |r Michiel W. H. Remme, Máté Lengyel and Boris S. Gutkin -- |t Dendrites Enhance Both Single Neuron and Network Computation / |r Romain D. Cazé, Mark D. Humphries and Boris S. Gutkin -- |t Dendritic Size and Topology Influence Burst Firing in Pyramidal Cells / |r Arjen van Ooyen and Ronald A. J. van Elburg -- |t Stochastic Ion Channel Gating and Probabilistic Computation in Dendritic Neurons / |r Cian O'Donnell and Matthew F. Nolan -- |t Cellular and Dendritic Memory Allocation / |r George Kastellakis and Panayiota Poirazi -- |t Synaptic Plasticity and Pattern Recognition in Cerebellar Purkinje Cells / |r Giseli de Sousa, Reinoud Maex, Rod Adams, Neil Davey and Volker Steuber -- |t Response of Gap Junction-Coupled Dendrites: A Sum-Over-Trips Approach / |r Yulia Timofeeva and Stephen Coombes -- |t Automated Parameter Constraining of Single-Neuron Models / |r Shaul Druckmann -- |t Morphological Reduction of Dendritic Neurons / |r Kathryn R. Hedrick and Steven J. Cox. |
| 505 | 0 | |a Part 1. Dendritic morphology -- Part 2. Dendritic computation. | |
| 500 | |a Includes index. | ||
| 520 | |a Neuronal dendritic trees are complex structures that endow the cell with powerful computing capabilities and allow for high neural interconnectivity. Studying the function of dendritic structures has a long tradition in theoretical neuroscience, starting with the pioneering work by Wilfrid Rall in the 1950s. Recent advances in experimental techniques allow us to study dendrites with a new perspective and in greater detail. The goal of this volume is to provide a rsum of the state-of-the-art in experimental, computational, and mathematical investigations into the functions of dendrites in a variety of neural systems. Thebook firstlooks at morphological properties of dendrites and summarizes the approaches to measure dendrite morphology quantitatively and to actually generate synthetic dendrite morphologies in computer models. This morphological characterization ranges from the study of fractal principles to describe dendrite topologies, to the consequences of optimization principles for dendrite shape. Individual approaches are collected to study the aspects of dendrite shape that relate directly to underlying circuit constraints and computation. The second main theme focuses on how dendrites contribute to the computations that neurons perform. What role do dendritic morphology andthe distributions of synapses and membrane properties over the dendritic tree have in determining the output of a neuron in response to its input? A wide range of studies is brought together, with topics ranging from general to system-specific phenomenasome having a strong experimental component, and others being fully theoretical. The studies come from many different neural systems and animal species ranging from invertebrates to mammals. Withthis broad focus, an overview is given of the diversity of mechanisms that dendrites can employ to shape neural computations. | ||
| 588 | 0 | |a Print version record. | |
| 583 | |a EBL dda |5 UPB | ||
| 650 | 0 | |a Dendrites. |0 http://id.loc.gov/authorities/subjects/sh85036698 | |
| 650 | 7 | |a Dendrites. |2 fast |0 (OCoLC)fst00890267 | |
| 655 | 4 | |a Electronic books. | |
| 700 | 1 | |a Cuntz, Hermann, |e editor. |0 http://id.loc.gov/authorities/names/n2014186014 |1 http://viaf.org/viaf/45379469 | |
| 700 | 1 | |a Remme, Michiel W. H., |e editor. |1 http://viaf.org/viaf/309829736 | |
| 700 | 1 | |a Torben-Nielsen, Benjamin, |e editor. |0 http://id.loc.gov/authorities/names/n2014186021 |1 http://viaf.org/viaf/309829739 | |
| 776 | 0 | 8 | |i Print version: |t Computing dendrite |z 9781461480938 |w (OCoLC)862732815 |
| 830 | 0 | |a Springer series in computational neuroscience ; |v volume 11. | |
| 856 | 4 | 0 | |u http://link.springer.com/10.1007/978-1-4614-8094-5 |y SpringerLink |
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