D
Daniel Tranchina
Researcher at New York University
Publications - 60
Citations - 5028
Daniel Tranchina is an academic researcher from New York University. The author has contributed to research in topics: Population & Receptive field. The author has an hindex of 31, co-authored 59 publications receiving 4675 citations. Previous affiliations of Daniel Tranchina include Albert Einstein College of Medicine & Center for Neural Science.
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A population density method for large-scale modeling of neuronal networks with realistic synaptic kinetics
TL;DR: Previous PDF methods for synapses with realistic kinetics are extended; synaptic current injection for inhibition is replaced with more realistic conductance modulation.
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Light adaptation in the turtle retina: embedding a parametric family of linear models in a single nonlinear model.
TL;DR: The methods presented can be used to develop specific physical models for light adaptation based on the chemical kinetics of phototransduction or on nonlinear neural feedback, and the relevance of the nonlinear models and construction techniques to modeling phototranduction is discussed.
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Kinetics of Inhibitory Feedback from Horizontal Cells to Photoreceptors: Implications for an Ephaptic Mechanism
TL;DR: The proposed ephaptic mechanism for HC feedback regulation of photoreceptor Ca2+ channels is eliminated and earlier proposals that synaptic cleft pH changes are more likely responsible are supported.
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Water impacts nutrient dose responses genome-wide to affect crop production.
TL;DR: It is shown that gene expression in rice responds differently to changes in the absolute amount of nitrogen available compared to nitrogen concentration and expression profiles associated with crop performance in arid, low-nutrient soils are identified.
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Recovery of Cable Properties Through Active and Passive Modeling of Subthreshold Membrane Responses From Laterodorsal Tegmental Neurons
TL;DR: An active membrane model that included a subthreshold A-type K+ current and/or a hyperpolarization-activated cation current (H-current) then was used to model cell behavior and the voltage traces calculated using this model were better able to reproduce the experimental data, and the cable parameters determined using this methodology were more consistent with those reported for other cells.