Predicting neuron types based on synaptic connectivity graphs
AssigneeX Development LLC
InventorsSarah Ann Laszlo, Georgios Evangelopoulos, Philip Edwin Watson
Life of this patent
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AssigneeX Development LLC
InventorsSarah Ann Laszlo, Georgios Evangelopoulos, Philip Edwin Watson
Estimating the term…
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining an artificial neural network architecture corresponding to a sub-graph of a synaptic connectivity graph. In one aspect, there is provided a method comprising: obtaining data defining a graph representing synaptic connectivity between neurons in a brain of a biological organism; determining, for each node in the graph, a respective set of one or more node features characterizing a structure of the graph relative to the node; identifying a sub-graph of the graph, comprising selecting a proper subset of the nodes in the graph for inclusion in the sub-graph based on the node features of the nodes in the graph; and determining an artificial neural network architecture corresponding to the sub-graph of the graph.
A method performed by one or more data processing apparatus, the method comprising:
The method of claim 6, wherein the particular function is a visual data processing function, and further comprising providing an artificial neural network having the artificial neural network architecture corresponding to the sub-graph of the graph for performing an image processing task.
A system comprising:
One or more non-transitory computer storage media storing instructions that when executed by one or more computers cause the one or more computers to perform operations comprising:
Dependencies are inferred from the claim text.