This poster introduces a theory of sequence memory in the neocortex called HTM Sequence Memory. This neural mechanism is based on how the brain processes streams of sensory inputs to perform sequence recognition, sequence prediction, and behavior generation.
The three key characteristics of HTM Sequence Memory are:
- Neurons learn to recognize hundreds of patterns using active dendrites.
- Recognition of patterns act as predictions by depolarizing the cell without generating an immediate action potential.
- A network of neurons with active dendrites forms a powerful sequence memory.
The HTM neuron models active dendrites that act as pattern detectors. Each cell can recognize hundreds of unique patterns.
HTM exhibits many desirable features for sequence learning:
- Unsupervised learning
- Quickly adapts to changes in data
- Learns high-order structure in sequences
- Robust and fault tolerant
- Makes multiple simultaneous predictions
- Works well on real-world problems
- Accurate biological model