This repository hosts the notebooks and scripts that we'll be using to simulate the NM imaging pipeline: starting from neuron activity to the generated df/f signal. The main goal is to assess how the calculation of f can affect the df/f signal produced.
- Simulation.ipynb is the notebook with the documentation of the analysis
- f_rate.py and f_rate2.py both have bleaching analyses to supplement the simulation notebook -- analyse the relation between the firing rate and the signal
- s_functions is the library that has the main simulation functions used in the bleaching analyses in the f_rate, f_rate2 and scripts
- b_factory is another library with some bleaching functions used in the comparison of bleach factors in the bleach_compare script
- bleach_compare calls the function in b_factory and was used to compare the effects of bleaching on the signal to noise ratio
- bleaching G0 is the first script that was used ibn the bleaching analysis: it was used as a foundation for the more up to date b_factory library
This repository is still new, so there's probably still errors in the code -- if you find some please raise an issue and we can resolve it.
Specifics on the simulation
We're modelling (simulating) the dynamics of neuromodulator concentration [x] and neuromodulator bound to sensor [x s] and to receptor [x r]. This is equivalent to intracellular calcium measurements in the presence of endogenous ca buffers and exogenous buffers (the sensors). Here, we assume that we are dealing with one compartment in equilibrium to start and everything is linear, including uptake. The Source of x is a train of spikes, each producing a fixed delta_x. -- the inspiration for the model comes from Neher's work with calcium that Karel suggested on email.