Castellani, Gastone and Verondini, E. and Giampieri, E. and Milanesi, L. and Bersani, F. and Zironi, I. and Remondini, D. (2009) Large-scale modelling of neuronal systems. Il nuovo cimento C, 32 (2). pp. 13-18. ISSN 1826-9885
|
Text
ncc9372.pdf - Published Version Download (178kB) | Preview |
Abstract
The brain is, without any doubt, the most complex system of the human body. Its complexity is also due to the extremely high number of neurons, as well as the huge number of synapses connecting them. Each neuron is capable to perform complex tasks, like learning and memorizing a large class of patterns. The simulation of large neuronal systems is challenging for both technological and computational reasons, and can open new perspectives for the comprehension of brain functioning. A well-known and widely accepted model of bidirectional synaptic plasticity, the BCM model, is stated by a differential equation approach based on bistability and selectivity properties. We have modified the BCM model extending it from a single-neuron to a whole-network model. This new model is capable to generate interesting network topologies starting from a small number of local parameters, describing the interaction between incoming and outgoing links from each neuron. We have characterized this model in terms of complex network theory, showing how this learning rule can be a support for network generation.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Systems biology ; Neural networks and synaptic communication ; Networks and genealogical trees |
| Subjects: | 500 Scienze naturali e Matematica > 530 Fisica |
| Depositing User: | Marina Spanti |
| Date Deposited: | 24 Mar 2020 17:07 |
| Last Modified: | 24 Mar 2020 17:07 |
| URI: | http://eprints.bice.rm.cnr.it/id/eprint/16476 |
Actions (login required)
 |
View Item |
