timkimd/plnde
Code for "Inferring Latent Dynamics Underlying Neural Population Activity via Neural Differential Equations"
This helps neuroscientists understand the underlying, hidden brain activity that drives observed neural spikes. You input recordings of neural spike trains and any associated sensory inputs, and it outputs a model that reveals the low-dimensional, continuous 'latent' dynamics, or patterns of activity, within the neural population. This is ideal for computational neuroscientists studying how brain circuits process information.
No commits in the last 6 months.
Use this if you need to infer the continuous, unobservable brain states that give rise to recorded neural spiking patterns.
Not ideal if your goal is to analyze individual neuron behavior rather than population-level dynamics, or if you don't work with neural spike train data.
Stars
14
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Language
Julia
License
MIT
Category
Last pushed
Jul 26, 2021
Commits (30d)
0
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