Voxelbased lesionsymptom mapping: An introduction and a tutorial - PowerPoint PPT Presentation
1 / 34
Title:
Voxelbased lesionsymptom mapping: An introduction and a tutorial
Description:
Ahmanson-Lovelace Brain Mapping Center. University of California, Los Angeles ... behavioral neurology but blinded to the clinical status. of the patient. ... – PowerPoint PPT presentation
Number of Views:433
Avg rating:3.0/5.0
Title: Voxelbased lesionsymptom mapping: An introduction and a tutorial
1
Voxel-based lesionsymptom mapping An
introduction and a tutorial
- Stephen M. Wilson
- Ahmanson-Lovelace Brain Mapping Center
- University of California, Los Angeles
- Center for Research in Language, UCSD
- October 22, 2004
2
Collaborators
- Elizabeth Bates, UCSD
- Ayse Pinar Saygin, UCSD
- Frederic Dick, UCSD
- Marty Sereno, UCSD
- Robert Knight, UC Berkeley
- Nina Dronkers, UC Davis
- Thanks also to David Wilkins and Carl Ludy. This
work was funded by the Department of Veterans
Affairs Medical Research, the National Institute
of Neurological Disorders and Stroke (PO1
NS17778, NINDS 21135, PO1 NS40813), and the
National Institute of Deafness and Communication
Disorders (NIH/NIDCD 2 R01 DC00216).
3
Lesion-symptom mapping
- Until a few decades ago, themain sources of
evidence onbrain/behavior relationshipswere
cases which came toautopsy. - The advent of noninvasive structural imaging (CT,
MRI, etc.) has made possible the acquisition of
much larger datasets. - This makes it important to establish quantitative
methods for making inferences about the
relationship between lesions and the symptoms
they produce.
4
Voxel-based lesion-symptom mapping (VLSM)
- VLSM (Bates et al., 2003)exploits continuous
behavioraland continuous lesioninformation. - The method does not requirepatients to be
grouped either bylesion site or by
arbitrarybehavioral cutoffs. - Instead, statistical analyses of the relationship
between tissue damage and behavior are carried
out on a voxel-by-voxel basis.
5
Previous approaches
- Groups defined by behavior
- Groups defined by lesion
- Voxel-based approaches (Adolphs et al., 1996,
2000)
6
Groups defined by behavior
- Patients are divided into groups according to
whether or not they exhibit a particular
behavioral deficit (e.g. apraxia of speech in
Dronkers, 1996 aphasic syndromes in Kertesz,
1979). - The lesions of the impaired patients are
overlaid to determine if there is a common locus
of infarction. - An overlay of the sparedpatients lesions can
also bemade to confirm that theidentified area
is spared.
7
Groups defined by behavior (2)
- The main limitation of this approach is that it
forces a yes/no decision to be made about whether
a patient is impaired - In situations where deficits are not binary, an
arbitrary cutoff must be stipulated and
information about varying degrees of performance
is lost.
8
Groups defined by lesion
- Patients are divided into groups based on broad
lesion locations (e.g. dorsolateral prefrontal
cortex in Chao Knight, 1998). - Behavioral measures of interest are then compared
to other groups or to controls. - This approach therefore dichotomizes the data not
based on behavior but based on lesion. Again,
potentially valuable information about patients
lesion locations cannot enter into the analysis.
9
VLSM methods
- VLSM is fully continuous in both the brain and
behavior domains. - In this study, we analyzed speech fluency and
language comprehension data for 101
left-hemisphere-damaged stroke patients. - Behavioral measures consisted of subscales from
the Western Aphasia Battery (Kertesz, 1979).
Fluency scores reflect a combination of
articulatory, word finding, and sentence
production skills, while the auditory
comprehension measure represents the average
score on yes/no questions, single word
recognition, and enactment of 1, 2 and 3-part
commands. - Patients lesions were reconstructed onto
templates bya board-certified neurologist (RTK)
with expertise inbehavioral neurology but
blinded to the clinical statusof the patient. - VLSM algorithms were programmed in MATLAB andare
freely available online at http//crl.ucsd.edu/vls
m.
10
Voxel-by-voxel statistics
- At each voxel, patients are divided into two
groups according to whether their lesions do or
do not include that voxel. - These groups are thencompared (e.g. with a
t-test)and the resultant statisticsare
displayed as color maps. - So this is a massive univariateapproach similar
to neuro-imaging analysis and subjectto similar
challenges
11
Results for fluency and comprehension
12
Anterior insula for fluency
- The anterior insula has also been implicated as
important for fluency in several neuroimaging
studies (Wise et al., 1999 Blank et al., 2002).
13
MTG for comprehension
- Classic Wernickes area is the posterior STG. But
recent neuroimaging studies (e.g. Scott et al.,
2000 Davis Johnsrude, 2003) agree with VLSM
that the STS and MTG are more important for
comprehension.
14
Comparing VLSM and fMRI
- This data is from the exact same experiment (2AFC
environmental sound to picture matching) on
patients (Saygin et al., 2003) and fMRI of
controls (Dick et al., 2003).
15
Basic methodological issues
- Differential power in different regions
- Which statistic to plot? (t, d, mean of lesioned
patients, p, ) - Multiple comparisons
- Choice of scale
- Slice selection
16
Distribution of lesions
- Most aphasic stroke patients have MCA lesions, a
few have PCA, ACA or other. - This means that power is greatest in perisylvian
regions.
17
Plotting effect size
- d difference in means divided by pooled
standard deviation. - For large samples, results are similar to t.
18
Multiple comparisons
- A pervasive problem in imaging analysis.
- Bonferroni correction is too conservative.
- False discovery rate is a useful procedure for
VLSM. - Proposed by Benjamani Hochberg (1995).
- Controls the expected proportion of false
positives at a stated alpha level. - Spatial autocorrelation is still a problem.
- Best not to attach too much importance to
significance.
19
Correlated lesions
- As is always the case in lesion studies, an area
may emerge as relevant because it plays a direct
causal role, or because of a diaschitic effect
involving highly correlated lesions some distance
away. - Could the insula be emerging just because it is
close to Brocas area? Could the MTG be
identified just because it is adjacent to
Wernickes area? - VLSM allows questions such as these to be
addressed.
20
Approaches
- If one had an enormous number of patients (say
1000), then it might be possible to treat dozens
of ROIs and interactions between them as factors
in a big ANOVA. - In the real world, we can ask about the
potentially confounding effects of single voxels
(or regions). - At each voxel, an ANCOVA is performed where the
lesion status of a voxel of interest is covaried
out.
21
ANCOVAs
- We selected four voxels-of-interest based on
anatomical criteria in the centers of - Brocas area
- the anterior insula
- Wernickes area (posterior STG)
- MTG
- Four maps were then constructed by performing an
ANCOVA at each voxel covarying out the lesion
status (lesioned vs. intact) of the reference
voxel-of-interest.
22
ANCOVA results
23
Comparing maps
- It can be useful toquantitativelycompare VLSM
maps. - One way of doing thisis to run a regressionwith
voxels as subjects. - For fluency vs. comprehension, a correlation
value of r 0.59 was obtained, because
perisylvian regions are more important than
peripheral areas in both domains.
24
Sample size
- How many patients does it take to make reliable
inferences? - Few neuropsychological studies have more than
about 20 patients, and the mode number of
patients is of course 1! - With a metric for comparing maps (correlation),
we can use repeated sampling of our 101 patients
to discover how similar two maps of the same
measure tend to be, as a function of sample size. - 10 pairs of maps were made each for sample sizes
ranging from 10 to 50.
25
Sample size
- Increasing reliability is roughly linear.
- Hard to interpret r2, need to look at maps to
get a sense of similarity.
26
Example of a pair of images
- N 25, r2 0.3
27
More applications
- Grammaticality judgment
- Auditory word recognition
- Environmental sounds
- Pantomime comprehension
- Biological motion perception
- WCST
- Complex grammatical deficits (CYCLE)
28
Grammaticality judgment
29
A role for anterior areas in comprehension
30
ANCOVA factoring out MTG
31
Environmental sounds
32
Summary
- VLSM is an improvement on previous lesion-symptom
mapping techniques because it uses all available
information, eliminating reliance on cutoff
scores, clinical diagnoses, or specified regions
of interest. - VLSM makes use of graphic formats and analytical
methods closely related to those used in
functional neuroimaging analysis, facilitating
quantitative comparisons between lesion and
imaging results.
33
References
- VLSM website http//crl.ucsd.edu/saygin/vlsmpape
rs.html - To download software http//crl.ucsd.edu/vlsm
- Bates, E., Wilson, S. M., Saygin, A. P., Dick,
F., Sereno, M. I., Knight, R. T. Dronkers, N.
F. (2003). Voxel-based lesion-symptom mapping.
Nature Neuroscience, 6, 448-450. - Rorden, C. Karnath, H.-O. (2004). Using human
brain lesions to infer function a relic from a
past era in the fMRI age? Nature Reviews
Neuroscience, 5, 813-819.
34
Tutorial
- Using MATLAB
- Lesion file formats
- Specifying the patient set (vlsm_openpatientset)
- The behavioral data file (vlsm_openbehavdata)
- Creating statistical maps (vlsm_overlay)
- Displaying statistical maps (vlsm_display)
- Exporting figures (vlsm_export)
Recommended
CrystalGraphics Presentations
