Literature DB >> 10620749

Progress and perspectives in computational neuroanatomy.

G A Ascoli1.   

Abstract

The tremendous increase in processing power of personal computers has recently allowed the construction of highly sophisticated models of neuronal function and behavior. Anatomy plays a fundamental role in supporting and shaping nervous system activity, yet to date most details of such a role have escaped the efforts of experimental and theoretical neuroscientists, mainly because of the problem's complexity. When accurate cellular morphologies are included in electrophysiological computer simulations, quantitative and qualitative effects of dendritic structure on firing properties can be extensively characterized. Complete models of dendritic morphology can be implemented to allow the computer generation of virtual neurons that model the anatomical characteristics of their real counterparts to a great degree of approximation. From a restricted and already available experimental database, stochastic and statistical algorithms can create an unlimited number of non-identical virtual neurons within several mammalian morphological classes, storing them in a compact and parsimonious format. When modeled neurons are distributed in three-dimensional and biologically plausible rules governing axonal navigation and connectivity are added to the simulations, entire portions of the nervous system can be "grown" as anatomically realistic neural networks. These computational constructs are useful to determine the influence of local geometry on system neuroanatomy, and to investigate systematically the mutual interactions between anatomical parameters and electrophysiological activity at the network level. A detailed computer model of a "virtual brain" that was truly equivalent to the biological structure could in principle allow scientists to carry out experiments that could not be performed on real nervous systems because of physical constraints. The computational approach to neuroanatomy is just at its beginning, but has a great potential to enhance the intuition of investigators and to aid neuroscience education. Anat Rec (New Anat): 257:195-207, 1999. Copyright 1999 Wiley-Liss, Inc.

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Year:  1999        PMID: 10620749     DOI: 10.1002/(SICI)1097-0185(19991215)257:6<195::AID-AR5>3.0.CO;2-H

Source DB:  PubMed          Journal:  Anat Rec        ISSN: 0003-276X


  9 in total

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2.  Non-parametric algorithmic generation of neuronal morphologies.

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Review 3.  Quantifying neuronal size: summing up trees and splitting the branch difference.

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4.  Cross-Species Evidence of Interplay Between Neural Connectivity at the Micro- and Macroscale of Connectome Organization in Human, Mouse, and Rat Brain.

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5.  One rule to grow them all: a general theory of neuronal branching and its practical application.

Authors:  Hermann Cuntz; Friedrich Forstner; Alexander Borst; Michael Häusser
Journal:  PLoS Comput Biol       Date:  2010-08-05       Impact factor: 4.475

6.  An information integration theory of consciousness.

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7.  A simulation study on the effects of dendritic morphology on layer V prefrontal pyramidal cell firing behavior.

Authors:  Maria Psarrou; Stefanos S Stefanou; Athanasia Papoutsi; Alexandra Tzilivaki; Vassilis Cutsuridis; Panayiota Poirazi
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8.  Optimization principles of dendritic structure.

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9.  Comparing basal dendrite branches in human and mouse hippocampal CA1 pyramidal neurons with Bayesian networks.

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  9 in total

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