Figure 3.

Computational proposals for prediction and memory. (a) A depiction of the initial, sensory-evoked response (gray arrows and green circles) at the first time point (t = 0). All other panels depict the processing that happens at the next time point (t = Δt) for three different models of prediction. (b) A predictive architecture in which memories of recent stimulus history are stored via adaptation (red arrows), which can take the form of gain adaptation (bottom layer, lighter green circles) or adaptation of the feedforward synapses that connect the layers. In this class of model, connectivity is exclusively feedforward. (c) A predictive architecture in which memories of recent stimulus history are maintained via persistent, recurrent activity (red arrows) and extrapolation of recent events into future predictions happens via feedback (blue arrows). (d) A predictive architecture that extrapolates the current sensory input forward in time using hippocampal pattern completion and integrates this information with incoming sensory signals via feedback (blue arrows).