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Input strength and time-varying oscillation peak frequency (Cohen MX 2014)

modeldb.science/154770

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Name		Name	Last commit message	Last commit date
Latest commit History 1 Commit
adex_network2column.py		adex_network2column.py
adex_network2column_sineinput.py		adex_network2column_sineinput.py
adex_static_basic_analysis.m		adex_static_basic_analysis.m
eegfilt.m		eegfilt.m
eqs4bursting.py		eqs4bursting.py
eqs4fastspiking.py		eqs4fastspiking.py
eqs4reguspiking.py		eqs4reguspiking.py
izh_freqslide_static.m		izh_freqslide_static.m
izh_freqslide_timevaryinginput.m		izh_freqslide_timevaryinginput.m
izh_freqslide_timevaryinginput3networks.m		izh_freqslide_timevaryinginput3networks.m
readme.html		readme.html
screenshot2c.png		screenshot2c.png
screenshot2e.png		screenshot2e.png
screenshotAPraster.png		screenshotAPraster.png
screenshotLFPpower.png		screenshotLFPpower.png

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<html><pre>
Readme file for:

Cohen, MX (2014). Fluctuations in oscillation frequency control spike
timing and coordinate neural networks. Journal of Neuroscience.

These files were contributed by Mike X Cohen.

Matlab files (*.m) are for Figure 2. They are cross-platform and do
not require any toolboxes. The neuron equations are based on
Izhikevich 2003. Additional comments can be found in the .m files.

The code for Fig. 2c is izh_freqslide_timevaryinginput.m and
generates:

<img src="./screenshot2c.png" alt="screenshot 2c" width="550">

Running the Fig. 2e code, izh_freqslide_timevaryinginput3networks.m,
generates a figure like

<img src="./screenshot2e.png" alt="screenshot 2e" width="550">

Python files (*.py) are for Figure 3. The scripts require the Brian
toolbox (Goodman and Brette, 2008) in Python 2.7. (Running the scripts
in a different version of Python or Brian may require some
re-programming.) The script will produce a .mat file that can be
imported into Matlab. Additional comments can be found in the files
adex_*.py.

An example run of the network in a linux shell prompt:

$ python adex_network2column_sineinput.py 20140602_1650.mat

then analyzed at the matlab command prompt:

>> load 20140602_1650.mat
>> adex_static_basic_analysis

makes graphs of the network activity:

<img src="./screenshotAPraster.png" alt="raster plot" width="550">

and power spectrum that includes the region in Figure 3A:

<img src="./screenshotLFPpower.png" alt="power spectrum" width="550">

however as the matlab figure is just one example its a lot more noisy
because figure 3A contains the results averaged over 100 runs.

</pre></html>