Single Action Potentials and Subthreshold Electrical Events Imaged in Neurons with a Fluorescent Protein Voltage Probe

Paper site

A genetically encoded sensor of membrane potential, FlaSh, was first introduced by Siegel and Isacoff (1997) as a fusion between the Shaker potassium channel and wild-type green fluorescent protein from Aequorea victoria (aqGFP).

Subsequent ion channel-based voltage sensors were designed to include a single fluorescent protein or FPs that form Förster Resonance Energy Transfer pairs (FRET).

Reconstructing Networks with excitatory and inhibitory interactions from dynamics using Transfer Entropy

The inverse problem for neuronal networks is to infer its topology from analyzing its dynamics. Recently, transfer entropy[1], an information theoretical measure of directed interactions has become more popular for solving the inverse problem[2]. Due to its model-free nature, it can easily be applied to data in a variety of fields such as neuroscience, physiology, climate research and financial markets.

A hypothetical rivalry in retina and some spike sorting progress

As observed in my experiments, "achromatic" receptive fields may react similarly to blue or green light stimuli, which are the two observable colors in bullfrogs. However, under intermeshed blue and green light stimulus, we constantly (such experiment had been repeated for more than five times) see the activity of recorded ganglion cells synchronize to only one color. I suspect that the retina randomly "follow" a color, since the same retina could produce activity following blue or green light under a same stimulus, and uninfluenced by the starting color.

Workshop on Mathematical Biology & Complex Systems

NCTS Interdisciplinary Workshop on Mathematical Biology & Complex Systems
Date: Friday December 19, 2014, Saturday December 20, 2014
Place: Lecture Room B, 4F, General 3rd Building, NTHU
   Mathematics Biology Focus Program & Complex Systems Focus Group
   National Center for Theoretical Sciences, Hsinchu, Taiwan

Linear Nonlinear Model as a approximation for firing-rate coding neural system

Linear-nonlinear(LN) model is a approximation method for linking the time trace of stimulus with the firing rate. However, this is only a approximation and we can actually have some intuitive understanding about when it will fail.


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