FINSIG'05 25/8/2005 1Eini Niskanen, Dept. of Applied Physics, University of Kuopio Principal...
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Transcript of FINSIG'05 25/8/2005 1Eini Niskanen, Dept. of Applied Physics, University of Kuopio Principal...
FINSIG'05 25/8/2005
1Eini Niskanen, Dept. of Applied Physics, University of Kuopio
Principal Component Regression Principal Component Regression Approach for Functional Connectivity Approach for Functional Connectivity of Neuronal Activation Measured by of Neuronal Activation Measured by
Functional MRIFunctional MRI
1University of Kuopio
Dept. of Applied Physics
P.O.Box 1627, FIN-70211 Kuopio
FINLAND
†E-mail: [email protected]
Eini I. Niskanen1,†, Mika P. Tarvainen1, Mervi Könönen2,
Hilkka Soininen3, and Pasi A. Karjalainen1
2Kuopio University HospitalDept. of Clinical NeurophysiologyP.O.Box 1777, FIN-70211 Kuopio
FINLAND
3University of KuopioDept. of Neuroscience and Neurology
P.O.Box 1627, FIN-70211 KuopioFINLAND
FINSIG'05 25/8/2005
2Eini Niskanen, Dept. of Applied Physics, University of Kuopio
functional Magnetic Resonance Imaging (fMRI)functional Magnetic Resonance Imaging (fMRI)
FINSIG'05 25/8/2005
3Eini Niskanen, Dept. of Applied Physics, University of Kuopio
fMRI signalfMRI signal
• Each fMRI study contains a huge number of voxel time series (70 000 – 100 000 or more) depending on the imaging parameters
• Typical interscan interval is ~ 1-3 seconds ⇒ low sampling frequency
• A lot of noise from head motion, cardiac and respiratory cycles, and hardware-related signal drifts
FINSIG'05 25/8/2005
4Eini Niskanen, Dept. of Applied Physics, University of Kuopio
Blood Oxygenation Level Dependent (BOLD) Blood Oxygenation Level Dependent (BOLD) responseresponse
Paramagnetic deoxyhemoglobin causes local inhomogeneities in transversal magnetization
⇒ signal decrease in T2*-weighted images
Stimulus increases the need of oxygen in active cortical areas
Blood flow and blood volume increase
concentration of oxygenated hemoglobin increases
relative concentration of deoxygenated hemoglobin decreases
in T2*-weighted images this is seen as a signal increase = BOLD response
FINSIG'05 25/8/2005
5Eini Niskanen, Dept. of Applied Physics, University of Kuopio
BOLD responseBOLD response
• BOLD response is slow: time to peak ~3-5 s, total duration over 10 s
• The signal change due to functional activation is small ~ 0.5 – 5 %
• The shape of the BOLD response varies across subjects and also within subject depending on the type of the stimulus and active cortical area
• The summation of the consecutive responses for short interstimulus intervals is highly nonlinear
FINSIG'05 25/8/2005
6Eini Niskanen, Dept. of Applied Physics, University of Kuopio
0outf
Balloon modelBalloon model
Stimulusu
s
s
f
inf
1
εu Inflowf ′
0inf
signals′
00E
Efin deoxyHb
q′
volumev ′
v
qfout
0
BOLD signal
vk
v
qkqkVz 111 3210
Buxton et al. 1998, MRM 39:855-864
Obata et al. 2004, NeuroImage 21:144-153
Friston et al. 2000, NeuroImage 12:466-477
s
FINSIG'05 25/8/2005
7Eini Niskanen, Dept. of Applied Physics, University of Kuopio
Functional connectivityFunctional connectivity
“the temporal correlations among neurophysiological events between spatially remote cortical areas”
Primary visual cortex, Brodmann area 17
Primary motor cortex, Brodmann area 4
?
Area 1 Area 2
How to detect the functional connectivity
from the fMRI data
FINSIG'05 25/8/2005
8Eini Niskanen, Dept. of Applied Physics, University of Kuopio
Principal Component Regression (PCR)Principal Component Regression (PCR)
• The data is presented as a weighted sum of orthogonal basis functions
• The basis functions are selected to be the eigenvectors of either covariance or correlation matrix of the data
• The eigenvectors are obtained from eigenvalue decomposition
• The first eigenvector is the best mean square fit to the ensemble of the data, thus, often similar to the mean.
• The significance of each eigenvector is described by the corresponding eigenvalue
FINSIG'05 25/8/2005
9Eini Niskanen, Dept. of Applied Physics, University of Kuopio
SimulationsSimulations
• A young healthy volunteer was scanned in the Department of Clinical Radiology in the Kuopio University Hospital with a Siemens Magnetom Vision 1.5 T MRI scanner
• ~700 T2*-weighted gradient-echo echo-planar (EP) images
were acquired with interscan interval of 2.5 seconds
• Each EP image comprised of 16 slices, slice thickness 5 mm, in-plane resolution 4×4 mm
• A voxel from primary visual cortex (area 1) and primary motor cortex (area2) were selected for analysis and 70 artificial BOLD-responses were added to both voxel time series
• Two data sets were created: one set where the response in area 2 was independent on the neuronal delay in area 1, and the other where the response in area 2 was dependent on the neuronal delay in area 1
FINSIG'05 25/8/2005
10Eini Niskanen, Dept. of Applied Physics, University of Kuopio
Artificial activationsArtificial activations
• The artificial BOLD responses were generated using the Balloon model
• Response amplitude was scaled 5 % above the fMRI time series baseline
FINSIG'05 25/8/2005
11Eini Niskanen, Dept. of Applied Physics, University of Kuopio
Artificial activationsArtificial activations
• The artificial BOLD responses were generated using the Balloon model
• Response amplitude was scaled 5 % above the fMRI time series baseline
• Sampling interval was 2.5 seconds = used interscan interval
FINSIG'05 25/8/2005
12Eini Niskanen, Dept. of Applied Physics, University of Kuopio
Artificial activationsArtificial activations
• The artificial BOLD responses were generated using the Balloon model
• Response amplitude was scaled 5 % above the fMRI time series baseline
• Sampling interval was 2.5 seconds = used interscan interval
• 70 artificial BOLD responses with variable delay were added to both time series
FINSIG'05 25/8/2005
13Eini Niskanen, Dept. of Applied Physics, University of Kuopio
Artificial activationsArtificial activations
• A delay on response onset time effects on the sampled activation time series
FINSIG'05 25/8/2005
14Eini Niskanen, Dept. of Applied Physics, University of Kuopio
Artificial activationsArtificial activations
• A delay on response onset time effects on the sampled activation time series
• Small delays are seen as change on amplitude in sampled response
• Larger delays may change the shape of the sampled response
FINSIG'05 25/8/2005
15Eini Niskanen, Dept. of Applied Physics, University of Kuopio
• The neuronal delays were assumed to be Χ2 distributed in both areas
• Two data sets were created: in the dependent case the delay in area 1 was a part of the total delay in area 2, and in the independent case the delay in area 2 did not depend on the delay in area 1
• A constant delay of 300 ms between the responses in area 1 and area 2 was assumed in both data sets
Simulated data setsSimulated data sets
FINSIG'05 25/8/2005
16Eini Niskanen, Dept. of Applied Physics, University of Kuopio
ResultsResults
1. The voxel time series were divided into adequate BOLD responses and an augmented data matrix Z was formed
2. Data correlation matrix was estimated
and its eigenvectors and corresponding eigenvalues were solved
RZV = V λ
FINSIG'05 25/8/2005
17Eini Niskanen, Dept. of Applied Physics, University of Kuopio
ResultsResults
Independent data set Dependent data set
λi1 = 0.5968
λi2 = 0.1220
λi3 = 0.0850
λd1 = 0.6055
λd2 = 0.1390
λd3 = 0.0711
FINSIG'05 25/8/2005
18Eini Niskanen, Dept. of Applied Physics, University of Kuopio
Discussion and conclusionsDiscussion and conclusions
• A PCR based method for studying functional connectivity in fMRI data was presented
• Using the method the dependency between two cortical areas can be determined from the second and the third eigenvectors
• In case of independent responses, the second and third eigenvectors are required to cover the time variations of the BOLD responses
• In case of dependent responses, this time variation can be mainly covered by one eigenvector
• The second and third eigenvalues in the independent case are somewhat closer to each other than in the dependent case
(Δλi23 = 0.0370 vs. Δλd23 = 0.0679) ⇒ the third eigenvector is not so significant in the dependent case as in the independent case
• In the future the method will be tested with real fMRI data and the trial-to-trial information of the BOLD responses is further estimated from the principal components