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SUPPLEMENTARY MATERIALS
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The Movement Time Analyser task investigated with functional Near InfraRed Spectroscopy:
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an ecologic approach for measuring hemodynamic response in the motor system
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Roberta Vasta1*, Antonio Cerasa1§*, Vera Gramigna1, Antonio Augimeri1, Giuseppe Olivadese1,
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Giovanni Pellegrino3, Iolanda Martino1, Alexis Machado3, Zhengchen Cai3; Manuela Caracciolo1,
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Christophe Grova3,4,5, Aldo Quattrone1,2.
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Probabilistic Model of Photon Migration through the Head and Sensitivity Analysis
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In performing an fNIRS analysis, the projection of the probes geometry on the cortical surface
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should be evaluated to determine if it is successfully targeting the desired brain regions. Moreover it is
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necessary to model the photon migration through the head using a probabilistic approach. Indeed, this
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allows evaluating whether the area of interest is sufficiently reached by photons and which of the
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channels are more sensitive to the target region. Based on a realistic model of light propagation in
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biological tissues (Monte Carlos simulations) [1s], we computed brain sensitivity profile for each
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possible
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[http://mcx.sourceforge.net/cgi-bin/index.cgi], Monte Carlo simulation software for time-resolved
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source/detector
pair.
We
used
Monte
Carlo
eXtreme,
or
MCX
photon transport, to define a probabilistic path of photons through the head.
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The investigation of photons spatial distribution in the head tissues, the so-called banana shape,
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is very important in brain function measurement, since it allows measuring the effective optical path
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length of the detected signal or the effect of optical fiber configuration on the target regions or its
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sensitivity [2s]. A specific quantity of emitted photons can travel through the head within the tissues
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following a diffusive process, reaches the subcortical regions to a depth of 2-3 cm, and then is
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backscattered to the scalp and eventually to the detectors [3s]. Since in human tissue photon scattering
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is higher than photon absorption, and assuming that any light intensity variation occurs on a time-scale
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much greater than the mean transit time of light, photon propagation can be modeled using a time-
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independent diffusion equation, solved through a Monte Carlo approach [1s]. This method simulates
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photon transport and migration in tissues, taking into account the specific anatomy of each patient.
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Indeed it requires a realistic multilayered head model (scalp, skull, CSF, gray matter (GM) and white
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matter (WM)), built from the anatomical magnetic resonance imaging (MRI) of the subject. Details
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about the Monte Carlo code can be found in Boas et al [1s].
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Absorption and scattering coefficient values at 695 nm and 830 nm, associated with each tissue
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type constituting the segmented anatomical head model, were available from literature [4s] and showed
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in Table 1. Tissue anisotropy coefficient equal to 0.9 and refractive indices of air and tissue, set to 1.0
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and 1.37 respectively, were used in Monte Carlo simulation. To decrease the computational burden, we
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used the MC method, implemented in the Monte Carlo eXtreme software by Fang and Boas [5s].
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Tissues
690 nm
830 nm
Scalp
0.0159/10
0.0191/8.25
Skull
0.0101/12.5
0.0136/10.75
CF (Cerebrospinal Fluid)
0.0004/0.125
0.0026/0.125
GM (Gray Matter)
0.0178/15.625
0.0186/13.875
WM (White Matter)
0.0178/15.625
0.0186/13.875
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Table S1 Monte Carlo simulations parameters: absorption/scattering coefficients (mm-1).
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The sensitivity profiles for each possible pair and for both wavelengths were evaluated. A slice
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of sensitivity profile at 830 nm for two specific source/detector measurements ( (A) Channel 7 on the
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primary motor cortex and (B) Channel 16 on the supplementary motor area) was depicted in Figure S1.
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The superimposition of sensitivity matrix on one subject-specific anatomical MRI, indicating probe
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location for the corresponding channels was showed (Figure S1 C-D). Moreover, Monte Carlo
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simulation on MNI152 standard-space T1-weighted template (1mm) was performed in order to
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evaluate sensitivity profile on a head atlas for channels covering (E) the primary motor cortex and (F)
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the supplementary motor area (Figure S1). The visual comparison between sensitivity analysis
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performed on the Atlas and that performed on a single subject showed similar good performance.
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The results confirmed that our probe spatial configuration was suitable to the target region
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and the experimental protocol. In particular, primary motor area and supplementary motor cortex are
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highly sensitive to light propagation, allowing the subcortical regions at a depth of around 2 cm to be
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achieved by a significant quantity of photons.
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Fig. S1 Sensitivity matrix coefficients visualization of two source/detector pairs, corresponding to
Channel 7 (A) on the primary motor cortex and Channel 16 (B) on the supplementary motor area,
determined by the propagation of light emanated from a source [P1] and recorded by a detector [P2].
(C) and (D) represent the corresponding probe position on the anatomical MRI, overlaid on sensitivity
profile. (E) and (F) represent sensitivity profiles performed on the MNI152 standard-space T1weighted template (1mm) for channels covering the primary motor cortex and the supplementary
motor area, respectively.
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Further studies need to be performed in order to assess the effect of cerebral cortex folding
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geometry and on source-detector separation (LSD) on light propagation. Recently, simulation studies
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based on head models containing a cerebrospinal fluid (CSF) layer have demonstrated that light
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propagation is highly affected by the presence of CSF. Because the cerebral surface is folded as gyri and
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sulci filling with CSF, it is probable that the cerebral cortex folding geometry is also important for light
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propagation in the head. Possibly, the gyri and sulci might change the shape of spatial sensitivity
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profiles.
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In Li et al. [6s], spatial sensitivity profile turned out to seem like a fat tropical fish with strong
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distortion along the folding cerebral surface. For this reason, spatial sensitivity distribution on the brain
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region sampled by fNIRS at varied LSD was analyzed. These results indicate that the cerebral cortex
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folding geometry actually has substantial effects on light propagation, which should be necessarily
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considered for applications of functional near-infrared spectroscopy. Other two investigations have
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been concerned with the effect of cerebral cortex folding geometry on light propagation. Okada et al.
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[7s] used a layered slab, with slots to imitate the sulci, and found little effect of the sulci on the spatial
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sensitivity profile for 3- or 4-cm LSD. In the other study, using a two-dimensional (2-D) head model
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based on a single magnetic resonance imaging (MRI) scan, Fukui et al. [8s] showed that the spatial
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sensitivity profile formed like a banana, but distorted around the structure of cerebral surface, with
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LSD of 2–5 cm.
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MTA task-related reproducibility
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For evaluating the reproducibility of our data we performed two different MTA tasks in the
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same subject in two different sessions. Comparing the grand average of fNIRS patterns similar and
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consistent behaviors were detected (Figure S2). Both figures showed the concentration of oxy-Hb (red),
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deoxy-Hb (blue) and total-Hb (green) for channel 4 covering the primary motor cortex during the two
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right-hand MTA task sessions.
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Fig. S2: Grand average of changes in oxy-Hb (red), deoxy-Hb (blue) and total-Hb (green)
concentration during (right-hand) MTA task, performed by the same subject in two different sessions.
For channel 4, corresponding to primary motor area, the x-axis denotes task duration (0s ÷ 60s) and the
y-axis represents activation range ((-6÷6)*10-5 [mol/L]).
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MTA task-related hemodynamic response
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For display purpose, a typical MTA task-related hemodynamic response (Channel 4) for three
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different subjects was reported (Figure S3). We generally found a rapid increase of oxy-Hb
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concentration after starting (around 15 s), which decreases after 30 s (15s ÷ 45s) to the baseline value
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until the end of task.
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Fig. S3 Grand average of changes in oxy-Hb concentration during right-hand MTA task for three
different subjects, in the channel corresponding to the primary motor cortex (channel 4). The x-axis
denotes task duration (0s ÷ 60s) and the y-axis represents activation range ([mol/L]).
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Whole-brain fMRI analysis results:
In order to investigate the involvement of subcortical regions engaged in the primary motor
network, which are not identifiable by fNRIS technology, we performed a whole-brain fMRI analysis
during MTA. As it can be seen in Figure S4, whole-brain group analysis confirmed the involvement of
the contralateral motor and premotor regions together with cerebello-striatal activation for both the
execution sides.
Fig. S4 Results of whole-brain fMRI t-test of A) right and B) left MTA task (p<0.05, FWE correction
for multiple comparisons), showed the involvement of contralateral motor and premotor regions
together. The color bar represents T-statistics
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Additional References
[1s] Boas D, Culver J, Stott J, Dunn A. Three dimensional Monte Carlo code for photon migration
through complex heterogeneous media including the adult human head. Opt Express. 2002;10:159–
170.
[2s] Mansouri C, L’Huillier JP, Kashou NH, Humeau A (2010) Depth sensitivity analysis of functional
near-infrared spectroscopy measurement using three-dimensional Monte Carlo modelling-based
magnetic resonance imaging, Lasers in Medical Science, Volume 25, Number 3, Page 431.
[3s] McCormick PW, Stewart M, Lewis G, Dujovny M, Ausman JI (1992) Intracerebral penetration of
infrared light. Technical note. J Neurosurg 76(2):315-8.
[4s] Strangman G, Franceschini MA, Boas DA (2003) Factors affecting the accuracy of near-infrared
spectroscopy concentration calculations for focal changes in oxygenation parameters. NeuroImage
Volume 18, Issue 4, , Pages 865-879.
[5s] Fang Q and Boas DA (2009) Monte Carlo Simulation of Photon Migration in 3D Turbid Media
Accelerated by Graphics Processing Units. Opt Express vol. 17, issue 22, pp. 20178-20190
[6s] Li T, Gong H, and Luo Q (2011) Visualization of light propagation in visible Chinese human head
for functional near-infrared spectroscopy. J Biomed Opt 16(4):045001
[7s] Okada E, Firbank M, Schweiger M, Arridge SR, Cope M, and Delpy DT (1997) Theoretical and
experimental investigation of nearinfrared light propagation in a model of the adult head. Appl Opt 36:
21-31
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[8s] Fukui Y, Ajichi Y, and Okada E (2003) Monte Carlo prediction of nearinfrared light propagation in
realistic adult and neonatal head models. Appl optics 42: 2881-2887
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