Left: The average PCI (indicated by the color scale) in CA3-CA3 projections for different DDN networks as a function of the mixing parameter α and the sparseness of the patterns a (see Fig 1). Sixteen sequences were stored. Based on our criteria, the CA3 network is able to successfully store and retrieve memory sequences when PCI > 0. PCI values are averaged across 20 repetition of the simulation. Right: The average proportion of large correlations between pairs of stored patterns, 〈ξCA3〉. The patterns in both panels confirm that PCI memory retrieval is only possible, i.e., PCI > 0, if 〈ξCA3〉 is near zero.</p
In addition to recurrent and output sparsity, we explored the effects of input connection sparsity. ...
The CA3 region of the hippocampus is a recurrent neural network that is essential for the storage an...
Recurrent Neural Networks (RNNs) are variants of Neural Networks that are able to learn temporal rel...
Left: Recall performance as quantified by the pattern completion index (PCI) in CA3-CA3 projections,...
The average PCI value, which is calculated based on the results in Fig 3, right column, are shown in...
Average recall performance 〈PCI〉 in the complete loop for different DDN networks as a function of th...
Left: Shown is the average PCI when comparing the retrieval quality of the first and last patterns o...
Left: Each panel on the left column shows an example of the retrieval quality in a CA3 model as labe...
<p><b>A</b>: Recall performance in the model as proposed in [<a href="http://www.ploscompbiol.org/ar...
Histograms of correlations between retrieved patterns and corresponding stored patterns (blue) and b...
The retrieval correlations of the last sequence element in the output is compared to the retrieval q...
Each panel shows the average correlation between retrieved and originally stored patterns for a diff...
Episodic memories have been suggested to be represented by neuronal sequences, which are stored and ...
Episodic memories have been suggested to be represented by neuronal sequences, which are stored and ...
International audienceWe study various models of associative memories with sparse information, i.e. ...
In addition to recurrent and output sparsity, we explored the effects of input connection sparsity. ...
The CA3 region of the hippocampus is a recurrent neural network that is essential for the storage an...
Recurrent Neural Networks (RNNs) are variants of Neural Networks that are able to learn temporal rel...
Left: Recall performance as quantified by the pattern completion index (PCI) in CA3-CA3 projections,...
The average PCI value, which is calculated based on the results in Fig 3, right column, are shown in...
Average recall performance 〈PCI〉 in the complete loop for different DDN networks as a function of th...
Left: Shown is the average PCI when comparing the retrieval quality of the first and last patterns o...
Left: Each panel on the left column shows an example of the retrieval quality in a CA3 model as labe...
<p><b>A</b>: Recall performance in the model as proposed in [<a href="http://www.ploscompbiol.org/ar...
Histograms of correlations between retrieved patterns and corresponding stored patterns (blue) and b...
The retrieval correlations of the last sequence element in the output is compared to the retrieval q...
Each panel shows the average correlation between retrieved and originally stored patterns for a diff...
Episodic memories have been suggested to be represented by neuronal sequences, which are stored and ...
Episodic memories have been suggested to be represented by neuronal sequences, which are stored and ...
International audienceWe study various models of associative memories with sparse information, i.e. ...
In addition to recurrent and output sparsity, we explored the effects of input connection sparsity. ...
The CA3 region of the hippocampus is a recurrent neural network that is essential for the storage an...
Recurrent Neural Networks (RNNs) are variants of Neural Networks that are able to learn temporal rel...