<p><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0002577#pone-0002577-g001" target="_blank">Figure 1</a>, top, (left): a network with 100 units with connections of random strength and with no specific pattern learned (for clarity only neighbouring connections are shown). <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0002577#pone-0002577-g001" target="_blank">Figure 1</a>, top (middle and right): learning pattern ‘A’. Top (middle): presenting ‘A’; top (right): connections between units related to ‘A’ are strengthened. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0002577#pone-0002577-g001" target="_blank">Figure 1</a>, bottom, (left): presenting part of ‘A’. Bottom (righ...
<p>The single network is fully connected. The excitatory neurons are divided into N selective pools ...
This paper demonstrates how a feedforward network with constant connection matrices may be used to t...
<p><b>A</b>, An example of connectivity matrix for 80 excitatory neurons containing a single cluster...
<p><b>(A)</b> Alternate network schematic with hypercolumns (large black circles), along with their ...
seung~bell-labs.com One approach to invariant object recognition employs a recurrent neu-ral network...
International audienceAre humans able to learn never seen items from pattern attractors generated by...
Attractor networks are widely believed to underlie the memory systems of animals across different sp...
A network graph describes the web of connections between entities in a system. Network graphs are a ...
A learning algorithm for single layer perceptrons is proposed. First, cone-like domains, each of whi...
A. Illustration of the network topology searching. Dashed arrows are regulations sampled. The topolo...
Most theoretical studies of the computational capabilities of balanced, recurrent E/I networks assu...
The dataset contains the data underlying the results presented in: Boscaglia, M., Gastaldi, C., G...
<p><b>Copyright information:</b></p><p>Taken from "A neuroanatomically grounded Hebbian-learning mod...
<p>(<b>A–C</b>) Discrete input patterns give rise to clusters in the functional connectivity of the ...
An attractor neural network on the small-world topology is studied. A learning pattern is presented...
<p>The single network is fully connected. The excitatory neurons are divided into N selective pools ...
This paper demonstrates how a feedforward network with constant connection matrices may be used to t...
<p><b>A</b>, An example of connectivity matrix for 80 excitatory neurons containing a single cluster...
<p><b>(A)</b> Alternate network schematic with hypercolumns (large black circles), along with their ...
seung~bell-labs.com One approach to invariant object recognition employs a recurrent neu-ral network...
International audienceAre humans able to learn never seen items from pattern attractors generated by...
Attractor networks are widely believed to underlie the memory systems of animals across different sp...
A network graph describes the web of connections between entities in a system. Network graphs are a ...
A learning algorithm for single layer perceptrons is proposed. First, cone-like domains, each of whi...
A. Illustration of the network topology searching. Dashed arrows are regulations sampled. The topolo...
Most theoretical studies of the computational capabilities of balanced, recurrent E/I networks assu...
The dataset contains the data underlying the results presented in: Boscaglia, M., Gastaldi, C., G...
<p><b>Copyright information:</b></p><p>Taken from "A neuroanatomically grounded Hebbian-learning mod...
<p>(<b>A–C</b>) Discrete input patterns give rise to clusters in the functional connectivity of the ...
An attractor neural network on the small-world topology is studied. A learning pattern is presented...
<p>The single network is fully connected. The excitatory neurons are divided into N selective pools ...
This paper demonstrates how a feedforward network with constant connection matrices may be used to t...
<p><b>A</b>, An example of connectivity matrix for 80 excitatory neurons containing a single cluster...