EEG and MEG: Functional Brain Imaging with High Temporal ...EEG and MEG: functional brain imaging with high temporal resolution Syed Ashrafulla . electrical signals in the brain Source:

EEG and MEG: functional brain imaging with high temporal resolution

Syed Ashrafulla

electrical signals in the brain

Source: Baillet, S., Mosher, J. C., & Leahy, R. M. (2001). Electromagnetic brain mapping. IEEE SIgnal Processing Magazine, (November).

recordable signals Pyramidal Neuron

Soma

Apical Dendrites

Axon

Right Hand Rule

Source:Matti Hamalainen

Murakami, S., & Okada, Y. (2006). Contributions of principal neocortical neurons to magnetoencephalography and electroencephalography signals. The Journal of physiology, 575(Pt 3), 925–36. doi:10.1113/jphysiol.2006.105379

measurable currents

• We can only measure assemblies of neurons.

0.2pAm

10nAm Or 50,000 synchronous cells

Weakest measurable cortical signal Model as one “dipole”

Current dipole of cortical pyramidal cell

Area 0.63mm2

Cortical area

0.9mm

electroencephalography (EEG)

intracellu

lar curren

t extr

acel

lula

r cu

rren

t

extracellular cu

rrent

magnetoencephalography (MEG)

induced magnetic field

MEG signal strength

MEG artifacts

• Use signal space projection and noise cancellation techniques in preprocessing.

what can/can’t be seen

Source: Matti Hamalainen

what can/can’t be seen

Source: Matthew Longo

sensitivity profiles

EE

G

ME

G axial grad

iom

eter M

EG

pla

nar

gra

dio

met

er

ME

G m

agn

eto

met

er

EEG vs MEG

EEG MEG Signal magnitude 10 mV (easy to detect) 10 fT, difficult to detect

Measurement Secondary currents Primary currents

Signal purity Skull/scalp attenuation Little effect of skull/scalp

Temporal Resolution ~ 1 ms ~ 1 ms

Spatial Localization ~ 1 cm < 1 cm

Experimental Flexibility Moves with subject Stationary with subject

Dipole Orientation Tangential & radial Most sources are not fully radial

Only tangential

Source: Matthew Longo

EEG/MEG vs. fMRI

EEG/MEG fMRI Temporal Resolution ~ 1 ms ~ 1 s

Signal Type Direct (currents) Indirect (BOLD)

Signal Reconstruction Ill-posed inversion Deconvolution

Spatial Localization ~ 1 cm ≅ 1 mm for high-T

Sensitivity depth ~ 4 cm Whole-brain

Sensitivity profile drops off as square of distance from sensor

Signal orientation Tangential (and radial) Can cause signal cancellation

Agnostic

resolution comparison

modelling EEG/MEG recordings

1Am

Or in matrix form:

qam1

m2

m3m4

m5

m6

m7

g1

g2

g3g4

g5

g6

g7

m1 = g1 ´1

m2 = g2 ´1

m1 = g1

a ´qa + g1

b ´qb + g1

c ´qc

m2 = g2

a ´qa + g2

b ´qb + g2

c ´qc

qb

qc

m =

m1

m2

é

ë

êêêê

ù

û

úúúú

=

g1

a g1

b

g2

a g2

b

é

ë

êêêê

ù

û

úúúú

1

0

é

ë

êêê

ù

û

úúú

=G

1

0

é

ë

êêê

ù

û

úúú

m =

m1

m2

é

ë

êêêê

ù

û

úúúú

=

g1

a g1

b

g2

a g2

b

é

ë

êêêê

ù

û

úúúú

qa

qb

é

ë

êêêê

ù

û

úúúú

+

n1

n2

é

ë

êêêê

ù

û

úúúú

=Gq+ n

Sensor (measurement) noise

inverse imaging

s1

s2

sn

Assume a density of dipoles oriented normally to the cortical surface. Find their amplitude.

m =Gq+nÞ q̂ = argminq

m-Gq2

q̂ = HmÜ q̂a = Ha

TmÜ Ha = argminh

hTGa=1

hT Cov m( )( )h

Minimum-norm estimation (MNE):

Minimum-variance beamforming (LCMV):

(Hui2010, NeuroImage)

(Hauk2004, NeuroImage)

time-frequency decompositions

Ä

X st

=

t

f

Cstf = X st *wtf

θ band: 4-7Hz α band: 8-14Hz β band: 15-30Hz γ band: 30-100Hz

s: spatial index t: temporal index f: frequency index Source: Dimitrios Pantazis

connectivity & EEG/MEG • Connectivity = Relation between x[n] and y[n] Correlation: do x[n] and y[n] change at the same time?

Coherence: do x[n] and y[n] change at the same time for frequency f?

Causality: Is y[n] required to generate x[n]?

Granger causality: Does y[n-1] help predict x[n]?

All methods benefit from the high temporal resolution of EEG/MEG.

BrainStorm demonstration