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The cost of linearization.

Abstract：

:Linear additivity of synaptic input is a pervasive assumption in computational neuroscience, and previously Bernander et al. (Journal of Neurophysiology 72:2743-2753, 1994) point out that the sublinear additivity of a passive neuronal model can be linearized with voltage-dependent currents. Here we re-examine this perspective in light of more recent findings and issues. Based on in vivo intracellular recordings, three voltage-dependent conductances seem to be of interest for pyramidal cells of the forebrain: two of them are amplifying, I ( NaP ) and I ( h ); and one of them is attenuating, I ( A ). Based on particular I-V characteristics reported in the literature, each of these three voltage-dependent currents linearizes a particular range of synaptic excitation. Computational simulations use a steady-state, one-compartment model. They establish maximal linear ranges, where supralinear effects-due to adding too much of any one conductance-limit these ranges. Specific, carefully selected pairwise combinations of these currents can linearize larger ranges than either current alone. In terms of parameters, the steady-state I-V characteristics of each current are critical. On the other hand, the relationships between the results here and resting conductance to ground, synaptic conductance, and number of active synapses are simple and easily scaled; thus in regard to these three latter dependences, the results here are easily generalized. Finally, to improve our understanding of evolved function, the relative metabolic costs of linearization are quantified. In one case, there is a clear preference arising from this cost consideration (a particular I ( h ), I ( NaP ) pairing is less costly compared to a particular I ( A ), I ( NaP ) pairing that produces an equivalent, linearized range). However in other cases, a preference will depend on the required range; but in any event, the largest linearized range observed here (28 mV), from a combination of I ( h ) and I ( A ), is significantly more costly than the 20 mV range that the I ( h ), I ( NaP ) pair produces.

journal_name

J Comput Neurosci

journal_title

Journal of computational neuroscience

authors

Morel D,Levy W

doi

10.1007/s10827-009-0141-y

subject

Has Abstract

pub_date

2009-10-01 00:00:00

pages

259-75

issue

eissn

0929-5313

issn

1573-6873

journal_volume

pub_type

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The cost of linearization.