Dipole Modelling in Cognitive Neuroscience - Low Temperature ...
Dipole Modelling in Cognitive Neuroscience - Low Temperature ...
Dipole Modelling in Cognitive Neuroscience - Low Temperature ...
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<strong>Dipole</strong> <strong>Modell<strong>in</strong>g</strong><br />
<strong>in</strong> <strong>Cognitive</strong> <strong>Neuroscience</strong><br />
Riitta Salmel<strong>in</strong><br />
Bra<strong>in</strong> Research Unit<br />
<strong>Low</strong> <strong>Temperature</strong> Laboratory<br />
Aalto University<br />
Espoo, F<strong>in</strong>land<br />
riitta@neuro.hut.fi
<strong>Dipole</strong> <strong>Modell<strong>in</strong>g</strong><br />
<strong>in</strong> <strong>Cognitive</strong> <strong>Neuroscience</strong><br />
What type of questions?<br />
RS/Apr10
Example: Dual-Route Model of Read<strong>in</strong>g<br />
FAMILIAR<br />
WORDS<br />
Neural markers...?<br />
UNFAMILIAR<br />
WORDS<br />
adapted from<br />
Coltheart et al. Psychol Rev 1993
Example: Dual-Route Model of Read<strong>in</strong>g<br />
TALO<br />
LAUTANEN<br />
ROKI<br />
SOIJINTO<br />
short word (F<strong>in</strong>nish)<br />
long word (F<strong>in</strong>nish)<br />
short nonword<br />
long nonword<br />
Lexical route dom<strong>in</strong>ates,<br />
length has little effect<br />
Grapheme-to-phoneme,<br />
length has strong effect<br />
100 different stimuli of each type, <strong>in</strong> a randomized order<br />
Silent read<strong>in</strong>g, prompt to read aloud (“?”) <strong>in</strong> 4% of trials<br />
Wydell et al. JoCN 2003
Sensor Signals Are Informative<br />
... Especially Planar Gradiometers<br />
Short words<br />
Long words<br />
Short nonwords<br />
Long nonwords<br />
fT/cm<br />
100<br />
0<br />
-200...800 ms<br />
0 800 ms<br />
N=1<br />
Current<br />
flow<br />
Wydell et al. JoCN 2003
<strong>Dipole</strong> <strong>Modell<strong>in</strong>g</strong><br />
<strong>in</strong> <strong>Cognitive</strong> <strong>Neuroscience</strong><br />
What type of questions?<br />
Why source analysis?<br />
RS/Apr10
Work<strong>in</strong>g at the Source Level Is Useful<br />
because...<br />
Decomposition of the sensor-level signals <strong>in</strong>to their<br />
approximate cortical source areas can markedly<br />
clarify the stimulus/task effects<br />
It is useful to have a general idea of the bra<strong>in</strong> areas<br />
<strong>in</strong>volved <strong>in</strong> the task performance<br />
--- BUT ---<br />
Do not th<strong>in</strong>k primarily <strong>in</strong> terms of location!<br />
RS/Apr10
Source Analysis Models the Source...<br />
Equivalent Current <strong>Dipole</strong><br />
ECD<br />
Activation<br />
strength<br />
(nAm)<br />
20<br />
0<br />
0 1000<br />
Time (ms)<br />
Physiologically & physically sound<br />
M<strong>in</strong>imum number of assumptions<br />
Benefits from expertise<br />
Conta<strong>in</strong>s an element of subjectivity<br />
RS/Apr10
Source Analysis Models the Source<br />
Same data & tool -> same map<br />
Subjective ROIs, thresholds<br />
Benefits from expertise<br />
or Limits the Solution<br />
Statistical test<strong>in</strong>g on ROI time<br />
courses, not maps (MEG≠fMRI)<br />
M<strong>in</strong>imum Norm Estimate<br />
MNE<br />
RS/JV/Apr10
Source Analysis Models the Source<br />
or Limits the Solution<br />
© Mika Seppä<br />
Appearance is determ<strong>in</strong>ed by<br />
the choice of analysis method,<br />
not by the structure of the active<br />
bra<strong>in</strong> areas<br />
MEG (or EEG) gives an estimate<br />
of the centre of an active area but<br />
(<strong>in</strong> typical record<strong>in</strong>gs) no direct<br />
<strong>in</strong>formation of its spatial extent<br />
RS/Apr10
Check for Artefacts at the Sensor Level<br />
Silent picture nam<strong>in</strong>g<br />
(N=1)<br />
Set 1<br />
Set 2<br />
Set 3<br />
100 fT/cm<br />
-200...1000 ms<br />
Elekta Neuromag<br />
Current<br />
flow<br />
RS/Apr10
Check for Artefacts at the Sensor Level<br />
Overt picture nam<strong>in</strong>g<br />
(N=1)<br />
Set 1<br />
Set 2<br />
Set 3<br />
100 fT/cm<br />
-200...1000 ms<br />
Elekta Neuromag<br />
Current<br />
flow<br />
RS/Apr10
Field Patterns Are Even More Tell<strong>in</strong>g<br />
Neural<br />
activation<br />
... with<br />
bl<strong>in</strong>k<br />
... with<br />
mouth movement<br />
RS/Apr10
<strong>Dipole</strong> <strong>Modell<strong>in</strong>g</strong><br />
<strong>in</strong> <strong>Cognitive</strong> <strong>Neuroscience</strong><br />
What type of questions?<br />
Why source analysis?<br />
Why dipole modell<strong>in</strong>g? How?<br />
RS/Apr10
In Source Analysis, Probably Correct<br />
Is Better than Reproducibly Wrong<br />
Measured<br />
bl<strong>in</strong>k<br />
ECD MNE<br />
artefact!<br />
...cortex?<br />
RS/JV/Apr10
ECD Solutions Are Mostly Obvious<br />
Auditory<br />
evoked<br />
responses<br />
(N=1)<br />
N100m<br />
Elekta Neuromag<br />
Current<br />
flow<br />
RS/Apr10
ECD Solutions Are Mostly Obvious<br />
60 ms 85 ms 150 ms<br />
0 100 200<br />
Time (ms)<br />
0 100 200 0 100 200<br />
Salmel<strong>in</strong> <strong>in</strong> “MEG. An Introduction to Methods”, OUP 2010
ECD Solutions Are Mostly Obvious<br />
N100m<br />
P200m<br />
Left<br />
Right<br />
Left<br />
Right<br />
80%<br />
g<br />
10 nAm<br />
0 100 200<br />
Time (ms)<br />
Salmel<strong>in</strong> <strong>in</strong> “MEG. An Introduction to Methods”, OUP 2010
ECD Solutions Are Mostly Obvious<br />
Right median nerve<br />
stimulation<br />
(N=1)<br />
100 fT/cm<br />
-50...250 ms<br />
Elekta Neuromag<br />
Current<br />
flow<br />
RS/Apr10
ECD Solutions Are Mostly Obvious<br />
20 ms 30 ms 50 ms<br />
75 ms 95 ms 105 ms<br />
Salmel<strong>in</strong> <strong>in</strong> “MEG. An Introduction to Methods”, OUP 2010
There Is No Need to Decide the<br />
Number of ECDs <strong>in</strong> Advance<br />
20 ms 30 ms 50 ms<br />
75 ms 95 ms 105 ms<br />
Salmel<strong>in</strong> <strong>in</strong> “MEG. An Introduction to Methods”, OUP 2010
There Is No Need to Decide the<br />
Number of ECDs <strong>in</strong> Advance<br />
SI<br />
PPC<br />
SII c<br />
SII i<br />
0 100 200<br />
Time (ms)<br />
20 nAm<br />
RS/Apr10
ECD Orientation Is a Useful Measure<br />
Spoken words, sentences etc.<br />
Allows to separate<br />
different functional<br />
responses<br />
0 400 800<br />
0 400 800<br />
Time (ms)<br />
Time (ms)<br />
10 nAm<br />
0 400 800<br />
0 400 800<br />
Biermann-Ruben et al. Neuroimage 2005<br />
Uusvuori et al. Cereb Cortex 2008<br />
Bonte et al. Cereb Cortex 2006
Dipolar Field Patterns Are Also<br />
Fully Identifiable <strong>in</strong> <strong>Cognitive</strong> Data<br />
Short words<br />
Long words<br />
Short nonwords<br />
Long nonwords<br />
fT/cm<br />
100<br />
0<br />
0 800 ms<br />
Current<br />
flow<br />
Wydell et al. JoCN 2003
fT/cm<br />
100<br />
0<br />
100<br />
0<br />
Dipolar Field Patterns Are Also<br />
Fully Identifiable <strong>in</strong> <strong>Cognitive</strong> Data<br />
0 800 ms<br />
0 800 ms<br />
Short<br />
words<br />
Long<br />
words<br />
Short<br />
nonwords<br />
Use the same ECD for all conditions<br />
Long<br />
nonwords<br />
Salmel<strong>in</strong> <strong>in</strong> “MEG. An Introduction to Methods”, OUP 2010
ECDs Allow Quantitative Comparison<br />
between Conditions<br />
< 200 ms<br />
200-400 ms<br />
> 400 ms<br />
Group-level cluster<strong>in</strong>g of the sources by location and tim<strong>in</strong>g<br />
... and by function:<br />
Long nonwords ><br />
short real words<br />
< 200 ms<br />
> 200 ms<br />
Wydell et al. JoCN 2003
ECDs Allow Quantitative Comparison<br />
40<br />
20<br />
0 200<br />
Time (ms)<br />
between Conditions<br />
Activation<br />
strength<br />
(nAm)<br />
40<br />
20<br />
0 200 400 600<br />
Time (ms)<br />
Short words<br />
Long words<br />
Short nonwords<br />
Long nonwords<br />
Wydell et al. JoCN 2003
ECDs Allow Quantitative Comparison<br />
nAm<br />
40<br />
20<br />
between Conditions<br />
Strength Duration<br />
ms<br />
200<br />
100<br />
Short words<br />
Long words<br />
Short nonwords<br />
Long nonwords<br />
Letter-str<strong>in</strong>g length < 200 ms <strong>in</strong> occipital cx (Tarkia<strong>in</strong>en et al. Bra<strong>in</strong> 1999)<br />
Length x lexicality > 250 ms <strong>in</strong> the left superior temporal cx<br />
... phonological analysis if we accept the dual-route model<br />
Wydell et al. JoCN 2003
<strong>Dipole</strong> <strong>Modell<strong>in</strong>g</strong><br />
<strong>in</strong> <strong>Cognitive</strong> <strong>Neuroscience</strong><br />
What type of questions?<br />
Why source analysis?<br />
Why dipole modell<strong>in</strong>g? How?<br />
Are the results reliable?<br />
RS/Apr10
Source-Level F<strong>in</strong>d<strong>in</strong>gs Must Make Sense<br />
Short w<br />
Long w<br />
Short nw<br />
Long nw<br />
Current flow<br />
<strong>in</strong> Light of Sensor-Level Effects<br />
0 800 ms<br />
9<br />
5<br />
1 4<br />
6 2<br />
8<br />
7<br />
3<br />
1<br />
2<br />
3<br />
4<br />
5<br />
6<br />
7<br />
8<br />
9<br />
0 400 ms<br />
RS/Apr10
Good-Quality Data Yields Reliable Neural<br />
Time Courses with Multiple Methods<br />
Word read<strong>in</strong>g (N=15)<br />
ECD<br />
MNE<br />
~100 ms ~150 ms ~300-400 ms<br />
Vartia<strong>in</strong>en et al., submitted
<strong>Dipole</strong> <strong>Modell<strong>in</strong>g</strong><br />
<strong>in</strong> <strong>Cognitive</strong> <strong>Neuroscience</strong><br />
What type of questions?<br />
Why source analysis?<br />
Why dipole modell<strong>in</strong>g? How?<br />
Are the results reliable?<br />
Evoked data but also oscillatory activity?<br />
RS/Apr10
ECDs Can Be Used<br />
to Localize Cortical Rhythms<br />
Time (s)<br />
Frequency<br />
spectra<br />
300 fT/cm<br />
0 20 40 Hz<br />
0 2 4 6 8<br />
Rest<br />
Motion<br />
Eyes<br />
closed<br />
Eyes<br />
open<br />
Salmel<strong>in</strong> & Hari EEG J 1994<br />
Hari & Salmel<strong>in</strong> TiNS 1997
ECDs Can Be Used<br />
to Localize Cortical Rhythms<br />
10 Hz 20 Hz<br />
Hand SI<br />
Central sulcus<br />
Salmel<strong>in</strong> & Hari Neurosci 1994<br />
Salmel<strong>in</strong> et al. Neuroimage 1995<br />
Liljeström et al. Neuroimage 2005
Read<strong>in</strong>g aloud<br />
20-Hz effects<br />
10 fT/cm<br />
0 2 4 s<br />
... and Characterize Task-Related<br />
Modulation of Oscillatory Activity<br />
-1...5 s<br />
N=1<br />
word<br />
0 300<br />
speech<br />
?<br />
800 ms<br />
0 2 4 s<br />
Salmel<strong>in</strong> et al. Bra<strong>in</strong> 2000
... and Characterize Task-Related<br />
Modulation of Oscillatory Activity<br />
w ?<br />
Source 20 Hz N=10<br />
Hand<br />
Mouth<br />
Hand<br />
Mouth<br />
2 nAm<br />
0 2 4 s<br />
Salmel<strong>in</strong> et al. Bra<strong>in</strong> 2000, HBM 2002; Saar<strong>in</strong>en et al. Cereb Cortex 2005
For Successful Source Analysis...<br />
Learn to read MEG sensor signals, know your data<br />
– dipole modell<strong>in</strong>g does a very good job there<br />
Learn to do dipole modell<strong>in</strong>g – it is worth the effort<br />
Identify clear field patterns, get well-behaved models<br />
Verify source effects aga<strong>in</strong>st the sensor-level effects<br />
Use multiple experimental conditions: function, modell<strong>in</strong>g<br />
Put effort <strong>in</strong> experimental design and data quality<br />
RS/Apr10
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