Papers that might be of interest

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Hello everyone!

I wanted to let you know about the recent publication of two
Computational Neuroscience papers by Poirazi, P. Brannon T. and Mel, BW.
at "Neuron", which you might find interesting. I'm attaching the
abstracts here. There is also an online supplement describing the CA1
model cell. Please let me know if you would like a reprint and do not
have access to "Neuron".

Arithmetic of subthreshold synaptic summation in a model CA1 pyramidal cell.
Neuron 2003 Mar 27;37(6):977-87
Poirazi P, Brannon T, Mel BW.

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

The rules of synaptic integration in pyramidal cells remain obscure, in
part due to conflicting interpretations of existing experimental data.
To clarify issues, we developed a CA1 pyramidal cell model calibrated
with a broad spectrum of in vitro data. Using simultaneous dendritic and
somatic recordings and combining results for two different response
measures (peak versus mean EPSP), two different stimulus formats (single
shock versus 50 Hz trains), and two different spatial integration
conditions (within versus between-branch summation), we found that the
cell's subthreshold responses to paired inputs are best described as a
sum of nonlinear subunit responses, where the subunits correspond to
different dendritic branches. In addition to suggesting a new type of
experiment and providing testable predictions, our model shows how
conclusions regarding synaptic arithmetic can be influenced by an array
of seemingly innocuous experimental design choices.

Pyramidal neuron as two-layer neural network.
Neuron 2003 Mar 27;37(6):989-99
Poirazi P, Brannon T, Mel BW.

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

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.

Best regards,

Yiota

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Dr. Panayiota Poirazi
Research Assistant Professor
Computational Biology Laboratory
Institute of Molecular Biology and Biotechnology
Foundation of Research and Technology, Hellas (FO.R.T.H)
Vassilika Vouton
P.O.Box 1527
GR 711 10 Heraklion, Crete
GREECE

Tel: +30 2810 391100
Fax: +30 2810 391101
email: poirazi@imbb.forth.gr
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