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Gated working memory is defined as the capacity of holding arbitrary information at any time in order to be used at a later time. Based on electrophysiological recordings, several computational models have tackled the problem using dedicated and explicit mechanisms. We propose instead to consider an implicit mechanism based on a random recurrent neural network. We introduce a robust yet simple reservoir model of gated working memory with instantaneous updates. The model is able to store an arbitrary real value at random time over an extended period of time. The dynamics of the model is a line attractor that learns to exploit reentry and a nonlinearity during the training phase using only a few representative values. A deeper study of the model shows that there is actually a large range of hyperparameters for which the results hold (e.g., number of neurons, sparsity, global weight scaling) such that any large enough population, mixing excitatory and inhibitory neurons, can quickly learn to realize such gated working memory. In a nutshell, with a minimal set of hypotheses, we show that we can have a robust model of working memory. This suggests this property could be an implicit property of any random population, that can be acquired through learning. Furthermore, considering working memory to be a physically open but functionally closed system, we give account on some counterintuitive electrophysiological recordings.
This article was published in the following journal.
Name: Neural computation
There are inherent trade-offs between the flexibility and the capacity of working memory, or the ability to temporarily hold information "in mind." In a recent issue of Neuron, Bouchacourt and Buschma...
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Type of declarative memory, consisting of personal memory in contrast to general knowledge.
Method of isolation and maintenance of a working heart for various cardiac measurements. The model allows for the separation of cardiac and systemic variables in the denervated heart.
Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc.
People who are in the labor force either working or looking for work for 27 weeks or more in a year, but whose income fall below a given poverty line.
A neuropsychological test designed to assess different memory functions. It may incorporate an optional cognitive exam (Brief Cognitive Status Exam) that helps to assess memory related cognitive function.