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What is thinking? The dynamics of mental exploration

What is thinking? The dynamics of mental exploration. ‘Thinking’ is a process by which a computational system can generate an effective action in a novel situation, based on exploring the possibilities (often combinatorial) implicit in previously acquired knowledge.

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What is thinking? The dynamics of mental exploration

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  1. What is thinking?The dynamics of mental exploration

  2. ‘Thinking’ is a process by which a computational system can generate an effective action in a novel situation, based on exploring the possibilities (often combinatorial) implicit in previously acquired knowledge.

  3. Sound waves in a simple gas molecular viewpoint molecules j of mass m, molecular forces m dvj/dt = Fj (Newton’s laws for 1028 molecules) Fj = - Skgrad V(rj – rk) no sound waves without molecular interactions Navier-Stokes viewpoint pressure fluctuations in a fluid: mean density r compressibility k k-1 (∂2/∂x2 + ∂2/∂y2 + ∂2/∂z2) p = r ∂2p/∂t2 The existence of molecules and their microscopic interactions has disappeared

  4. Drift and diffusion model of decision-making Sliding motion along a coordinate Drift caused by available evidence (slope) Diffusion (random walk addition) caused by noise Decision made when green dot reaches an end Reaching lower end means decision correct Reaching upper end means erroneous decision

  5. Mental exploration A protracted evolution of the pattern of neural activity, while an animal is not yet taking actions and while sensory input may be constant (or irrelevant), followed by an apt behavioral action that directly relates to the activity states during the exploration.

  6. Where action potentials ‘spikes’ are generated in a typical rat hippocampal place cell during exploration of a familiar space Box environment with visual clues on walls

  7. from Wills, Lever, Cacucci, Burgess and O’Keefe (2005)Science 308, 873

  8. Mapping brain cell activity to a useful spatial display cell location in brain spatial display for a rectangular environment arrowheads at position of maximal activity of corresponding neuron

  9. ‘’near water” neuron (connections learned) Spatial representation of activity pattern (reordering of pattern in hippocampus) Strongly active neurons in hippocampus when animal is at location w o

  10. from Wills, Lever, Cacucci, Burgess and O’Keefe (2005)Science 308, 873

  11. Animal in R environment Animal in H environment Rectangle H environment environment display display

  12. Mental exploration While stationary, mentally explore extensively to search for water in present environment make a stable activity clump in any particular environment make the activity clump explore that environment If water is found, find a (the?) mental pathway between present physical location and location of water Remember the pathway so that it can be mentally repeated Use mental recapitulation of motion to guide corresponding physical motion along the mental path

  13. Exploration in one dimension Each neuron has a location of maximum activity Arrange neurons in this natural order for display purposes Connect each neuron k to M others (denoted by j) that are most strongly active when k is active. This defines the connection matrix Tkj “neurons that fire together wire together” c Tkj

  14. Firing rate adapation input

  15. Mental exploration While stationary, mentally explore extensively to search for water in present environment If water is found, find a (the?) mental pathway between present physical location and location of water Remember the pathway so that it can be mentally repeated Use mental recapitulation of motion to guide corresponding physical motion along the mental path

  16. Mentally learning a physical trajectorymove along a pathsensory input dominates place cells Skj = (activity of neuron k )* (activity of neuron j) accumulate Skj throughout this motionFor all synapses that are non-zero (i.e. Tkj = 1)if Skj > threshold valueincrease Tkj by 50%{Strengthens synapses that would be useful along the path}

  17. MLS

  18. Motor controllerintegrate-and-fire neuron slow excitatory pathway each output spike approximately reverses direction of motion with random spread  60o input balanced fast inhibition long-lasting self-inhibition [Ca-dependent Inhibitory currents]

  19. No control signal control input from olfactory cells Gaussian spatial odor profile

  20. MLS Area E activity is a moving bump representing intended action Area A has two ‘bumps’ of input Sensory input represents where the animal is Input from area E reflects the intended position When these coincide, area A has maximal activity When well separated, area a has little activity Motor system will move animal to intended location

  21. recapitulate mental success to guide physical motion mentally explore for w

  22. Activity-position movie 10 frames/sec Red * instantaneous location of animal Black points . Center of receptive field of strongly active place cells 100 randomly chosen place cells in the interior of a T environment

  23. Explanation of movie The mouse goes one branch to another, not directly repeating. (perhaps a learned behavior) Hippocampal place cells have indirect inputs from the sensory+vestibular system. They have a selective filter on this input resulting in spatial receptive fields. When the animal is at X, the cells with place field centers near X are strongly active, driven by sensory input that characterizes being at X {Being at X causes corresponding neural activity WRONG} There is NO sensory input to these place cells (in E = ca3?) during the movie. A moving cluster of place cells with is active through mutual feedback. When this cluster is at X, the animal ‘wants to be at X’ (i.e., this activity causes the motor system to move the animal to X). Intrinsic neurodynamics makes the active cluster moves in mental space, causing the animal to move correspondingly in real space. CAUSALITY IS REVERSED

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