Temporal processing scheme and sensorimotor information processing

A computing device, comprising:

• a processor;
• a first node comprising:
• a spatial pooler configured to detect a plurality of spatial patterns in an input data at a first time, and generate a first sparse vector in a sparse distributed representation based on the plurality of spatial patterns detected at the first time;
• and
• a sequence processor configured to:
• predict spatial patterns to appear in the input data at a second time subsequent to the first time by processing the generated first sparse vector based on connections representing stored relationships of temporal sequences of spatial patterns in the input data detected before the first time, and
• generate output vectors from the first node that vary over time based on the prediction, first elements of the output vectors maintained active for a first period of time responsive to prediction associated with the first elements as being determined inaccurate, second elements in the output vectors maintained active for a second period of time longer than the first period responsive to prediction associated the second elements determined as being accurate, and
• update, as part of training, the connections based on activation of the first elements for the first period of time and the second elements for the second period of time.