1. A node in a computer-implemented hierarchical temporal memory network, the node associated with a child node, the node comprising: a spatial pooler adapted to generate and store information about spatial co-occurrences of first input patterns received at the node based on spatial similarity of the first input patterns in a learning stage, the spatial pooler generating an output representing information about second input patterns received in an inference stage subsequent to the learning stage corresponding to the spatial co-occurrences based on the spatial co-occurrences information, at least part of the first input patterns and at least part of the second input patterns received from the child node; a temporal pooler adapted to generate and store temporal statistics data indicating whether the second input patterns include a spatial co-occurrence based on spatial co-occurrences preceding the spatial co-occurrence in the second input patterns and temporal relationships of the spatial co-occurrences learned in the learning stage; and a top-down message generator adapted to generate a first top-down message representing information about a state of the node in the inference stage based on the spatial co-occurrences information and the temporal statistics data, the top-down message generator adapted to send the first top-down message to the child node.
1. A node in a computer-implemented hierarchical temporal memory network, the node associated with a child node, the node comprising: a spatial pooler adapted to generate and store information about spatial co-occurrences of first input patterns received at the node based on spatial similarity of the first input patterns in a learning stage, the spatial pooler generating an output representing information about second input patterns received in an inference stage subsequent to the learning stage corresponding to the spatial co-occurrences based on the spatial co-occurrences information, at least part of the first input patterns and at least part of the second input patterns received from the child node; a temporal pooler adapted to generate and store temporal statistics data indicating whether the second input patterns include a spatial co-occurrence based on spatial co-occurrences preceding the spatial co-occurrence in the second input patterns and temporal relationships of the spatial co-occurrences learned in the learning stage; and a top-down message generator adapted to generate a first top-down message representing information about a state of the node in the inference stage based on the spatial co-occurrences information and the temporal statistics data, the top-down message generator adapted to send the first top-down message to the child node. 4. The node of claim 1 , wherein the top-down message generator is adapted to generate the first top-down message by multiplying a downward dynamic variable, the output of the spatial pooler in the inference stage, and the temporal statistics data, the downward dynamic variable representing history of a state of the node.