Basic physiology of fMRI: signal and noise

Overview

•  Brief overview of fMRI •  Contrast mechanisms

–  Source of the fMRI signal

•  Sources of Noise (& corrections) –  Motion

–  Cardiac

–  Respiration

Brain activity during cued finger tapping

Measuring Brain Function with MRI

Task

Neuronal Activity

Red Blood Cells

How can we see brain function with MRI?

red blood cells

oxygenated

deoxygenated

L. Pauling, C. D. Coryell, Proc.Natl. Acad. Sci. USA 22, 210-216, 1936.

Oxygenated and deoxygenated red blood cells have different magnetic properties

diamagnetic

paramagnetic

Detecting “activation”

Capillaries!

Veins!Arteries!

Capillaries!

Veins!Arteries!

χ1 χ2 χ2 χ2

ΔS =

0

0.2

0.4

0.6

0.8

1

1.2

0 50 100 150 200

M0a e-t/T2*a - M0r e-t/T2*r

time

Sig

nal

ΔS S0

= M0a

M0r e-tΔR2* - 1

Measuring Brain Function with MRI

Task

t

t

task Hemodynamics Neuronal Activity

Red Blood Cells

Task Blood Flow deoxy-Hb MRI signal

BOLD = Blood Oxygenation Level Dependent

The Blood Oxygenation Level Dependent Response

Task

neuronal activity

BF

deoxy-Hb

MR signal

The Blood Oxygenation Level Dependent Response

Task

neuronal activity

BF

HbO2 deoxy-Hb

MR signal

CMRO2 BV - - +

0 20 40 60

Time (sec)

Sig

nal

0 5 10 15 Time (sec)

Sig

nal

Temporal dynamics of fMRI signal change

Delay

Activation amplitude

Arbitrary Scale

+ 2 sec

- 2 sec

0 sec 0 10 20 30 40 50

-2 -1.5 -1 -0.5 0 0.5 1 1.5 2

Num

ber o

f Vox

els

Delay (sec)

t

task fMRI signal

0 10 s

Functional Magnetic Resonance Imaging (fMRI)

Typical MRI t

Functional MRI

Look for changes in MRI signal over time

Task Blood Flow MRI signal deoxy-Hb

Brain activity during cued finger tapping

t

t

task

Map the changes in MRI signal over time

Functional MRI

t

t

Task-related Neuronal Activity

Physiologic noise (cardiac, respiration)

Subject motion

Scanner instabilities Image reconstruction errors

Spontaneous Neuronal Activity

Hemodynamics resting state

Problem: Subject Motion

motion

t

t

t

Signal changes occur at edges

t

Correcting for subject motion

•  Image registration

t = 0 t = 1

•  Prevent Motion

•  Regress out motion-related changes

Problem: motion during the volume

Problem: motion during the volume

slices are actually acquired like this… expected acquisition:

Problem: motion during the volume

Potential solution: Prospective motion correction

slice tracks with the motion

•  C.C. Lee, et al., Magn. Res. Med., 39, 1998. •  H.A. Ward, et al., Magn. Res. Med., 43, 2000. •  O. Speck, et al., Magma 19, 2006.

Physiological noise

0 40 80 120 160 200 240 280 320 time (s)

Cardiac

M.S. Dagli et al., NeuroImage 9, 1999

Respiration

time 00 TIME = 110 s

ΔΦ =90 o 400

200

B0

Field Map

Figure courtesy of J. Bodurka

Can filtering (<0.1Hz) reduce cardiac noise?

0 5 10 15 20 time (s)

Sign

al

Cardiac fluctuation (1.1 Hz) Sampled every TR (2s)

0 0.5 1 1.5 2 Frequency (Hz)

0

0.1

0.2

0.3

Pow

er

•  Not always: Aliasing

Correction of physiological noise

RETROICOR (G. Glover et al., Magn. Reson. Med. 44, 2000.)

Pulse Oximeter

0 1 2 3 4 5 6 7 8 9 10 time (s)

Respiration

MR Images

φc

φr

sin( φc )

cos( φc )

sin( 2φc )

cos( 2φc )

sin( φr )

cos( φr )

sin( 2φr )

cos( 2φr )

Additional Regressors:

Correction of physiological noise

time

Sig

nal

Reshuffle the data based on its cardiac or respiration phase

0 1 2 3 4 5 6

Sig

nal

phase

Correction: Cardiac + Respiration

X. Hu et al., Magn. Res. Med. 1995

At what stage should physio correction be done?

•  Preprocessing –  Motion correction –  Physiological noise correction –  Slice time correction –  Nuisance Regression –  Spatial Smoothing –  Convert to percent signal change –  Temporal filter

•  Define ROI (seed) •  Average EPI time course over ROI •  Regression T.B. Jones et al., Neuroimage 42, 2008

Physio. fluctations can occur at low frequencies

Variations in breathing during rest ΔBOLD signal

PETCO2

BOLD (GM)

BOLD (WM)

R.G. Wise et al., NeuroImage 21, 2004

ΔPETCO2 correlated w/ ΔBOLD

Resting fluctuations in respiration

RVT = Respiration Volume per Time

50 100 150 200 250 300 350

0

6

|Z|

group (n=11)

RVT-related changes

RVT

Heart Rate

Birn et al. (unpublished)

RVHRcor (Respiration Volume + Heart Rate)

C. Chang et al., Neuroimage 2009

Nuisance Regression

H.J. Jo et al., NeuroImage 52, 2010

The effect of global signal regression

The global signal is highly correlated w/ RVT

-1

-0.5

0

0.5

1

CC

: RV

T ~

glob

al s

igna

l

without global regression

with global regression

Connectivity maps

0.5

0.3

-0.1

0

(separate study, n = 18)

Global Signal Regression

K. Murphy, et al., Neuroimage, 2008

Can introduce anti-correlations

Global Signal Regression

Z.S. Saad, et al., Brain Connectivity, 2012

Can alter group differences …under certain conditions

Nuisance Regression

H.J. Jo et al., NeuroImage 52, 2010

PSTCor (Phase-shifted Soft Tissue Corr.)

J.S. Anderson et al., HBM 32, 2011

“FIX” (FMRIB’s ICA-based X-noisifier)

L. Griffanti, et al., Neuroimage 2014

ICA-AROMA

ICA-AROMA

R.H.R. Pruim et al., NeuroImage 112 (2015)

Tools to correct for physiological noise

•  Filtering - Works only if TR is short enough (< 400ms)

•  IMPACT (Chuang et al., 2001) – if TR short enough

•  Retrospective correction (k-space) (X. Hu et al., 1995)

•  RETROICOR (Glover et al., 2000)

•  CORSICA (V. Pelbarg, et al., 2007)

•  PESTICA (E.B. Beall, et al., 2007)

•  RVTcor (R.M. Birn, et al., 2006) •  RVHRcor (C. Chang, et al., 2009) •  ANATICOR (H-J. Jo, et al., ) •  APPLECOR, PEARCOR (M Marx, et al., 2013) •  PSTCor (J.S. Anderson, et al., 2011) •  CompCor (Y. Behzadi, et al., 2007)

•  FIX (L. Griffanti, et al., 2014)

•  ICA-AROMA (###, et al., 2015)

Should we perform physio corrections?

•  Reduces fluctuations related to heart beat and respiration –  Reduce false positives –  Reduce false negatives

•  Some physiological fluctuations are

associated with neuronal activity –  E.g. Heart rate variability

This is still an open question in the field

Signal / Physiologic Noise

Tem

pora

l Sig

nal t

o N

oise

Rat

io

TSNR vs SNR

Signal-to-Noise Ratio

J. Bodurka

TSNR vs SNR