Cool progress on a new model organism and toolbox for behavioral analysis. The main advantage appears to be the spatial separation of neurons. (I have not yet r

Cool progress on a new model organism and toolbox for behavioral analysis. The main advantage appears to be the spatial separation of neurons. (I have not yet read the paper in Cell.) As to the “mind” of a jellyfish, mouse, or human: much of the core computational activity is molecular, synaptic, and electrotonic—and is not associated with large membrane voltage swings. These lower tiers of processing are orders of magnitude faster and smaller than the network activity patterns linked to behavior. It is great to understand crude input-output relations—now at neuronal network level dynamics. But how is this much different than what we know about spinal cord circuitry for reflex control in mammals or cortical-cerebellar control of movement initiation and control. Is it fundamentally a better system or is it simply more colorful, “elegant”, and semi-real time? IMHO; the latter. Not sure these are quite the right metaphors, but imagine trying to understand microprocessor function from either just input and output relations or from timelapse data on CPU transistor currents—but only every few milliseconds. To understand neuronal computation we must, at a minimum, record synaptic and membrane currents across cells and circuits at the 0.1 millisecond levels over minutes and hours. And preferably across many environmental perturbations (see Ev Marder’s amazing work on the shocking complexity of somatogastric ganglia of crustaceans.) And to understand the true sources of behavioral variation in a causally rigorous way we will also need gentle genetic perturbation generated by natural DNA variants—not knockouts on one genetic background—that is a misdirected focus of so much reductionist N=1 neuroscience.