A lighthouse for neural modeling [Book Review]

A famous theorem in astrophysics states, "A black hole has no hair." It implies that, under steady-state conditions, a macroscopic black hole, such as the monster engulfing the center of our galaxy, can be exactly described by three variables: its mass, angular rotation and charge. This is not an approximation under highly idealized conditions but describes the real universe. Contrast this with a single chemical synapse characterized by a myriad of pre- and postsynaptic properties—the probability of release of a vesicle, its ionic reversal potential, number and time constants of activation and inactivation of the underlying channels and so on—that change in complex and ill-understood ways as a function of the prior usage of the synapse. No wonder, then, that theoreticians have had a vastly more difficult time making sense of the nervous system than physicists have had in rendering the structure and evolution of the universe comprehensible. It is therefore immensely satisfying to open the pages of Theoretical Neuroscience to see how much progress has occurred over the past 20 years in our emerging understanding of computation, coding, representation and learning in brains.