David W. Tank, Ph.D.
Biological Computation Research Department
Murray Hill, New Jersey
May 1, 2000
Cellular and Network Mechanisms of Persistent Neural Activity
Persistent neural activity is a sustained change in sodium action potential firing that has been observed in many brain areas involved in short term memory. We are studying the oculomotor neural integrator where persistent activity is a neural correlate of the short-term memory of eye position. The experimental preparation is the goldfish, which is particularly advantageous for a cellular and computational analysis of mechanisms. We find no evidence for plateau potentials or intrinsic oscillatory dynamics, two hypothesized cellular mechanisms for persistent neural activity. Partial pharmacological inactivation and analysis of changes in the rate of synaptic potentials are consistent with network mechanisms based on recurrent synaptic excitation. Finally, a visual training stimulus can profoundly alter the dynamics of persistent neural activity. The dependence on stimulus parameters suggests visual input is normally used to tune-up the neural integrator for better performance.
To test the reverberation hypothesis for persistent activity, the oculomotor integrator has been modeled as a network of conductance-based neurons interacting by recurrent excitation. The strength of synaptic feedback is tuned so that the network realizes "linear attractors" where the level of persistent activity varies linearly with the gaze position. The precision with which synaptic weights need to be fine-tuned depends on the time constant of the recurrent synapses, as it was emphasized previously by Seung. The issue of robustness for continuous attractors is discussed. These insights from computational modeling may be applied to short-term memory networks for a continuous quantity (in the form of continuous attractors) in general.