Python & Machine leaning project

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شرح پروژه

Here are the directives for the work:

For 2 interconnected mean-field model of neural colomns, make a 2D graph for 4 adaptation values b (1,20,40,60) pico ampere and for each of the 4 populations of the two columns (2 populations per column) for ithe nterconnected mean-fields.
I would need to correct and run simulations (the structure and simulation codes are already ready and attached in the zip file).
The range of excitatory synaptic weights in which irregular asynchronous states, limit cycle oscillations, and up and downs states .., etc are observed should be first found for each value of b =[1,20,40,60] pico ampere.

Once the interval has been defined for each value of b, run the main simulation (nested loops of excitatory synaptic weights and the delay between connections [1 to 5] milliseconds ) and finally draw a 2D graph of the mean firing rate of each population as a function of the pair of [delays, synaptic weights] (example of the desired graph attached).

However I do need someone to:
1- Fix the MeanField_dn_dp_delay function in the MF_functions_clean.py file to make sure that the delay is taken into account in the simulations and that there is increment of x values for each time step

Please find attached, the details of the task.
The paragraph below highlighted in blue needs to be done and delivered by 5th Nov. In case the client is not happy with the initial work, the order will be refunded hence exceptional quality is required.

I would like to see for the first value of b=1pA the graphics of the mean firing rate of the four population and the bifurcation state transition if these ones are good then I will go on with your expert
Is it possible to do this please at first ? I mean following the work done to be sure he/she is an expert and knows everything about what I ask for
Let’s say within half a week I could get the first results and then if everything seems good (the interpretation as well)

Zip file https://1drv.ms/u/s!AvkMh6nFocMJgfUZ22UEltRKhFJXkA?e=SRzQis

Here are the directives for the work:

For 2 interconnected mean-field model of neural colomns, make a 2D graph for 4 adaptation values b (1,20,40,60) pico ampere and for each of the 4 populations of the two columns (2 populations per column) for ithe nterconnected mean-fields. The configuration of the connections is displayed in an image attached. The inhibitors are not connected and the columns receive only lateral exciters connections. (Rs-fs scheme).
I would need to correct and run simulations (the structure and simulation codes are already ready and attached in the zip file).
The range of excitatory synaptic weights in which irregular asynchronous states, limit cycle oscillations, and up and downs states .., etc are observed should be first found for each value of b =[1,20,40,60] pico ampere.

Once the interval has been defined for each value of b, run the main simulation (nested loops of excitatory synaptic weights and the delay between connections [1 to 5] milliseconds ) and finally draw a 2D graph of the mean firing rate of each population as a function of the pair of [delays, synaptic weights] (example of the desired graph attached).

However I do need someone to:
1- Fix the MeanField_dn_dp_delay function in the MF_functions_clean.py file to make sure that the delay is taken into account in the simulations and that there is increment of x values for each time step

2- Test in interconn_sim1_delay_new.py the 10 qe values and 5 delay values for each b value to determine where the system limits (0Hz to 200Hz) and identify where there are oscillations. For the integration method rk4_dn_dp_general (runge kutta fourth order) is better.

PS: normally for b=1pA, qe=[1. 6e-9, at 2. 2e-9] or [4. 5e-9 to 5e-9] and for b=60pA, qe=[2e-9, 2. 4e-9]

3- Check that the connection indices of the synaptic connection matrix and the delays matrix are corrects

4- Make a graph for all the system, excitatory and inhibitory populations (4 graphs of mean firing rate for each b value and 4 graphs of bifurcation of states of the brain obtained by peak of the power spectrum or study of the standard deviation of each population). An example is attached for the birfurcation and 4 examples are attached for the mean firing rate of each population.

4- Check with the code AdEx_twoNW_2.py by replacing qe and delays for oscillations cases to compare with the mean-field graph


5- Do the same graph with the AdEx models with the code AdEx_twoNW_2.py to check the validity of the mean-field models

The codes are provided, but you have to dtect what doesn’t work because I can’t get a correct  2D graphic simulation. I want to be constantly in touch  with the supervisor to move forward.

این پروژه شامل 2 فایل مهم است، لطفا قبل از ارسال پیشنهاد حتما نسبت به بررسی این فایل اقدام فرمایید.

مهارت ها و تخصص های مورد نیاز

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