Abstract
The two-compartment Pinsky and Rinzel version of the Traub model offers a suitable solution for hardware-based emulation, since it has a good trade-off between biophysical accuracy and computational resources. Many applications based on conductance-based models require a proper characterization of the neuron behaviour in terms of its parameters, such as tuning firing parameters, changing parameters during learning processes, replication and analysis of neuron recordings, etc. This work presents a study of the dynamics of such model especially suitable for hardware-based development. The morphology of the neuron is taken into account while the analysis focuses primarily on the relation between the firing/bursting properties and the relevant parameters of the model, such as current applied and morphology of the cell. Two different applied currents were considered: short duration and long steady. Seven different types of burst patterns were detected and analysed. The transformation process of the membrane voltage when a long steady current varies was classified into five stages. Finally, examples of neuron recording replication using the present methodology are developed.
Original language | English |
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Title of host publication | NCTA 2014 - Proceedings of the International Conference on Neural Computation Theory and Applications |
Publisher | INSTICC Press |
Pages | 85-93 |
Number of pages | 9 |
ISBN (Print) | 9789897580543 |
Publication status | Published - 1 Jan 2014 |
Event | 6th International Conference on Neural Computation Theory and Applications, NCTA 2014, Part of the 6th International Joint Conference on Computational Intelligence, IJCCI 2014 - Rome, United Kingdom Duration: 22 Oct 2014 → 24 Oct 2014 |
Conference
Conference | 6th International Conference on Neural Computation Theory and Applications, NCTA 2014, Part of the 6th International Joint Conference on Computational Intelligence, IJCCI 2014 |
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Country/Territory | United Kingdom |
City | Rome |
Period | 22/10/14 → 24/10/14 |
Keywords
- Biophysically accurate hardware-model
- Bursting analysis
- Firing analysis
- Neuron modelling
- Pinsky-rinzel model
- Traub model
- Two-compartment models