Pyramidal neuron as two-layer neural network.
The pyramidal neuron is the principal cell type in the mammalian forebrain, but its function remains poorly understood. Using a detailed compartmental model of a hippocampal CA1 pyramidal cell, we recorded responses to complex stimuli consisting of dozens of high-frequency activated synapses distributed throughout the apical dendrites. We found the cell's firing rate could be predicted by a simple formula that maps the physical components of the cell onto those of an abstract two-layer "neural network." In the first layer, synaptic inputs drive independent sigmoidal subunits corresponding to the cell's several dozen long, thin terminal dendrites. The subunit outputs are then summed within the main trunk and cell body prior to final thresholding. We conclude that insofar as the neural code is mediated by average firing rate, a two-layer neural network may provide a useful abstraction for the computing function of the individual pyramidal neuron.
Poirazi
Panayiota
P
Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology, Hellas (FORTH), Vassilica Vouton, PO Box 1527, GR 711 10 Heraklion, Crete, Greece. poirazi@imbb.forth.gr
Brannon
Terrence
T
Mel
Bartlett W
BW
D055592:Biophysical Phenomena; D001703:Biophysics; D002118:Calcium / Q000378:metabolism; D003712:Dendrites / Q000502:physiology; D004553:Electric Conductivity; D004594:Electrophysiology; D008433:Mathematics; D008954:Models, Biological; D009415:Nerve Net / Q000502:physiology* / Q000648:ultrastructure; D015221:Potassium Channels / Q000502:physiology; D017966:Pyramidal Cells / Q000502:physiology* / Q000648:ultrastructure; D015222:Sodium Channels / Q000502:physiology; D013569:Synapses / Q000502:physiology
D015221:Potassium Channels; D015222:Sodium Channels; D002118:Calcium