ML/Neuroscience: TensorFlow vs PyTorch vs Keras for bulding NN models of the nervous system? I would be very grateful to people with experience in using neural network models in neuroscience for advice!

What approach would you recommend for building neural networks?

I am choosing between TensorFlow, PyTorch and Keras. An important aspect for me is to be able to easily access the params of the NN (especially the weights). I want to build encoding models of biological neurons so for me model transparency, interpretability and exploration capacity is as important (if not more) than performance metrics or efficiency.

Thanks!
If you want to build a neural network as a biological simulation, maybe none of these are the best options, since they are more suitable for deep neural networks. If you want to mimic synapses using some model as Hodgkin and Huxley, you must use some different approaches. For that, you may use NEURON environment (https://neuron.yale.edu/neuron/), which has some implementations of the theoretical models behind action potentials. It comes with a gui, but personally I don't like it, so I just code everything using their python's library. 

On the other hand, if you are just looking for a way to model a network, without adding too much complexity, then any of your examples are probably are ok to build directed graphs.