<p>(A) Examples of natural images used for training. The square denotes model V1 receptive field size. (B) V1 receptive fields after training. Plots are scaled in magnitude so that each fills the gray scale, but with zero always represented by the same gray level. Black depicts off-regions in the model V1 receptive field, white depicts on-regions.</p
<p>a) Maximum number of spikes in response to a black or white stimulus for the superficial layers, ...
<p>(A) Panoramic high dynamic range input image used exemplarily for stimulation. (B) Color coded st...
<p><b>A</b>: The model consists of two separate feature channels (Feat-1 and Feat-2) each with two l...
<p>(A) Examples of receptive fields learned by the 81- and 36-hidden unit models after training on d...
<p>Population analyses of receptive field properties of output neurons during succcessive stages of ...
<p>(<b>a</b>) Information as a function of the number of learning steps peaks and then plateaus. The...
<p>The figure depicts learned connection weights from 64 LGN off-center type ...
<p>Orientation maps and simple cell receptive fields generated by the model. The orientation map and...
<p>(A) Simple cell receptive fields of the SC model. Each square is of size 3232 pixels and shows th...
There is no special feature before training since the weights are initialized randomly. As the train...
<p><b>A</b> Image patch (bottom left) showing an intersection of two branches extracted from a grey-...
We study several statistically and biologically motivated learning rules using the same visual envir...
We study several statistically and biologically motivated learning rules using the same visual envir...
<p>(A) An example set of generative fields , for ( pixels). Due to the normalization, different rec...
<p>(<b>a-i</b>) Receptive field obtained for network simulations with the quadratic rectifier (top),...
<p>a) Maximum number of spikes in response to a black or white stimulus for the superficial layers, ...
<p>(A) Panoramic high dynamic range input image used exemplarily for stimulation. (B) Color coded st...
<p><b>A</b>: The model consists of two separate feature channels (Feat-1 and Feat-2) each with two l...
<p>(A) Examples of receptive fields learned by the 81- and 36-hidden unit models after training on d...
<p>Population analyses of receptive field properties of output neurons during succcessive stages of ...
<p>(<b>a</b>) Information as a function of the number of learning steps peaks and then plateaus. The...
<p>The figure depicts learned connection weights from 64 LGN off-center type ...
<p>Orientation maps and simple cell receptive fields generated by the model. The orientation map and...
<p>(A) Simple cell receptive fields of the SC model. Each square is of size 3232 pixels and shows th...
There is no special feature before training since the weights are initialized randomly. As the train...
<p><b>A</b> Image patch (bottom left) showing an intersection of two branches extracted from a grey-...
We study several statistically and biologically motivated learning rules using the same visual envir...
We study several statistically and biologically motivated learning rules using the same visual envir...
<p>(A) An example set of generative fields , for ( pixels). Due to the normalization, different rec...
<p>(<b>a-i</b>) Receptive field obtained for network simulations with the quadratic rectifier (top),...
<p>a) Maximum number of spikes in response to a black or white stimulus for the superficial layers, ...
<p>(A) Panoramic high dynamic range input image used exemplarily for stimulation. (B) Color coded st...
<p><b>A</b>: The model consists of two separate feature channels (Feat-1 and Feat-2) each with two l...