Jack Tuszynski From Quantum Physics to Quantum Biology in 100 Years. How long to quantum medicine?

From Quantum Physics to Quantum
Biology in 100 years
How long to Quantum Medicine?
Jack Tuszynski
University of Alberta
Edmonton, Canada

Solvay Conference
Brussels 1927

Basics of Quantum Mechanics
 Classical mechanics (Newton's mechanics) and Maxwell's
equations (electromagnetic theory) can explain
MACROSCOPIC phenomena such as motion of billiard
balls or rockets.
 Quantum mechanics is used to explain MICROSCOPIC
phenomena such as photon-atom scattering and flow of
the electrons in a semiconductor. But there are
macroscopic quantum effects in: superfluids,
superconductors, lasers and crystal dynamics (phonons)
 QUANTUM MECHANICS developed postulates based on a
huge number of experimental observations. It has a
precise mathematical formalism of Hermitian operators
in Hilbert spaces

 Microscopic physical systems can act as both particles
and waves  WAVE-PARTICLE DUALITY
 Quantum state is a superposition of a number of
possible outcomes of measurements of physical
properties  Quantum mechanics uses the language of
PROBABILITY theory
 An observer cannot observe a microscopic system
without altering some of its properties (an observer
problem)
 QUANTIZATION of energy is yet another property of
"microscopic" particles.

Heisenberg Uncertainty Principle
 One cannot unambiguously specify the values of
particle's position and its momentum for a
microscopic particle, i.e.
 Position and momentum are, therefore,
considered as incompatible variables (same for
angle and angular momentum; time and energy)


22
1
00 )()( h
x tptx

The Photoelectric Effect
A Photocell is Used to Study the Photoelectric Effect
Larger frequency, means smaller wavelength, and larger Energy=hf.

Additional experiments demonstrating quantum
nature of the microscopic universe
 The Compton effect (photon-electron scattering)
 Atomic absorption/emission spectra
 Double slit experiments (electrons and photons)
 Stern-Gerlach experiment (magnetic spin)

The First Postulate of QM
States of microscopic systems are represented by wave functions 
STATE FUNCTIONS (square integrable).
First postulate of Quantum mechanics:
Every physically-realizable state of the system is described in
quantum mechanics by a state function  that contains all accessible
physical information about the system in that state.
 State function  function of position, momentum, energy that is
spatially localized.
 If 1 and 2 represent two physically-realizable states of the
system, then so is their linear combination

The Second Postulate of Quantum Mechanics
If a system is in a quantum state represented by a wavefunction ,
then
is the probability that in a position measurement at time t the
particle will be detected in the infinitesimal volume dV.
Note:
 position and time probability density
According to the second postulate of quantum mechanics, the
integrated probability density can be interpreted as a probability that
in a position measurement at time t, we will find the particle
anywhere in space (i.e one= certainty)
dVPdV
2

2
),( tx

The Third Postulate of Quantum Mechanics -
Every observable in quantum mechanics is represented by an operator which is used to
obtain physical information about the observable from the state function. For an
observable that is represented in classical physics by a function Q(x,p), the corresponding
operator is ),( pxQ

.
Observable Operator
Position x

Momentum
xi
p




Energy
)(
2
)(
2 2
222
xV
xm
xV
m
p
E 






- Fourth Postulate of Quantum
Mechanics -1926 Erwin Schrödinger proposed an equation that describes the evolution of a quantum-
mechanical system  SWE which represents quantum equations of motion, and is of the
form:
t
itxxV
xm
txxV
xm 
















 

),()(
2
),()(
2 2
22
2
22
This work of Schrödinger was stimulated by a 1925 paper by Einstein on the quantum
theory of ideal gas, and the de Broglie theory of matter waves.
Note:
Examining the time-dependent SWE, one can also define the following operator for the
total energy:
t
iE


 


Describes well quantum vibrational modes of molecular gases

Describes well specific heats of solids

Macroscopic Quantum Effects
• Superconductivity
• Superfluidity
• Laser Action
• Crystal Vibrations (Phonons)
• Magnetism

Quantum Mechanics and Life
 Nature over 2B years of experimentation on Earth
must have taken advantage quantum mechanics

• Where does quantum
weirdness fit in?
• Coherence
– superposition of states
• Entanglement
– “spooky action at a
distance”:
distant particles affecting
one another without
energy transfer

 Five Gifts of Quantum Mechanics to
Nature
Stability
Countability
Information
Information Processing
Randomness

physicists think everything reduces to physics

But interactions matter:
hierarchies of systems form
Biochemistry
Chemistry
Condensed matter
Physics
Elementary particle
Physics
nucleic acids  proteins
ions  molecules
(valence is important)
quarks  nucleons
electrons & protons  solids

Combinatorial Barriers
Elsasser’s immense number
I = 10110
I = atomic weight of the Universe measured in
proton’s mass (daltons) time the age of the
Universe in picoseconds (10-12
s)
No conceivable computer could store a list of
I objects, and even if it could, there would be
no time to inspect it !

Dimensions Matter, too
Organism
Cell
System
Biomolecule
Molecule
Atom
1020 Atoms
1010 Atoms
105 Atoms
103 Atoms
101 Atoms
1 Atom
Thermodynamics
Mesoscale:
Quantum Biology?
Quantum
Chemistry
Quantum
Physics

Energy/Affinity Scale
 Covalent bond 90 kcal/mol at 1.5 Å
 Ion-Ion 60 kcal/mol at 5 Å
 Disulphide bond 40 kcal/mol at 2.2 Å
 Salt bridge 4-7 kcal/mol at 2.8 Å
 Ion-dipole 6 kcal/mol at 5 Å
 Hydrogen bond 0.5-12 kcal/mol at 3-5 Å
 VdW 1-4 kcal/mol at 3.5 Å
 kT at 310K is ~0.6 kcal/mol
 GTP/ATP hydrolysis (biological energy quanta):
3 kcal/mol-60 kcal/mol

Many discounted QM in biology because…
• Life is big (cells) in comparison to photons/electrons where QM is
applicable
• Life is hot (and active) in comparison to where QM works best in
cold isolated environments where it is currently studied [to keep QM
coherence]
• Life is wet in comparison to controlled QM experimental
environments where it is studied in a vacuum to avoid
environmental influences which decoheres QM effects
• Life is slow in comparison to QM events where it is measured in
milliseconds or less
• Life is complex, requiring billions of particle relationships/bonds in
comparison to simple QM relationships/entanglements involving <
100 particles
• Life is not fuzzy (yes/no) and real in comparison to the QM random
world which is probablistic multi value/states superpositions
• Life is real, local, and stable in comparison to Heisenberg QM
uncertainty and non-local realism
• Life brings out discrete realism/information and QM always reverts
to its fuzzy world
• … BUT Nature is the nanotech MASTER!!!!! … so it was soon
found out that IT can!! since QM works in the nano-world
of BIO

• Collective dynamics of many freedom degrees.
• Life – a metastable state.
• Various types of local and global order.
• Structural and dynamic hierarchy, successive levels.
• Biological complexity – order without repetition.
• Short- and long-range correlations and interactions.
• Living organisms are open, irreversible, disipative systems.
• They are self-organized, optimal systems (->homeostasis), with
cooperative interactions.
• Nonlinear interactions, highly integrated dynamics.
• Such features – to some degree in various complex non-living
systems – but only organisms join them altogether.
Features of life unsolved by molecular
biology

 Quantum computers
use entanglement
and coherence
 These states are
fragile
 environmental
decoherence
 keep cold & isolated
 Biological systems
 too “warm and wet”
 Or are they?

Physiological Quantum Effects
• Light detection by the human eye
• Resonant recognition of aromatic
molecules in olfaction (sense of smell)
• Bird navigation
• Photosynthesis
• Mitochondrial Metabolism
• Consciousness (?)

Quantum biology
• N.Bohr, W. Heisenberg, E. Schrodinger, J. von Neumann, C. von
Weizsacker, W. Elsasser, V. Weisskopf, E. Wigner, F. Dyson, A. Kastler,
and others – QM essential for understanding life.
• Quantum biology (QB): “speculative interdisciplinary field that links
quantum physics and the life sciences” (Wikipedia) –Some directions
:
– Quantum metabolism.
– “Biophoton” (ultraweak emission) statistics.
– Photosynthesis, light harvesting
– Solitons (Davydov), phonons, conformons, plasmons, etc.
– Decoherence, entanglement, quantum computation.
– Long-range coherent excitations – Froehlich.
– QED coherence in cellular water – Vitiello,Preparata, Del Giudice.

• Herbert Fröhlich postulated a dynamical order based on correlations
in momentum space, the single coherently excited polar mode, as the
basic living vs. non-living difference. Assumptions:
• (1) pumping of metabolic energy above a critical threshold;
• (2) presence of thermal noise due to physiologic temperature;
• (3) a non-linear interaction between the freedom degrees.
Physical image and biological implications:
• A single collective dynamic mode excited far from equilibrium.
• Collective excitations have features of a Bose-type condensate.
• Coherent oscillations of 1011-1012 Hz of electric dipoles arise.
• Intense electric fields allow long-range Coulomb interactions.
• The living system reaches a metastable minimum of energy.
• This is a terminal state for all initial conditions (e.g. Duffield 1985);
thus the genesis of life may be much more probable.
Fröhlich’s long-range coherence in living systems

Morphogenetic fields
• 1912:AlexanderGurwitsch introduced for the first time in biology the idea of a
field as a supracellular ordering principle corresponding to spatial but immaterial
factors of morphogenesis.
• Kraftfeld,a field in which a force is exerted.
• Gurwitsch tried to solve the biological problem of morphogenesis: How living
tissues transform and transfer information about the size and shape of different
organs.
• Chemical reactions do not contain spatial or temporal patterns a priori, and that
is why Gurwitsch looked for a "morphogenetic field".
• Geschehensfeld,afield in which events, occur in an integrated, coordinated
manner.Gurwitsch, A.G. (1912). Die Vererbung als Verwirklichungsvorgang,
Biologisches Zentralblatt, vol. 32, no. 8, pp. 458-486.

Modern bioelectromagnetic field
concepts
• 1970 Presman:Review on Soviet research in bioelectromagnetism stimulated the
breakthrough and beginning of modern theories
• Non-equilibrium thermodynamics Organisms as open systems that exchange
energy, matter and information –how they establish a stable state far from
equilibrium A.Gurwitsch, E.Bauer, V.Vernadsky, and L.Bertalanffy.
• Contributions to modern concepts
• Negative entropy Organisms preserve their high order by feeding on negentropy
(highly-organized energy) from the environment Erwin Schrodinger, Albert Szent
Gyorgyi, Ilya Prigogine.
• Ilya Prigogine introduced his theory of dissipative structures, a discovery that
won him the Nobel Prize in Chemistry in 1977
• •Herbert Frohlich introduced his concept of biological coherence.

Anatomy of the Intelligent Cell
Gunther Albrecht-Buehler, NWUniv Chicago

Centriole-Mitochondria Connection (G.
Albrecht-Buehler)
The control center detects objects and
other cells objects by pulsating near
infrared signals.
Cells have ‘eyes’ in the form of
centrioles. They are able to detect
infrared signals and steer the cell
movements towards their source.
Percentage of cells that removed the
light scattering particle as a function
of wavelength. The near infrared
wavelength, between 800 and 900
nm, is most attractive.
Extension of surface
projections towards the
pulsating light source.

Centrioles
Basal bodies and centrioles
consist of a 9-fold arrangement
of triplet microtubules. A molecular
cartwheel fills the minus end of the cylinder;
it is involved in initiating the assembly of the structure.
The cylinders – now called cetrioles – are always found in
pairs orientated at right angles. Dense clouds of sattelite
material associated with the outer cylinder surfaces are
responsible for the initiation of cytoplasmatic microtubules.

DNA
TF
MT
Free Tubulin Dimer
Nuclear Wall
Membrane
Cytoplasm
MT Bundle
Chromosome
Pair
Centrosome
Mitotic Cell
. . . . .
Microtubule: function

Quantum Metabolism
Metabolic activity is localized in the biomembranes
(1.) Plasma membrane  Uni-cells
(2.) Thylakoid membrane  Chloroplasts in plants
(3.) Inner membrane  Mitochondria in animals

Evidence for quantum coherence
•Engel 2007: Quantum Beating: direct evidence of quantum
coherence
•Lee 2007: “correlated protein environments preserve
electronic coherence in photosynthetic complexes and allow the
excitation to move coherently in space”
•Sarovar 2009: “a small amount of long-range and multipartite
entanglement exists even at physiological temperatures.”
•What does this mean for other biological systems?

Photosynthesis
 Light energy absorbed by light harvesting
complexes (LHC)
 LHCs transfer energy to photosynthetic reaction
centers (RCs)
 RCs chemically store some energy (ie. ATP)
 Remaining energy removes electrons from water
or sulphates.
 Electrons used to turn CO2 into organic
compounds.

Photosynthesis
 LHCs are pigment-protein antennas,
 Densely packed chromophores eﬃcient at
transporting excitation energy in
disordered environments (~99%)
 Chromophore number and spacing vary
but separations on the scale of 15˚A

FMO Complex in C. Tepidum
 From a New Zealand
hot spring.
 Grow in dense mats
over hot springs that
contain sufficient
hydrogen sulfide
 LHCs made of bacterio
-chlorophylls (Bchls)

Quantum Search Algorithms
 Mohseni et. al.
investigated
quantum
search
algorithms in
FMO based on
the Cho et. al.
Hamiltonian

single-celled algae have a light-harvesting
system where quantum coherence is
present.
A UNSW Australia-led team has discovered how cryptophytes that survive in very low
levels of light are able to switch on and off a weird quantum phenomenon that occurs
during photosynthesis.

Quantum Entanglement
 Evidence for the existence of entanglement in
the FMO complex for picosecond timescales
 Prediction of entanglement is experimentally
veriﬁable because of these timescales.
 Evidence for the beneﬁcial role of quantum
coherence in LHC excitation transport.
 Entanglement a by-product of quantum
coherence.

Quantum Beating and Coherence
 Superposition states formed during a fast
excitation event
 allows the excitation to reversibly sample relaxation
rates from all component exciton states,
 efficiently directs the energy transfer to find the most
effective sink.
 The system is essentially performing a single
quantum computation
 Analogous to Grover’s algorithm,
 Hamiltonian describing both relaxation to the lowest
energy state and coherence transfer

Extensions
Penrose and Hameroff suggest quantum
computations in microtubules as playing a
role in higher brain functions
“Aromatic" ring structures provide regions
of delocalizable/ polarizable electrons and
electronic excited states.
Tryptophan has an "indole ring" giving it a
high electron resonance and fluorescence
 indole rings may take part in energy
transfer (photon exchange).
Unexplained 8 MHz non-thermal radiation
from microtubules.
Tryptophan path in tubulin and MT
Spacing ~ 20 Ang

A lattice of seven tubulin dimers as found in the microtubule
lattice. Red lines connect tryptophans, and rectangles show
four possible winding patterns.
(The work of Alexander Nip, Université de Montréal.)

• In photosynthesis coherent energy transferred between
chromophoric chlorophyll molecules.
• Tubulin possesses a unique arrangement of chromophoric
tryptophan amino acids.
• Spacing comparable to photosynthetic units.
Chromophore Network in Tubulin
55

Dipole Interactions in Tubulin
• Chromophores transfer energy via transition dipole moments.
• Tryptophan may be excited by 260 - 305 nm light (UV range)
• Possesses a transition dipole moment of ~ 5.5 - 6 Debye
• Non-negligible dipole coupling strengths
Vmn = ((5.04m2
)
( ˆmm × ˆmn -3( ˆmm × ˆRmn )( ˆmn × ˆRmn ))
Rmn
3
H = emam
t
am + Vmn (
n<m
8
å
m=1
8
å am
t
an + an
t
am )
56

Tryptophan excitations in
tubulin
In collaboration with Travis Craddock

Excitation Coherence in Tubulin
• Diagonalization of the Hamiltonian Matrix yields the excitation
energies and distribution.
• Values indicate a significant delocalization of the excitation over
several tryptophan residues.
• Quantum and local field corrections of protein environment taken into
account. 58
DecreasingEnergy
<10%
10-20%
20-30%
30-40%
40-50%
50-60%
60-70%
70-80%
80-90%
90-100%

Regulation of the Metabolic Pathway
Regulated by several Mechanisms:
•Product Inhibition
•Feedback Inhibition
•Reactant Activation
A lot of redundancy among pathways

Electron Transport Chain – Oxidative
Phosphorylation
•Movement of electrons from NADH to terminal electron acceptor through
Redox reactions
•Release of energy as electron moves from high to low Redox potential
facilitates movement of H+ across the mitochondrial inner membrane
•Movement of H+ back across membrane through ATPase results in ATP
synthesis from ADP

Energy consumption in
organisms history
1. Laplace and Lavoisier (1780)
Respiration is a form of combustion
Metabolic rate could be measured by the amount of heat
produced by the organism
• Rubner (1904)
i. Body size and metabolic rate of domesticated animals
ii. Body size and life span
1. Kleiber (1940)
Systematic study of the relation between basal
metabolic rate and body size

Body Size – Metabolism
Allometric Relation
Y = α Wβ
W = body size
The Parameter Y
a) Measures of physiological time:
I. Respiratory Cycle
II. Cardiac Cycle
b) Measures of metabolic activity:
I. Basal metabolic Rate
II. Field metabolic Rate
III. Maximal metabolic Rate
Y = Physiological time : β ~ 1/4
Y = Basal metabolic rate:
uni-cells: β = 3/4
plants: 2/3 < β < 1
animals: 2/3 < β < 3/4

Problems
What is the mechanistic basis for these
scaling rules?
Issues to be addressed
1. Variation in proportionality constant
α (Birds) > β (Mammals)
1. Variation in scaling exponents
β (Plants) > β (Animals)
β (Large mammals) > β (Small birds)

Quantum Metabolism
Metabolic activity has its origin in biochemical
processes which occur within biomembranes.
The theory integrates three classes of
phenomena:
i. The chemiosmotic coupling between the electron
transfer process and ADP phosphorylation
ii. The storage of this metabolic energy in vibrational
modes among the molecular components of the
membrane
iii. The quantization of the energy stored in the
membrane

QM: molecular phenomena
1. Chemiosmotic coupling: Mitchell (1970)
Process with ADP phosphorylation
Coupling of electron transport
• Energy storage: Froehlich (1968)
Storage of metabolic energy in the dipolar
oscillation modes
among the molecular components
• Energy quantization: After Debye (1912)
Analogies between: coupled oscillations of atoms
in
crystalline solids and coupled oscillations of
molecules
in biomembranes

Results – e vs. V0, T = 300 K
• Only Type IIB behaviour
below e of 7.8.
• A narrow range of
parameters are defined for
MTs capable of
information processing.

L. Demetrius (2003) Quantum statistics and allometric scaling of organisms. Physica
A: Statistical Mechanics and its Applications 322:477-490.

Biological “Planck constant”: E=kf
• Human energy production: 1021 ATP molecules per second
• There are on the order of 3.5 × 1013 cells in the human body
• each cell has on the order of 103 mitochondria, so there are approximately 3.5 x10 16
mitochondria in the human body
• hence approximately 3 × 104 ATP production events per mitochondrion per second.
• net effect: conversion of 1 molecule of glucose into 38 molecules ATP.
• each ATP synthase operates at a rate of 600 ATP molecules/s, we estimate that each
mitochondrion has on average 50 ATP synthase enzymes.
• Consequently, the frequency of the oxidative phosphorylation reaction is
approximately 1,000 cycles per second for each complex.
• Using: E0 = κf where E0 ~ 10 -20 J is the biological energy quantum we conclude that the
biological equivalent of Planck’s constant is κ = 10-24 J s which, when compared to the
physical Planck’s constant h = 6.6 × 10−34 J/s, gives a ratio of κ/h = 1.8 × 1011.
• The physical Planck’s constant corresponds to a single atom, the biological constant
corresponds to a mitochondrion. There are approximately 1.9 × 1014 atoms per cell and
approximately 1000 mitochondria per cell, which gives 1.9 × 1011 atoms per
mitochondrial “sphere of influence” within the cell.

The Microtubule Cytoskeleton
Hameroff et. al., In: Toward a Science of
Consciousness pp. 507-540 (1996)
• Microtubules (MTs) form elaborate networks in neurons
• Learning/memory involves reordering of the MT cytoskeleton.
• Cognitive diseases (Alzheimer ’ s, Dementias, Bipolar Disorder,
Schizophrenia) show dysfunction in the neuronal MT cytoskeleton.
76

Dendritic spine has microtubules interacting with
membrane receptors.

Challenge: integration of various levels
in a hierarchy
Building a bridge between
 the molecular level (cytoskeleton)
 the membrane level (synaptic activity, AP)

Microtubule: structure
 is made of a- and b- tubulins
a
b

Source of UV Radiation
• Tryptophan requires UV radiation to be excited.
• Is there a UV source inside cells?
• Rahnama et. al. 2010 (arxiv.org/pdf/1012.3371)
points out:
– Absorption/emisison of tryptophan dependent on
tubulin conformation
– Microtubule polymerization is sensitive to UV
(Staxén et al. 1993)
– Mitochondria are sources of biophotons at this
wavelength (Vladimirov and Proskurnina 2009,
Hideg et al. 1991, Batyanov 1984)
– Microtubules co-localize with mitochondria
(Tuszynski, Microtubule Plenary, TSC 2011)
http://www.mitochondrion.info/

Quantum link to function
• Mitochondria provide UV source.
• TRP excitations influenced by:
– C-terminal tail positions
– Microtubule associated
proteins (MAPs)
– Post-translational
modifications
• Resulting TRP dipole could affect:
– C-terminal tail position
– MAP attachment
– Ionic currents around MTs
• Quantum computation in TRPs
could couple to MT-MAP
computations 81

Modes of
Communication/Signaling
C-termini oscillations
Electron hopping
Tryptophan excitations
Conformational changes

Brain questions
• What makes the brain special?
• What is consciousness?
• Where is memory stored?
• What is the computational
power of the brain?
• Is information processing in the
brain classical, quantum, or
fractal resonant (or something
else)?
• How can the brain work with so
low power compared to
computers?

The Human Brain:
a computer cluster of computers
• 1011 neurons in our brains
• 1015 synapses operating at about 10 impulses/second
(CPUs have 108 transistors)
• Approximately 1016 synapse operations per second i.e.
at least 10 PF ( Blue Gene performs at 1015 FLOPS=1
PETAFLOP)
• Total energy consumption of the brain is about 25 watts
(Blue Gene requires 1.5 MW)
• Is there anything special inside each neuron?
• YES, probably another computer that has both classical
and quantum processors
http://www.merkle.com/brainLimits.html

Potential for Memory Storage,
Computation and Signaling in MTs
 C-termini states (4 per dimer)
 Electron hopping (4 per dimer)
 Conformational changes/GTP states
(2 per dimer)
Phosphorylation states: 4 per dimer
Total: 128 states/ dimer
100 kB/MT or 1 GB/neuron
100 billion neurons: 1020 bits/brain
At microsecond transitions: 1026 flops=
100 yottaflops!!!
BlueGene 1015 flops = 1 Petaflop

Energy limitations on information processing in
the brain
• P = 25 W but 60% used by ribosomes on protein synthesis alone
• Approximately 70% of the rest used to maintain temperature, so we
assume that 3 W at most is used for information processing
• Cost of 1 bit is at least 3 10 -21 J, if ATP used, then 5 10 -20 J
• The amount of information processed then depends on the clocking
rate but ranges from 109 to to 10 10 bits/neuron/sec.
• The clocking time ranges from 1 ns for a microtubule exciton to
1 ms for protein conformational changes to 1 ms for action potentials
to 1 s for brain’s Libet pre-processing times.
So: the number of bits per time step per neuron can vary between:
1-10 (ns), 1000-10,000 (ms), 1,000,000-10,000,000 (ms) to billions (s)
Hierarchical model of information processing: Few fast transitions but
many processing units ( 1018 tubulins in brain)
Many slow transitions but few processing units (1011 neurons per brain)

Fractal organization on time and
spatial scales
Ghosh S., et al. Information 2014, 5:28-100.
.
Hierarchical model of information processing: Few fast (ns) transitions but many
processing units ( 1018 tubulins in brain)
Many slow (s) transitions but few processing units (1011 neurons per brain)

Brain has a bandwidth of 1030 Hz
(from 10-15 to 1015 Hz)
Anirban Bandhopadhyay.

Focusing on the Dendrite
Previous and
current study
future study

MTs and Neurodegenerative
diseases
 A common feature: a deteriorating cytoskeleton:
 Typical sequence of events:
DNA Mutation or PTM ->misfolding->aggregation ->loss of function->
Neurodegenration
Examples: AD, PD, CJD, ALS, HD, TBI
 Bioengineered cytoskeletal protein products or pharmacological
agents can stabilize, or destabilize the existing cytoskeletal matrix,
and prevent neuronal degeneration resulting from multiple causes.

Alzheimer’s disease
 Both the neuronal and cognitive consequences of cytoskeletal
protein disruption
 Cortical neurons in AD brain accumulate hyperphosphorylated tau, a
MAP, which triggers the formation of neurofibrillary tangles.
 Neurons in AD demonstrate impaired axonal transport and
compromised MT matrixes, even in the absence of neurofibrillary
tangles.
 Beta amyloid protein accumulates in the ECM

93
Alzheimer’s Disease (AD)
• Alzheimer’s disease (AD) characterized by b-Amyloid plaques
(bAPs) and neurofibrillary tangles (NFTs).
• NFTs formed from hyperphosphorylated MAP-tau.
• bAPs correlate with cell death, NFTs with memory impairment.
• Link between these unknown.
93

MT’s in Parkinson’s and
Huntington’s diseases
 Mutations in genes for α-synuclein and parkin proteins lead to
familial Parkinson’s, and contribute to sporadic cases
 Altered α-synuclein and parkin proteins result in impaired axonal
transport of dopamine-containing vesicles. Dopamine is released
and degraded into toxic by-products that kill dopamine-containing
neurons.
 Huntington’s chorea: an autosomal dominant disorder caused by
mutations in huntingtin protein, characterized by polyglutamine
repeat expansion. Polyglutamine repeats in huntingtin protein
disrupt its binding to microtubules resulting in impaired axonal
transport.

 Stroke and traumatic brain injury – The cytoskeleton is
disrupted following ischemia due to blood hemorrhage, occlusion, or
injury.
 Epilepsy – Microtubule-associated protein, MAP2, shows decreased
phosphorylation in parts of brain where epileptic seizure activity is
prevalent. This is indicative of impaired cytoskeletal dynamics.
 Amyotropic lateral sclerosis (ALS) – Axonal transport is
compromised in this movement disorder as a result of cytoskeletal
disruption.
 Charcot-Marie-Tooth disease – A cause of impaired axonal
transport may be stalled microtubules that assume a hyperstabilized
state due to mutated dynamin2 protein.
 Multiple sclerosis – This demyelinating disease also involves
disruption of axonal cytoskeleton.

96
What is Memory?
 Ability to encode, store and
recall information.
 Postulated to be represented by
vastly interconnected networks of
synapses in the brain.
 Memories formed by changing
synaptic strengths (Hebbian
Theory / Synaptic Plasticity)
 Supported by the paradigm of
Long-Term Potentiation (LTP)
 How is this achieved on the
molecular level?
 What is the underlying substrate?
96

Memory storage
Holographic: Lashley, Pribram: mouse studies
Fractal, resonant, tubulin: Anirban
Sheldrake: Memories not stored
in the brain at all
caterpillar study, slime mold, ants
Plants that learn.
Bacteria that learn.
Mice descendants that do mazes more
quickly

• Is memory localized? Persistence of long-term
memory after head regeneration
Memory Storage
Shomrat & Levin, Journal of Experimental Biology 216:3799-3810, 2013
98

• If we want to listen to our intuition or gut
feeling, what information are we accessing?
• Is this information holographic or localized?
Are microtubules involved to access it?
• Can we measure this ability?
– Galvanic skin response (lie detector)
– Heart rate variability
– Noninvasive nanosensor biofeedback
Memory, Intuition, Gut feeling
99

Capacity of Human Memory?
 Von Neumann (1950) – 3x1020 bits
Total life experience -we agree
 Anatomists (1970’s) – 1013-1015 synapses
allowing 1016 syn-ops/sec
 Landauer (1986*) – 109 bits
 assumed we retain 2 bits/sec of visual, verbal,
tactile, musical memory!
 Human lifetime ~ 2.5 billion seconds
Thomas K. Landauer "How Much Do People Remember? Some Estimates
of the Quantity of Learned Information in Long-term Memory" Cognitive Science
10, 477-493, 1986

Historical Perspective
 1 Human = 1019 bytes
 # of Words ever written = about 1016 bytes
 # of Words ever spoken = about 1019 bytes
 Data on all Digital Media = 3x1019 bytes
http://www.lesk.com/mlesk/ksg97/ksg.html

102
Cytoskeletal Involvement in
Memory
 Synaptic plasticity:
 neuronal differentiation, movement,
synaptogenesis and regulation.
 All involve cytoskeletal remodeling.
 Assembly/reorganization of Microtubules
(MTs) and MAP cross bridges
 Directing motor proteins transporting
molecular cargo along MTs
 MT-MAP alterations correlate with
memory formation.
 Dysfunction affects learning/memory.
 MT disrupting agents affect memory.
102

Calmodulin kinase complex CaMKII as memory
read/write device

104
Information Storage
• Phosphorylation conveys
information.
• Each CaMKII – MT event
conveys 64 - 5218 bits.
• Each kinase event releases
~20 kT
• Robust encoding
104

Memory storage
Long-term Potentiation (LTP):
synaptic strength
Craddock:
MT phosphorylation
“Cytoskeletal Signaling: Is Memory Encoded in Microtubule Lattices
by CaMKII Phosphorylation?” by Craddock, Tuszynski, Hameroff
(2012).

106
Ca2+/Calmodulin Kinase II (CaMKII)
• Vital for memory (long term potentiation – LTP)
• Single point mutations cause memory impairment.
• Suggested as a molecular switch for memory.
• Records synaptic activity, retaining a ‘memory’ of past Ca2+
influx events in terms of activated phosphorylation states.
106

107
CaMKII Phosphorylates MT
• CaMKII phosphorylates S/T residues in many protein substrates.
• Tubulin one target of CaMKII.
• a,b-tubulin phosphorylated on S/T beyond residue 306.
• Phosphorylation alters MT interactions with MAPs.
107
Serine
Threonine
Positive
Negative

108
Geometric Matching
•Basic homology
models of CaMKII and
MT.
•Positional geometry
aligned.
•Kinase regions found to
closely match MT
lattice geometry with
multiple forms.
108

109
Electrostatic Matching
• Field lines convergent
showing electrostatic
attraction.
• ~10 kT/e (6 kcal/mol at
310 K) attraction for single
kinase.
• Considerable binding
energy.
109

110
Information Storage
• Phosphorylation conveys
information.
• Each CaMKII – MT event
conveys 64 - 5218 bits.
• Each kinase event releases
~20 kT
• Robust encoding
110

How does this affect neural function?
111
• PTMs may serve as tags
for MAPs to bind.
• Control:
• Neural structure
• Transport
• Synapse structure
• TRP excitation

Potential base for Universal Logic
112
AND XOR

Computational predictions and partial experimental conformation
exists for the binding of psychoactive drugs to tubulin which
suggests enhancement of cognitive functions by the action of these
drugs
This is consistent with the Hameroff hypothesis of the quantum
states of tubulin being involved (if not responsible) for mental
processes.
Anesthetics quench quantum hopping
Psychoactive drugs enhance quantum transitions
Our hypothesis: these compounds interact with the quantum
information processing in MTs
Mental Activity, Microtubules and Quantum Biology

Caffeine THC Marijuana LSD Adrenaline
Nicotine MDMA Ecstasy Chocolate Methamphetamine
Xanax Heroin Rohypnol (Date rape) Alcohol

What about Consciousness?
• Much harder to define.
• Related to brain function and memory.
• Penrose-Hameroff “Orch OR” most
comprehensive extended thcory
• Quantum computation in brain MTs.
• Anesthetics inhibit quantum states.
• But, isn’t biology too “warm and wet”
for quantum effects?
• Recently, quantum coherent energy
transfer shown photosynthetic systems.
• Can microtubules support similar
phenomena?
• Could anesthetics inhibit this
phenomena?
116

Anesthetic-Microtubule
Interactions?
 Hypothesis: The microtubule (MT)
network in dendrites is related to
memory, and interaction with
anesthetics can influence
consciousness and alter memory
formation.
 Anesthetics natural probe for
functional sites of consciousness
 Memory formation and learning rely
on normal MT cytoskeleton
functioning
 Postoperative Cognitive Dysfunction
(POCD)
 Exacerbation of diseases (Alzheimer’s,
FTD, Schizophrenia) following
anesthesia
http://www.brainleadersandlearners.com/wp-
content/uploads/2008/09/blog-brain-business2.

GAs Possess Dissimilar Structure
Inhaled Intravenous
Propofol
Ketamine
Etomidate

119
What about anesthetics?
119
• Anesthetics provide analgesia, hypnosis, paralysis
and amnesia.
• Volatile anesthetics reduce polymerized MTs
• MT to macrotubule transformation by halothane.
• Halothane modifies colchicine-tubulin binding.
• Tubulin altered out to 3 days by desflurane.
• Tubulin altered out to 28 days by sevoflurane in rat.
• Halothane binds specifically to tubulin in humans
• Tubulin is changed by halothane and isoflurane in
rat.
• Of ~500 detectable proteins, tubulin among the
~2% affected by halothane, and ~1% altered by
isoflurane (1 of 3 affected by both)
• Location/ mechanism of interaction unknown

120
• 47 Distinct Sites found
• 9 sites found to persist for more than 70% of the 5 ns simulation.
• Of these 9, key sites of interaction include:
– GTP binding site (responsible for dimer stability)
– Colchicine binding site (a MT depolymerizing agent)
– Vinca Alkaloid binding site (a MT depolymerizing agent)
– Putative zinc binding sites (involved in MT polymerization)
• Findings indicate only longitudinal/intradimer interactions are affected.
Putative Anesthetic Binding Sites
120

Anesthetics and Tryptophan Excitation
• Anesthetics possess a large dipole moment.
• Putative anesthetic sites lie as close as 7 Å to tryptophan
residues.
• Anesthetic dipole can influence tryptophan transition dipoles.
• Plausible that anesthetics interfere with potential energy transfer.
121

Quantum Psychology
The Development of a New Formalism: Second Quantization:
Transitions between Normal States of Mind (Maslow’s hierarchy of
needs)
Bosons and Fermions
Creation and annihilation operators
Commutator and anti-commutator algebras
Quantum energy states and the action of creators and annihilators on
energy eigenstates (excitation and de-excitation processes)
In mental states, the processes that either spontaneously or by
external intervention take the subject either to a higher level of mental
excitation or towards depression
Excitation in affective or psychotic terms
Coherent states and squeezed states

Psycho-Pathology
• The Development of a New Formalism: Q-Deformed Algebras and the
Distorted States of Mind in Mental Diseases
• q-bosons and q-fermions
• q-statistics
• the number of q deformations and the strength of deformation
• examples: an extension to quaternion values of the deformation parameter
• I= affective polarization (Fermi-Dirac statistics)
• J=cognitive efficacy (Superpositional probability)
• K=social integration (Bose-Einstein statistics)
• defining mental state axes in stages, (1) psychotic-non psychotic; (2)
affective-euthymic: (3) impulsive-controlled, (4) anxious – not anxious: (5)
autononous – enmeshed;

Connection to clinical psychiatry
• multidimensional classification systems taking account of quantum
statistics
• transitional states between normality and illness (even healthy people at
times can experience psychiatric problems
• transitional states grading severity of illness and predicting clinical course
• predictable and random effects determining clinical course and catastrophic
events

Future Goals
• To use quantum models to create a more adequate explanatory framework
for psychopathological phenomenology.
• To enlist quantum-formal actuarial tools for rigorous prospective estimation
of the impact of random and potentially predictable events on the evolution
of illness states and catastrophic events
• To use quantum statistics in actual risks assessments in a prospective and
hence more realistic context.

126
The Problem with Embryology
Egon Schiele
Kneeling Male Nude (Self-
Portrait). 1910.
http://www.moma.org/exhibitions/schiele/artistwork.
html
Nikas, G., T. Paraschos, A. Psychoyos & A.H. Handyside (1994). The zona reaction in human
oocytes as seen with scanning electron microscopy. Hum. Reprod. 9(11), 2135-2138.
?
How did your spherically
symmetrical egg turn into
such a highly
asymmetrical shape?
1,000,000 µm = 1 meter

Staging of Axolotl Development
127
Top views 
Side views 
Bottom views 
Side view
L R
Bordzilovskaya, N.P.,
T.A. Dettlaff, S.T.
Duhon & G.M.
Malacinski (1989).
Developmental-stage
series of axolotl
embryos. In:
Armstrong, J.B. &
G.M. Malacinski,
Developmental
Biology of the Axolotl,
New York: Oxford
University Press, p.
201-219.

128
Staging of Axolotl Development
head
tail
right side
Timing, at 20oC:
Stage Time
in
hours
What’s
starting
2- 0 Synchronous
cleavage
2 0.6 2 cells
3 2 4 cells
8 16 Blastulation,
asynchronous
cleavage
10 26 Gastrulation
14 36 Neurulation
19 69 Neural tube,
eyes, somites
44 340 =
14 days
Mouth opens,
hatching
16

129
Stages 23-35 of Axolotl Development

130
Stages 36-44 of Axolotl Development
No increase in dry weight
since it was an egg!

131
The Cell State
Splitter
MF =
microfilament ring
MT =
annular apical
microtubule mat
IF =
intermediate
filament ring

132
The Unstable (Bistable) Mechanical Equilibrium
between the Microfilament Ring and the
Microtubule Mat in the Cell State Splitter
Gordon, R., N.K.
Björklund & P.D.
Nieuwkoop (1994).
Dialogue on
embryonic induction
and differentiation
waves. Int. Rev.
Cytol. 150, 373-
420.
MF ring is a torus of radius r and cross sectional area A,
empirically of constant volume V
Force F A
V = 2πrA, so
F 1/r, a hyperbola

133
The Differentiation Tree
Embryogenesis may be
modelled as a bifurcating
sequence of tissues
generated as each tissue
is split into two new
tissues by pairs of
contraction and expansion
waves.
Unsolved problems:
1. What launches these
waves at specific times
and locations?
2. What confines their
trajectories?
3. What stops them?

134
The Differentiation Tree is the Physical Embodiment
of Conrad Waddington’s Epigenetic Landscape
Held Jr., L.I. (1992). Models for Embryonic Periodicity, Basel: Karger.

135
Nouri, C., R. Luppes, A.E.P. Veldman,
J.A. Tuszynski & R. Gordon (2008).
Rayleigh instability of the inverted one-
cell amphibian embryo [In: "Physical
Aspects of Developmental Biology"
special issue]. Physical Biology 5,
015006.
in collaboration with:
Institute of Mathematics & Computing
Science
University of Groningen

136
Cortical Rotation
• Forced Cortical Rotation:
Direction of the last forced rotation determines the left-right symmetry.
Gerhart et al (1989)
Many observers report the alignment of
microtubules during and after the cortical rotation

137
When an egg is inverted:
• 1. The egg will not develop at all.
• 2. It will develop but with colors of dorsal and vegetal .
regions exchanged.
We suggest that it has to do with the way the heavy fluid on
top sloshes down the inverted egg’s volume, Case 1 corresponds
to symmetric fluid flow. Case 2 to asymmetric flow.
One of the following happens:
Wakahara, et al (1984), Neff, et al (1986), Malacinski and Neff (1989),

138
Working Hypothesis
• Cortical rotation aligns microtubules attached
to the inner surface of the cortex via global
torque T
• Microtubules drive the cortical rotation by
polymerization and/or motor molecules
attached to them, each contributing torque Ti,
with T = Ti
• This can be represented as a mean field Ising
model in which the mean field is precisely the
same as the local field

139
ComFlo Computational Fluid
Dynamics Simulation
Symmetric sloshing of the heavier liquid (yolk) in the inverted egg. This particular case has too
low a viscosity.

140
Summary
• Memory depends on the neuronal cytoskeleton.
• This basis yields:
– A molecular mechanism of synaptic plasticity and memory
encoding.
– A link between the hallmarks of Alzheimer’s Disease.
– A mechanism for the amnesiac affect of anesthetics.
• Quantum phenomena in microtubules could serve as a basis for
consciousness, and anesthetics could potentially inhibit this
phenomena.
140

Implications for Health and
Disease
Quantum coherence= a healthy state
Decoherence=transition to disease
Location of decoherence determines
“disconnection” from the rest of the organism;
canonical example: cancer
141

• Already doing this with EKG, EEG for
diagnostic purposes
Body: Bioelectric medicine
142

• Is this an avenue for non-invasive signals?
– Yes
• Able to deliver quality information on the
health of the body?
– Yes
• Able to detect disease at an early stage?
– That’s what we’re working on
Bioelectric medicine
143

• Bioelectric signals
• Morphogenesis
• Cell membrane (cancer depolarized)
Michael Levin
144

Morphogenesis and cancer
Levin, BioSystems 109:243-261, 2012
145

• Hypothesized by Dr. James Oschman
• High-speed electric communication system
made up of biological wires in the body:
networks of:
– Microtubules
– Actin
– Collagen
The Living Matrix
Friesen et al. BioSystems 127:14-27, 2015
146

Microtubule conductivity
Friesen et al. BioSystems 127:14-27, 2015
Coherent
Energy
Transfer
147

• Flexible, transient electronics
Nanotechnology advances
John A. Rogers Group
University of Illinois
148

• NanoFET (Nano Field Effect
Transistor)
• Intracellular electrical
recordings
• Charles M. Lieber group
(Harvard)
Nanotechnology advances
Tian and Lieber, Annu. Reb. Anal. Chem 6:31-51, 2013
149

• Nanosensors to measure health of body, in
terms of communication within cells and
between cells and between organs and tissues
(pictures of nanosensors)
• Possible explanation of acupuncture meridian
system, and 24 hour monitoring of this system
• Further understanding of microtubule to
understand possible quantum computation and
access to holographic information
• Better models to understand why processes
like NLP work
Bioelectronic future
150

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