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SI Appendix 2 We simulated a large-scale thalamocortical network consisting of one million neurons and up to one
 

Summary: SI Appendix 2
We simulated a large-scale thalamocortical network consisting of one million neurons and up to one
billion synaptic connections. Parameters of the network are scaled to preserve ratios found in the mam-
malian thalamocortical system. The white matter anatomy of the model is reconstructed from human
diffusion tensor imaging (DTI) data using fiber-tracktography methods. The gray-matter anatomy con-
sists of 5 cortical layers with microcircuitry of a "generic primary sensory area" and specific, non-specific,
and reticular thalamic nuclei. The model has 12 types and numerous subtypes of neurons with multi-
compartment dendritic trees; synapses with AMPA, NMDA, GABAA, GABAB, and gap-junction kinetics;
axonal lengths and conduction delays; synaptic short-term depression and facilitation; synaptic long-term
spike-timing-dependent plasticity (STDP); and neuromodulation derived from the brainstem dopaminergic
reward system. The parameters of the model are taken from the published literature, mostly on cat area
17 and lamina A of dorsal thalamus. In some cases, a number of arbitrary but justifiable choices had to
be made.
As compared to real cortex, the model has a scaled down density of neurons and synapses per mm2
of cortical surface. Model neurons have scaled down number of synapses and impoverished dendritic trees
in comparison with real cortical neurons. Moreover, we do not model subcortical structures other than
the thalamus. We do not model developmental changes other than that reflected in activity-dependent
fine-tuning of connectivity.
Most simulations were performed with one million neurons, though a variant of the model was simulated
with 1011 neurons and almost one quadrillion synapses, which corresponds to the full size of the human

  

Source: Andrzejak, Ralph Gregor - Departament de Tecnologia, Universitat Pompeu Fabra

 

Collections: Computer Technologies and Information Sciences