Search

Population coding, where neurons with broad and overlapping firing rate tuning curves collectively encode information about a stimulus, is a common feature of sensory systems. We use decoding methods and measured properties of NMDA-mediated LTP induction to study the impact of long-term potentiation of synapses between the neurons of such a coding array. We find that, due to a temporal asymmetry in the induction of NMDA-mediated LTP, firing patterns in a neuronal array that initially represent the current value of a sensory input will, after training, provide an experienced-based prediction of that input instead. We compute how this prediction arises from and depends on the training experience. We also show how the encoded prediction can be used to generate learned motor sequences, such as the movement of a limb. This involves a novel form of memory recall that is driven by the motor response so that it automatically generates new information at a rate approximate for the task being performed.

Using experimental facts about long-term potentiation (LTP) and hippocampal place cells, we model how a spatial map of the environment can be created in the rat hippocampus. Sequential firing of place cells during exploration induces, in the model, a pattern of LTP between place cells that shifts the location coded by their ensemble activity away from the actual location of the animal. These shifts provide a navigational map that, in a simulation of the Morris maze, can guide the animal toward its goal. The model demonstrates how behaviorally generated modifications of synaptic strengths can be read out to affect subsequent behavior. Our results also suggest a way that navigational maps can be constructed from experimental recordings of hippocampal place cells.

1. We present a new mathematical description of the complete distribution of electrical responses to stochastic synaptic activity (quantal analysis) that is intended as a model of experiments on central neuronal synapses. Unlike previous treatments, this distribution is calculated for each instant after the release of transmitter into the cleft. 2. We follow the traditional description of probabilistic presynaptic vesicle release. On the postsynaptic side, however, we assume that channel fluctuations are important and we take them into account. The probability of finding a given channel open after a certain amount of transmitter is released is calculated from detailed receptor/channel and neurotransmitter clearance kinetics. This approach allows us to naturally include the nonlinear dependence of open probability on the amount of transmitter released, with saturation for large transmitter doses. The distribution of open channels is calculated from this probability. 3. We also allow the possibility that multiple synaptic inputs to a target neuron may be active in a typical experiment. We have not treated cable effects. We explore the implications of multiple synapses for the nonlinearities of the system. The most important of these is that vesicles in different synapses have independent responses, and therefore their effects add linearly. 4. The resulting distributions depend heavily on what region of the nonlinear dose-response curve the synapses are in. Far from saturation, peaks in the distribution are due to vesicles, and close to saturation they are due to active synapses. Peak widths are due to channel fluctuations and instrumental noise, which we introduce to make closer contact with experiments.(ABSTRACT TRUNCATED AT 250 WORDS)