<p>The strength of the synaptic weights are indicated by the colour (red being high and blue being low). Before training (top) the weight matrix is random (unstructured). After training (bottom) there are strong connections from all the inputs representing all transforms of one stimulus to particular output neurons (indicated by horizontal red stripes) and likewise for the input neurons representing transforms of the other stimulus to a different set of output neurons.</p
(A) Mean performance (red line) and standard deviation (blue lines) over time: unsupervised training...
(A) Mean performance (red line) and standard deviation (blue lines) over time: unsupervised training...
<p><b>(A)</b> Evolution of synaptic weights in the network during plasticity. After each batch of le...
<p>The top and the middle show the averaged weights before and after learning, respectively. The hei...
<p>Distribution of synaptic weights for different connection types: feedforward (left), feedback (mi...
<p>Plots A-D show the connection weights from neurons representing each cue (i.e., red and green) to...
<p><b>(A)</b> Initial connectivity matrix of the random network. Each excitatory neuron is connected...
<p>The input synaptic weight values are plotted in chronological order, with respect to their associ...
<p>Distribution of synaptic weights for three different connection types: feedforward (left), feedba...
(A) Dynamics of all incoming synapses to a single output layer neuron during InterleavedS,T1 trainin...
<p><b>A</b>: The training set, consisting of five samples of a handwritten <i>1</i>. Below a cartoon...
<p>The averaged weights after learning are shown. The height of each bar reflects the synaptic stren...
<p>(<b>A</b>) The network consists of a square grid of units with periodic boundary conditions in b...
<p>(A, B, C) These plots show the strength of synaptic outputs of three different cells over the cou...
<p>The development of the firing responses and synaptic weights of output neuron #79 before and afte...
(A) Mean performance (red line) and standard deviation (blue lines) over time: unsupervised training...
(A) Mean performance (red line) and standard deviation (blue lines) over time: unsupervised training...
<p><b>(A)</b> Evolution of synaptic weights in the network during plasticity. After each batch of le...
<p>The top and the middle show the averaged weights before and after learning, respectively. The hei...
<p>Distribution of synaptic weights for different connection types: feedforward (left), feedback (mi...
<p>Plots A-D show the connection weights from neurons representing each cue (i.e., red and green) to...
<p><b>(A)</b> Initial connectivity matrix of the random network. Each excitatory neuron is connected...
<p>The input synaptic weight values are plotted in chronological order, with respect to their associ...
<p>Distribution of synaptic weights for three different connection types: feedforward (left), feedba...
(A) Dynamics of all incoming synapses to a single output layer neuron during InterleavedS,T1 trainin...
<p><b>A</b>: The training set, consisting of five samples of a handwritten <i>1</i>. Below a cartoon...
<p>The averaged weights after learning are shown. The height of each bar reflects the synaptic stren...
<p>(<b>A</b>) The network consists of a square grid of units with periodic boundary conditions in b...
<p>(A, B, C) These plots show the strength of synaptic outputs of three different cells over the cou...
<p>The development of the firing responses and synaptic weights of output neuron #79 before and afte...
(A) Mean performance (red line) and standard deviation (blue lines) over time: unsupervised training...
(A) Mean performance (red line) and standard deviation (blue lines) over time: unsupervised training...
<p><b>(A)</b> Evolution of synaptic weights in the network during plasticity. After each batch of le...