neurovascular coupling - brainmapping.org · t” neurovascular coupling vascular dynamics ... dp t...
TRANSCRIPT
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Neu
ron
al A
cti
vit
y
“Ele
ctr
ical E
ven
ts”
Fu
ncti
on
al
Imag
ing
“BO
LD
Effect”
Neurovascular
Coupling
Vascular
Dynamics
Linear System
Linear Convolution Model r
BOLD k HRF ky t h t d • Relation with physiology? • Dysfunctions? Diseases
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Physiology of the neurovascular coupling Biophysical models for vascular dynamics
Particulars for Dementia (AD) & Epilepsy
Topics for this talks
![Page 4: Neurovascular Coupling - brainmapping.org · t” Neurovascular Coupling Vascular Dynamics ... dp t t t p t dt H p t dt x x 4 ww f x x u x x H DGl l l 2G c The high-dimensionality](https://reader030.vdocuments.site/reader030/viewer/2022040522/5e7de9fca1643354d20b4c23/html5/thumbnails/4.jpg)
Physiology of the neurovascular coupling Biophysical models for vascular dynamics
Particulars for Dementia (AD) & Epilepsy
Topics for this talks
![Page 5: Neurovascular Coupling - brainmapping.org · t” Neurovascular Coupling Vascular Dynamics ... dp t t t p t dt H p t dt x x 4 ww f x x u x x H DGl l l 2G c The high-dimensionality](https://reader030.vdocuments.site/reader030/viewer/2022040522/5e7de9fca1643354d20b4c23/html5/thumbnails/5.jpg)
Hamel, J Appl Physiol, 2006
EXTRINSIC INNERVATION
superior cervical (SCG) sphenopalatine (SPG) otic (OG) trigeminal (TG)
Ganglion
SUBCORTICAL VASOACTIVE PATHWAYS
NA- norepinephrine NKA- neurokinin A NPY- neuropeptide Y VIP- vasointentinal polypeptide SP- substance P CGRP- calcitonin gene-related peptide PACAP- pituitary adenylate-cyclase activating polypeptide NOS- nitric oxide synthase ACh- Acetylcholine 5-HT- serotonin SOM- somatostatin
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Cauli et al., J Neurosci, 2004
Single interneuron stimulation induces
dilation or constriction of cortical blood
vessels
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Hamel, J Appl Physiol, 2006
SUBCORTICAL VASOACTIVE PATHWAYS
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Drew
el al. P
NA
S, 20
11
Phasic Pathway (NO, PGE2)
Tonic Pathway (Astrocytes)
Riera, Brain Product Press Release, 2011
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Gas Diffusion
NO
NO NO
1
nNOS
Phasic Pathway NADPHd-positive
neuron
Cortical neurons synthetizing NO
Estrada and DeFelipe, Cerebral Cortex, 1998
Nitrergic Neurons
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Stefanovic et al., JCBFM 2007
7NI – Inhibitor nNOS (specific)
killed
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PGE2 Lipid Diffusion
2
PGE2 Lipid Diffusion
Phasic Pathway
Glutamatergic Neurons
Wang et al., Cerebral Cortex, 2005
Large COX-2 labeled dendrites (COX-d1 and d2) are apposed (black block arrows) by nNOS-
containing terminals (NOS-t1 and t2)
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W, Whisker; F, forepaw; H, hindpaw; T, trunk; VC, visual cortex.
Boorman et al., J Neurosci, 2010
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Goense et al., (2012)
PBR
NBR
CBF and CBV increased in the center of the cortex
“Laminar Differences in Neurovascular Coupling
For positive BOLD responses:
For negative BOLD responses: CBF decreased superficially while CBV increased in the center
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Patrick Drew (Personal Communication) Penn State
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Neuronal Astrocytes
Vascular Astrocytes
Cx43 (blue) and Cx30 (red)
Gia
um
e e
t al
., N
RN
, 20
10
Domains do not overlap
Differentially expressed in barrels (dark) and septa (light)
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G βPLC
R
IP3R [Ca2+]ER
Cytosol [Ca2+]
Agonist
SERCA
[Ca2+] Extrusion
SCO
PLC
influx
micro-domain
[Ca2+] CCE
[Ca
2+]
Multiple-Channel Patches
IP3R “hot regions” (clusters) ~ 10 M
Channel
Cluster
Riera et al., Biophysical J (2010)
A biophysical model (astrocytes)
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Population Astrocytic Ca2+ activity (WT mice)
Nimmerjahn et al., Nat Methods (2004)
Cerebral Cortex (in vivo)
Ca2+ activity
Propagation
Hippocampus (in vitro)
Riera et al., unpublished
1
2
Fluo-4 AM
10 m
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Takano et al., Nature Neuroscience 2006
FITC-Dextran (green) Rhod-2 (red)
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Wang et al., Nature Neuroscience 2006
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Neuronal Activity
Neuronal ATP Consumption
Neuronal O2
Consumption
Tissue
pO2
Level
Ca2+
Waves
Glu Glu
Glu Glu
NO NO
NO
NO
Gas Diffusion
AA AA
AA
AA
AA
Acid Diffusion
AA
CYP2C
COX-1
PGT
PGE2 PGE2
LACTATE LACTATE
LACTATE
glycolysis LDH
MCT-1&4
NO +
EET
+
PGE2
+
AA
20-HETE
-
+
NO -
NO
cGMP Modulation
Astrocyte
Riera & Sumiyoshi, CON 2010
Tonic Pathway
soluble Guanylate Cyclase
lactate dehydrogenase (LDH) monocarboxylate transporter (MCT)
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Gordon et al., Nature 2008
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• NO-mediated 20-HETE/EET unbalance hypothesis for vasoconstriction and vasodilations
• Lactate–PGE2 coupling hypothesis
Tonic Pathway
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Physiology of the neurovascular coupling Biophysical models for vascular dynamics
Particulars for Dementia (AD) & Epilepsy
Topics for this talks
![Page 24: Neurovascular Coupling - brainmapping.org · t” Neurovascular Coupling Vascular Dynamics ... dp t t t p t dt H p t dt x x 4 ww f x x u x x H DGl l l 2G c The high-dimensionality](https://reader030.vdocuments.site/reader030/viewer/2022040522/5e7de9fca1643354d20b4c23/html5/thumbnails/24.jpg)
, , , , , ,r t r t t r t r fx x i
,k kt k tr t gy x ε
a) Performing statistical inference about the states,
exogenous inputs and network topology
b) Combining different modalities of functional neuroimaging
data
Why Are Model Needed?
State-Space Model
Discrete nonparametric models
Continuous parametric models , ,l l l l l
l ld t t t dt d t fx x u G w
, 0, , , ,k k k k k
l l l l
t l t l t l tk N
fx x u
,, 2l l
l lE t t
Dw w
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The Fokker-Planck equation describes the time evolution of the probability density function
2, 1, , , ,
2
l
l l l l l l
l l l ij l
ij i j
dp tt t p t dt H p t
dt x x
f
xx u x x
2l l lH DGG
The high-dimensionality of the Fokker-Planck equation can be reduced by using the mean-field approximation
, ,l k l
l l kkp t p tx x
, , , ,k l l l
l k k k k lt t t f x u
l l
k kt E t x
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Riera, Encyclopedia Computation Neuroscience, 2014
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Hemodynamic Model
Riera et al., Hum Brain Map, 2006
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Windkessel Theory
Capillary OEF Mass Balance Equation
Wn
ag e
t al
., N
eu
roIm
age
, 20
06
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spike-density function
Transient Neural Response
Logothetis et al., Nature ,2001
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BOLD signal & EEG recordings
X = -40 mm Y = 8 mm Z = -24 mm
Sumiyoshi et al., Neuroimage, 2011
Wistar Rats (Adult)
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Sumiyoshi et al., Neuroimage 2012, In Press
Coefficient P-value
Intercept (b0) -5.27000 0.100
Regression slope for "PaO2" (bO2) +0.00037 0.700
Regression slope for "PaCO2" (bCO2) -0.00067 0.800
Regression slope for "pH" (bpH) +0.78000 0.060
Regression slope for "MABP" (bMABP) -0.00140 0.070
Regression slope for "HR" (bHR) +0.00094 0.007
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Multiple Compartmental Model
Lay
er V
Py
ram
idal
Cel
l
Riera et al., Hum Brain Map, 2006
Dendrite + Soma
Dendrite
(Tuft)
Dendrite
(Basal)
Soma
Electrotonic Propagation
Intra- & Extra- Cellular Components
GA
BA
ergic
In
tern
euro
ns
Neurona Mass Model
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Phasic (NO) Hemodynamic Model
NO
W
u t t C d
,
lIN PC
NO IN IN PC PC
l T F
C t g S g S
Lin
ear F
ilte
r
(Diffu
sio
n a
nd S
cavenges)
21 exp /k C k C kg I I
Estrada and DeFelipe, Cerebral Cortex, 1998
(NADPHd)
histochemistry
Riera et al., Hum Brain Map, 2006
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Visual Integration
Contrast SPM2 t-test
PCD Orientations
BOLD Effect (Time Course)
Riera et al., Hum Brain Map, 2007
PCD Amplitude (Time Course) Where are these components
coming from?
C1
C2
C3
C4
C2
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Riera et al., Hum Brain Map, 2007
Mes
o-s
co
pic
Vari
ab
les
NO
dHb
CBF
CBV
Synaptic Inputs
Visual Integration
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INTEGRATOR
(apical trunk)
LENGTH
MEAN±SD(μm)
DIAMETER
MEAN±SD(μm)
Branch 1 205.89±25.00 1.26±0.05
Last Compartment 2.48±0.61 2.48±0.61
PROPAGATOR (dendritic trunk)
LENGTH
MEAN±SD(μm)
DIAMETER
MEAN±SD(μm)
Compartment 10 61.64±4.99 2.76±0.25
Compartment 9 60.47±7.68 2.69±0.55
Compartment 8 62.05±5.71 2.80±0.48
Compartment 7 61.66±8.69 2.71±0.38
Compartment 6 63.29±7.01 2.91±0.47
Compartment 5 62.51±7.44 3.01±0.79
Compartment 4 61.43±8.69 2.99±0.45
Compartment 3 61.93±6.68 3.05±0.45
Compartment 2 61.47±5.12 3.33±0.20
Compartment 1 60.66±9.06 4.34±0.46
DIAMETER
MEAN±SD(μm)
COLLECTOR
(soma) 13.40±1.40
Electrotonic Characteristics of layer V PCs
Wang et al., Neural Comp, 2013
10
0
m
Crivaro et al., J Microscopy, 2011
Extended Split-Gradient Deconvolution Method
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0 1 2 3
1 1 1k
k
t k k
k
q tb V k q t k k v t
v t
van der Zwaag et al., (2009) & Uludag et al., (2009)
BOLD Signal Model 1 0
12k E
20k
31k
7T MRI
Scanner
1
0
0
0
, 1 1 11
f t
EE f E g
g
00.49g g
Vazquez et al., JCBM (2009)
10
0
,dq t E f Ef t v t q t
dt E
11dv t
f t v tdt
Windkessels Theory
4
f t r t Generalized Poiseuille's Equation
2sNO NO PGE PGE EET EET HETE HETE d
dr tn n n n r t
dt
Phasic Response
Stephenson et al., (1994); Golanov et al., (1994);
Alkayed et al., (1995); Ma et al., (1996); Lindauer et al., (1996);
Alonso-Galicia et al., (1997); Sun et al., (2000);
Niwa et al., (2001); Bakalova et al., (2002); Peng et al., (2002);
Xu et al., (2003); Takano et al., (2006); Stefanovic et al., (2007);
Hoffmeyer et al., (2007); Leithner et al., (2009)
34%sPGE
34%
EET
19%HETE
13%NO
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2
2 2 2
2
1 0 0 2
PGE
PGE PGE COX PGT in PGE COX
dn tn t Ca t C L t L n t E t
dt
2
0
EET
EET EET
dn tn t Ca t C
dt P2C
2
0
NOHETE n t
HETE HETE
dn tn t Ca t C e
dt
P4A
2
2
NO O f
NO NO NO NO O NO E I
dn tn t n t n t n f t E t I t
dt
2 2 2 2
2 2 2 0,
O O O O
O O pp E E O
dn tn t l t E t I t E f E
dt
2
2
0 0in in in
in G NO f
L L L NO L PGT in PGE
E I pp
TCA TCA TCA
dL tn t Ca t C n t f t L t L n t
dt
E t I t l t
Dynamic Model Metabolites Astrocytes
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Blinder et al. Nature, 2013
Communities Resistances
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Vascular-steal/leakage effect
CBF CBV
CBF CBV CBF CBV
NA
O2
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Pa
PIC = PCV
CW1 RW1
Ra1(t)
CW2 RW2
Ra2
Rv Rv R12
Windkessel Model Parallel Compartment
Rak (t0)+ RWk0
+ Rv = 1
0.60 % 0.30 % 0.10 %
bA
-β1
kk
V V WkC
0
k
kk
V
VV RR W0Wk
bwo0RF
0V A
- Laminar Flow b - Diminished Volume Reserve P
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0 2 4 6 8 10 12 14 16 18 200.985
0.99
0.995
1
1.005
1.01
1.015
Time (Sec)
[Hb
r]
2 4 6 8 10 12 14 16 18 20
1
1.05
1.1
2 4 6 8 10 12 14 16 18
0.994
0.996
0.998
1
Time (Sec)
CB
F
0 2 4 6 8 10 12 14 16 18 200.9
1
1.1
0 2 4 6 8 10 12 14 16 18 200.995
1
1.005
1.01
1.015
Time (Sec)
CB
V
0 2 4 6 8 10 12 14 16 18 20-0.03
-0.02
-0.01
0
0.01
0.02
0.03
Time (Sec)
BO
LD
PBR
NBR
R12 =[.1, .45, .8, 1.15, 1.5]
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Physiology of the neurovascular coupling Biophysical models for vascular dynamics
Particulars for Epilepsy and Dementia (AD)
Topics for this talks
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L R
A
P D V
A
B
C
D
R L
2.08 mm
Song et al. OHBM Poster 2264
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32 Channel EEG
Mini-Cap
MRI based template
Sharp-Wave
Spikes
EEG Waveforms Topography Tomography
EEG Source Analysis
Bae et al. OHBM Poster 2198
Magnetic Resonance Research
Center
Yale University
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sL
OR
ETA
(Co
rtica
l)
EE
G-T
rigg
ere
d B
OL
D
BOLD Effect
vs.
Current Source Imaging
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Yinchen Song, PhD Candidate
1 2
Electrophysiological Recording
Laser Doppler Flowmetry
System
for R
eco
rdin
g In
trinsic O
ptical Sign
als
A B
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Electrocorticography (ECoG)
Pediatric Focal Epilepsy
500 nm 700 nm
Intrinsic Optical Imaging
Low-Frequency Oscillations
Out-of-phase
Rat FCD
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WT APP-Tg
Mouse strain C57BL/6J C57BL/6J
Genotype WT BE-APP65Sw/Lo
Phenotype normal Promotion of Ab deposition Increase in senile plaque Being prone to dementia
Early: 6-10 months
Middle: 11-20 months
Late: 21-28 months
GROUPS
Animal Model
Riera et al., J Biophysics, 2011
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Pike et al., Exp. Neurol., (1995)
Gliosis in Alzheimer’s Disease
Astrocytes surround the area of
diffuse amyloid accumulation with
long processes
Primitive “Classic” Plaques
- Increases in relation to neurite
dystrophy (Mrak et al., J Neuropathol
Exp Neurol., 1996)
- Contributes to the immunological
cascade, e.g., by initiating an
inflammation with increased IL-6 release
(Huell et al., Acta Neuropathol, 1995;
Wood et al., Brain Res., 1993)
Advanced Stage Plaques
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Takano et al., Ann. N.Y. Acad. Sci., (2007)
Age: 2-4 months
fluo-4 AM
Sulforhodamine 101
Fluorescent Indicators
Triple transgenic (3XTg-AD)
Dutch/Iowa mutation (DI)
APP Sweden Tg-2576 (APP)
Mouse Stream
Kuchibhotla et al., Science, (2009)
• Mutant human Ab precursor
protein (APP)
• Mutant presenilin 1 (PS1) in
neurons
(APPswe:PS1ΔE9)
Mouse Stream
Age: 6-8 months OGB-1 AM + (FLIM)
methoxy-XO4 (Ab)
Sulforhodamine 101
Fluorescent Indicators
Dysfunctions in Alzheimer disease
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Riera et al. Biophysical Journal, 2011
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De
ns
ity o
f C
on
ne
cti
on
s
WT APP-Tg
Str
en
gth
o
f c
on
ne
cti
on
s
0.025
0.020
0.015
0.010
0.005
0 APP-Tg WT
mean±SD
Astrocytic connections: density (WT<APP) and strength (WT=APP)
Percentage of active cells with age: increase (WT) and reduce (APP)
High frequency: > 6 transients / 10 min
WT APP-Tg
Pe
rce
nta
ge
of
ce
lls
Wit
h h
igh
fre
qu
en
cy (
%)
Perc
enta
ge o
f active c
ells
(%
) mean±SD
APP-Tg
WT
Early Middle Late
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Hippocampus L
ate
Ag
e
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1.0
0.8
0.6
0.4
0.2
0.0
Probability Map
(White Noise)
WT APP
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Long-term neuronal activity deprivation decreased Aβ plaque formation/growth
Bero et al., Nat Neurosci (2011)
Sustained Metabolic Activation in the
brain’s default-mode networks
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Early Middle Late
age
Ca
2+
activity
APP
WT Reactivity Dysfunction
Functionality of astrocytes is very
compromised in AD Development
Plasticity
A severely impairment of the cerebral autoregulation in AD
Claassen & Zhang, Cereb Blood Flow Metab (2011)
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Model
“Neurons”
Vasculature
LFP/Unit-Activity
EEG/MEG
Large-Scale
Small-Scale
fMRI-BOLD
Large-Scale
Astrocytes
Vasomotions
Neuronal
Modulation
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Thanks