1. A computer-implemented method for detecting anomalous events using a long- term memory in a video analysis system configured to observe patterns of behavior depicted in a sequence of video frames, comprising: receiving an active percept, wherein the active percept comprises a sub-graph of a neural network excited by a semantic symbol stream, wherein the semantic symbol stream describes objects depicted in the sequence of video frames; querying the long-term memory using the active percept as an input stimulus; receiving, in response to the querying, a retrieved percept from the long-term memory and an occurrence frequency (F) of the retrieved percept, wherein the retrieved percept encodes a pattern of behavior previously observed by the video analysis system; determining a distance (d) between the active percept and the retrieved percept; and upon determining the distance (d) exceeds a specified threshold, publishing an alert notification indicating the occurrence of an anomalous event, as represented by the active percept.