Biological neurons have apical dendrites and basal dendrites. These are not modeled in the HTM model which uses: (1) an input, either from a sensory organ or another neuron (2) The predictive state of the neuron, which says if the neuron is expacted to fire based on previous neural states (I will call that the context).
Now let’s do a little thought experiment:
A cube is moving a constant speed on a flat table. As said in the HTM model, at each time t, my brain predict the next state of the cube and the neurons encoding that next state are put in a predictive state. As the cube moves at a constant speed, this state is validated by the next visual input, no problem. Now, in the real brain, if I close my eyes (cut the visual input), I can continue to predict what is the current state of the cube and when I open my eyes again, it is very likely that the state I predicted is almost exactly the state of the cube since its motion is quite simple. Despite the lack of visual input, my brain was able to keep the predictive states of the neurons rolling without the need for these states to be validated by a real visual input.
But in the HTM theory, that is impossible. In HTM model, only inputs can trigger a neuron to fire, no matter how certain the system is of the next state of the input. It can never fire based on prediction alone.
That feels like a shortcoming of the HTM model. The brain ability to hallucinate the world by constantly mixing real sensory inputs with expected input and context feels like a major part of the thinking process.
Do you guys have papers I could check out on that subject ? Or do you know if this topic has been discussed at Numenta ?