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PPT

  1. 1. Brain Rhythms, Anatomy, and the Emergence of Consciousness: Why Hearts Don’t Love and Brains Don’t Pump Memphis Workshop. Consciousness, Brain Rhythms, and the Action-Perception Cycle, May 3-4, 2008 Paul L Nunez PhD Emeritus Professor, Tulane University, New Orleans, LA
  2. 2. Pearls of Wisdom 2008 • Your enemy is your best teacher (old Buddhist saying) • Capitalism is the astounding belief that the most wickedest men will do the most wickedest things for the greatest good of everyone (John Maynard Keynes)
  3. 3. References PL Nunez, Oxford U Press, 2009 ?Mind, Brain, and the Emergence of Consciousness ?Science, Religion, and the Mysteries of Consciousness PL Nunez and R Srinivasan, Electric Fields of the Brain: The Neurophysics of EEG, Oxford U Press, 2006 www.electricfieldsofthebrain.com PL Nunez, Neocortical Dynamics and Human EEG Rhythms, Oxford U Press, 1995
  4. 4. EEG, MEG, fMRI, PET,… Thinking and behavior Large scale synaptic action fields ( , ), ( , ),...e it tΨ Ψr r Embedded cell assemblies (neural networks) Dynamic theory (Nonlinear mathematics) The Holy Grail of brain science: connecting psychology to physiology
  5. 5. The dynamics of complex systems • Global weather (sun’s energy, earth’s rotation, frictional forces, oceans, etc) • Roulette wheel (initial velocities of ball and wheel, frictional forces, hole geometry, etc) • What anatomical and physiological features of brains determine their dynamic (EEG) behaviors? • Features that underlie observed dynamics may also be required for consciousness
  6. 6. Summary of Today’s Talk • Experimental windows on the mind. What do the data tell us? • Large scale models. What are the essential properties of anatomy and physiology? • Consciousness will not be “explained” today • Correlation need not imply causality
  7. 7. What are the sources of the information presented today? • Neurophysiology • Neuroanatomy • EEG (recorded from scalp) • Electrophysiology (intracranial data) • Complex physical systems • Mathematical models • Hunches
  8. 8. San Diego 1976: 16 channel EEG and PDP12 computer Irvine 2006: 131 channel EEG and modern computer
  9. 9. Human EEG Spontaneous Evoked Clinical Applications epilepsy, head trauma, drug overdose, brain infection, sleep disorder, coma, stroke, Alzheimer’s disease, brain tumor, multiple sclerosis, surgical monitoring Scalp Depth ECoG Transient Steady State Cognitive Science sensory pathways, stimulus encoding, motor process, spatial task, verbal task, mathematics, short term memory, memory encoding, selective attention, task context, general intelligence, dynamic brain theory PL Nunez, EEG, Encyclopedia of the Brain, 2003
  10. 10. Selective Sensitivity of EEG and MEG PL Nunez, Neocortical Dynamics and Human EEG Rhythms, Oxford U Press, 1995
  11. 11. s(r, w, t) V(r, t) Potentials Generated by Synaptic Action in Cortical Columns r w P(r, t) Potential N columns V ~ P N (synchronous, parallel)V ~ P N ½ (random) 1 cm2 cortex = 105 minicolumns Random contribution equals synchronous contribution for 0.3% synchronous columns PL Nunez & R Srinivasan, Electric Fields of the Brain: The Neurophysics of EEG, 2nd Ed, Oxford U Press, 2006
  12. 12. fMRI, PET Good spatial resolution and poor temporal resolution. Tip of the iceberg measures, 3% above background. Great red spot on the brain.
  13. 13. EEG, MEG Behavior/Cognition MRI, PET Cell Groups 1 Cell Groups 2Cell Assemblies Synaptic Action & Action Potential Fields Ψe(r, t), Ψi(r, t), Θ(r, t) Causal Causal Speculative Speculative Causal Causal Correlative Correlative PL Nunez, Behavioral and Brain Sciences, 2000
  14. 14. Cell assemblies at multiple scales, forming nested hierarchies
  15. 15. EEG Coherence • A correlation coefficient expressed as a function of frequency • Measures the phase consistency between two signals U(t) and V(t) – one measure of phase synchronization • Mostly independent of amplitude • Depends on spatial scale (like all physical measures) 2 0 ( ) 1UV fγ≤ ≤
  16. 16. Robust Coherence Changes Occur with Changes in Brain State • Various kinds of mental activity are associated with increased coherence between some electrode pairs in some frequency bands • At the same time coherence of other electrode pairs and other bands may decrease • Evidence for the formation and dismantling of neural networks on 100 ms time scales?
  17. 17. Electrode pairs with 100% consistent coherence increases (left) or reductions (right) during (1-min) periods of mental calculations. Comparison with resting periods; 11 brain state transitions. PL Nunez, BM Wingeier & RB Silberstein, Human Brain Mapping, 2001 8 Hz
  18. 18. Electrode pairs with 100% consistent coherence increases (left) or reductions (right) during (1-min) periods of mental calculations. Comparison with resting periods; 11 state transitions. PL Nunez, BM Wingeier & RB Silberstein, Human Brain Mapping, 2001 5 Hz
  19. 19. High Resolution EEG Given perfect knowledge of scalp potential, solution for dura potential is unique Accuracy is limited by spatial sampling, head model and noise The surface Laplacian provides a relatively robust estimate of dura potential independent of head model
  20. 20. 3602 sources cortex Scalp potential 0.627 Spline-Laplacian 0.974 Dura image 0.954 Simulation of scalp potential (3600 cortical dipole sources). Laplacian and dura image using 131 scalp samples PL Nunez, BM Wingeier & RB Silberstein, Human Brain Mapping, 2001
  21. 21. Potential Laplacian Simulated Scalp Maps
  22. 22. Simulated Scalp Cortical Map demonstrating fractal-like neocortical dynamics
  23. 23. Selective Sensitivity of Potential and Laplacian Measures to Distinct Spatial Scales of Cortical Source Activity 1 1 2 2 S S S S L L Φ >> Φ
  24. 24. Potential and Laplacian sensitivities to dipole layers of different sizes
  25. 25. Alpha rhythm recorded with 111 channels: Potential plots reveal global source field consistent with anterior--posterior standing wave
  26. 26. Alpha rhythm recorded with 111 channels: Laplacian plots reveal local source patches in central and occipital cortex, consistent with local networks embedded in global field
  27. 27. Some properties of brain tissue to consider in relation to consciousness • Hierarchical interactions across spatial scales; analogy with social systems • Non-local interactions by cortico-cortical fibers • Resonant interactions between networks and between networks and global fields
  28. 28. Some observations on neocortical anatomy/physiology and consciousness • Neocortex is interconnected by both intracortical (local) and about 1010 corticocortical (non-local) fibers • Any pair of cortical neurons is separated by no more than 2 or 3 synapses • Transit times across the entire brain are of the order of 30 ms • Consciousness requires about 500 ms to develop – implying multiple positive feedback loops between widespread brain regions is required for consciousness to occur
  29. 29. Hierarchical Dynamics of Human Interactions Neocortex Macrocolumn Module Minicolumn Neuron ??? Global population Nation City Neighborhood Individual Equality of time scales? Top-down, multi- scale neocortical dynamic plasticity? Biochemistry Quantum Fields ???PL Nunez, Behavioral and Brain Sciences, 2000
  30. 30. What Makes the Human Brain “Human”? • Cerebral cortex is critical to consciousness, but human cortex looks much like cat, rat or cow cortex • Brain size Issues: Why are there no elephants, whales and dolphins at this workshop ? • Explanations based on ratio of brain to body weight are not useful
  31. 31. Human Cortico-cortical Fibers (Non-local Interactions) ~100 fibers dissected fibers by Krieg. Actual number is about 1010 , or 100 million for every one shown; see PL Nunez, Neocortical Dynamics and Human EEG Rhythms, Oxford U Press, 1995)
  32. 32. Local versus non-local interactions
  33. 33. Mathematical Models of Real Systems Real World Model World 1 Model World 2 Model World N Black Swans The Black Swan, Nassim Taleb, 2007. Rare events with large impacts.
  34. 34. δΨ e(r,t) = δΨ0(r,t)+ dv 0 ∞ ∫ Γ(r,r1,v)δΘ r1,t − r − r1 v         d2 r1 cortex ∫∫ Synaptic action field Action potential field Velocity integral Cortico-cortical fibers (nonlocal) A linear “brain wave equation” in 2 dependent variables: Standing waves in the brain.
  35. 35. Standing and traveling brain waves 2 2 2 ( ) ( 1) R k v k v ω = −β λ γ = λ β − 1 1 ( ) ( ) 6 15 Hz 2 R k f k ω = ∼ − π 2 2 21 1 1 1 1 ( ) 4 10 m/secR P k v v k k k ω = = −β λ −:
  36. 36. 100,000 cortico-cortical fibers 2,000 thalamocortical fibers 1 mm diameter cortical macrocolumn Dominance of Tangential Over Radial Connections in the Human Brain
  37. 37. Ratio of cortico-cortical input fibers to thalamocortical input fibers 0 5 10 15 20 25 30 Rat Rabbit Dog Chimp Human Ratio
  38. 38. A Proposed Marriage of Hebbian Neurophysiology to Gestalt Psychology • Cell assemblies (neural networks) embedded in global synaptic action fields • Metaphor—Social networks embedded in a culture • Top down and bottom up interactions between networks and global fields (“circular causality”)
  39. 39. Resonant Interactions Between Semi- autonomous Oscillators • Weakly connected oscillators substantially interact only when certain resonant relations exist between the characteristic frequencies of the autonomous oscillators (a mathematical statement largely independent of neural oscillator models) • Eugene Izhikevich, SIAM J App Math, 1999
  40. 40. Resonant Interactions Between Oscillators 1 0 0 1 1 2 2 0m f m f m f+ + = 0f 1f 2f 0 0, 1, 2,...m = ± ± 1 2, 1, 2,...m m = ± ±
  41. 41. Resonant Interactions Between Oscillators 2 0 0 1 1 2 2 0m f m f m f+ + = 0f 1f 2f Global Synaptic Field (x, t)
  42. 42. Summary: The following physical properties may be critical for consciousness to occur • Nested hierarchical interactions across spatial scales. Minicolumns within cortico-cortical columns within macrocolumns within lobes, etc. • Non-local interactions by cortico-cortical fibers, allowing for much more complex dynamics. • Resonant interactions between networks and between networks and global fields or “binding by resonance” analogous to chemical bonds. • This raises the speculation that consciousness depends critically on resonance phenomena and only properly tuned brains can orchestrate the beautiful music of sentience.
  43. 43. Does the brain create the mind? • Prop 1. Brain creates mind, prob. x • Prop 2. Brain is “antenna,” prob. 1 – x My view • Brain scientists might consider making a distinction between how they proceed as scientists (x ≈ 100%) and what they believe based on our measly knowledge (x ≈ 50%)
  44. 44. END OF SEMINAR Begin next 100 years of brain research !

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