How far can RiaB go as a platform for linking behavior to neural activity?

[jerlich]

My understanding of the current implementation is that the OVC and place cells in RiaB are essentially sensory neurons (activity is controlled by relationship of the agent to the world with no intrinsic dynamics, no internal connections and no state), and yet we know these neurons are deep in the brain, deeply interconnected, we know there are phenomena like remapping, and state dependent phenomena.

Is RiaB an appropriate platform / foundation for examining these more realistic neural mechanisms? What does the path to there look like?

[TomGeorge1234]

Hi Jeff, in summary I advocate for the approach the RiaB should provide the essentials and users should consider the complexities. In more details, to some extent yes, to some extent no:

• No because (in my opinion, others may disagree) RiaB should focus on providing the core tools necessary to make biologically realistic models of neural data and behaviour...not the models themselves (in reality this isn't so black and white and feature creep is possible). Users are encouraged to make their own cell classes which build from, but may be more complex than, PlaceCells, ObjectVectorCells` etc.
• Yes because, to some extent, we already do this. The FeedForwardLayer class are intermediate neurons. Their activity isn't explicitly controlled by the state of the Agent but by the state of their input Neurons which may (in the case of PlaceCells) or may not (in the case of other FeedForwardLayers) directly encode the state of the Agent. Coming soon is (name tbc) NeuralNetworkNeurons where the mapping from input neurons to firing rate is defined by the user in terms of any pytorch nn.Module neural network thus allowing users to create highly complex, and trainable cell classes which still benefit from the nice RiaB plotting functions, Agent etc.

More abstract StateNeurons which depend not simply on the Agents position/velocity would be easy to make and I encourage it but for now I don't think I want to go down the path of providing them in-house as the scope is so broad. I'm thinking of making a demo which might point people in the right direction...any ideas (maybe SplitterCells which could be nice as you'd require a state encoding which arm you recently came down)?

P.s. PlaceCells have remapping (try call PlaceCells.remap()) but even the existence of this method should raise alarm bells (how does remapping work? Is it fully random, it's not in the brain! Does it remap by the same mechanisms of neurons in the brain) which demonstrate why it's about as far down the biological realism rabbit hole I'd like to go for now.