pepe' dan（檀一平太）

Spatial considerations for achieving intermodal cross-referencing of fNIRS data

Ippeita ‘Pepe’ Dan（檀一平太）

Functional Brain Science Lab.Jichi Medical University,

Tochigi, Japan

Today’s slides are available at

http://www.jichi.ac.jp/brainlab

(Go to English site)

fMRIWhat is the best toolto study human brain?

Anatomy+ function

PET

Quantification

MEG

Temporal& spatial rez.

EEG/ERP

Temporal rez.& flexibility

TMS

Noninvasiveintervention

fNIRS

High-flexibility

No single toolNeed for integrative understanding

fMRIDo we have the common language?

Anatomy+ function

PET

Quantification

MEG

Temporal& spatial rez.

EEG/ERP

Temporal rez.& flexibility

TMS

High-flexibility

Tower of BabelPieter Bruegel, 1563

fNIRS

Noninvasiveintervention

An important issueis spatial data compatibility

Common spatial platform is necessary

This is the prerequisite for cross-modal data reference

fNIRS data should not exist in vacuum but be related to other imaging modality

This is either common coordinate system or macroanatomy

Are you sure that the data is appropriately registered?

TypicalfNIRS data

(visual processing)

Primary motor cortexPrimary somatosensory cortex

Parietal association cortex(spatial information processing

advanced somatosensory processing)

Temporal association cortex (hearing, advanced visual processing)

Secondary motor cortex

Prefrontal cortex

planning of movements,

(working memory,

inhibition of inappropriate behaviors)

Occipital association cortex

Primary visual cortex

Function Structure

What’s Human Brain Mapping

Incomplete tool for HBM

fNIRSprobes are placed on HEAD but not BRAIN surface

？

Function Structure

What’s Human Brain Mapping

Ideal solution: why don’t you use MRI

We would like to do without MRI

But How?

fNIRS measurement Structural image acquired by MRI

fNIRS data registered to MRI of the subject

Expensive, time consuming

Individual data: OK; Group data: needs some technique

Practical solution: registration to MNI space

in a probabilistic manner without acquiring MRI

＋ ＋ ＋

＋ ＋ ＋

Cannot see faces through masks

Normalize to a common coordinate system

Structural estimation through masks is possible

International 10-20 systemused in EEG

Stereotaxic brain coordinate system

Landmark measurement on head surface

Okamoto et al. NeuroImage 21, 99-111 (2004)

MNI (or Talairach) systemused in fMRI & PET

Link

International 10-20 system

Periauricular point

Nasion

Inion

10%

20%

20%

10%

20%

20%

20% 20%10%

Jasper, H. H. 1958. Electroenceph. Clin. Neurophysiol. 10: 367-380.

Primary reference points

Relative head surface division to set more landmarks

Normalized brain

MNI（Montreal Neurological Institute） standard brain coordinate system

X Y

Z

Subject’s Brain MNItemplate

(X, Y, Z )=(-55,33,18 )

Anterior

Commissure

Posterior

Commissure

Y

Z

X

Y

Z

Y

Z

Y

Z

Align

Warp

Affine

Before normalization

Template(MNI152)

After normalization

After normalizationCentral sulcus & Sylvian fissure

Standard coordinate system can realize the common spatial platform for probabilistic expression

Itnl 10-20 system

Head surface

Manual measurement for establishing transcranialcorrespondence

MNI coordinates

Cortical surface

Fp2Right MFG：65%Right SFG：35%

10-20 standard positions on MNI standard cortical surface

Virtual 10-20 measurement on MRI

Jurcak et al. NeuroImage (2005)

Reference database can be expanded if MRIs are available

Jurkak et al.NeuroImage 34, 1600-1611 (2007)

Extending cranio-cerebral correspondence to 10/10 and 10/5 systems

Now also incorporated in eLORETA

10/5 nomenclature

10/5 landmarkson MNI coordinate system

Practical way to use these data

• Place fNIRS probes, channels, or ROIs in reference to 10-20, 10-10, or 10-5 positions

• Describe fNIRS probes, channels, or ROIs in reference to 10-20, 10-10, or 10-5 positions

• Visit www.jichi.ac.jp/brainlab/tools.htmlfor 10-5 probe positions

• Cite Okamoto et al., 2003 NeuroImage for 10/20

• Cite Jurkak et al. 2007 NeuroImage for 10/10 and 10/5

More sophisticated way for using the landmark information

• Cranial landmarks for transformation to MNI space

• Estimation of fNIRS channel positions– by creating reference head and brain

database– performing “probabilistic” or “virtual”

registrations

Borrow other’s brain instead of yours

3D-magnetic digitizer for MRI-free probabilistic registration

Polhimus Fast-track

3D spatial measurement

10-20 standard positions

Arbitrary origin

fNIRS channel

Subject i without structural MRI

Estimation of fNIRS channel positions using reference database

Measuring 10-20 and fNIRS channel positions using 3D magnetic digitizer

Digitized dada inReal world coordinate system

(Subject i )

10-20 standard positions for subject ifNIRS channel position for subject i

10-20 standard positions for reference head j

Affine transformation

MNI coordinate system(Reference head j)

．．．

Ref. data 1

Sujbect iChannel estimation

and errorfor Subject i(Brain, MNI)

Reference database (MNI, m=17)

Channel (Head, MNI) Channel (Brain, MNI)

Channel (Head, RW)

Virtual registration of subject i’s data on reference brain and head database

Ref. data 2

Ref. data m

Ref. data 1

Ref. data 2

Ref. data m

Ref. data 1

Ref. data 2

Ref. data m

Projection

Within-subject error

．．．

Subject 1

Subject 2

Subject n

Channel

Channel

Channel

Virtual registration of subject i’s data on reference brain and head database

Subject 1

Subject 2

Subject n

Head, Real World Channel estimation

& errorMNI, Brain

Most likelychannel estimation

for the groupMNI, Brain

Between-subject error

＋＝

Between-subject errors

CMij i j ijP e 2, , ~ (0, )i j ije N

Pooled within-subject errorsTotal errors for channel estimation of the group

PCMij ：most likely channel location； μ：expected value； αi ：error fo rsubject i； βj：error for ref. nrain j ； eij: ：residual

Summerizing spatial registration estimation errors for group analysis

fNIRS group analysis data can now be registered onto MNI space without MRI

Center of a circle: Most likely coordinate values

Radius of a circle: Standard deviationError (SD) <1cm

Singh AK et al.NeuroImage 27,842-851 (2005)

Probabilistic registration using reference database without MRI & with 3D-digitizer

Stable landmarks

Cz:Iz dependent

Stable landmarks

Subject’s real world space MNI space

Probabilistic registration Ｉz:unstable

Cz

Anchor-based probabilistic registration using any given scalp anchor point

Tsuzuki et al. Neurosci Res (2012)

Stable landmarks

Any given scalp anchor point

Stable landmarks

Corresponding point to the anchor

Anchor-basedprobabilistic registration

Much faster& easier

C3 Cz

T3

Can’t we do without a digitizer?Virtual registrationAssuming that probe setting and deformation are reproducible,we can simulate placement and deformation of probe holders

Tsuzuki, D et al. NeuroImage 34, 1600-1611 (2007)

Kinds of fNIRS holders

Fixed-size

Elastic (Hitachi Med. Co.) Flexible（Shimadzu）

Simulation for holder placement

Verification on a spherical phantom

Verification on a real head

C3 Cz

T3

Problem: holder size is fixed, but sizes and shapes of heads are different

Virtual registrationusing reference database

without MRI & without 3D-digitizer

Tsuzuki, D et al. NeuroImage 34, 1600-1611 (2007)

Example of virtual registration

Error of spatial registration is below 1cm

Gyrus-level estimation is possible

Atlas-guided DOT(diffused optical tomography) using probabilistic registration

Custo et al. NeuroImage (2010), Cooper et al. NeuroImage (2012)

MRI-based registration for group data

Continuous imaging data:You can depend on SPM procedureNIRS-SPM can deal with this issue (tentatively, tough)

Tsuzuki et al. Neurosci Res 72, 163-71 (2012)

MRI-based registration for group data

Discrete channel-wise data:SPM procedure is not straight-forward

Brain can be normalized to MNI152based on structural information

?fNIRS channels/probes cannot be directly normalized to MNI152due to lack of structural information

MRI-based registration for group data

Normalization to MNI152based on structural information

Adopt the deformation field to fNIRSchannel/probe locations

Extract deformation field(=Jacobian matrix for warping)

Merge with normalized subject’s brain

Subject’s own MRI

Subject’s own fNIRS channel/ probe locations

Prb X Y Z1 47 48 262 29 55 34| | | |9 53 31 39

MRI-based registration for group data

Prb X Y Z1 47 48 262 29 55 34| | | |9 53 31 39

Prb X Y Z1 48 49 252 29 56 32| | | |9 54 32 41

Prb X Y Z1 46 47 272 27 54 32| | | |9 53 32 38

Prb X Y Z1 49 50 262 30 55 31| | | |9 56 34 37

Prb X Y Z SD1 47.3 48.4 26.0 8.82 28.5 54.5 34.4 7.9| | | |9 53.3 31.2 39.8 6.8

Summary data In the standard brain

Averaged point tends to sink

Slight adjustment

Project back to the cortical surface (“shell”)

Sbjct1 Sbjct2 Sbjct3 SbjctN

・・・

Frequent misunderstanding in fMRI study

AAL (Automatic Anatomical Labeling)

fMRI can measure structure & function for INDIVIDUAL data

For GROUP analysis, you have to look at a representative atlas to estimate cortical mactoanatomy

Tzourio-Mazoyer et al., NeuroImage 2002

Link to Anatomical labeling tools in MNI space

AAL (Automatic Anatomical Labeling)

Brodmann Area Labeling via MRIcro

AAL (Automatic Anatomical Labeling)

Brodmann Area Labeling via MRIcro

Link to Anatomical labeling tools in MNI space

Other registration tools are also available

nfri_mni_plot

Virtual registration library

User-unfriendly development policyUser-friendly software needs sophisticated graphical interface which-is highly integrated-requires lots of energy to develop-is difficult to maintain-is hard to be transferred to other software packages

We chose developer-friendliness-open-source cords-fully public domain for academic use-Developed as Matlab functionsNow incorporated into-POTATo from Hitachi, Japan (by Dr. Katsura et al.)-NIRS-SPM from KAIST, Korea (by Drs. Ye & Tak)-HOMER from MGH, US (by Drs. Huppert & Boas)

Please feel free to steal

them !

Registration tools in POTATo

Platform for Optical Topography Analysis Tools (POTATo)by Dr. Katsura et al. at Hitachi Ltd. Japan

-Suitable for discrete channel-wise analysis-Highly flexible capacity for filtering in data-preprocessing-Capability for sophisticated signal processing e.g. ICA, PRCA-Suited for exploratory use (needs lots of thinking)-Flexible design to incorporate other tools-Batch process for 2nd level group analysis

Registration tools in NIRS-SPM

NIRS-SPMby Drs. Ye & Takat KAIST, Korea

-Continuous 2D image data generated from any given discrete channel data-Elaborated image reconstruction & FWEC by Sun’s tube formula at 1st level

-Mostly automatic with high affinity to GLM regression

Registration tools in HomER

Hemodynamic Evoked ResponseNIRS data analysis GUIby Drs. Huppert & Boas at MGH, US

-Highly flexible channel design with excellent GUI-Compatibility to common spatial platforms such as MNI, FreeSurfer-Affinity to 3D DOT analyses -Flexibility and capability for expansion-Suited for exploratory use (needs lots of thinking)

Our tools are available starting from HomER 2

What would I do as a user?

Discrete channel-wise data

Exploratory study

POTAToFWE correction

Group level analysis for selected channels

2D continuous data

NIRS-SPMROI extraction

Group level analysis for 2D ROI

3D continuous data

HomER ROI extraction

Group level analysis for 3D ROI

Flexible group analyses with SPSS, SAS etc

Where is activated by Strooptask in ADHD adults?

Is SMG activated by Strooptask in ADHD adults?

In any case

HomER

Strong functional hypothesis

Individual level analysis

Spatial registration profile of fNIRS data in MNI coordinate system

Okamoto M et al. NeuroImage 31, 796-806 (2006)

e.g. our taste encoding study

考察

Oro-lingual foci＊

Verbal encoding (Visual)

Verbal encoding (Auditory)

Taste encoding vs verbal encoding

Comparison of NIRS/OT data with former fMRI and PET studies

考察

Oro-lingual foci＊

Nonverbal encoding (Visual)

Nonverbal encoding (Auditory)

Nonverbal encoding (somatosensory)

Taste encoding vs non-verbal encoding

Comparison of NIRS/OT data with former fMRI and PET studies

Conclusion in spatial consideration of fNIRS

Cross-modal reference can be achieved using the same spatial platform: MNI space or Talairach space

Additional MRI measurement is omitted for fNIRS

Future agendaNeeds adjustment for Infant and children data (under development)Needs more direct probabilistic inference to macro-anatomyFine adjustment for POTATo, NIRS-SPM and HOMEREspecially expansion to 3D DOT-based analyses

More user-friendly manuals, demos at least…

Still, gyrus-level inference is possible

Related tools & today’s presentationare available

(or will be available)at

http://www.jichi.ac.jp/brainlab

dan@jichi.ac.jp

or e-mail me at