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Book by Jeff Hawkins

On Intelligence: How a New Understanding of the Brain will Lead to the Creation of Truly Intelligent Machines is a 2004 book by Jeff Hawkins and Sandra Blakeslee. The book explains Hawkins' memory prediction framework theory of the brain and describes some of its consequences.

Hawkins' basic idea is that the brain is a mechanism to predict the future, specifically, hierarchical regions of the brain predict their future input sequences. Perhaps not always far in the future, but far enough to be of real use to an organism. As such, the brain is a feed forward hierarchical state machine with special properties that enable it to learn.

2. In primary sensory cortex, Hawkins predicts, for example, "we should find anticipatory cells in or near V1, at a precise location in the visual field (the scene)". It has been experimentally determined, for example, after mapping the angular position of some objects in the visual field, there will be a one to one correspondence of cells in the scene to the angular positions of those objects. Hawkins predicts that when the features of a visual scene are known in a memory, anticipatory cells should fire before the actual objects are seen in the scene.

3. In layers 2 and 3, predictive activity (neural firing) should stop propagating at specific cells, corresponding to a specific prediction. Hawkins does not rule out anticipatory cells in layers 4 and 5.

4. Learned sequences of firings comprise a representation of temporally constant invariants. Hawkins calls the cells which fire in this sequence "name cells". Hawkins suggests that these name cells are in layer 2, physically adjacent to layer 1. Hawkins does not rule out the existence of layer 3 cells with dendrites in layer 1, which might perform as name cells.

5. By definition, a temporally constant invariant will be active during a learned sequence. Hawkins posits that these cells will remain active for the duration of the learned sequence, even if the remainder of the cortical column is shifting state. Since we do not know the encoding of the sequence, we do not yet know the definition of ON or active; Hawkins suggests that the ON pattern may be as simple as a simultaneous AND (i. e., the name cells simultaneously "light up") across an array of name cells. See Neural ensemble#Encoding for grandmother neurons which perform this type of function.

6. Hawkins' novel prediction is that certain cells are inhibited during a learned sequence. A class of cells in layers 2 and 3 should NOT fire during a learned sequence, the axons of these "exception cells" should fire only if a local prediction is failing. This prevents flooding the brain with the usual sensations, leaving only exceptions for post processing.

7. If an unusual event occurs (the learned sequence fails), the "exception cells" should fire, propagating up the cortical hierarchy to the hippocampus, the repository of new memories.

8. Hawkins predicts a cascade of predictions, when recognition occurs, propagating down the cortical column (with each saccade of the eye over a learned scene, for example).

9. Pyramidal cells should be capable of detecting coincident events on thin dendrites, even for a neuron with thousands of synapses. Hawkins posits a temporal window (presuming time encoded firing) which is necessary for his theory to remain viable.

10. Hawkins posits, for example, that if the inferotemporal (IT) level has learned a sequence, that eventually cells in V4 will also learn the sequence.

11. Hawkins predicts that "name cells" will be found in all regions of the cortex.