- Poster presentation
- Open Access
Scaling of a biophysical neocortical attractor model using Parallel NEURON on the Blue Gene /P
© Silverstein and Lansner; licensee BioMed Central Ltd. 2011
- Published: 18 July 2011
- Pyramidal Cell
- Network Size
- Virtual Node
- Biophysical Model
- Basket Cell
This work entails scaling a biophysical model of the neocortex using parallel NEURON  while running on a Blue Gene / P in virtual node mode. Previous scaling experiments have been done with the SPLIT simulator on the Blue Gene / L with a similar neocortical model . We chose a biophysical model of medium complexity based on the Hodgkin-Huxley formalism because this provides the capability of exploring the effects of psychotropic drugs as well as the oscillatory effects of cortical microcircuits and globally correlated network activity. Neocortical simulations were performed to determine both strong (fixed network size, increasing cores) and weak (increasing network size, fixed load per core) scaling with two variations of a square necortical patch of hypercolumns and internal minicolumns. The first variation consists of minicolumns with 20 layer 2/3 pyramidal cells, 2 basket cells and 5 layer 4 pyramidal cells and has orthogonally stored memory patterns, encoded with long-range excitatory connections between individual minicolumns across hypercolumns. The second variation has an additional 2 regular spiking non-pyramidal interneurons per minicolumn and instead uses sparse, randomly overlapping memory patterns encoded with both excitatory and inhibitory long-range connections between hypercolumns. Simulations were performed with both single patches of increasing area and cascades of multiple patches with feed-forward and feed-backward projections.
- Carnevale NT, Hines ML: The NEURON Book. 2006, Cambridge University PressView ArticleGoogle Scholar
- Djurfeldt M, Lundqvist M, Johansson C, Rehn M, Ekeberg Ö, Lansner A: Brain-scale simulation of the neocortex on the IBM Blue Gene/L supercomputer. 2008, IBM Journal of Research and Development, 52: 31.Google Scholar
This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.