Physiology
Return to Library
Researchers from University of Virginia describe findings in computational neuroscience
2009 OCT 27 - (NewsRx.com) -- "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," scientists writing in the Journal of Computational Neuroscience report. "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)," wrote D. Morel and colleagues, University of Virginia. The researchers concluded: "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." Morel and colleagues published their study in the Journal of Computational Neuroscience (The cost of linearization. Journal of Computational Neuroscience, 2009;27(2):259-275). Additional information can be obtained by contacting W.B. Levy, University of Virginia, Dept. of Neurosurgery, Charlottesville, VA 22908, USA. The publisher of the Journal of Computational Neuroscience can be contacted at: Springer, Van Godewijckstraat 30, 3311 Gz Dordrecht, Netherlands. Keywords: United States, Charlottesville, Computational Neuroscience, Neurophysiology, Physiology, University of Virginia. This article was prepared by Life Science Weekly editors from staff and other reports. Copyright 2009, Life Science Weekly via NewsRx.com.
|
