The LNKS model is used in the lab to understand the computations and properties of contrast adaptation in the retina. The model consist of a cascaded connection of four model blocks - linear filter, nonlinearity(threshold, saturation), a first-order dynamic system(markov chain like transition), and a nonlinearity with a feedback. The four blocks have close connection to the biophysical mechanisms in the retina, allowing us to discover where and how the adaptive properties arise in the retinal circuitry.

This repository keeps the tools and examples for using Linear-Nonlinear-Kinetics-Spiking(LNKS) model, also including tools for Linear-Nonlinear-Kinetics(LNK) model and Spiking(S) model as well.

Reference of LNK model and contrast adaptation: Ozuysal and Baccus, Neuron 2012

Clone the repo, and compile the c-extension

$ git clone https://github.com/baccuslab/LNKS.git
$ cd LNKS
$ ./setup

Add LNKS/code and LNKS/optimization-src directories path to the PYTHONPATH.

Please see the example of using cellclass.

Optimization instructions can be found in optimization-src directory.

Managing optimization results in MySQL database gives much more efficiency. Download the MySQL dmg file here.