Self-referential forces are sufficient to explain different dendritic morphologies
Dendritic morphology constrains brain activity, as it determines first which neuronal circuits are possible and second which dendritic computations can be performed over a neuron's inputs. It is known that a range of chemical cues can influence the final shape of dendrites during development. H...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2013-01-01
|
Series: | Frontiers in Neuroinformatics |
Subjects: | |
Online Access: | http://journal.frontiersin.org/Journal/10.3389/fninf.2013.00001/full |
id |
doaj-9bb154b98bf948bdb75b9c54f0f00b41 |
---|---|
record_format |
Article |
spelling |
doaj-9bb154b98bf948bdb75b9c54f0f00b412020-11-24T21:02:53ZengFrontiers Media S.A.Frontiers in Neuroinformatics1662-51962013-01-01710.3389/fninf.2013.0000138867Self-referential forces are sufficient to explain different dendritic morphologiesHeraldo eMemelli0Benjamin eTorben-Nielsen1James eKozloski2Stony Brook UniversityThe Hebrew UniversityIBM Research DivisionDendritic morphology constrains brain activity, as it determines first which neuronal circuits are possible and second which dendritic computations can be performed over a neuron's inputs. It is known that a range of chemical cues can influence the final shape of dendrites during development. Here, we investigate the extent to which self-referential influences, cues generated by the neuron itself, might influence morphology. To this end, we developed a phenomenological model and algorithm to generate virtual morphologies, which are then compared to experimentally reconstructed morphologies. In the model, branching probability follows a Galton-Watson process, while the geometry is determined by "homotypic forces" exerting influence on the direction of random growth in a constrained space. We model three such homotypic forces, namely an inertial force based on membrane stiffness, a soma-oriented tropism, and a force of self avoidance, as directional biases in the growth algorithm. With computer simulations we explored how each bias shapes neuronal morphologies. We show that based on these principles, we can generate realistic morphologies of several distinct neuronal types. We discuss the extent to which homotypic forces might influence real dendritic morphologies, and speculate about the influence of other environmental cues on neuronal shape and circuitry.http://journal.frontiersin.org/Journal/10.3389/fninf.2013.00001/fullsimulationmorphologyDendritecomputationalGrowth coneModel |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Heraldo eMemelli Benjamin eTorben-Nielsen James eKozloski |
spellingShingle |
Heraldo eMemelli Benjamin eTorben-Nielsen James eKozloski Self-referential forces are sufficient to explain different dendritic morphologies Frontiers in Neuroinformatics simulation morphology Dendrite computational Growth cone Model |
author_facet |
Heraldo eMemelli Benjamin eTorben-Nielsen James eKozloski |
author_sort |
Heraldo eMemelli |
title |
Self-referential forces are sufficient to explain different dendritic morphologies |
title_short |
Self-referential forces are sufficient to explain different dendritic morphologies |
title_full |
Self-referential forces are sufficient to explain different dendritic morphologies |
title_fullStr |
Self-referential forces are sufficient to explain different dendritic morphologies |
title_full_unstemmed |
Self-referential forces are sufficient to explain different dendritic morphologies |
title_sort |
self-referential forces are sufficient to explain different dendritic morphologies |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Neuroinformatics |
issn |
1662-5196 |
publishDate |
2013-01-01 |
description |
Dendritic morphology constrains brain activity, as it determines first which neuronal circuits are possible and second which dendritic computations can be performed over a neuron's inputs. It is known that a range of chemical cues can influence the final shape of dendrites during development. Here, we investigate the extent to which self-referential influences, cues generated by the neuron itself, might influence morphology. To this end, we developed a phenomenological model and algorithm to generate virtual morphologies, which are then compared to experimentally reconstructed morphologies. In the model, branching probability follows a Galton-Watson process, while the geometry is determined by "homotypic forces" exerting influence on the direction of random growth in a constrained space. We model three such homotypic forces, namely an inertial force based on membrane stiffness, a soma-oriented tropism, and a force of self avoidance, as directional biases in the growth algorithm. With computer simulations we explored how each bias shapes neuronal morphologies. We show that based on these principles, we can generate realistic morphologies of several distinct neuronal types. We discuss the extent to which homotypic forces might influence real dendritic morphologies, and speculate about the influence of other environmental cues on neuronal shape and circuitry. |
topic |
simulation morphology Dendrite computational Growth cone Model |
url |
http://journal.frontiersin.org/Journal/10.3389/fninf.2013.00001/full |
work_keys_str_mv |
AT heraldoememelli selfreferentialforcesaresufficienttoexplaindifferentdendriticmorphologies AT benjaminetorbennielsen selfreferentialforcesaresufficienttoexplaindifferentdendriticmorphologies AT jamesekozloski selfreferentialforcesaresufficienttoexplaindifferentdendriticmorphologies |
_version_ |
1716775036472262656 |