Neural Dynamics and Biophysics of Active Memory

The life of all mammals and birds often involves situations where information has to be integrated across short periods of time. This is for instance the case when consistent temporal relations between events in a sequence are to be exploited for prediction, or when a behavioral choice crucially depends on recently encountered stimuli ('non-Markovian decision problems'). Such situations require active (working) memory, the ability to maintain information within the ongoing neural dynamics (as opposed to, e.g., synaptic long-term plasticity). Based on in-vivo electrophysiological recordings from behaving animals, various neuro-dynamical mechanisms for the active maintenance of information have been suggested. Most of them rest on the idea of multistability in the sense of multiple co-existing attractor states of the population firing rate. More recent models, again fed by physiological observations, employ long effective time constants close to bifurcations, or store information within the phase-relation patterns of neural spike times (weak phase-locking). These ideas and their empirical basis will be discussed, with emphasis on the biophysical mechanisms that could give rise to the various dynamical phenomena. In particular, the special role of NMDA synaptic currents in controlling neural system dynamics in intriguing and computationally important ways will be highlighted.