Capturing Brain Dynamics: a combined
neuroscience and engineering approach
Adrian KC Lee, ScD
!
Department of Speech & Hearing Sciences
Institute for Learning and Brain Sciences University of Washington
!
June 30, 2015
[LABS]N
Speech & Hearing !
Sciences
Laboratory for
Auditory
Brain
Sciences &
Neuroengineering
Listen up! There may be a price!
Human can do this effortlessly,
computers cannot (for now).
Can I order
your Huskies
cocktail?
Do you like this!
small batch! Did you order!
order your
rye?
Manhattan with!
bourbon or rye?
Artwork: Michelle Drews
That’ll be!
$9.50
Rye. Wanna try?
Alex Katz, The Cocktail Party, 1965. Licensed by VAGA, New York, NY
Cocktail party problem (Cherry, ’53)
Neuroengineering
Listeners attend to “objects”
Let’s play “password”
(Listen to the male voice)
What’s the password?
What did you miss out on?
Neuroengineering
Top-down selective attention
Let’s play “password”
(Listen to the male voice)
What’s the password?
What did you miss out on?
Neuroengineering
Neurons
Neurons
‣ Building blocks of the nervous system
# neurons
# synapses
Sponge
0
0
Roundworm
302
5,000
Mouse
75,000,000
Cat
1,000,000,000
Human
http://en.wikipedia.org/wiki/List_of_animals_by_number_of_neurons
~10
~10
85,000,000,000 ~10
Neuroengineering
Neuron morphology
Dendrites
Soma
Axon
Myelin
sheath
Terminal
Button
http://animatlab.com/Help/Documentation/NeuralNetworkEditor/NeuralSimulationPlugins/FiringRateNeuralPlugin/NeuronBasics/tabid/117/Default.aspx
Neuroengineering
Types of neurons (structural)
‣ Bipolar
• 2 processes: 1 axon & 1
dendrite - seen in special sensory
neurons for olfaction
and vision
‣ Pseudo-unipolar
• 1 process
- most sensory neurons
‣ Multipolar
• multiple processes
- most common
http://droualb.faculty.mjc.edu/Course%20Materials/Physiology%20101/Chapter%20Notes/Fall
%202011/chapter_7%20Fall%202011.htm
Neuroengineering
Types of neurons (functional)
‣ Functional classification
• Afferent
- neurons transmitting sensory information from
sensory receptors to the CNS
• Interneurons
- perform complex integrative and analytical
functions. Most neurons are interneurons
• Efferent
- neurons transmitting commands from the
CNS to sensory organs.
Neuroengineering
Action potential / Myelination
‣ Action Potential YouTube video
• http://www.youtube.com/watch?v=ifD1YG07fB8
‣ Myelination
• several-layer wrapping around axon
• prevents ion flow across membrane
• Nodes of Ranvier: regions of exposed axon, action potentials
regenerate here
Node of
Ranvier
http://www.nature.com/nrn/journal/v4/n12/fig_tab/nrn1253_F1.html
Neuroengineering
Graded Potentials
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Graded vs. Action Potentials
‣ Graded potentials
• Variable magnitude
• +ve or -ve
- excit. or inhib.
• Passive propagation
• Spatial and temporal
summation
‣ Action potentials
• All-or-none
- Threshold
- Post-AP refractory
period
• Active propagation
• Saltatory propagation
(in myelinated axon)
Neuroengineering
Brain Structures
Brain Structures
‣ Cerebrum (or cortex)
http://www.youtube.com/watch?v=h5f56Ynb01E
• largest part of the human brain
• 4 lobes: frontal, parietal, occipital, temporal
‣ Cerebellum
• “little brain”
‣ Limbic system • contains thalamus,
hypothalamus, amygdala
and hippocampus
‣ Brainstem
• made of midbrain, pons
and medulla
http://www.withthebraininmind.org/buildingbrains/unit_3/unit_3_03.php
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Lobes of the brain
Frontal
lobe
Parietal
lobe
Occipital
lobe
Temporal
lobe
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Brodmann area
Primary
Somatosnsory
Primary area (3, 1, 2)
motor (4)
‣ Cerebral cortex defined by
Wernicke’s
cytoarchitecture
Broca’s area
area
(39,40)
• based on structure and (44, 45)
organization of cells • first published by German
anatomist Korbinian
Broadmann in 1909
• published maps in
humans, monkeys and
other species.
Auditory cortex (41, 42)
Neuroengineering
Gray / White matter
‣ Gray matter
• made up of cell bodies
‣ White matter
• made up of nerve fiber / mylinated axons
Neuroengineering
Methodology
Neuroanatomy
‣ Gross anatomy of the brain
Suzana Herculano-Houzel, 2009
Neuroengineering
‣ Golgi
• whole neurons
Staining
‣ Immuno
• attach dye to
specific chemical
markers
‣ Nissl
• cell bodies
http://en.wikipedia.org/wiki/
File:Anaplastic_astrocytoma_-_gfap__very_high_mag.jpg
http://www.conncad.com/gallery/spines_synapses.html
http://vanat.cvm.umn.edu/neurHistAtls/pages/neuron6.html
Neuroengineering
Magnetic Resonance Imaging (MRI)
‣ Non-invasive technique
• Limited spatial
resolution ‣ Adjust signal contrast to
differentiate tissues,
nuclei based on different
magnetic properties
‣ Measures brain
morphometry
Neuroengineering
Determining connectivity
‣ Non-invasive techniques using MRI
• Diffusion tensor imaging
• Diffusion spectrum
The Connectum Project
http://upload.wikimedia.org/wikipedia/commons/d/d2/Illus_dti.gif
Neuroengineering
Functional anatomy
Lomber and Malhotra, 2008
http://philosophicaldisquisitions.blogspot.com/2012/05/
hauskeller-on-enhancement-for-common.html
‣ Lesion studies
• chronic
- patient studies, surgical lesions
• reversible
- transcranial magnetic stimulation; cooling
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Functional anatomy
‣ Functional neuroimaging
• non-invasive techniques
- most common: fMRI, EEG, MEG
- other techniques: PET, NIRS, ASL: ★
★
★
PET = Positron emission tomography
NIRS = Near-infrared spectroscopy
ASL = Arterial Spin Labeling
Neuroengineering
Functional MRI
Measuring BOLD response
‣ Blood-oxygen-level-dependent contrast (BOLD)
• Discovered in the early 1990’s
- Belliveau et al (HMS)
- Ogawa et al (AT&T)
• Oxygenated blood is diamagnetic
- minimal effects on magnetic field
• Deoxygenated blood is paramagnetic
- clearly measurable additive magnetic field
Neuroengineering
Temporal dynamic of BOLD response
‣ BOLD hemodynamic response
• Sampling rate at 0.5Hz is adequate
• Repetition Time (TR) -
Depends on SNR
Spatial coverage (# of slices)
Long TR maximizes SNR
Short TR maximizes fMRI stats
BOLD signal amplitude
- M/EEG sampling rate ~1kHz
~20s
Time
© 2004 Sinauer Associates, Inc.
Neuroengineering
fMRI “Event-related designs”
‣ Assumes BOLD signal to be Linear Time-Invariant
Estimate individual BOLD signal:
1. Parametrically (based on a canonical
waveform, e.g., gamma functions)
II. Non-parametrically (finite impulse
response estimation)
Block designs -- good for detection
Event-related -- good for estimating shape of HRF
Neuroengineering
M/EEG
Right-Hand Rule
Neuroengineering
Action Potentials
Current configurations
m
Q
m
B
Synapse
Action currents Postsynaptic currents
Courtesy of Matti Hämäläinen, Aug 2010
Time behavior
‣ Electric signals propagate
within the brain along axons
as a series
of action potentials
100 mV
10 mV
(AP)
• 1 ms
Modeled as “quadrupolar”
10 ms
source
Action potential Postsynaptic potential
• Mediated by Na and K
voltage-dependent ionic
conductances
http://www.youtube.com/watch?v=ifD1YG07fB8
http://www.youtube.com/watch?v=LT3VKAr4roo
Neuroengineering
Postsynaptic Potentials
Current configurations
m
Q
m
B
Synapse
Action currents Postsynaptic currents
Time behavior
‣ Postsynaptic potential (PSP)
• In synapses, chemical
transmitter
100 mVchange ion
10 mV
permeabilites of
postsynaptic membrane
1 ms
10 ms
• Can adequately be
Action potential Postsynaptic potential
described as a single current
dipole oriented along the
dendrite
Courtesy of Matti Hämäläinen, Aug 2010
Neuroengineering
AP vs. PSP
Current configurations
Time behavior
Current
Source
m
Q
m
B
Synapse
Approx.
100 mV
AP
Quadrupolar
1 ms
10 ms
Action
potential
PSP
Field “falls
off” rate
10 mV
1/r
Postsynaptic
potential
Dipolar
1/r
Action currents Postsynaptic currents
Courtesy of Matti Hämäläinen, Aug 2010
Neuroengineering
Time-varying electrical currents
Current configurations
Time behavior
‣ Action potential
• fast time course (~ms)
‣ Postsynaptic potential
100 mV
10 mV
m
Q ms)
• slower time course (~10
m
1 ms
10 ms
‣ Temporal summation of B
Synapse
currents is more
effective for Action potential Postsynaptic potential
synaptic currents
Action currents Postsynaptic currents
M/EEG signals are
‣ Therefore,
largely due to synaptic current
flow
Courtesy of Matti Hämäläinen, Aug 2010
Neuroengineering
Physics of M/EEG signals
EEG
V
Jp
Primary currents
Courtesy of Matti Hämäläinen, Aug 2010
Neuroengineering
Physics of M/EEG signals
EEG
V
Jp
‣ The primary current is related
to the postsynaptic activity
‣ The primary current generates
a potential distribution (EEG) Primary currents
and the associated volume
currents
‣ The primary and volume
currents together also create a
magnetic field (MEG)
Courtesy of Matti Hämäläinen, Aug 2010
Neuroengineering
=
Physics of M/EEG signals
Conductivity profile is irrelevant
B=0
B=0
No magnetic
fieldradial
from radial currents
No magnetic
field from
currents in the sphere model
Primary currents
cortex
EEG
MEG = 0
EEG x 0
V
Jp
“MEG sees less, but
sees more clearly.”
- David Cohen, MEG inventor
MEG x 0
EEG x 0
current sources
Courtesy of Matti Hämäläinen, Aug 2010
Neuroengineering
MEG vs. EEG field patterns
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Maxwell Equations
‣ Equations describing the fundamental relationship
between electricity and magnetism
Quasi-static E = Electric Field
approximation
B = Magnetic Field
0
J = Total current density
∂B
ρ = Total charge density
∇×E=−
∂t
ε0 = Permittivity of free space
∇⋅B = 0
0 µ0 = Permeability of free space
∇⋅= Divergence operator
∂E +
(
∇ × B = µ0 * J + ε 0
∇× = Curl operator
-
ρ
∇⋅E =
ε0
)
∂t ,
Neuroengineering
Neuronal
Synchronization
Neural synchronization
‣ A red Ferrari sports car drives by you’re perceiving:
• color -- red
• stimulus category -- car
• motion -- moving fast
‣ But information processed in different subregions of
the brain
• What binds these information?
- phase synchronization supports neural communication
- “communication through coherence”
Neuroengineering
Neural synchronization
‣ In animal experiments
• extracellular action potentials
- correlations between spikes in two regions
- coupling between spikes in one region and local field potentials
in the same or a different region (spike-field coherence)
‣ M/EEG
• Phase relation between 2 regions
- phase synchronization
• Important to note:
- no intrinsic relationship between power effects and phase
synchronization on a larger spatial scale
Neuroengineering
Phase synchronization
Phase synchronization
phase lag = 0
phase lag ≠ 0
No phase synchronization
Neuroengineering
Cross-frequency coupling
phase-amplitude
coupling
phase-phase
coupling
Neuroengineering
fMRI vs M/EEG
fMRI vs. EEG and MEG
‣ E/MEG = Electro-/ Magneto-encephalography
• electric potential / magnetic field measured
on / near the scalp
- directly measures synaptic (postsynaptic)
current flow
- EEG and MEG provide complementary
information
★
simultaneous E/MEG with additional MRI information can
increase spatial resolution
- temporal resolution: ~ ms
Neuroengineering
Trade-offs of fMRI and M/EEG
Imaging Modality
Temporal
resolution
Physiological
Signals
fMRI
~ seconds
Hemodynamic
~ milliseconds
Post-synaptic
potential
M/EEG
‣ Trade-offs:
• fMRI spatial resolution (~ 1mm) < M/EEG (~ 1cm)
• ms-resolution is important for auditory research
• M/EEG can reveal oscillatory activities
Salmelin, Parkkon, MEG: an introduction to methods
Neuroengineering
Choosing the right methodology
Neuroengineering
Source Imaging
Forward Modeling
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Inverse Estimate
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Towards solving the Inverse Problem
‣ Mapping MEG signal onto the cortex
Forward solution
M/EEG
y = Gq + ε
{ }
E εε T = C
Inverse estimate
(
q̂ = arg min y − Gq
q
Equivalent
currents
2
C
Observed data
Noise covariance
+ f ( q)
) Minimum L2-norm: |q|
2
Minimum Current: |q|
Penalty term
Neuroengineering
Neuroengineering
Next generation hearing-aid design?
Artwork: Michelle Drews
Sound
Sound
Brain
Amp
Amp
Noise
Reduction
Brain
Speech enhancement
Feedforward only
Sound
Amp
Brain
with feedback
Eric Larson
Research scientist
Majid Mirbagheri
Postdoc fellow
Mark Wronkiewicz
Grad student (Neuro)
Neuroengineering