Good point, and yes, feedback is critical in CNS networks at several levels. But much of neural network analyses started with neural retina (retina is a fun wo

Good point, and yes, feedback is critical in CNS networks at several levels. But much of neural network analyses started with neural retina (retina is a fun word that is derived from reticulum = net). And the retina is mainly a feed-forward system or was perceived as such in the 1950s through 1970s. Even the cortex was and still is crudely modeled using mainly feed-forward connections. But the more you know about CNS structure and function, the more you see and appreciate feedback. Horizontal cells in retina provide a strong feedback integration/bias signal back to rod photoreceptors. Reciprocal dendro-dendritic synapses are key in many systems. Presynaptic terminals also respond to the same and transmitters that they release and the ion fluxes that they induce. At the level of connectomes the recursion is deep and hierarchical—see the lovely work by David van Essen and colleagues on the laughably complex connections among the dozens of cortical regions that respond to visual input from thalamus and midbrain (by the way—true, this is even in mouse). The ultimate feedback is of course generated by our own behavior——whether a blink, a saccade, or our own movements. Plunk an LLM in a Roomba but add with more input modes and more recursive self-prompting. That is a non-threatening start at what could also become SkyNet.