Creating a population-averaged standard brain template for Japanese macaques (M. fuscata)

Automatic macaque brain segmentation based on 7T MRI

BACKGROUND

In monkey neuroimaging, particularly magnetic resonance imaging (MRI) studies, quick and accurate automatic macaque brain segmentation is essential. However, there are few processing and analysis tools dedicated to automatic brain tissue segmentation and labeling of the macaque brain on a subject-specific basis. As a result, currently most adopted methods are through direct implementation of existing tools that have been designed for human brain. However, the operation steps combining different functional modules of a variety of processing and analysis tool software are inevitably complicated, cumbersome, time-consuming and labor-intensive.

NEW METHOD

In this study, we proposed a novel quick and accurate automatic macaque brain segmentation method based on multi-atlas registration and majority-vote algorithm. First, the single-atlas method based on S-HAMMER is used to register each template image of the reference atlas set (including brain tissue labeled images and brain anatomical structure labeled images) to the preprocessed image to be segmented. Thus, we obtain the corresponding deformation field and spatially transform the labeled image, and then get multiple segmentation results by local weighted voting method, which perform label fusion to obtain the final labeled images of brain structures segmentation result.

RESULTS

By collecting high SNR and high spatial resolution images of macaque brain images from our 7T human MRI scanner, we have constructed two brain templates for each individual macaque subject, and macaque brain tissues and brain anatomical structure by one-atlas method. However, segmentation result of single-atlas method is not much accurate in some brain tissue area. It takes about 2 h and need more manual correction for segmentation. Automatic segmentation of macaque brain structure based on multi-atlas method was reasonably successful, the accuracy of segmentation was greatly improved without manual correction. Also, the proposed method provided good tissue fitting to V1 with smooth and continuous boundary. The Dice similarity of multi-atlas method showing 3.24%, 4.24%, 2.55%, 2.85%, 3.05%, and 0.35% improvement in image slices of 63, 66, 70, 71, 99 and 100, respectively. The entire processing time for the construction of a single template map took ~40 min.

CONCLUSIONS

This study proposed a novel automatic segmentation method of individual macaque brain structure based on multi-atlas registration method, which is concise and reliable. It may offer a valuable tool to applications in the field of brain and neuroscience research using the macaque as an experimental animal model.

Depression induced by low-frequency repetitive transcranial magnetic stimulation to ventral medial frontal cortex in monkeys

The medial frontal cortex (MFC), especially its ventral part, has long been of great interest with respect to the pathology of mood disorders. A number of human brain imaging studies have demonstrated the abnormalities of this brain region in patients with mood disorders, however, whether it is critically and causally involved in the pathogenesis of such disorders remains to be fully elucidated. In this study, we examined how the suppression of neural activity in the ventral region of the MFC (vMFC) affects the behavioral and physiological states of monkeys by using repetitive transcranial magnetic stimulation (rTMS). By using low-frequency rTMS (LF-rTMS) as an inhibitory intervention, we found that LF-rTMS targeting the vMFC temporarily induced a depression-like state in monkeys, which was characterized by a reduced movement activity level, impaired sociability, and decreased motivation level, as well as increased plasma cortisol level. On the other hand, no such significant changes in behavioral and physiological states were observed when targeting the other MFC regions, dorsal or posterior. We further found that the administration of an antidepressant agent, ketamine, ameliorated the abnormal behavioral and physiological states induced by the LF-rTMS intervention. These findings causally indicate the involvement of the vMFC in the regulation of mood and the validity of the LF-rTMS-induced dysfunction of the vMFC as a nonhuman primate model of depression.

Longitudinal brain atlases of early developing cynomolgus macaques from birth to 48 months of age

Longitudinal brain imaging atlases with densely sampled time-points and ancillary anatomical information are of fundamental importance in studying early developmental characteristics of human and non-human primate brains during infancy, which feature extremely dynamic imaging appearance, brain shape and size. However, for non-human primates, which are highly valuable animal models for understanding human brains, the existing brain atlases are mainly developed based on adults or adolescents, denoting a notable lack of temporally densely-sampled atlases covering the dynamic early brain development. To fill this critical gap, in this paper, we construct a comprehensive set of longitudinal brain atlases and associated tissue probability maps (gray matter, white matter, and cerebrospinal fluid) with totally 12 time-points from birth to 4 years of age (i.e., 1, 2, 3, 4, 5, 6, 9, 12, 18, 24, 36, and 48 months of age) based on 175 longitudinal structural MRI scans from 39 typically-developing cynomolgus macaques, by leveraging state-of-the-art computational techniques tailored for early developing brains. Furthermore, to facilitate region-based analysis using our atlases, we also provide two popular hierarchy parcellations, i.e., cortical hierarchy maps (6 levels) and subcortical hierarchy maps (6 levels), on our longitudinal macaque brain atlases. These early developing atlases, which have the densest time-points during infancy (to the best of our knowledge), will greatly facilitate the studies of macaque brain development.

MRI-based Parcellation and Morphometry of the Individual Rhesus Monkey Brain: the macaque Harvard-Oxford Atlas (mHOA), a translational system referencing a standardized ontology

Investigations of the rhesus monkey (Macaca mulatta) brain have shed light on the function and organization of the primate brain at a scale and resolution not yet possible in humans. A cornerstone of the linkage between non-human primate and human studies of the brain is magnetic resonance imaging, which allows for an association to be made between the detailed structural and physiological analysis of the non-human primate and that of the human brain. To further this end, we present a novel parcellation method and system for the rhesus monkey brain, referred to as the macaque Harvard-Oxford Atlas (mHOA), which is based on the human Harvard-Oxford Atlas (HOA) and grounded in an ontological and taxonomic framework. Consistent anatomical features were used to delimit and parcellate brain regions in the macaque, which were then categorized according to functional systems. This system of parcellation will be expanded with advances in technology and, like the HOA, will provide a framework upon which the results from other experimental studies (e.g., functional magnetic resonance imaging (fMRI), physiology, connectivity, graph theory) can be interpreted.

A Probabilistic Atlas of the Pineal Gland in the Standard Space

Pineal gland (PG) is a structure located in the midline of the brain, and is considered as a main part of the epithalamus. There are numerous reports on the facilitatory role of this area for brain function; hormone secretion and its role in sleep cycle are the major reports. However, reports are rarely available on the direct role of this structure in brain cognition and in information processing. A suggestion for the limited number of such studies is the lack of a standard atlas for the PG; none of the available MRI templates and atlases has provided parcellations for this structure. In this study, we used the three-dimensional (3D) T1-weighted MRI data of 152 healthy young volunteers, and provided a probabilistic map of the PG in the standard Montreal Neurologic Institute (MNI) space. The methods included collecting the data using a 64-channel head coil on a 3-Tesla Prisma MRI Scanner, manual delineation of the PG by two experts, and robust template and atlas construction algorithms. This atlas is freely accessible, and we hope importing this atlas in the well-known neuroimaging software packages would help to identify other probable roles of the PG in brain function. It could also be used to study pineal cysts, for volumetric analyses, and to test any associations between the cognitive abilities of the human and the structure of the PG.

MRI brain templates of the male Yucatan minipig

The pig is growing in popularity as an experimental animal because its gyrencephalic brain is similar to humans. Currently, however, there is a lack of appropriate brain templates to support functional and structural neuroimaging pipelines. The primary contribution of this work is an average volume from an iterative, non-linear registration of 70 five- to seven-month-old male Yucatan minipigs. In addition, several aspects of this study are unique, including the comparison of linear and non-linear template generation, the characterization of a large and homogeneous cohort, an analysis of effective resolution after averaging, and the evaluation of potential in-template bias as well as a comparison with a template from another minipig species using a "left-out" validation set. We found that within our highly homogeneous cohort, non-linear registration produced better templates, but only marginally so. Although our T1-weighted data were resolution limited, we preserved effective resolution across the multi-subject average, produced templates that have high gray-white matter contrast and demonstrate superior registration accuracy compared to an alternative minipig template.

In vivo Population Averaged Stereotaxic T2w MRI Brain Template for the Adult Yucatan Micropig

Population averaged brain templates are an essential tool for imaging-based neuroscience research, providing investigators with information about the expected size and morphology of brain structures and the spatial relationships between them, within a demographic cross-section. This allows for a standardized comparison of neuroimaging data between subjects and provides neuroimaging software with a probabilistic framework upon which further processing and analysis can be based. Many different templates have been created to represent specific study populations and made publicly available for human and animal research. An increasingly studied animal model in the neurosciences that still lacks appropriate brain templates is the adult Yucatan micropig. In particular, T2-weighted templates are absent in this species as a whole. To address this need and provide a tool for neuroscientists wishing to pursue neuroimaging research in the adult micropig, we present the construction of population averaged (n = 16) T2-weighted MRI brain template for the adult Yucatan micropig. Additionally, we present initial analysis of T1-weighted (n = 3), and diffusion-weighted (n = 3) images through multimodal registration of these contrasts to our T2 template. The strategies used here may also be generalized to create similar templates for other study populations or species in need of template construction.

A population stereotaxic positron emission tomography brain template for the macaque and its application to ischemic model

PURPOSE

Positron emission tomography (PET) is a non-invasive imaging tool for the evaluation of brain function and neuronal activity in normal and diseased conditions with high sensitivity. The macaque monkey serves as a valuable model system in the field of translational medicine, for its phylogenetic proximity to man. To translation of non-human primate neuro-PET studies, an effective and objective data analysis platform for neuro-PET studies is needed.

MATERIALS AND METHODS

A set of stereotaxic templates of macaque brain, namely the Institute of High Energy Physics & Jinan University Macaque Template (HJT), was constructed by iteratively registration and averaging, based on 30 healthy rhesus monkeys. A brain atlas image was created in HJT space by combining sub-anatomical regions and defining new 88 bilateral functional regions, in which a unique integer was assigned for each sub-anatomical region.

RESULTS

The HJT comprised a structural MRI T1 weighted image (T1WI) template image, a functional FDG-PET template image, intracranial tissue segmentations accompanied with a digital macaque brain atlas image. It is compatible with various commercially available software tools, such as SPM and PMOD. Data analysis was performed on a stroke model compared with a group of healthy controls to demonstrate the usage of HJT.

CONCLUSION

We have constructed a stereotaxic template set of macaque brain named HJT, which standardizes macaque neuroimaging data analysis, supports novel radiotracer development and facilitates translational neuro-disorders research.

A high-throughput neurohistological pipeline for brain-wide mesoscale connectivity mapping of the common marmoset

Understanding the connectivity architecture of entire vertebrate brains is a fundamental but difficult task. Here we present an integrated neuro-histological pipeline as well as a grid-based tracer injection strategy for systematic mesoscale connectivity mapping in the common marmoset (Callithrix jacchus). Individual brains are sectioned into ~1700 20 µm sections using the tape transfer technique, permitting high quality 3D reconstruction of a series of histochemical stains (Nissl, myelin) interleaved with tracer labeled sections. Systematic in-vivo MRI of the individual animals facilitates injection placement into reference-atlas defined anatomical compartments. Further, by combining the resulting 3D volumes, containing informative cytoarchitectonic markers, with in-vivo and ex-vivo MRI, and using an integrated computational pipeline, we are able to accurately map individual brains into a common reference atlas despite the significant individual variation. This approach will facilitate the systematic assembly of a mesoscale connectivity matrix together with unprecedented 3D reconstructions of brain-wide projection patterns in a primate brain.

Three-Dimensional Digital Template Atlas of the Macaque Brain

We present a new 3D template atlas of the anatomical subdivisions of the macaque brain, which is based on and aligned to the magnetic resonance imaging (MRI) data set and histological sections of the Saleem and Logothetis atlas. We describe the creation and validation of the atlas that, when registered with macaque structural or functional MRI scans, provides a straightforward means to estimate the boundaries between architectonic areas, either in a 3D volume with different planes of sections, or on an inflated brain surface (cortical flat map). As such, this new template atlas is intended for use as a reference standard for macaque brain research. Atlases and templates are available as both volumes and surfaces in standard NIFTI and GIFTI formats.

Construction of population-specific Indian MRI brain template: Morphometric comparison with Chinese and Caucasian templates

OBJECTIVE

Spatial normalization of brain MR images is highly dependent on the choice of target brain template. Morphological differences caused by factors like genetic and environmental exposures, generates a necessity to construct population specific brain templates. Brain image analysis performed using brain templates from Caucasian population may not be appropriate for non-Caucasian population. In this study, our objective was to construct an Indian brain template from a large population (N = 157 subjects) and compare the morphometric parameters of this template with that of Chinese-56 and MNI-152 templates. In addition, using an independent MRI data of 15 Indian subjects, we also evaluated the potential registration accuracy differences using these three templates.

METHODS

Indian brain template was constructed using iterative routines as per established procedures. We compared our Indian template with standard MNI-152 template and Chinese template by measuring global brain features. We also examined accuracy of registration by aligning 15 new Indian brains to Indian, Chinese and MNI templates. Furthermore, we supported our measurement protocol with inter-rater and intra-rater reliability analysis.

RESULTS

Our results showed that there were significant differences in global brain features of Indian template in comparison with Chinese and MNI brain templates. The results of registration accuracy analysis revealed that fewer deformations are required when Indian brains are registered to Indian template as compared to Chinese and MNI templates.

CONCLUSION

This study concludes that population specific Indian template is likely to be more appropriate for structural and functional image analysis of Indian population.

A population MRI brain template and analysis tools for the macaque

The use of standard anatomical templates is common in human neuroimaging, as it facilitates data analysis and comparison across subjects and studies. For non-human primates, previous in vivo templates have lacked sufficient contrast to reliably validate known anatomical brain regions and have not provided tools for automated single-subject processing. Here we present the "National Institute of Mental Health Macaque Template", or NMT for short. The NMT is a high-resolution in vivo MRI template of the average macaque brain generated from 31 subjects, as well as a neuroimaging tool for improved data analysis and visualization. From the NMT volume, we generated maps of tissue segmentation and cortical thickness. Surface reconstructions and transformations to previously published digital brain atlases are also provided. We further provide an analysis pipeline using the NMT that automates and standardizes the time-consuming processes of brain extraction, tissue segmentation, and morphometric feature estimation for anatomical scans of individual subjects. The NMT and associated tools thus provide a common platform for precise single-subject data analysis and for characterizations of neuroimaging results across subjects and studies.

Dopamine and glutamate release in the anterior default system during rest: A monkey microdialysis study

Human neuroimaging studies have demonstrated the presence of a default system in the brain, which shows a default mode of brain activity, i.e., greater activity during rest than during an attention-demanding cognitive task. Our previous study on monkeys has revealed a default mode of brain activity in medial cortical areas. We have observed an increase in dopamine (DA) release during a working memory (WM) task compared with that during rest in the monkey lateral prefrontal cortex (LPFC). However, no previous study has examined DA release related to the default mode of brain activity. We used a microdialysis technique to investigate changes in DA release in the medial prefrontal cortex (MPFC), which constitutes the anterior default system, during the WM task and rest. Because DA and glutamate (Glu) release in the LPFC is interrelated, we also examined Glu release in the MPFC. We observed a significant increase in DA release, but no significant change in Glu release during rest compared with that during the WM task. We also observed an inhibitory relationship between the two transmitters in the MPFC. Considering that human default brain activity is related to internal thought processes and increased DA release in the LPFC plays an important role in executive control, increase in DA release during rest in the monkey anterior default system may be related to some form of internal thought process.

Development of new population-averaged standard templates for spatial normalization and segmentation of MR images for postnatal piglet brains

PROPOSE

To design a set of brain templates for postnatal piglet brains based on high-resolution T1-weighted imaging for voxel-based morphometric analysis.

MATERIALS AND METHODS

Using a 3.0 T magnetic resonance (MR) scanner, a population-based whole brain template was developed by averaging forty T1 images in the brains of postnatal piglets at 38 days of age. The templates for gray and white matter, and cerebrospinal fluid were designed based on the corresponding probability maps by adapting individual data sets using statistical parametric mapping. Anatomical labeling maps were generated from labeling propagation derived from the established Pig Brain Atlas. Differences in the coordinates from four significant structural landmarks in the template, plus an additional 12 normalized images and anatomical labeling maps were measured to validate the accuracy of the registration of the template.

RESULTS

A whole brain template, a set of tissue-specific probability and anatomical labeling maps were developed. The location deviation of the four significant structural landmarks, including the anterior and posterior regions in the corpus callosum, and the left and right caudate nucleus, was found to be <0.25 cm, validating the sensitivity and resolution of the template.

CONCLUSION

A whole brain template map and a set of tissue-specific probability and anatomical labeling maps were developed to analyze the morphometric imaging of the postnatal piglet brain, an animal model of the human infant.

A multi-atlas based method for automated anatomical Macaca fascicularis brain MRI segmentation and PET kinetic extraction

MRI templates and digital atlases are needed for automated and reproducible quantitative analysis of non-human primate PET studies. Segmenting brain images via multiple atlases outperforms single-atlas labelling in humans. We present a set of atlases manually delineated on brain MRI scans of the monkey Macaca fascicularis. We use this multi-atlas dataset to evaluate two automated methods in terms of accuracy, robustness and reliability in segmenting brain structures on MRI and extracting regional PET measures.

METHODS

Twelve individual Macaca fascicularis high-resolution 3DT1 MR images were acquired. Four individual atlases were created by manually drawing 42 anatomical structures, including cortical and sub-cortical structures, white matter regions, and ventricles. To create the MRI template, we first chose one MRI to define a reference space, and then performed a two-step iterative procedure: affine registration of individual MRIs to the reference MRI, followed by averaging of the twelve resampled MRIs. Automated segmentation in native space was obtained in two ways: 1) Maximum probability atlases were created by decision fusion of two to four individual atlases in the reference space, and transformation back into the individual native space (MAXPROB)(.) 2) One to four individual atlases were registered directly to the individual native space, and combined by decision fusion (PROPAG). Accuracy was evaluated by computing the Dice similarity index and the volume difference. The robustness and reproducibility of PET regional measurements obtained via automated segmentation was evaluated on four co-registered MRI/PET datasets, which included test-retest data.

RESULTS

Dice indices were always over 0.7 and reached maximal values of 0.9 for PROPAG with all four individual atlases. There was no significant mean volume bias. The standard deviation of the bias decreased significantly when increasing the number of individual atlases. MAXPROB performed better when increasing the number of atlases used. When all four atlases were used for the MAXPROB creation, the accuracy of morphometric segmentation approached that of the PROPAG method. PET measures extracted either via automatic methods or via the manually defined regions were strongly correlated, with no significant regional differences between methods. Intra-class correlation coefficients for test-retest data were over 0.87.

CONCLUSIONS

Compared to single atlas extractions, multi-atlas methods improve the accuracy of region definition. They also perform comparably to manually defined regions for PET quantification. Multiple atlases of Macaca fascicularis brains are now available and allow reproducible and simplified analyses.

The INIA19 Template and NeuroMaps Atlas for Primate Brain Image Parcellation and Spatial Normalization

The INIA19 is a new, high-quality template for imaging-based studies of non-human primate brains, created from high-resolution, T₁-weighted magnetic resonance (MR) images of 19 rhesus macaque (Macaca mulatta) animals. Combined with the comprehensive cortical and sub-cortical label map of the NeuroMaps atlas, the INIA19 is equally suitable for studies requiring both spatial normalization and atlas label propagation. Population-averaged template images are provided for both the brain and the whole head, to allow alignment of the atlas with both skull-stripped and unstripped data, and thus to facilitate its use for skull stripping of new images. This article describes the construction of the template using freely available software tools, as well as the template itself, which is being made available to the scientific community (http://nitrc.org/projects/inia19/).

Diffusion tensor imaging and tractography of the spinal cord: from experimental studies to clinical application

Diffusion-weighted magnetic resonance imaging provides detailed information about biological structures. In particular, diffusion tensor imaging and diffusion tensor tractography (DTT) are powerful tools for evaluating white matter fibers in the central nervous system. We previously established a reproducible spinal cord injury model in adult common marmosets and showed that DTT could be used to trace the neural tracts in the intact and injured spinal cord of these animals in vivo. Recently, many reports using DTT to analyze the spinal cord area have been published. Based on the findings from our experimental studies, we are now routinely performing DTT of the human spinal cord in the clinic. In this review we outline the basic principles of DTT, and describe the characteristics, limitations, and future uses of DTT to examine the spinal cord.

Segmentation of the C57BL/6J mouse cerebellum in magnetic resonance images

The C57BL mouse is the centerpiece of efforts to use gene-targeting technology to understand cerebellar pathology, thus creating a need for a detailed magnetic resonance imaging (MRI) atlas of the cerebellum of this strain. In this study we present a methodology for systematic delineation of the vermal and hemispheric lobules of the C57BL/6J mouse cerebellum in magnetic resonance images. We have successfully delineated 38 cerebellar and cerebellar-related structures. The higher signal-to-noise ratio achieved by group averaging facilitated the identification of anatomical structures. In addition, we have calculated average region volumes and created probabilistic maps for each structure. The segmentation method and the probabilistic maps we have created will provide a foundation for future studies of cerebellar disorders using transgenic mouse models.

An analysis approach for high-field fMRI data from awake non-human primates

fMRI experiments with awake non-human primates (NHP) have seen a surge of applications in recent years. However, the standard fMRI analysis tools designed for human experiments are not optimal for analysis of NHP fMRI data collected at high fields. There are several reasons for this, including the trial-based nature of NHP experiments, with inter-trial periods being of no interest, and segmentation artefacts and distortions that may result from field changes due to movement. We demonstrate an approach that allows us to address some of these issues consisting of the following steps: 1) Trial-based experimental design. 2) Careful control of subject movement. 3) Computer-assisted selection of trials devoid of artefacts and animal motion. 4) Nonrigid between-trial and rigid within-trial realignment of concatenated data from temporally separated trials and sessions. 5) Linear interpolation of inter-trial intervals and high-pass filtering of temporally continuous data 6) Removal of interpolated data and reconcatenation of datasets before statistical analysis with SPM. We have implemented a software toolbox, fMRI Sandbox (http://code.google.com/p/fmri-sandbox/), for semi-automated application of these processing steps that interfaces with SPM software. Here, we demonstrate that our methodology provides significant improvements for the analysis of awake monkey fMRI data acquired at high-field. The method may also be useful for clinical applications with subjects that are unwilling or unable to remain motionless for the whole duration of a functional scan.