Referential framework for transcranial anatomical correspondence for fNIRS based on manually traced sulci and gyri of an infant brain

Neuroscience Research 80 (2014) 55–68

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Referential framework for transcranial anatomical correspondence for fNIRS based on manually traced sulci and gyri of an infant brain Mie Matsui a , Fumitaka Homae b , Daisuke Tsuzuki c , Hama Watanabe d , Masatoshi Katagiri a , Satoshi Uda a , Mitsuhiro Nakashima a , Ippeita Dan c,∗ , Gentaro Taga d a

Department of Psychology, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, Japan Department of Language Sciences, Tokyo Metropolitan University, 1-1 Minami Osawa, Hachioji, Tokyo 192-0397, Japan c Applied Cognitive Neuroscience Laboratory, Research and Development Initiatives, Chuo University, 1-13-27 Kasuga, Bunkyo-ward, Tokyo 112-8551, Japan d Graduate School of Education, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan b

a r t i c l e

i n f o

Article history: Received 18 September 2013 Received in revised form 27 December 2013 Accepted 6 January 2014 Available online 18 January 2014 Keywords: Optical topography Sulcus Manual tracing Parcellation Transcranial neuroimaging Baby

a b s t r a c t Functional near infrared spectroscopy (fNIRS), which is compact, portable, and tolerant of body movement, is suitable for monitoring infant brain functions. Nevertheless, fNIRS also poses a technical problem in that it cannot provide structural information. Supplementation with structural magnetic resonance images (MRI) is not always feasible for infants who undergo fNIRS measurement. Probabilistic registration methods using an MRI database instead of subjects’ own MRIs are optimized for adult studies and offer only limited resources for infant studies. To overcome this, we used high-quality infant MRI data for a 12-month-old infant and manually delineated segmented gyri from among the highly visible macroanatomies on the lateral cortical surface. These macroanatomical regions are primarily linked to the spherical coordinate system based on external cranial landmarks, and further to traditional 10-20based head-surface positioning systems. While macroanatomical structures were generally comparable between adult and infant atlases, differences were found in the parietal lobe, which was positioned posteriorly at the vertex in the infant brain. The present study provides a referential framework for macroanatomical analyses in infant fNIRS studies. With this resource, multichannel fNIRS functional data could be analyzed in reference to macroanatomical structures through virtual and probabilistic registrations without acquiring subject-specific MRIs. © 2014 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

1. Introduction Examination of the structures and functions of infant brains is a fundamental part of understanding human development. Infant brains undergo drastic functional and structural changes (Dehaene-Lambertz et al., 2006; Guillery, 2005; Homae, 2014; Huttenlocher and de Courten, 1987; Huttenlocher and Dabholkar, 1997; Minagawa-Kawai et al., 2011; Smyser et al., 2011). In early research, structural examination using postmortem brains was the predominant approach to studying infant brains (Chi et al., 1977; Kinney et al., 1994; Kostovic and Judas, 2010; Moore and Guan, 2001) until the advent of electroencephalography (EEG), which enabled the functional examination of living

∗ Corresponding author. Tel.: +81 3 3817 7272. E-mail addresses: [email protected], [email protected] (I. Dan).

infant brains (Hughes et al., 1948). Although EEG became deeply ingrained in pediatric clinical situations to detect epilepsy, auditory abnormalities, dysmaturity and so on (Nordli et al., 1997; van Straaten, 1999; Watanabe et al., 1999), it was not suited for source analyses which aimed to associate functions with structures in infant brains. Then, there came a major methodological turning point: the advent of functional magnetic resonance imaging (fMRI), which enabled concurrent analyses of structures and functions in living infant brains (Born et al., 1996; Dehaene-Lambertz et al., 2002; Yamada et al., 1997). However, its implementation involves constraints in experimental settings. In practice, the most promising neuroimaging method for studying infant brain function is functional near infrared spectroscopy (fNIRS), which can monitor brain functions of both typically and atypically developing infants (Homae et al., 2011; Lloyd-Fox et al., 2010; Taga et al., 2011; Watanabe et al., 2013). fNIRS is a developing optical imaging technique that uses near-infrared light to

http://dx.doi.org/10.1016/j.neures.2014.01.003 0168-0102/© 2014 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

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non-invasively monitor cortical activity utilizing the tight correspondence between regional neuronal activity and hemodynamic response (Obrig and Villringer, 2003). Although it is difficult to obtain direct evidence for the tight coupling between regional neuronal activity and the hemodynamic response even in human adults, an increasing number of studies on region-specific hemodynamic changes in response to visual or auditory stimuli in infants suggests that the neuro-vascular coupling is established by at least 3 months of age (Homae et al., 2011; Taga et al., 2011; Watanabe et al., 2013). fNIRS enjoys several advantages over other noninvasive functional neuroimaging techniques such as fMRI and positron emission tomography (PET): it is compact, portable, and relatively more tolerant of body movement (Ferrari and Quaresima, 2012). These merits enable fNIRS to be applied in a wide range of experimental applications in neuropsychological and diagnostic situations (Ehlis et al., 2014; Irani et al., 2007), especially those involving infants (Lloyd-Fox et al., 2010). From the early stages of its development, fNIRS has been adopted for the cortical monitoring of infants during visual, auditory, and olfactory processing (Bartocci et al., 2000; Meek et al., 1998; Pena et al., 2003; Sakatani et al., 1999; Taga et al., 2003). Recent application of fNIRS to functional connectivity analyses of infants further extended its potential in studying the development of the network properties of the cortex in infants (Homae et al., 2010; Imai et al., 2014; White et al., 2012). Despite the suitability of fNIRS in infant studies, it also poses a technical problem: fNIRS itself is unable to acquire structural information (Tsuzuki and Dan, 2014). fNIRS measures the cortical hemodynamic state of the head surface, but cannot identify the source of activation on the cortical structure. For spatially assessing fNIRS data, the scalp location where an fNIRS measurement is performed, must be registered to its underlying cortical surface where the source signal is located. Several practical solutions have been proposed for fNIRS studies in adults. First, fNIRS data may be directly registered to the structural MR images of the subjects (Tsuzuki and Dan, 2014). Second, when subjects’ MRIs are not available, fNIRS data can be registered to the canonical brain template in the standard stereotaxic coordinate system through a process called probabilistic registration, which utilizes an MRI database instead of the subjects’ own MRIs (Singh et al., 2005; Tsuzuki et al., 2007). Third, fNIRS channel or probe positions may be linked to a scalp-based positioning system, such as the 10-20, 1010 or 10-5 systems (Jurcak et al., 2007; Okamoto et al., 2004), and spherical coordinate systems (Lagerlund et al., 1993; Towle et al., 1993; Tsuzuki et al., 2012). In practice, these three methods are interlinked with one another and can be further linked to anatomical atlases such as AAL, Brodmann’s atlas, and LPBA40 (Lancaster et al., 2000; Shattuck et al., 2008; Tzourio-Mazoyer et al., 2002). Nevertheless, the development of structural analyses tools for fNIRS in infants has faced the technical difficulty that high quality MRIs for all infants to be tested are difficult to obtain. Macro-anatomical segmentation of neonatal and early infant brains was difficult to perform because only low-contrast images can be obtained compared to adult head scans. Developmental MRI analyses on the brains of young children have been extensively performed over the first decade of this century and beyond (reviewed in Giedd and Rapoport, 2010), but the prevalence of low-contrast images prevents image processing methods such as tissue segmentation and skull stripping. Thus, currently, stable macro-anatomical segmentation is only possible from the age of two (Gousias et al., 2008). However, the neuroimaging community is gradually conquering this difficulty, and large-scale MRI datasets are beginning to be released (Almli et al., 2007; Altaye et al., 2008). The tissue contrast is improved by using 3T scanners. Technical quality has improved gradually and infant brain templates based on highquality MRI scans have been made (Sanchez et al., 2012). In addition, Gilmore et al. (2012) examined developmental changes in

the gray matter volumes of various cortical and subcortical regions based on longitudinal studies from birth to two years in a group of 72 children. Unfortunately, although these studies provided a fundamental understanding of the structural development of the brains of young children, direct use of their results for fNIRS data is not feasible. For the structural analyses of fNIRS data, gyrus-level macroanatomical structural information along the lateral cortical surface is of great importance. As far as we know, an atlas of the infant brain based on precise anatomical observation with reproducible descriptions of anatomical structures is not available in a form that can be linked to other common referential systems. Concurrently, image processing methods have been fine-tuned for manual tracing morphometry (Matsuzawa et al., 2001; Suzuki et al., 2005; Takahashi et al., 2006), such that now sufficient quality data for manual tracing on the lateral cortical surface are often available for infants under one year old. Indeed, on the slice level, macro-anatomical manual tracing for longitudinal volumetry of developmental brains has been implemented in some studies (Tanaka et al., 2012; Uematsu et al., 2012). Since acquisition of these data is optimized for manual tracing procedures, macroanatomical features of the lateral cortical surface are generally more visible than they are in typical MRIs at corresponding ages. Even though high-quality infant MRI data are becoming available, standard coordinate system resources, which are further linked to anatomical atlases, are still limited. It would be ideal to establish and verify brain templates representing various developmental stages, and to express them in a manner compatible with the standard stereotaxic coordinate system, most exemplified by the Montreal Neurological Institute (MNI) coordinate system (Brett et al., 2002). This would create a seamless link from infant brains to adult brains with access to various resources accumulated in the standard coordinate systems. However, despite the fact that many templates for infant brain segmentation have been produced, without satisfactory access to macro-anatomical atlases they have different degrees of compatibility with MNI space. To overcome this problem in infant fNIRS neuroimaging studies, an alternative method would be to standardize spatial data to relative scalp-coordinate systems with direct macro-anatomical links. One plausible solution may be to utilize a spherical coordinate system, as was once introduced for standardizing electroencephalography data in the early 1990s (Lagerlund et al., 1993; Towle et al., 1993). Also, it would be possible to express scalp and cortical positions via the international 10-20 system or its derivatives (Jurcak et al., 2007). If these resources were linked to a manual tracing of macro-anatomical structures at the gyrus level, it would result in a useful system enabling macro-anatomical inference in infant fNIRS studies. Hence, the current study strove to create a link between the scalp-based reference systems, including 10-20-based and spherical coordinates systems, and a macroanatomical atlas based on manual tracing. Upon careful examination of the MRI dataset for longitudinal developmental manual tracing, we found that one data entry (a 12-month-old normally developed infant) was of sufficient quality to enable manual gyrus-level segmentation (Tanaka et al., 2012; Uematsu et al., 2012). Utilizing this high-quality infant MRI data, here we present a feasibility study to link macroanatomical cortical structures and scalp-based positioning systems optimized for analyzing infant fNIRS studies. Although this is based on a single subject’s macroanatomical structure, as is the case for automatic anatomical labeling (AAL), which has been widely used in fMRI studies, manual-tracing is necessary to create an infant-brain macroanatomical atlas that could evolve from a single-subject sample to a multiple-subject sample equipped with the standard spatial platform. We first delineate manually segmented gyri along the lateral cortical surface. These macroanatomical regions are primarily linked to traditional 10-20-based head-surface positioning

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Fig. 1. Infant and adult brains. For comparison, the lateral cortical surface of the infant brain (dark magenta) and head (light magenta) were overlaid on the averaged adult brain cortical surface (dark cyan) and head surface (light cyan) (Okamoto et al., 2004) aligned to the AC–PC line: top view (A) and side lateral view (B).

systems, and further to the spherical coordinate system based on external cranial landmarks. We also compare macroanatomical structures on the lateral surfaces of infant and adult brains using 10-20-based systems, and transformation based on the spherical coordinate system, which enables template-free normalization. Combining these, we propose an initial shape for a referential framework for macroanatomical structural analyses of infant fNIRS neuroimaging data.

2. Methods 2.1. Imaging acquisition The MRI data for the 12-month-old normally developing infant were obtained from the MRI data set previously reported (Tanaka et al., 2012; Uematsu et al., 2012). Briefly, original participants included 114 healthy and normally developing Japanese (60 males and 54 females) from 1 month to 25 years old (mean age in months ± S.D. = 106.00 ± 83.15). Their entire study was approved by the Research and Ethics Committee at the University of Toyama. They acquired MRI data as follows. T1-weighted axial images with 1.0 mm thickness were obtained on a 1.5T Magnetom Vision scanner (Siemens, Erlangen, Germany) while the participant was asleep, using the fast low angle shot gradient refocused 3dimensional sequence with the following parameters: echo time (TE) = 6 ms, repetition time (TR) = 35 ms, flip angle = 35◦ , nex = 1, field of view = 256 mm, and matrix size = 256 × 256. The entire scan was completed in 15 min. From the resulting MRI pool, we chose the youngest participant with sufficient MR image quality, as described above. 2.2. Image preprocessing For the present study, acquired MRI data were aligned to the anterior commissure (AC) and posterior commissure (PC), with the AC providing the origin, the AC–PC line forming the y-axis with the AC posterior, and a midline forming the z-axis (Fig. 1). The x-axis ran left to right. Skull stripping was performed using the automated brain extraction tool (BET) (Smith, 2002) provided as a part of the FMRIB Software Library (FSL, http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/) (Smith et al., 2004). Fractional intensity threshold was set at 0.56. Next, we smoothed the brain volume and extracted the cortical surface using the spm-surf sub-function included in SPM8 (https://github.com/satra/SLT/blob/master/spm2edits/spm surf.m)

(Ashburner and Friston, 1999; Ashburner et al., 2000), using a 3 × 3 × 3 smoothing kernel with the default parameters (Fig. 2). 2.3. Procedure for manual tracing of sulci and fissures As in the previous study by Tzourio-Mazoyer et al. (2002), we first tracked sulci and fissures using the three-dimensional surface renderings (Duvernoy, 1999). Second, we traced the sulci in the transverse, coronal, and sagittal MRI slices, all of which were then drawn on the reconstructed cortical surfaces. First, two primary raters (FH, ID) independently assessed the lateral surface structures and slices of the MRI data, and upon discussion, determined target sulci and fissures to be traced according to the criteria described below. Second, three secondary raters (MK, SU, MN) independently traced the lateral parts of the target sulci using the MRIcron software package (Rorden et al., 2007), and saved the traces in separate volumes of data. The resulting three sets of traced 29 sulci and fissures were visually inspected by the primary raters, who found no major mismatches. The resultant sulci and fissures were thickened by one voxel in all three coordinate directions and overlaid across the data obtained by the secondary raters, and were projected to the surface shell of the lateral cortical surface using a balloon-inflation protocol as previously described (Okamoto and Dan, 2005). The voxels that were detected by at least two secondary raters were extracted. Based on the resulting lines overlaid along the lateral shell of the cortex, auxiliary lines were drawn to define gyri according to the procedures described below (Fig. 3). To delineate gyri and cortical regions, first we extracted the parts in the lateral cortical shell surrounded by appropriate sulci, fissures and auxiliary lines. Delineation of sulci is shown in Appendix A. Within these regions, voxel gaps resulting from branches were filled. At this stage, boundaries of the cortical regions and gyri had different thicknesses, and they were converted to an even thickness by adopting a mode filter. 2.4. Delineation of gyri 2.4.1. Precentral gyri (PrCG) In the right hemisphere, the upper edge of the central sulcus (CS) was slightly separated from the interhemispheric fissure (IHF). Thus, they were connected by drawing an auxiliary line from the upper edge of the CS to the nearest point on the IHF (Fig. 3E-a). Similarly, another auxiliary line was drawn to connect the upper edge of the precentral sulcus (PrCS) to the nearest point on the

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Fig. 2. Lateral cortical surface of the infant brain. The T1-weighted images of the 12-month-old infant underwent skull-stripping and were rendered using MRIcroGL. Front view (A), back view (B), left side view (C) and right side view (D) and top view (E) are shown with the subject’s own MRI aligned to the AC–PC line (y-axis) with the AC as origin using real-world coordinates.

IHF (Fig. 3E-b). A small gap in the left PrCS was filled with a short auxiliary line (Fig. 3E-b*). In both hemispheres, the lower edge of the CS was separated from the Sylvian fissure (SF). Thus, they were connected by drawing an auxiliary line from the lower edge of the central sulcus to the nearest point on the SF (Fig. 3C, D-a*, a ). The region surrounded by the auxiliary PrCS, the IHF, the auxiliary CS, and the SF was defined as the PrCG. 2.4.2. Post-central gyri (PoCG) In the right hemisphere, the postcentral sulcus (PoCS) reached the IHF on the top, but was divided into two parts in the inferior part. An auxiliary line was drawn from the inferior edge of the posterior part of the PoCS to the crossing point between the anterior part of the PoCS and the SF (Fig. 3D-c). The PoCS was separated from the IHF on the top. Thus, they were connected by drawing an auxiliary line from the upper edge of the PoCS to the nearest point on the IHF (Fig. 3E-c*). The region surrounded by the auxiliary PoCS, SF, CS and IHF was delineated as the PoCG. Also, in the left hemisphere, the PoCS was separated from the IHF on the top.

Thus, they were connected by drawing an auxiliary line similarly (Fig. 3E-c ). Moreover, an auxiliary line was drawn from the inferior edge of the PoCS vertically along the z-axis to the SF (Fig. 3C-c ). The region surrounded by the auxiliary PoCS, SF, auxiliary CS and IHF was delineated as the PoCG. 2.4.3. Frontal pole (FP) Sulcus structure is usually ambiguous at the anterior part of the frontal lobe, and this area has often been designated as the FP (e.g., Rademacher et al., 1992). In the right hemisphere, the right superior frontal sulcus (SFS) extended anteriorly from the PrCS and terminated in the anterior part of the frontal lobe. Hence, the anterior part from the SFS termination point along the y-axis (AC–PC line) was delineated as the frontal pole (Fig. 3D-d). The left frontal lobe of the participant was complicated mainly by the presence of the middle frontal sulcus (MFS). Since sulcus structure becomes ambiguous beyond the anterior end of the MFS, the anterior part from the end of inferior branch of the middle frontal gyrus (MFG) along the y-axis was delineated as the FP (Fig. 3C-d*).

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2.4.4. Superior frontal gyrus (SFG) In both hemispheres, the regions surrounded by PrCS, SFS, IHF, and the frontal pole border were delineated as the SFG. 2.4.5. Middle frontal gyrus (MFG) On the right hemisphere, the inferior frontal sulcus (IFS) extended anteriorly from the PrCS and turned ventrally at around the FP border. From the anterior end of the horizontal ramus of the SF, an auxiliary line was drawn horizontally to the FP border (Fig. 3D-e). The region surrounded by the SFS, the FP border, the auxiliary horizontal ramus of the SF, the IFS, and the PrCS was delineated as the MFG. In the left hemisphere, the IFS was separated into two parts. The first auxiliary line was drawn to connect the two parts of the IFS (Fig. 3C-f). The second auxiliary line drawn

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from the anterior end of the IFS to the anterior end of the inferior branch of the MFS (Fig. 3C-f*). The region surrounded by the SFS, the FP border, the auxiliary IFS, and the PrCS was delineated as the MFG. 2.4.6. Inferior frontal gyrus (IFG) On the right hemisphere, the horizontal ramus of the SF was extended anteriorly along the y-axis using an auxiliary line (Fig. 3De). The region surrounded by the PrCS, the IFS, and the SF including its auxiliary horizontal ramus was delineated as the IFG. In the left hemisphere, the horizontal ramus of the SF extended along the yaxis anteriorly. This was used as the lower limit of the IFG, which was further surrounded by the FP border, the auxiliary IFS, and the PrCS.

Fig. 3. Manually delineated sulci and auxiliary lines. Front view (A), back view (B), left side view (C) and right side view (D) and top view (E) are shown with the subject’s own MRI (real-world coordinates). Auxiliary lines are shown in black with numbers (see corresponding part of the text for detailed explanation). Sulci are depicted with the following colors: SFS, orange; MFS, magenta; IFS, green; SF, yellow; PrCS, cyan; CS, red; PoCS, blue; STS, orange; ITS, green; AOS, cyan; IPS, magenta; JS, green; LOS, blue; POS, cyan; IHF, yellow; TFC, purple. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of the article.)

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The parts below the horizontal ramus (and its extension) were defined as orbital parts of the IFG but excluded from the analyses. 2.4.7. Temporal pole (TP) Sulcus structure is usually ambiguous at the anterior part of the temporal lobe, and this area has been often designated as the TP (e.g., Rademacher et al., 1992). In the right hemisphere, the anterior end of the right inferior temporal sulcus (ITS) terminated near the anterior-most part of the temporal lobe. Hence, the anterior part from the ITS termination point along the y-axis was delineated as the TP (Fig. 3D-g, g*). The superior temporal sulcus (STS) also terminated at around the TP border. On the coronal plane corresponding to the temporal pole border, the bottom-most point was determined. A sagittal plane was drawn through this point (Fig. 3Ah, h*). In the left hemisphere, the SF crossed this point. In the right hemisphere, the SF was extended along the border of the frontal and temporal lobes until it crossed the bottom-most point (Fig. 3Ai). The region surrounded by the coronal and sagittal TP borders and the SF including its extension was delineated as the TP. 2.4.8. Superior temporal gyrus (STG) In the right hemisphere, the posterior limit of the STS was rather ambiguous. Thus, we used two particular landmarks: on the posterior parts of the SF and the STS there were major ascending branches. The feet of these branches were connected to each other to determine the posterior limit of the STG (Fig. 3D-j). In the left hemisphere, since the thus drawn auxiliary line (Fig. 3C-j*) almost overlapped the ascending branch of the STS, it replaced the lower part of the auxiliary line. Consequently, in both hemispheres, the region surrounded by the SF, the SF-STS connection line, the STS including its ascending branch, and the coronal temporal pole border was delineated as the STG. 2.4.9. Middle temporal gyrus (MTG) In both hemispheres, the anterior occipital sulcus (AOS) was used as the posterior limit of the MTG. Since the dorsal most point of the AOS in the right hemisphere deviated from the STS, an auxiliary line was drawn to the nearest point on the STS (Fig. 3D-k). Since the posterior end of the inferior temporal sulcus (ITS) deviated from the AOS, an auxiliary line was drawn to the temporo-occipital notch (Fig. 3D-l). The region surrounded by the STS, the auxiliary AOS, the auxiliary ITS, and the temporal pole border was delineated as the MTG. 2.4.10. Inferior temporal gyrus (ITG) On both hemispheres, the anterior limit of the ITG was defined by the temporal pole border (Fig. 3C-g*, D-g), while the posterior limit was defined by the AOS. The region below the ITS was delineated as the ITG. The inferior edge of the ITG was determined by drawing an auxiliary line from the bottom-most point on the coronal TP plane to the temporo-occipital notch (Fig. 3C-m*, D-m). The more lateral part of the auxiliary line was delineated as the ITG. 2.4.11. Supramarginal gyrus (SMG) On the right hemisphere, the intraparietal sulcus (IPS) was separated into two parts. The ventral part of the IPS was connected anteriorly to the PoCS, but terminated posteriorly slightly above the first ascending branch of the STS. An auxiliary line was drawn to connect the posterior end of the ventral part of the IPS and the foot of the first ascending branch of the STS (Fig. 3D-n). The region surrounded by the auxiliary ventral part of the IPS extending to the first STS branch, the SF-STS connection line, the SF, and the auxiliary PoCS was delineated as the SMG. In the left hemisphere, the intermediate sulcus of Jensen (JS) was present extending ventrally from the crossing point of the IPS and PoCS, and terminated near the main trunk of the STS. From the ventral-most edge of the JS, an

auxiliary line was drawn to the nearest point at the main trunk of the STS (Fig. 3C-o). Also from the dorsal-most edge of the JS, a short auxiliary line was drawn to the nearest point at the IPS to stabilize delineation of the SMG (Fig. 3C-o*). The region surrounded by the STS including its ascending branch, the SF-STS connection line, the posterior part of the SF, the auxiliary PoCS, and the auxiliary JS, was delineated as the SMG. 2.4.12. Angular gyrus (AG) In the right hemisphere, the IPS was separated into two parts. The dorsal part was separated from the PoCS. An auxiliary line was drawn from the anterior edge of the dorsal part of the IPS to the point of the PoCS where the ventral part of the IPS was connected (Fig. 3E-p). The main trunk of the STS was separated into a “y” shape. From the foot of the y-shaped branches, an auxiliary line was drawn through the dorsal IPS to the crossing point between the parietooccipital sulcus (POS) and the IHF (lateral parieto-occipital border) (Fig. 3B-q). The region surrounded by the auxiliary ventral IPS, the auxiliary dorsal IPS, the lateral parieto-occipital border, and the STS was delineated as the AG. In the left hemisphere, the main trunk of the STS was separated into a small “y” shape. From the foot of the y-shaped branches, an auxiliary line was drawn through the dorsal IPS to the crossing point between the POS and the IHF (lateral parieto-occipital border) (Fig. 3B-q*). The region surrounded by the auxiliary JS, the main trunk of the STS, the lateral parieto-occipital border, and the IPS was delineated as the AG. 2.4.13. Superior parietal lobule (SPL) In both hemispheres, the region surrounded by the lateral parieto-occipital border, the IPS (auxiliary dorsal IPS on the right), the auxiliary PoCS, and the IHF was delineated as the SPL. 2.4.14. Superior and inferior part of the occipital lobe In both hemispheres, the lateral occipital sulcus (LOS) extended from the AOS horizontally toward the IHF. The edges of the LOS were connected by an auxiliary line (Fig. 3B-r). The occipital lobe above and below the auxiliary LOS was delineated as the superior and inferior parts of the occipital lobe. 2.5. 10-20-based systems Pre-auricular points (AL, AR) were defined at the anterior roots of the tragi on MRI slices together with Nz and Iz by the two primary raters (ID, FH). 10-20, 10-10 and 10-5 systems were defined on the head surface of the infant according to the same method as used in Jurcak et al. (2007). To project a given scalp position to the underlying cortical surface, we searched for the closest point on the cortical surface, adjusting for local curvature with the balloon-inflation method, as previously described (Okamoto and Dan, 2005). This procedure is robust against regional differences in the thickness of the scalp, skull, and subdural space. Each position of 10-20, 1010 and 10-5 systems was projected onto the infant atlas that we created. The infant-brain macroanatomical features revealed using this projection method were compared to the macroanatomical features of adult-brain 10-20, 10-10 and 10-5 positions (Jurcak et al., 2007) projected onto the lateral cortical surfaces of the adult atlas, LPBA40, which was created based on 40 subjects with macroanatomical segmentation at the gyrus level (Shattuck et al., 2008) using the same projection method (Okamoto and Dan, 2005). 2.6. Spherical coordinate system The spherical coordinate system was defined according to Tsuzuki et al. (2012). Briefly, pre-auricular points (AL, AR) were defined at the anterior roots of the tragi on MRI slices together

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Fig. 4. Manually delineated gyri and cortical regions. Top view (A), front view (B), back view (C), right side view (D) and left side view (E) are shown with the subject’s own MRI (real-world coordinates). Gyri and cortical regions are depicted with the following colors (with some overlapping color selection): FP, magenta; SFG, light gray; MFG, blue; IFG, red; orbital part of frontal lobe, olive; PrCG, yellow; TP, navy blue; STG, beige; MTG, brown; ITG, orange; PoCG, green; STL, purple; SMG, pink; AG, dark gray; superior part of occipital lobe, light green; inferior part of occipital lobe, cyan. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of the article.)

with Nz and Iz, as aforementioned. The mid-point of AL and AR served as the origin. The y-axis was defined so that it penetrated the origin perpendicular to the x-axis on the plane defined by Nz and the preauricular points with posterior being negative and anterior being positive. Also, the spherical coordinate system was originally adopted to the adult atlas, LPBA40 (Shattuck et al., 2008). Here, the resultant image was transformed to the infant atlas space by replacing the radii of the adult atlas to those of the infant atlas.

(AL, AR, Nz and Iz), which were determined on the infant MRI slices, were used as reference points to place the specific channels of the fNIRS probe. According to the aforementioned procedure for probe placement, all the channels were virtually arranged on the head surface using a virtual registration method (Tsuzuki et al., 2007).

3. Results 3.1. Delineated cortical gyri and regions

2.7. Placement of virtual fNIRS probe Virtual 94 fNIRS channels were estimated onto the infant brain with the procedure previously described in Watanabe et al., 2013. The 94 channels were generated from 2 sets of 3 × 10 fNIRS probes. Three pieces of optodes, whose interoptode distances were fixed at 2 cm, were arranged vertically, and 10 movable triple-optodes were arranged over each hemisphere at even horizontal distances (approximately 2 cm). The landmark points over the head surface

Utilizing manually traced sulci and fissures along the lateral cortical surface of the infant brain with use of auxiliary lines, 15 gyri and regions were delineated in each hemisphere. These results were depicted on the surface shell that continuously covered the lateral surface of the infant brain. The atlas was aligned to the infant brain’s own real-world coordinate system, in which the AC formed the origin, the PC provided the y-axis, and the midline defined the z-axis as in the MNI coordinate system (Fig. 4).

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Fig. 5. Distribution of 10-20 based landmarks over the infant head surface. 10-20 (red), 10-10 (green) and 10-5 positions (blue) are overlaid on the surface of the infant head (A–E). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of the article.)

3.2. Comparison between infant and adult macroanatomical atlases via 10-20 based systems Using the landmarks, AL, AR, Nz and Iz, defined on MRI slices, 10-5, 10-10 and 10-20 positions were determined on the infant head surface as shown in Fig. 5. These positions were further projected onto the lateral cortical surface of the infant atlas as shown in Fig. 6A–E (see Supplementary data for a text-based list). To compare macroanatomical features of the infant and adult brains, these positions were projected onto the lateral cortical surfaces of the LPBA40 as shown in Fig. 6F–J. In addition, Fig. 7 exhibits macroanatomical brain regions inversely projected onto the head surface of the infant with the positions of 10-20-based systems so as to facilitate an intuitive grasp of these anatomical correlates. The overall relation between 10-5 positions and macroanatomical regions was generally comparable between lateral cortical surfaces of the adult and infant brains. 10-20 positions were located on virtually the same gyri. However, a major discrepancy was found around the fronto-parietal border. The parietal lobe was

positioned posteriorly, especially around the vertex. While the anterior part of the PrCS was located around Cz in both infant and adult brains, the CS and PoCS were positioned posteriorly in the infant brain: the CS and PoCS were located around the CPz and CPPz in the infant brain, while they were located around the CCPz and CPz in the adult brain. Since the POS was located near the POz in both the infant and adult brains, the parietal lobe narrowed around the posterior part of the vertex. This tendency was observed in the inferior parts of the parietal lobe, but less markedly. C3 and C4 were located near the CS in both the infant and adult brains. Also, around the peri-Sylvian region, the coronal reference curve across T8, C4, Cz, C3 and T7 was located slightly posterior to the CS in the infant brain, but overlapped with the PoCS in the adult brain. 3.3. Comparison between infant and adult macroanatomical atlases via the spherical coordinate system The macroanatomical comparison between infant and adult atlases via the 10-20-based systems presented above was further

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Fig. 6. Distribution of 10-20 based landmarks over the infant and adult atlases. 10-20 (red), 10-10 (green) and 10-5 positions (blue) are overlaid on the surface of the infant (A–E) and adult (F–J) lateral macroanatomical atlases. Gyri and cortical regions are depicted with the same colors as in Fig. 4 except for the following cases: the FP and TP are not defined in the adult atlas; medial regions appear on the occipito-parietal surface in the adult atlas; the occipital lobe is divided into three regions in the adult atlas instead of two. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of the article.)

verified using the spherical coordinate system. The origin of the spherical coordinate system was set at the midpoint between AL and AR defining the x-axis, perpendicular to which, the y-axis was defined to yield azimuth and elevation values of zero. Transformation of the adult brain to the infant brain was performed by replacing the radii of the adult cortical surface points with those of the infant brain surface (Fig. 8). Overall, macroanatomical structures were compatible between the infant and adult atlases while a posterior shift, especially at the vertex as described above, was also observed. 3.4. Implementation of actual probe placement To demonstrate the actual implementation of the current results, the channel locations of 94 channel measurements used in an infant fNIRS study (Watanabe et al., 2013) were overlaid onto the manually traced atlas using the virtual registration method (Tsuzuki et al., 2007; Fig. 9). This probe setting was expected to cover the macroanatomical structures including the frontal pole, MFG, IFG, PrCG, PoCG, SFG, MFG, SMG, AG, and superior and inferior occipital lobes. The 94-channel setting was found to cover each of these regions by at least one channel. 4. Discussion In the current study, we aimed to develop a referential framework for a macroanatomical structural reference for infant fNIRS data. Based on the manually traced sulci and fissures for the lateral surface of a 12-month-old infant brain, a macroanatomical atlas was produced, which was further linked to 10-20, 10-10, and 105 scalp landmarks and to a spherical coordinate system. Although this is based on a single subject’s macroanatomical structure, as is the case for automatic anatomical labeling (AAL), which has been widely used in fMRI studies, the current referential framework can

be developed to integrate data from multiple subjects. It should be noted that the atlas we created should not be taken as a canonical template but rather as an example of a macroanatomical structural reference. To date, many efforts have been made to systematically describe infant cortical structures, and important advances have been made in recent years. Altaye et al. (2008) first developed a probabilistic brain template that can be used for segmentation and normalization based on the MRIs of 76 infants of 9–15 months old, enabling segmentation of gray matter, white matter and cerebrospinal fluid. This was followed by the development of age-specific templates for neonates to 4-year-old children (Sanchez et al., 2012), infant brains at any given stage between 29 and 44 gestational weeks (KuklisovaMurgasova et al., 2011), and 4.5- to 18.5-year-old children (Fonov et al., 2011). Another group has created an average-shape atlas made by aligning 68 neonatal brains to MNI space and averaging them after iterative affine and nonlinear transformation (Shi et al., 2010, 2011). Although this atlas includes 76 parcellated brain regions, their correspondence to macro-anatomy remains unclear. Thus, macroanatomical segmentation at the gyrus level has been lacking. In the current study, we delineated lateral macroanatomical cortical structures because this is of fundamental importance in fNIRS studies, in which signal source is mainly assumed on the lateral cortical surface and thus activation data must be associated with the lateral cortical structures (Tsuzuki and Dan, 2014). Upon examination of the longitudinal MRI dataset optimized for manual tracing procedures, we found that delineation of the lateral cortical structure was possible for a 12-month-old infant’s brain. In the younger brains, skull-stripping was technically difficult because of low contrast among tissues. Although this lateral macroanatomical atlas based on a12-month-old brain may provide a useful initial resource for the developmental of functional neuroimaging investigations, structural images of younger brains should be examined in

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Fig. 7. Inverse mapping of cortical regions on the head surface. Lateral surface cortical macroanatomical structures were inversely mapped on the head surface of the infant. Gyri and cortical regions are depicted with the same colors as in Fig. 4.

the future. This could be achieved through the development of better image acquisition protocols. Alternatively, skull-stripping may be abandoned and manual tracing could be performed based solely on MRI slices. Even if the lateral cortical structures are depicted, they should not exist in isolation but should be linked to other systems. Since, historically, cortical atlases have been made for adult brains, they are described mainly in the standard coordinate system most exemplified by the MNI system (e.g., Tzourio-Mazoyer et al., 2002; Shattuck et al., 2008; Zilles and Amunts, 2010). Reflecting such tradition, many recent efforts have tried to depict infant cortical structures in reference to the MNI system. In the aforementioned study, Shi et al. (2011) created a longitudinal deformation field to transform adult brains to infant brains, through which they projected AAL to neonate, 1-year-old and 2-year-old brains. Watanabe et al. (2013) also took a similar approach to transform scalp fNIRS channels to the cortical template in MNI space based on the assumption that the relative macro-anatomical structural patterns of young infant and child cortices are similar to those of adults. This assumption is partially validated by Hill et al. (2010), who demonstrated that the surface-based atlas of the cerebral cortex in term infants is similar to that of an adult in the pattern of individual variability. Specifically, they created a population-average surface-based atlas of the human cerebral cortex at term gestation, which was then used to compare cortical shape characteristics

of infants with those of adults. The authors eventually concluded that the cortical structure in term infants is largely similar to that in adults. Based on this assumption, Watanabe et al. (2013) performed the virtual registration of fNIRS probe and channel locations of 3-month-old infants to a neonate AAL atlas (Shi et al., 2011) transformed to MNI space (Altaye et al., 2008). Although the virtual registrations with adult and neonate brains showed that they are macroanatomically comparable, they were both transformed to MNI space through linear and non-linear transformation and thus may not necessarily reflect naïve structural characteristics of infant brains: the proportion of different cortical regions in infant brains may not be maintained but rather may be deformed to fit to the MNI template. Since developmental speeds of the maturation of cortical structures are not even (Gilmore et al., 2012; Li et al., 2013), especially in the early stages of life, a method of normalization that can maintain structural characteristics of infant brains is of great importance. As an alternative method, we performed MNI-free normalization based on the spherical coordinate system to compare adult and infant cortical structures in order to avoid deformation bias intrinsic to normalization to MNI space. However, somewhat to our surprise, major macroanatomical structures were generally comparable between adult and infant atlases with differences in definitions (e.g., frontal and temporal poles) aside. A major difference was found in the parietal lobe, which was positioned

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Fig. 8. Lateral surface cortical macroanatomical structures as assessed in the spherical coordinate system. Nodes of the spherical coordinate system at 15◦ pitches are overlaid onto the delineated gyri and cortical regions of the infant atlas (A–E). The LPBA40 macroanatomical atlas was transformed to the infant atlas, and is also depicted with 15◦ pitch nodes of the spherical coordinate system (F–J). Gyri and cortical regions are depicted with the same colors as in Fig. 6.

Fig. 9. Implementation of typical fNIRS channel locations. Virtual registration of the 94 channels (blue) typically used in fNIRS infant studies to the infant atlas is shown (A–D, and E). 10-20 positions (red) are overlaid on the surface of the infant atlas. Gyri and cortical regions are depicted with the same colors as in Fig. 4. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of the article.)

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posteriorly in the infant brain atlas, especially in the vertex region. Since the parieto-occipital border of the IHF was invariant between infant and adult brains, and the shift was less prominent in inferior regions, it was thus attributed to parietal narrowing in the vertex region. Whether the narrow parietal lobe is specific to this infant or is a general tendency needs to be clarified in further group studies. However, even if such a macroanatomical shift was present, the degree was in the order of one 10-5 row. Except for the vertex parietal region, macroanatomical structures were similarly labeled between infant and adult atlases for 10-5 reference landmarks. In an optimistic view, the current results provide further support for Hill’s assumption on commonality between infant and adult brain surface macroanatomical structures, but further generalization should be based on group studies. In the current study, we adopted both 10-20-based and spherical coordinate systems. They are not exclusive to one another but rather are regarded as compatible systems with a high affinity. Unlike the original effort made by Towle et al. (1993) and Lagerlund et al. (1993), we chose initial reference points at the nasion and preauricular points, which also serve as the fundamental initial reference points for 10-20 based systems. The major difference between the two systems is that while the spherical coordinate system is continuous, the 10-20 system describes the scalp in a discrete manner. Also, because of the spread of 10-20-based systems in clinical situations, intuitive handling of scalp locations is easy with 10-20-based systems. Thus, the two systems are used in an interchangeable manner. One merit in the use of a lateral cortical surface atlas is to determine the realm of macroanatomical inference. The 94-channel setting surrounding the lateral cortical surface produced channel settings that covered all the gyri and regions present in the measured regions of interest. A number of previous studies have shown that 3-month-old infants exhibit spatial functional differences at the gyrus level in visual and auditory processing (Homae et al., 2011; Taga et al., 2011; Watanabe et al., 2013). Thus we expect that this channel setting, with an inter-optode separation of 2 cm, would be moderate enough to infer functional characteristics, at least at the gyrus level in infant studies. The 94-channel fNIRS setting was not presented to demonstrate high-density multi-channel measurement covering most of the lateral brain surface, but rather to provide inclusive representation of various smaller channel settings, such as a 3 × 3 array, which have been typically used in previous fNIRS studies. It is important to note that optodes must be accurately placed in reference to 10-20 based landmarks to ensure a reliable correspondence between cortical regions and channel positions. Another distinct merit of adopting the spherical coordinate system is its high affinity to navigation systems. When reference landmark positions are measured using magnetic or optical digitizers, scalp locations are measured in reference to the spherical coordinate system. The coordinate locations may be linked to macroanatomical structures through a database. We are currently developing an anatomical navigation system utilizing the resources described in the current study. It should be noted that the anatomical atlas in this study is based on a single subject, and so deterministic usage should be avoided. While a difference in macroanatomical structure was found in the parietal lobe between the infant brain and the adult MNI template, it is undetermined whether this difference was due to the sampling of this particular infant or whether it represents a normative anatomical difference. However, it is also true that even an atlas based on a single brain provides a useful resource and facilitates research in the field. For example, AAL (Collins et al., 1994; TzourioMazoyer et al., 2002) is based on the Colin 27 standard brain (Collins et al., 1994), and has been used as a major anatomical reference in SPM-based analyses to date, attracting more than 3000 citations (as

of 2013). Thus, the current atlas would also provide a useful transitional resource until the advent of a more probabilistic atlas based on macroanatomies of multiple subjects. In addition, we should be reminded that registration alone may not be sufficient for spatial analyses of infant fNIRS data as the brain-scalp distance, optical properties of the infant brain and head tissues could affect fNIRS signals (Beauchamp et al., 2011). Such factors need to be explored in the future. In conclusion, the significance of the present study lies in providing an initial reference framework for macroanatomical analyses in infant fNIRS studies. With this resource, the future goal is to estimate the signal source of multichannel fNIRS measurement in reference to macroanatomical structures through virtual and probabilistic registrations without acquiring subject-specific MRIs. To resolve the issue of probabilistic registration, further studies with multiple infant MRI data must clarify individual variation and agedependent variation of the cortical surface structure in relation to the head-surface landmarks. Technically speaking, the present method for creating an atlas of the lateral cortical surface with a 12-month-old infant can be applied to infants as young as 3 or 6 months of age, as long as high quality MRI images are available. We believe that this lateral macroanatomical atlas of the infant brain will facilitate the growth of fNIRS-based functional developmental studies of infants. Acknowledgements We appreciate Kayo Asakawa, Keiko Hirano, and Hiroko Ishida for administrative assistance. We appreciate ELCS – English Language Consultation Services for proofreading the manuscript. This work was supported in part by the Grant-in-Aid for Scientific Research from the Japan Society for Promotion of Science (24680044 to FH, 22242012, 23390354, 2370885, and 23650217 to ID, and 24119002 to GT), JSPS Asian Core Program (to MM), Health and Labor Sciences Research Grants, Research on Psychiatric and Neurological Diseases and Mental Health (to ID), and The Mitsubishi Foundation (to GT). Appendix A. A.1. Sulci delineation The Rolandic fissure (central sulcus; CS) was delineated according to Rademacher et al. (1992) and Tzourio-Mazoyer et al. (2002). The CS started from near the vertex, and the anteroventral end point of this sulcus was situated near the superior lip of the Sylvian fissure (SF). This sulcus of the left hemisphere ended with an inverted “y” shape. The precentral sulcus (PrCS) was delineated according to Rademacher et al. (1992). The PrCS was anteriorly located near and roughly parallel to the CS. The PrCS crossed the superior frontal sulcus, and had end-to-side connection to the inferior frontal sulcus (IFS) in both hemispheres. The superior frontal sulcus (SFS) was delineated according to Rademacher et al. (1992) and Tzourio-Mazoyer et al. (2002). The SFS, which started from the junction with the PrCS, ran parallel to the interhemispheric fissure (IHF). Solely in the left hemisphere, the middle frontal sulcus (MFS) was present. The MFS is also referred to as the intermediate sulcus, and known to appear in 16% of the brain (Ono et al., 1990). The MFS was inferior to the SFS. The anterior part of the MFS ended with a “y” shape. The caudal end did not reach the PrCS. The inferior frontal sulcus (IFS) was delineated according to Rademacher et al. (1992). The IFS started from the junction with the PrCS, and it ran parallel to the SFS and the MFS (in the left

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hemisphere). The left IFS was separated into two segments. The ventral segment surrounded the ascending ramus of the SF. In the right hemisphere, the most anterior part of this sulcus ran downward, and surrounded the horizontal ramus of the SF. The horizontal Sylvian ramus was delineated according to Rademacher et al. (1992) and Tzourio-Mazoyer et al. (2002). The horizontal ramus of the SF started from the anterior end of the SF, and ran parallel to the ventral edge of the frontal lobe. The Sylvian fissure (SF) was delineated according to TzourioMazoyer et al. (2002). The SF started from the inferior frontal region. This fissure extended into the parietal lobe through the superior boundary of the temporal lobe, and ended with double parallel terminal ascending segments (Ono et al., 1990). The ventral end of the PrCS was connected to this fissure. The superior temporal sulcus (STS) was delineated according to Rademacher et al. (1992) and Tzourio-Mazoyer et al. (2002). The STS was inferior to the SF, and extended into the parietal and occipital lobes. The anterior point ended close to the temporal pole. In the left hemisphere, the caudal branch of this sulcus ended by a bifurcation into two rami. The posterior ramus joined the anterior occipital sulcus (AOS). The right STS extended into the occipital cortex. The inferior temporal sulcus (ITS) was delineated according to Rademacher et al. (1992). The ITS was parallel to the STS. In the left hemisphere, the ITS formed an end-to-side connection with the AOS. The postcentral sulcus (PoCS) was delineated according to Rademacher et al. (1992) and Tzourio-Mazoyer et al. (2002). The PoCS was posterior to the CS. The dorsal segment ended in a yshaped configuration at the hemispheric margin. This sulcus had end-to-side connection to the intraparietal sulcus (IPS) (Ono et al., 1990). In the right hemisphere, the PoCS consisted of two segments. The intraparietal sulcus (IPS) was delineated according to Rademacher et al. (1992) and Tzourio-Mazoyer et al. (2002). The IPS started from the midpoint of the PoCS to the occipital cortex in both hemispheres. The right IPS exhibited a double parallel pattern in the parietal lobe (Ono et al., 1990). The intermediate sulcus of Jensen (JS) was delineated according to Rademacher et al. (1992). The JS was observed in the left hemisphere. This sulcus was a side branch of the IPS, and ran from the junction of the PoCS and the IPS toward the inferior parietal region. The parieto-occipital sulcus (POS) was delineated according to Rademacher et al. (1992) and Tzourio-Mazoyer et al. (2002). On the medial cerebral surface, the POS started from a dorso-caudal point at the hemispheric margin. At the antero-ventral point, this sulcus formed a junction with the calcarine sulcus. The anterior occipital sulcus (AOS) was delineated according to Tzourio-Mazoyer et al. (2002). The AOS started from near the preoccipital notch and ran toward the STS. This sulcus in the left hemisphere was connected to one of the posterior branches of the STS. The lateral occipital sulcus (LOS) was delineated according to Rademacher et al. (1992). The LOS was connected anteriorly to the AOS, and ran horizontally to the occipital pole. In the left hemisphere, this sulcus crossed over the IPS. The interhemispheric fissure (IHF) ran between the left and right hemispheres. The transverse fissure of cerebellum (TFC) ran between the cerebrum and cerebellum. At the midpoint, the TFC connected with the IHF.

Appendix B. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.neures. 2014.01.003.

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