5-neuron-model of neocortex for producing realistic extracellular AP shapes (Van Dijck et al. 2012)

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This is a 5-neuron model of neocortex, containing one tufted layer-5 pyramidal cell, two non-tufted pyramidal cells, and two inhibitory interneurons. It was used to reproduce extracellular spike shapes in a study comparing algorithms for spike sorting and electrode selection. The neuron models are adapted from Dyhrfjeld-Johnsen et al. (2005).
1 . Van Dijck G, Seidl K, Paul O, Ruther P, Van Hulle MM, Maex R (2012) Enhancing the yield of high-density electrode arrays through automated electrode selection. Int J Neural Syst 22:1-19 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Extracellular; Neuron or other electrically excitable cell; Realistic Network;
Brain Region(s)/Organism:
Cell Type(s): Neocortex U1 L5B pyramidal pyramidal tract GLU cell; Neocortex U1 L2/6 pyramidal intratelencephalic GLU cell;
Gap Junctions:
Simulation Environment: GENESIS;
Model Concept(s):
Implementer(s): Maex, Reinoud [reinoud at bbf.uia.ac.be];
Search NeuronDB for information about:  Neocortex U1 L5B pyramidal pyramidal tract GLU cell; Neocortex U1 L2/6 pyramidal intratelencephalic GLU cell;
This dir deals with the fibres providing inputs to the
neurons of the network, and hence driving the network.

Fibres are Poisson processes whose instantaneous spike 
rate can be modulated by another process: 
- a point  process (with exponential decaying response) 
for forward fibres projecting from external sources
- the filtered membrane potential of a component neuron
for intracolumnar (hence feedback) fibres 

The files contain procedures for creating the fibres, 
positioning them, assigning them to different populations 
(excitatory versus inhibitory, feedforward versus 
intracolumnar feedback), connecting them to synapses on 
the neurons' compartments, and adapting their strengths 
according to their depth (layer) within the neocortex

The actual connections from the different fibre populations
to the individual neurons are laid by code within the main script 
(../Network/Network_make.g), using procedures described here.
The reason for coding these connections in the main script,
is that they have to be tuned by hand for each neuron separately,
in order to guarantee that each neuron would spike at a reasonable 

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