17 research outputs found
Short-Term Facilitation may Stabilize Parametric Working Memory Trace
Networks with continuous set of attractors are considered to be a paradigmatic model for parametric working memory (WM), but require fine tuning of connections and are thus structurally unstable. Here we analyzed the network with ring attractor, where connections are not perfectly tuned and the activity state therefore drifts in the absence of the stabilizing stimulus. We derive an analytical expression for the drift dynamics and conclude that the network cannot function as WM for a period of several seconds, a typical delay time in monkey memory experiments. We propose that short-term synaptic facilitation in recurrent connections significantly improves the robustness of the model by slowing down the drift of activity bump. Extending the calculation of the drift velocity to network with synaptic facilitation, we conclude that facilitation can slow down the drift by a large factor, rendering the network suitable as a model of WM
Synaptic mechanisms of interference in working memory
Information from preceding trials of cognitive tasks can bias performance in
the current trial, a phenomenon referred to as interference. Subjects
performing visual working memory tasks exhibit interference in their
trial-to-trial response correlations: the recalled target location in the
current trial is biased in the direction of the target presented on the
previous trial. We present modeling work that (a) develops a probabilistic
inference model of this history-dependent bias, and (b) links our probabilistic
model to computations of a recurrent network wherein short-term facilitation
accounts for the dynamics of the observed bias. Network connectivity is
reshaped dynamically during each trial, providing a mechanism for generating
predictions from prior trial observations. Applying timescale separation
methods, we can obtain a low-dimensional description of the trial-to-trial bias
based on the history of target locations. The model has response statistics
whose mean is centered at the true target location across many trials, typical
of such visual working memory tasks. Furthermore, we demonstrate task protocols
for which the plastic model performs better than a model with static
connectivity: repetitively presented targets are better retained in working
memory than targets drawn from uncorrelated sequences.Comment: 28 pages, 7 figure