Simulations of Synaptic Integration in Neocortical Pyramidal Cells

Despite their electrotonic compactness, neocortical pyramidal cells cannot be considered as point neurons because of nonlinear interactions between inputs on the same dendritic branch. Using compartmental simulations, we have shown that dendritic saturation is significant for physiological levels of synaptic activation. We also show that the firing of about 10% of the total number of inhibitory synapses on a cortical pyramidal cell is sufficient to reduce and even completely suppress the firing of neurons receiving strong excitatory input. Finally, we present a reduced pyramidal cell model (9 compartments) that runs significantly faster yet faithfully reproduces the behavior of the full 400 compartment model. The reduced model will be used for future physiological network simulations.

[1]  I Fariñas,et al.  Patterns of synaptic input on corticocortical and corticothalamic cells in the cat visual cortex. I. The cell body , 1991, The Journal of comparative neurology.

[2]  M Hines,et al.  A program for simulation of nerve equations with branching geometries. , 1989, International journal of bio-medical computing.

[3]  D. Ferster Orientation selectivity of synaptic potentials in neurons of cat primary visual cortex , 1986, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[4]  D. Ferster,et al.  EPSP-IPSP interactions in cat visual cortex studied with in vivo whole- cell patch recording , 1992, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[5]  Richard Durbin,et al.  The computing neuron , 1989 .

[6]  Kevan A. C. Martin,et al.  A Canonical Microcircuit for Neocortex , 1989, Neural Computation.

[7]  J Rinzel,et al.  Transient response in a dendritic neuron model for current injected at one branch. , 1974, Biophysical journal.

[8]  D. Whitteridge,et al.  Selective responses of visual cortical cells do not depend on shunting inhibition , 1988, Nature.

[9]  Kevan A. C. Martin,et al.  Control of Neuronal Output by Inhibition at the Axon Initial Segment , 1990, Neural Computation.