Trying things out. I will be posting mainly #neuroscience. So here is a question. What is the most important thing we need to be able to do to understand the principles on which brains work?

@dickretired Perturb brains circuits in the way that test state-space concepts of neural activity. E.g. stimulate on particular vectors to, e.g., move along a putative line attractor.

@SussilloDavid @dickretired I second this take from David. I would add, we need this for testing learning algorithms as well, bc we really need to be able to set specific activitystates to see how this induces changes downstream.

@tyrell_turing @SussilloDavid @dickretired Perturbing a system meaningfully requires first knowing the system. In this case a comprehensive #connectome that can serve as the basis for in silico analysis and simulation, and significant enrichment of the molecular properties and how the latter relate to the integration function of each neuron. Otherwise experimentation operates on far too incomplete data supplemented with educated guesses and assumptions.
#neuroscience

@albertcardona @tyrell_turing @SussilloDavid @dickretired Do you think this level of detail is as necessary in larger more complex brains? It seems if state spaces offer the right level of explanation then individual nodes of the network could rightfully be abstracted away.

@beneuroscience @tyrell_turing @SussilloDavid @dickretired Seems premature to dismiss data as unnecessary only because it’s hard to acquire.

@albertcardona @tyrell_turing @SussilloDavid @dickretired Not dismiss and maybe not unnecessary, but perhaps less of a priority? Just curious whether you think the level of explanation/abstraction should scale with the network complexity.