Individualized brain mapping for navigated neuromodulation

ABSTRACT

The brain is a complex organ that requires precise mapping to understand its structure and function. Brain atlases provide a powerful tool for studying brain circuits, discovering biological markers for early diagnosis, and developing personalized treatments for neuropsychiatric disorders. Neuromodulation techniques, such as transcranial magnetic stimulation and deep brain stimulation, have revolutionized clinical therapies for neuropsychiatric disorders. However, the lack of fine-scale brain atlases limits the precision and effectiveness of these techniques. Advances in neuroimaging and machine learning techniques have led to the emergence of stereotactic-assisted neurosurgery and navigation systems. Still, the individual variability among patients and the diversity of brain diseases make it necessary to develop personalized solutions. The article provides an overview of recent advances in individualized brain mapping and navigated neuromodulation and discusses the methodological profiles, advantages, disadvantages, and future trends of these techniques. The article concludes by posing open questions about the future development of individualized brain mapping and navigated neuromodulation.

Genoarchitectonics of the larval zebrafish diencephalon

The brain is spatially organized into subdivisions, nuclei and areas, which often correspond to functional and developmental units. A segmentation of brain regions in the form of a consensus atlas facilitates mechanistic studies and is a prerequisite for sharing information among neuroanatomists. Gene expression patterns objectively delineate boundaries between brain regions and provide information about their developmental and evolutionary histories. To generate a detailed molecular map of the larval zebrafish diencephalon, we took advantage of the Max Planck Zebrafish Brain (mapzebrain) atlas, which aligns hundreds of transcript and transgene expression patterns in a shared coordinate system. Inspection and co-visualization of close to 50 marker genes have allowed us to resolve the tripartite prosomeric scaffold of the diencephalon at unprecedented resolution. This approach clarified the genoarchitectonic partitioning of the alar diencephalon into pretectum (alar part of prosomere P1), thalamus (alar part of prosomere P2, with habenula and pineal complex), and prethalamus (alar part of prosomere P3). We further identified the region of the nucleus of the medial longitudinal fasciculus, as well as the posterior and anterior parts of the posterior tuberculum, as molecularly distinct basal parts of prosomeres 1, 2, and 3, respectively. Some of the markers examined allowed us to locate glutamatergic, GABAergic, dopaminergic, serotoninergic, and various neuropeptidergic domains in the larval zebrafish diencephalon. Our molecular neuroanatomical approach has thus (1) yielded an objective and internally consistent interpretation of the prosomere boundaries within the zebrafish forebrain; has (2) produced a list of markers, which in sparse combinations label the subdivisions of the diencephalon; and is (3) setting the stage for further functional and developmental studies in this vertebrate brain.

Anatomical organization of the cerebrum of the praying mantis Hierodula membranacea

Many predatory animals, such as the praying mantis, use vision for prey detection and capture. Mantises are known in particular for their capability to estimate distances to prey by stereoscopic vision. While the initial visual processing centers have been extensively documented, we lack knowledge on the architecture of central brain regions, pivotal for sensory motor transformation and higher brain functions. To close this gap, we provide a three-dimensional (3D) reconstruction of the central brain of the Asian mantis, Hierodula membranacea. The atlas facilitates in-depth analysis of neuron ramification regions and aides in elucidating potential neuronal pathways. We integrated seven 3D-reconstructed visual interneurons into the atlas. In total, 42 distinct neuropils of the cerebrum were reconstructed based on synapsin-immunolabeled whole-mount brains. Backfills from the antenna and maxillary palps, as well as immunolabeling of γ-aminobutyric acid (GABA) and tyrosine hydroxylase (TH), further substantiate the identification and boundaries of brain areas. The composition and internal organization of the neuropils were compared to the anatomical organization of the brain of the fruit fly (Drosophila melanogaster) and the two available brain atlases of Polyneoptera-the desert locust (Schistocerca gregaria) and the Madeira cockroach (Rhyparobia maderae). This study paves the way for detailed analyses of neuronal circuitry and promotes cross-species brain comparisons. We discuss differences in brain organization between holometabolous and polyneopteran insects. Identification of ramification sites of the visual neurons integrated into the atlas supports previous claims about homologous structures in the optic lobes of flies and mantises.

Functional MRI of the Brainstem for Assessing Its Autonomic Functions: From Imaging Parameters and Analysis to Functional Atlas

BACKGROUND

The brainstem is a crucial component of the central autonomic nervous (CAN) system. Functional MRI (fMRI) of the brainstem remains challenging due to a range of factors, including diverse imaging protocols, analysis, and interpretation.

PURPOSE

To develop an fMRI protocol for establishing a functional atlas in the brainstem.

STUDY TYPE

Prospective cross-sectional study.

SUBJECTS

Ten healthy subjects (four males, six females).

FIELD STRENGTH/SEQUENCE

Using a 3.0 Tesla MR scanner, we acquired T1-weighted images and three different fMRI scans using fMRI protocols of the optimized functional Imaging of Brainstem (FIBS), the Human Connectome Project (HCP), and the Adolescent Brain Cognitive Development (ABCD) project.

ASSESSMENT

The temporal signal-to-noise-ratio (TSNR) of fMRI data was compared between the FIBS, HCP, and ABCD protocols. Additionally, the main normalization algorithms (i.e., FSL-FNIRT, SPM-DARTEL, and ANTS-SyN) were compared to identify the best approach to normalize brainstem data using root-mean-square (RMS) error computed based on manually defined reference points. Finally, a functional autonomic brainstem atlas that maps brainstem regions involved in the CAN system was defined using meta-analysis and data-driven approaches.

STATISTICAL TESTS

ANOVA was used to compare the performance of different imaging and preprocessing pipelines with multiple comparison corrections (P ≤ 0.05). Dice coefficient estimated ROI overlap, with 50% overlap between ROIs identified in each approach considered significant.

RESULTS

The optimized FIBS protocol showed significantly higher brainstem TSNR than the HCP and ABCD protocols (P ≤ 0.05). Furthermore, FSL-FNIRT RMS error (2.1 ± 1.22 mm; P ≤ 0.001) exceeded SPM (1.5 ± 0.75 mm; P ≤ 0.01) and ANTs (1.1 ± 0.54 mm). Finally, a set of 12 final brainstem ROIs with dice coefficient ≥0.50, as a step toward the development of a functional brainstem atlas.

DATA CONCLUSION

The FIBS protocol yielded more robust brainstem CAN results and outperformed both the HCP and ABCD protocols.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 1.

Obtaining novel data-driven hypotheses from teaching activities: An example assessing the role of the FKBP5 gene in major depression

Many clinical and research efforts aim to develop antidepressant drugs for those suffering from major depressive disorder (MDD). Yet, even today, the available treatments are suboptimal and unpredictable, with a significant proportion of patients enduring multiple drug attempts and adverse side effects before a successful response, and, for many patients, no response at all. Thus, a clearer understanding of the mechanisms underlying MDD is necessary. In the 'Brain Development and Disease' class of our Master's program in Cognitive Sciences, we ask students to collect data about the expression of a gene whose altered expression and/or function is related to a brain disorder. The students' final exam assignment consists of writing a research article in which the collected data are discussed in relation to the relevant disorder. In the course of one of these assignments, we identified the FKBP5 gene as a key player uniting two major hypotheses of MDD pathogenesis and treatment response. FKBP5 controls biological processes including immunoregulation and glucocorticoid function, both of which are separately implicated in the development and prognosis of MDD. Gene expression analyses from the human, non-human primate and mouse Allen Brain Atlases revealed that FKBP5 is expressed in brain regions involved in MDD, particularly at ages susceptible to early-life stressors. Data re-analysis from published studies confirmed that FKBP5 expression is upregulated in relevant brain regions in human MDD and preclinical mouse models of MDD. Our experience shows that classes engaging students in data collection and analysis projects may effectively result in novel data-driven hypotheses.

Zebrafish brain atlases: a collective effort for a tiny vertebrate brain

In the past two decades, digital brain atlases have emerged as essential tools for sharing and integrating complex neuroscience datasets. Concurrently, the larval zebrafish has become a prominent vertebrate model offering a strategic compromise for brain size, complexity, transparency, optogenetic access, and behavior. We provide a brief overview of digital atlases recently developed for the larval zebrafish brain, intersecting neuroanatomical information, gene expression patterns, and connectivity. These atlases are becoming pivotal by centralizing large datasets while supporting the generation of circuit hypotheses as functional measurements can be registered into an atlas' standard coordinate system to interrogate its structural database. As challenges persist in mapping neural circuits and incorporating functional measurements into zebrafish atlases, we emphasize the importance of collaborative efforts and standardized protocols to expand these resources to crack the complex codes of neuronal activity guiding behavior in this tiny vertebrate brain.

Functional connectome through the human life span

The functional connectome of the human brain represents the fundamental network architecture of functional interdependence in brain activity, but its normative growth trajectory across the life course remains unknown. Here, we aggregate the largest, quality-controlled multimodal neuroimaging dataset from 119 global sites, including 33,809 task-free fMRI and structural MRI scans from 32,328 individuals ranging in age from 32 postmenstrual weeks to 80 years. Lifespan growth charts of the connectome are quantified at the whole cortex, system, and regional levels using generalized additive models for location, scale, and shape. We report critical inflection points in the non-linear growth trajectories of the whole-brain functional connectome, particularly peaking in the fourth decade of life. Having established the first fine-grained, lifespan-spanning suite of system-level brain atlases, we generate person-specific parcellation maps and further show distinct maturation timelines for functional segregation within different subsystems. We identify a spatiotemporal gradient axis that governs the life-course growth of regional connectivity, transitioning from primary sensory cortices to higher-order association regions. Using the connectome-based normative model, we demonstrate substantial individual heterogeneities at the network level in patients with autism spectrum disorder and patients with major depressive disorder. Our findings shed light on the life-course evolution of the functional connectome and serve as a normative reference for quantifying individual variation in patients with neurological and psychiatric disorders.

Identifying Alzheimer's disease and mild cognitive impairment with atlas-based multi-modal metrics

Introduction

Multi-modal neuroimaging metrics in combination with advanced machine learning techniques have attracted more and more attention for an effective multi-class identification of Alzheimer's disease (AD), mild cognitive impairment (MCI) and health controls (HC) recently.

Methods

In this paper, a total of 180 subjects consisting of 44 AD, 66 MCI and 58 HC subjects were enrolled, and the multi-modalities of the resting-state functional magnetic resonance imaging (rs-fMRI) and the structural MRI (sMRI) for all participants were obtained. Then, four kinds of metrics including the Hurst exponent (HE) metric and bilateral hippocampus seed independently based connectivity metrics generated from fMRI data, and the gray matter volume (GMV) metric obtained from sMRI data, were calculated and extracted in each region of interest (ROI) based on a newly proposed automated anatomical Labeling (AAL3) atlas after data pre-processing. Next, these metrics were selected with a minimal redundancy maximal relevance (MRMR) method and a sequential feature collection (SFC) algorithm, and only a subset of optimal features were retained after this step. Finally, the support vector machine (SVM) based classification methods and artificial neural network (ANN) algorithm were utilized to identify the multi-class of AD, MCI and HC subjects in single modal and multi-modal metrics respectively, and a nested ten-fold cross-validation was utilized to estimate the final classification performance.

Results

The results of the SVM and ANN based methods indicated the best accuracies of 80.36 and 74.40%, respectively, by utilizing all the multi-modal metrics, and the optimal accuracies for AD, MCI and HC were 79.55, 78.79 and 82.76%, respectively, in the SVM based method. In contrast, when using single modal metric, the SVM based method obtained a best accuracy of 72.62% with the HE metric, and the accuracies for AD, MCI and HC subjects were just 56.82, 80.30 and 75.86%, respectively. Moreover, the overlapping abnormal brain regions detected by multi-modal metrics were mainly located at posterior cingulate gyrus, superior frontal gyrus and cuneus.

Conclusion

Taken together, the SVM based method with multi-modal metrics could provide effective diagnostic information for identifying AD, MCI and HC subjects.

A brain-wide analysis maps structural evolution to distinct anatomical module

The vertebrate brain is highly conserved topologically, but less is known about neuroanatomical variation between individual brain regions. Neuroanatomical variation at the regional level is hypothesized to provide functional expansion, building upon ancestral anatomy needed for basic functions. Classically, animal models used to study evolution have lacked tools for detailed anatomical analysis that are widely used in zebrafish and mice, presenting a barrier to studying brain evolution at fine scales. In this study, we sought to investigate the evolution of brain anatomy using a single species of fish consisting of divergent surface and cave morphs, that permits functional genetic testing of regional volume and shape across the entire brain. We generated a high-resolution brain atlas for the blind Mexican cavefish Astyanax mexicanus and coupled the atlas with automated computational tools to directly assess variability in brain region shape and volume across all populations. We measured the volume and shape of every grossly defined neuroanatomical region of the brain and assessed correlations between anatomical regions in surface fish, cavefish, and surface × cave F2 hybrids, whose phenotypes span the range of surface to cave. We find that dorsal regions of the brain are contracted, while ventral regions have expanded, with F2 hybrid data providing support for developmental constraint along the dorsal-ventral axis. Furthermore, these dorsal-ventral relationships in anatomical variation show similar patterns for both volume and shape, suggesting that the anatomical evolution captured by these two parameters could be driven by similar developmental mechanisms. Together, these data demonstrate that A. mexicanus is a powerful system for functionally determining basic principles of brain evolution and will permit testing how genes influence early patterning events to drive brain-wide anatomical evolution.

Striatonigrostriatal connectivity-based cross-species parcellation of human and macaque substantia nigra

Anatomical and functional heterogeneous substantia nigra (SN) has been extensively studied in humans and animals like rhesus monkeys given its crucial role in modulating a broad range of behaviors. Increasingly important cross-species research of SN may require connectionally homogeneous and homologous subregions of SN as objective and stable starting points from which the evolutionary characteristics of brain could be inspected. However, existing atlases of SN were all inaccurate mappings as a cross-species connectome atlas due to inadequate homology constraint during their constructions, and arbitrary paired use of these atlases might cause unreliable findings. In this study, a reliable blind-source cross-species parcellation of SN was developed based on the following rationale: striatonigrostriatal circuits form major structure of nigral connectivity; different nigral components have unique striatonigrostriatal connectivity; and inter-species corresponding human and macaque nigral components have similar striatonigrostriatal connectivity. Specifically, all voxels in human and macaque SN were grouped together and then classified based on inter-species identically characterized striatonigrostriatal connectivity attributes. Our results delineated a pars compacta-pars reticulate-like parcellation and further demonstrated its reliability by illustrating best-matched whole-brain structural and functional connectivity profiles of inter-species corresponding nigral subregions. Detailed inter-species and inter-regional differences in multi-aspect connectivities of these nigral subregions were inspected. It is expected that this cross-species connectome atlas of SN can offer biologically reliable cornerstones and important information to facilitate future cross-species research.

A brain atlas for the camouflaging dwarf cuttlefish, Sepia bandensis

The coleoid cephalopods (cuttlefish, octopus, and squid) are a group of soft-bodied marine mollusks that exhibit an array of interesting biological phenomena, including dynamic camouflage, complex social behaviors, prehensile regenerating arms, and large brains capable of learning, memory, and problem-solving.^{1,2,3,4,5,6,7,8,9,10} The dwarf cuttlefish, Sepia bandensis, is a promising model cephalopod species due to its small size, substantial egg production, short generation time, and dynamic social and camouflage behaviors.¹¹ Cuttlefish dynamically camouflage to their surroundings by changing the color, pattern, and texture of their skin. Camouflage is optically driven and is achieved by expanding and contracting hundreds of thousands of pigment-filled saccules (chromatophores) in the skin, which are controlled by motor neurons emanating from the brain. We generated a dwarf cuttlefish brain atlas using magnetic resonance imaging (MRI), deep learning, and histology, and we built an interactive web tool (https://www.cuttlebase.org/) to host the data. Guided by observations in other cephalopods,^{12,13,14,15,16,17,18,19,20} we identified 32 brain lobes, including two large optic lobes (75% the total volume of the brain), chromatophore lobes whose motor neurons directly innervate the chromatophores of the color-changing skin, and a vertical lobe that has been implicated in learning and memory. The brain largely conforms to the anatomy observed in other Sepia species and provides a valuable tool for exploring the neural basis of behavior in the experimentally facile dwarf cuttlefish.

An anatomical and connectivity atlas of the marmoset cerebellum

The cerebellum is essential for motor control and cognitive functioning, engaging in bidirectional communication with the cerebral cortex. The common marmoset, a small non-human primate, offers unique advantages for studying cerebello-cerebral circuits. However, the marmoset cerebellum is not well described in published resources. In this study, we present a comprehensive atlas of the marmoset cerebellum comprising (1) fine-detailed anatomical atlases and surface-analysis tools of the cerebellar cortex based on ultra-high-resolution ex vivo MRI, (2) functional connectivity and gradient patterns of the cerebellar cortex revealed by awake resting-state fMRI, and (3) structural-connectivity mapping of cerebellar nuclei using high-resolution diffusion MRI tractography. The atlas elucidates the anatomical details of the marmoset cerebellum, reveals distinct gradient patterns of intra-cerebellar and cerebello-cerebral functional connectivity, and maps the topological relationship of cerebellar nuclei in cerebello-cerebral circuits. As version 5 of the Marmoset Brain Mapping project, this atlas is publicly available at https://marmosetbrainmapping.org/MBMv5.html.

Enhancing the network specific individual characteristics in rs-fMRI functional connectivity by dictionary learning

Most fMRI inferences are based on analyzing the scans of a cohort. Thus, the individual variability of a subject is often overlooked in these studies. Recently, there has been a growing interest in individual differences in brain connectivity also known as individual connectome. Various studies have demonstrated the individual specific component of functional connectivity (FC), which has enormous potential to identify participants across consecutive testing sessions. Many machine learning and dictionary learning-based approaches have been used to extract these subject-specific components either from the blood oxygen level dependent (BOLD) signal or from the FC. In addition, several studies have reported that some resting-state networks have more individual-specific information than others. This study compares four different dictionary-learning algorithms that compute the individual variability from the network-specific FC computed from resting-state functional Magnetic Resonance Imaging (rs-fMRI) data having 10 scans per subject. The study also compares the effect of two FC normalization techniques, namely, Fisher Z normalization and degree normalization on the extracted subject-specific components. To quantitatively evaluate the extracted subject-specific component, a metric named Overlap $$ Overlap $$ is proposed, and it is used in combination with the existing differential identifiability I diff $$ \left({I}_{diff}\right) $$ metric. It is based on the hypothesis that the subject-specific FC vectors should be similar within the same subject and different across different subjects. Results indicate that Fisher Z transformed subject-specific fronto-parietal and default mode network extracted using Common Orthogonal Basis Extraction (COBE) dictionary learning have the best features to identify a participant.

Glycemic Challenge Is Associated with the Rapid Cellular Activation of the Locus Ceruleus and Nucleus of Solitary Tract: Circumscribed Spatial Analysis of Phosphorylated MAP Kinase Immunoreactivity

Rodent studies indicate that impaired glucose utilization or hypoglycemia is associated with the cellular activation of neurons in the medulla (Winslow, 1733) (MY), believed to control feeding behavior and glucose counterregulation. However, such activation has been tracked primarily within hours of the challenge, rather than sooner, and has been poorly mapped within standardized brain atlases. Here, we report that, within 15 min of receiving 2-deoxy-d-glucose (2-DG; 250 mg/kg, i.v.), which can trigger glucoprivic feeding behavior, marked elevations were observed in the numbers of rhombic brain (His, 1893) (RB) neuronal cell profiles immunoreactive for the cellular activation marker(s), phosphorylated p44/42 MAP kinases (phospho-ERK1/2), and that some of these profiles were also catecholaminergic. We mapped their distributions within an open-access rat brain atlas and found that 2-DG-treated rats (compared to their saline-treated controls) displayed greater numbers of phospho-ERK1/2+ neurons in the locus ceruleus (Wenzel and Wenzel, 1812) (LC) and the nucleus of solitary tract (>1840) (NTS). Thus, the 2-DG-activation of certain RB neurons is more rapid than perhaps previously realized, engaging neurons that serve multiple functional systems and which are of varying cellular phenotypes. Mapping these populations within standardized brain atlas maps streamlines their targeting and/or comparable mapping in preclinical rodent models of disease.

Fetal MRI based brain atlas analysis detects initial in utero effects of prenatal alcohol exposure

Prenatal alcohol exposure (PAE) can change the normal trajectory of human fetal brain development and may lead to long-lasting neurodevelopmental changes in the form of fetal alcohol spectrum disorders. Currently, early prenatal patterns of alcohol-related central nervous system changes are unclear and it is unknown if small amounts of PAE may result in early detectable brain anomalies. This super-resolution fetal magnetic resonance imaging (MRI) study aimed to identify regional effects of PAE on human brain structure. Fetuses were prospectively assessed using atlas-based semi-automated 3-dimensional tissue segmentation based on 1.5 T and 3 T fetal brain MRI examinations. After expectant mothers completed anonymized PRAMS and TACE questionnaires for PAE, fetuses without gross macroscopic brain abnormalities were identified and analyzed. Linear mixed-effects modeling of regional brain volumes was conducted and multiple comparisons were corrected using the Benjamini-Hochberg procedure. In total, 500 pregnant women were recruited with 51 reporting gestational alcohol consumption. After excluding confounding comorbidities, 24 fetuses (26 observations) were identified with PAE and 52 age-matched controls without PAE were analyzed. Patients with PAE showed significantly larger volumes of the corpus callosum (P ≤ 0.001) and smaller volumes of the periventricular zone (P = 0.001). Even minor (1-3 standard drinks per week) PAE changed the neurodevelopmental trajectory.

3D-atlas of the brain of the cockroach Rhyparobia maderae

The Madeira cockroach Rhyparobia maderae is a nocturnal insect and a prominent model organism for the study of circadian rhythms. Its master circadian clock, controlling circadian locomotor activity and sleep-wake cycles, is located in the accessory medulla of the optic lobe. For a better understanding of brain regions controlled by the circadian clock and brain organization of this insect in general, we created a three-dimensional (3D) reconstruction of all neuropils of the cerebral ganglia based on anti-synapsin and anti-γ-aminobutyric acid immunolabeling of whole mount brains. Forty-nine major neuropils were identified and three-dimensionally reconstructed. Single-cell dye fills complement the data and provide evidence for distinct subdivisions of certain brain areas. Most neuropils defined in the fruit fly Drosophila melanogaster could be distinguished in the cockroach as well. However, some neuropils identified in the fruit fly do not exist as distinct entities in the cockroach while others are lacking in the fruit fly. In addition to neuropils, major fiber systems, tracts, and commissures were reconstructed and served as important landmarks separating brain areas. Being a nocturnal insect, R. maderae is an important new species to the growing collection of 3D insect brain atlases and only the second hemimetabolous insect, for which a detailed 3D brain atlas is available. This atlas will be highly valuable for an evolutionary comparison of insect brain organization and will greatly facilitate addressing brain areas that are supervised by the circadian clock.

An atlas of the developing Tribolium castaneum brain reveals conservation in anatomy and divergence in timing to Drosophila melanogaster

Insect brains are formed by conserved sets of neural lineages whose fibers form cohesive bundles with characteristic projection patterns. Within the brain neuropil, these bundles establish a system of fascicles constituting the macrocircuitry of the brain. The overall architecture of the neuropils and the macrocircuitry appear to be conserved. However, variation is observed, for example, in size, shape, and timing of development. Unfortunately, the developmental and genetic basis of this variation is poorly understood, although the rise of new genetically tractable model organisms such as the red flour beetle Tribolium castaneum allows the possibility to gain mechanistic insights. To facilitate such work, we present an atlas of the developing brain of T. castaneum, covering the first larval instar, the prepupal stage, and the adult, by combining wholemount immunohistochemical labeling of fiber bundles (acetylated tubulin) and neuropils (synapsin) with digital 3D reconstruction using the TrakEM2 software package. Upon comparing this anatomical dataset with the published work in Drosophila melanogaster, we confirm an overall high degree of conservation. Fiber tracts and neuropil fascicles, which can be visualized by global neuronal antibodies like antiacetylated tubulin in all invertebrate brains, create a rich anatomical framework to which individual neurons or other regions of interest can be referred to. The framework of a largely conserved pattern allowed us to describe differences between the two species with respect to parameters such as timing of neuron proliferation and maturation. These features likely reflect adaptive changes in developmental timing that govern the change from larval to adult brain.

Browsing Multiple Subjects When the Atlas Adaptation Cannot Be Achieved via a Warping Strategy

Brain mapping studies often need to identify brain structures or functional circuits into a set of individual brains. To this end, multiple atlases have been published to represent such structures based on different modalities, subject sets, and techniques. The mainstream approach to exploit these atlases consists in spatially deforming each individual data onto a given atlas using dense deformation fields, which supposes the existence of a continuous mapping between atlases and individuals. However, this continuity is not always verified, and this "iconic" approach has limits. We present in this study an alternative, complementary, "structural" approach, which consists in extracting structures from the individual data, and comparing them without deformation. A "structural atlas" is thus a collection of annotated individual data with a common structure nomenclature. It may be used to characterize structure shape variability across individuals or species, or to train machine learning systems. This study exhibits Anatomist, a powerful structural 3D visualization software dedicated to building, exploring, and editing structural atlases involving a large number of subjects. It has been developed primarily to decipher the cortical folding variability; cortical sulci vary enormously in both size and shape, and some may be missing or have various topologies, which makes iconic approaches inefficient to study them. We, therefore, had to build structural atlases for cortical sulci, and use them to train sulci identification algorithms. Anatomist can display multiple subject data in multiple views, supports all kinds of neuroimaging data, including compound structural object graphs, handles arbitrary coordinate transformation chains between data, and has multiple display features. It is designed as a programming library in both C++ and Python languages, and may be extended or used to build dedicated custom applications. Its generic design makes all the display and structural aspects used to explore the variability of the cortical folding pattern work in other applications, for instance, to browse axonal fiber bundles, deep nuclei, functional activations, or other kinds of cortical parcellations. Multimodal, multi-individual, or inter-species display is supported, and adaptations to large scale screen walls have been developed. These very original features make it a unique viewer for structural atlas browsing.

A 3D adult zebrafish brain atlas (AZBA) for the digital age

Zebrafish have made significant contributions to our understanding of the vertebrate brain and the neural basis of behavior, earning a place as one of the most widely used model organisms in neuroscience. Their appeal arises from the marriage of low cost, early life transparency, and ease of genetic manipulation with a behavioral repertoire that becomes more sophisticated as animals transition from larvae to adults. To further enhance the use of adult zebrafish, we created the first fully segmented three-dimensional digital adult zebrafish brain atlas (AZBA). AZBA was built by combining tissue clearing, light-sheet fluorescence microscopy, and three-dimensional image registration of nuclear and antibody stains. These images were used to guide segmentation of the atlas into over 200 neuroanatomical regions comprising the entirety of the adult zebrafish brain. As an open source, online (azba.wayne.edu), updatable digital resource, AZBA will significantly enhance the use of adult zebrafish in furthering our understanding of vertebrate brain function in both health and disease.

Effects of Brain Atlases and Machine Learning Methods on the Discrimination of Schizophrenia Patients: A Multimodal MRI Study

Recently, machine learning techniques have been widely applied in discriminative studies of schizophrenia (SZ) patients with multimodal magnetic resonance imaging (MRI); however, the effects of brain atlases and machine learning methods remain largely unknown. In this study, we collected MRI data for 61 first-episode SZ patients (FESZ), 79 chronic SZ patients (CSZ) and 205 normal controls (NC) and calculated 4 MRI measurements, including regional gray matter volume (GMV), regional homogeneity (ReHo), amplitude of low-frequency fluctuation and degree centrality. We systematically analyzed the performance of two classifications (SZ vs NC; FESZ vs CSZ) based on the combinations of three brain atlases, five classifiers, two cross validation methods and 3 dimensionality reduction algorithms. Our results showed that the groupwise whole-brain atlas with 268 ROIs outperformed the other two brain atlases. In addition, the leave-one-out cross validation was the best cross validation method to select the best hyperparameter set, but the classification performances by different classifiers and dimensionality reduction algorithms were quite similar. Importantly, the contributions of input features to both classifications were higher with the GMV and ReHo features of brain regions in the prefrontal and temporal gyri. Furthermore, an ensemble learning method was performed to establish an integrated model, in which classification performance was improved. Taken together, these findings indicated the effects of these factors in constructing effective classifiers for psychiatric diseases and showed that the integrated model has the potential to improve the clinical diagnosis and treatment evaluation of SZ.

Anatomy and function of retinorecipient arborization fields in zebrafish

In 1994, Burrill and Easter described the retinal projections in embryonic and larval zebrafish, introducing the term "arborization fields" (AFs) for the retinorecipient areas. AFs were numbered from 1 to 10 according to their positions along the optic tract. With the exception of AF10 (neuropil of the optic tectum), annotations of AFs remained tentative. Here we offer an update on the likely identities and functions of zebrafish AFs after successfully matching classical neuroanatomy to the digital Max Planck Zebrafish Brain Atlas. In our system, individual AFs are neuropil areas associated with the following nuclei: AF1 with the suprachiasmatic nucleus; AF2 with the posterior parvocellular preoptic nucleus; AF3 and AF4 with the ventrolateral thalamic nucleus; AF4 with the anterior and intermediate thalamic nuclei; AF5 with the dorsal accessory optic nucleus; AF7 with the parvocellular superficial pretectal nucleus; AF8 with the central pretectal nucleus; and AF9d and AF9v with the dorsal and ventral periventricular pretectal nuclei. AF6 is probably part of the accessory optic system. Imaging, ablation, and activation experiments showed contributions of AF5 and potentially AF6 to optokinetic and optomotor reflexes, AF4 to phototaxis, and AF7 to prey detection. AF6, AF8 and AF9v respond to dimming, and AF4 and AF9d to brightening. While few annotations remain tentative, it is apparent that the larval zebrafish visual system is anatomically and functionally continuous with its adult successor and fits the general cyprinid pattern. This study illustrates the synergy created by merging classical neuroanatomy with a cellular-resolution digital brain atlas resource and functional imaging in larval zebrafish.

Spatial Sequencing: A Perspective

Fluorescent spatial sequencing brings next-generation sequencing into a new realm capable of identifying nucleic acids in the cell's natural environment. For the first time, scientists are able to multiplex the assignment of specific locations to hundreds of transcriptional targets and lay the foundation for understanding how genetic changes control the fate of each cell within the tissue microenvironment. In this perspective, we discuss the capabilities of fluorescent spatial sequencing in the context of other spatial imaging technologies and describe how these new technologies offer a data-rich, multiomic solution to many research applications. Fluorescent spatial sequencing has opened options for exploring many fundamental questions in biology, helping us gain a better understanding of cell and tissue development and disease progression.

Automated brain structures segmentation from PET/CT images based on landmark-constrained dual-modality atlas registration

Automated brain structures segmentation in positron emission tomography (PET) images has been widely investigated to help brain disease diagnosis and follow-up. To relieve the burden of a manual definition of volume of interest (VOI), automated atlas-based VOI definition algorithms were developed, but these algorithms mostly adopted a global optimization strategy which may not be particularly accurate for local small structures (especially the deep brain structures). This paper presents a PET/CT-based brain VOI segmentation algorithm combining anatomical atlas, local landmarks, and dual-modality information. The method incorporates local deep brain landmarks detected by the Deep Q-Network (DQN) to constrain the atlas registration process. Dual-modality PET/CT image information is also combined to improve the registration accuracy of the extracerebral contour. We compare our algorithm with the representative brain atlas registration methods based on 86 clinical PET/CT images. The proposed algorithm obtained accurate delineation of brain VOIs with an average Dice similarity score of 0.79, an average surface distance of 0.97 mm (sub-pixel level), and a volume recovery coefficient close to 1. The main advantage of our method is that it optimizes both global-scale brain matching and local-scale small structure alignment around the key landmarks, it is fully automated and produces high-quality parcellation of the brain structures from brain PET/CT images.

Constructing the rodent stereotaxic brain atlas: a survey

The stereotaxic brain atlas is a fundamental reference tool commonly used in the field of neuroscience. Here we provide a brief history of brain atlas development and clarify three key conceptual elements of stereotaxic brain atlasing: brain image, atlas, and stereotaxis. We also refine four technical indices for evaluating the construction of atlases: the quality of staining and labeling, the granularity of delineation, spatial resolution, and the precision of spatial location and orientation. Additionally, we discuss state-of-the-art technologies and their trends in the fields of image acquisition, stereotaxic coordinate construction, image processing, anatomical structure recognition, and publishing: the procedures of brain atlas illustration. We believe that the use of single-cell resolution and micron-level location precision will become a future trend in the study of the stereotaxic brain atlas, which will greatly benefit the development of neuroscience.

Quantitative assessment of inter-individual variability in fMRI-based human brain atlas

Background

Inter-individual variability is an inherent and ineradicable feature of group-level brain atlases that undermines their reliability for clinical and other applications. To date, there have been no reports quantifying inter-individual variability in brain atlases.

Methods

In the present study, we compared inter-individual variability in nine brain atlases by task-based functional magnetic resonance imaging (MRI) mapping of motor and temporal lobe language regions in both cerebral hemispheres. We analyzed complete motor and language task-based fMRI and T1 data for 893 young, healthy subjects in the Human Connectome Project database. Euclidean distances (EDs) between hotspots in specific brain regions were calculated from task-based fMRI and brain atlas data. General linear model parameters were used to investigate the influence of different brain atlases on signal extraction. Finally, the inter-individual variability of ED and extracted signals and interdependence of relevant indicators were statistically evaluated.

Results

We found that inter-individual variability of ED varied across the nine brain atlases (P<0.0001 for motor regions and P<0.0001 for language regions). There was no correlation between parcel number and inter-individual variability in left to right (LtoR; P=0.7959 for motor regions and P=0.2002 for language regions) and right to left (RtoL; P=0.7654 for motor regions and P=0.3544 for language regions) ED; however, LtoR (P≤0.0001) and RtoL (P≤0.0001) inter-individual variability differed according to brain region: the LtoR (P=0.0008) and RtoL (P=0.0004) inter-individual variability was greater for the right hand than for the left hand, the LtoR (P=0.0019) and RtoL (P=0.0179) inter-individual variability was greater for the right language than for the left language, but there was no such difference between the right foot and left foot (LtoR, P=0.2469 and RtoL, P=0.6140). Inter-individual variability in one motor region was positively correlated with mean values in the other three motor regions (left hand, P=0.0145; left foot, P=0.0103; right hand, P=0.1318; right foot, P=0.3785). Inter-individual variability in language region was positively correlated with mean values in the four motor regions (left language, P=0.0422; right language, P=0.0514). Signal extraction for LtoR (P<0.0001) and RtoL (P<0.0001) varied across the nine brain atlases, which also showed differences in inter-individual variability.

Conclusions

These results underscore the importance of quantitatively assessing the inter-individual variability of a brain atlas prior to use, and demonstrate that mapping motor regions by task-based fMRI is an effective method for quantitatively assessing the inter-individual variability in a brain atlas.

Normative Analysis of Individual Brain Differences Based on a Population MRI-Based Atlas of Cynomolgus Macaques

The developmental trajectory of the primate brain varies substantially with aging across subjects. However, this ubiquitous variability between individuals in brain structure is difficult to quantify and has thus essentially been ignored. Based on a large-scale structural magnetic resonance imaging dataset acquired from 162 cynomolgus macaques, we create a species-specific 3D template atlas of the macaque brain, and deploy normative modeling to characterize individual variations of cortical thickness (CT) and regional gray matter volume (GMV). We observed an overall decrease in total GMV and mean CT, and an increase in white matter volume from juvenile to early adult. Specifically, CT and regional GMV were greater in prefrontal and temporal cortices relative to early unimodal areas. Age-dependent trajectories of thickness and volume for each cortical region revealed an increase in the medial temporal lobe, and decreases in all other regions. A low percentage of highly individualized deviations of CT and GMV were identified (0.0021%, 0.0043%, respectively, P < 0.05, false discovery rate [FDR]-corrected). Our approach provides a natural framework to parse individual neuroanatomical differences for use as a reference standard in macaque brain research, potentially enabling inferences regarding the degree to which behavioral or symptomatic variables map onto brain structure in future disease studies.

A Systematic Approach to Dissection of the Equine Brain-Evaluation of a Species-Adapted Protocol for Beginners and Experts

Introduction of new imaging modalities for the equine brain have refocused attention on the horse as a natural model for ethological, neuroanatomical, and neuroscientific investigations. As opposed to imaging studies, strategies for equine neurodissection still lack a structured approach, standardization and reproducibility. In contrast to other species, where adapted protocols for sampling have been published, no comparable guideline is currently available for equids. Hence, we developed a species-specific slice protocol for whole brain vs. hemispheric dissection and tested its applicability and practicability in the field, as well as its neuroanatomical accuracy and reproducibility. Dissection steps are concisely described and depicted by schematic illustrations, photographs and instructional videos. Care was taken to show the brain in relation to the raters' hands, cutting devices and bench surface. Guidance is based on a minimum of external anatomical landmarks followed by geometric instructions that led to procurement of 14 targeted slabs. The protocol was performed on 55 formalin-fixed brains by three groups of investigators with different neuroanatomical skills. Validation of brain dissection outcomes addressed the aptitude of slabs for neuroanatomical studies as opposed to simplified routine diagnostic purposes. Across all raters, as much as 95.2% of slabs were appropriate for neuroanatomical studies, and 100% of slabs qualified for a routine diagnostic setting. Neither autolysis nor subfixation significantly affected neuroanatomical accuracy score, while a significant negative effect was observed with brain extraction artifacts. Procedure times ranged from 14 to 66 min and reached a mean duration of 23.25 ± 7.93 min in the last of five trials in inexperienced raters vs. 16 ± 2.83 min in experts, while acceleration of the dissection did not negatively impact neuroanatomical accuracy. This protocol, derived analogously to the consensus report of the International Veterinary Epilepsy Task Force in dogs and cats, allows for systematic, quick and easy dissection of the equine brain, even for inexperienced investigators. Obtained slabs feature virtually all functional subcompartments at suitable planes for both diagnostic and neuroscientific investigations and complement the data obtained from imaging studies. The instructive protocol and brain dissection videos are available in Supplementary Material.

BrainWiki-A Wiki-Style, User Driven, Comparative Brain Anatomy Tool

The mouse is the most important animal model within neuroscientific research, a position strengthened by the wide-spread use of transgenic mouse models. Discoveries in animals are followed by corroboration in humans, and the interchange between these fields of research is essential to our understanding of the human brain. With the advent of advanced technologies such as single-cell transcriptomics, epigenetic profiling and diffusion MRI, many prominent research institutes and collaborations have emerged, aiming to construct complete human or mouse brain atlases with data on gene expression, connectivity and cell types. These initiatives are indispensable resources, but frequently require extensive, time-consuming development, and rely on updates by the provider. They often come in the shape of applications which require practice or prior technical know-how. Importantly, none of them place the human and the mouse brain next to each other to allow for immediate comparison. We present BrainWiki, a user-friendly, web-based atlas that links the human and the mouse brain together, side-by-side. The platform gives the user a simple overview of brain anatomy along with published articles relating to each brain region that allows the user to delve deeper into the current state of research concerning circuitry, brain functions and pathology. The website relies on interactivity and supports user contributions resulting in a dynamic website that evolves at the pace of neuroscience. It is designed to allow for constant updates and new features in the future which will contain data such as gene expression and neuronal cell types.

MonkeyCBP: A Toolbox for Connectivity-Based Parcellation of Monkey Brain

Non-human primate models are widely used in studying the brain mechanism underlying brain development, cognitive functions, and psychiatric disorders. Neuroimaging techniques, such as magnetic resonance imaging, play an important role in the examinations of brain structure and functions. As an indispensable tool for brain imaging data analysis, brain atlases have been extensively investigated, and a variety of versions constructed. These atlases diverge in the criteria based on which they are plotted. The criteria range from cytoarchitectonic features, neurotransmitter receptor distributions, myelination fingerprints, and transcriptomic patterns to structural and functional connectomic profiles. Among them, brainnetome atlas is tightly related to brain connectome information and built by parcellating the brain on the basis of the anatomical connectivity profiles derived from structural neuroimaging data. The pipeline for building the brainnetome atlas has been published as a toolbox named ATPP (A Pipeline for Automatic Tractography-Based Brain Parcellation). In this paper, we present a variation of ATPP, which is dedicated to monkey brain parcellation, to address the significant differences in the process between the two species. The new toolbox, MonkeyCBP, has major alterations in three aspects: brain extraction, image registration, and validity indices. By parcellating two different brain regions (posterior cingulate cortex) and (frontal pole) of the rhesus monkey, we demonstrate the efficacy of these alterations. The toolbox has been made public (https://github.com/bheAI/MonkeyCBP_CLI, https://github.com/bheAI/MonkeyCBP_GUI). It is expected that the toolbox can benefit the non-human primate neuroimaging community with high-throughput computation and low labor involvement.

Relationship between Brain Morphology and Life History in Four Bottom-Dwelling Gobiids

In terrestrial vertebrates, the hippocampus plays a major role in spatial cognition. Recent developmental, anatomical, and histological studies suggest that the ventral region of the lateral part of the dorsal telencephalic area (Dlv) in teleost fishes is homologous to the hippocampus in terrestrial vertebrates. We hypothesized that fish species with higher spatial cognitive demands have a more highly developed Dlv compared to closely related species with relatively lower spatial cognitive demands. The fishes selected for this study were Favonigobius gymnauchen, Istigobius hoshinonis, Tridentiger trigonocephalus, and Chaenogobius annularis; all are bottom-dwelling gobiid species found in habitats that vary with respect to their spatial complexity. Volumetric analysis of the telencephalic subregions, including the Dlv, and other major brain regions showed that species from stable rocky areas had a larger Dlv than species from relatively homogenous sandy/ muddy environments. These findings support the hypothesis that the teleost Dlv is homologous to the hippocampus in terrestrial vertebrates, and that the relative development of these areas is positively correlated with spatial cognitive demand in animals.

Optimizing Connectivity-Driven Brain Parcellation Using Ensemble Clustering

This work addresses the problem of constructing a unified, topologically optimal connectivity-based brain atlas. The proposed approach aggregates an ensemble partition from individual parcellations without label agreement, providing a balance between sufficiently flexible individual parcellations and intuitive representation of the average topological structure of the connectome. The methods exploit a previously proposed dense connectivity representation, first performing graph-based hierarchical parcellation of individual brains, and subsequently aggregating the individual parcellations into a consensus parcellation. The search for consensus—based on the hard ensemble (HE) algorithm—approximately minimizes the sum of cluster membership distances, effectively estimating a pseudo-Karcher mean of individual parcellations. Computational stability, graph structure preservation, and biological relevance of the simplified representation resulting from the proposed parcellation are assessed on the Human Connectome Project data set. These aspects are assessed using (1) edge weight distribution divergence with respect to the dense connectome representation, (2) interhemispheric symmetry, (3) network characteristics' stability and agreement with respect to individually and anatomically parcellated networks, and (4) performance of the simplified connectome in a biological sex classification task. Ensemble parcellation was found to be highly stable with respect to subject sampling, outperforming anatomical atlases and other connectome-based parcellations in classification as well as preserving global connectome properties. The HE-based parcellation also showed a degree of symmetry comparable with anatomical atlases and a high degree of spatial contiguity without using explicit priors.

ZEBrA: Zebra finch Expression Brain Atlas-A resource for comparative molecular neuroanatomy and brain evolution studies

An in-depth understanding of the genetics and evolution of brain function and behavior requires a detailed mapping of gene expression in functional brain circuits across major vertebrate clades. Here we present the Zebra finch Expression Brain Atlas (ZEBrA; www.zebrafinchatlas.org, RRID: SCR_012988), a web-based resource that maps the expression of genes linked to a broad range of functions onto the brain of zebra finches. ZEBrA is a first of its kind gene expression brain atlas for a bird species and a first for any sauropsid. ZEBrA's >3,200 high-resolution digital images of in situ hybridized sections for ~650 genes (as of June 2019) are presented in alignment with an annotated histological atlas and can be browsed down to cellular resolution. An extensive relational database connects expression patterns to information about gene function, mouse expression patterns and phenotypes, and gene involvement in human diseases and communication disorders. By enabling brain-wide gene expression assessments in a bird, ZEBrA provides important substrates for comparative neuroanatomy and molecular brain evolution studies. ZEBrA also provides unique opportunities for linking genetic pathways to vocal learning and motor control circuits, as well as for novel insights into the molecular basis of sex steroids actions, brain dimorphisms, reproductive and social behaviors, sleep function, and adult neurogenesis, among many fundamental themes.

Improving model-based functional near-infrared spectroscopy analysis using mesh-based anatomical and light-transport models

Significance: Functional near-infrared spectroscopy (fNIRS) has become an important research tool in studying human brains. Accurate quantification of brain activities via fNIRS relies upon solving computational models that simulate the transport of photons through complex anatomy. Aim: We aim to highlight the importance of accurate anatomical modeling in the context of fNIRS and propose a robust method for creating high-quality brain/full-head tetrahedral mesh models for neuroimaging analysis. Approach: We have developed a surface-based brain meshing pipeline that can produce significantly better brain mesh models, compared to conventional meshing techniques. It can convert segmented volumetric brain scans into multilayered surfaces and tetrahedral mesh models, with typical processing times of only a few minutes and broad utilities, such as in Monte Carlo or finite-element-based photon simulations for fNIRS studies. Results: A variety of high-quality brain mesh models have been successfully generated by processing publicly available brain atlases. In addition, we compare three brain anatomical models-the voxel-based brain segmentation, tetrahedral brain mesh, and layered-slab brain model-and demonstrate noticeable discrepancies in brain partial pathlengths when using approximated brain anatomies, ranging between - 1.5 % to 23% with the voxelated brain and 36% to 166% with the layered-slab brain. Conclusion: The generation and utility of high-quality brain meshes can lead to more accurate brain quantification in fNIRS studies. Our open-source meshing toolboxes "Brain2Mesh" and "Iso2Mesh" are freely available at http://mcx.space/brain2mesh.

Cognitive and Non-Cognitive Outcomes Associated with Student Engagement in a Novel Brain Chemoarchitecture Mapping Course-Based Undergraduate Research Experience

Course-based undergraduate research experiences (CUREs) engage emerging scholars in the authentic process of scientific discovery, and foster their development of content knowledge, motivation, and persistence in the science, technology, engineering, and mathematics (STEM) disciplines. Importantly, authentic research courses simultaneously offer investigators unique access to an extended population of students who receive education and mentoring in conducting scientifically relevant investigations and who are thus able to contribute effort toward big-data projects. While this paradigm benefits fields in neuroscience, such as atlas-based brain mapping of nerve cells at the tissue level, there are few documented cases of such laboratory courses offered in the domain. Here, we describe a curriculum designed to address this deficit, evaluate the scientific merit of novel student-produced brain atlas maps of immunohistochemically-identified nerve cell populations for the rat brain, and assess shifts in science identity, attitudes, and science communication skills of students engaged in the introductory-level Brain Mapping and Connectomics (BM&C) CURE. BM&C students reported gains in research and science process skills following participation in the course. Furthermore, BM&C students experienced a greater sense of science identity, including a greater likelihood to discuss course activities with non-class members compared to their non-CURE counterparts. Importantly, evaluation of student-generated brain atlas maps indicated that the course enabled students to produce scientifically valid products and make new discoveries to advance the field of neuroanatomy. Together, these findings support the efficacy of the BM&C course in addressing the relatively esoteric demands of chemoarchitectural brain mapping.

Individualized Cortical Parcellation Based on Diffusion MRI Tractography

The spatial topological properties of cortical regions vary across individuals. Connectivity-based functional and anatomical cortical mapping in individuals will facilitate research on structure-function relationships. However, individual-specific cortical topographic properties derived from anatomical connectivity are less explored than those based on functional connectivity. We aimed to develop a novel individualized anatomical connectivity-based parcellation framework and investigate individual differences in spatial topographic features of cortical regions using diffusion magnetic resonance imaging (dMRI) tractography. Using a high-quality, repeated-session dMRI dataset (42 subjects, 2 sessions per subject), cortical parcels were derived through in vivo anatomical connectivity-based parcellation. These individual-specific parcels demonstrated good within-individual reproducibility and reflected interindividual differences in anatomical brain organization. Connectivity in these individual-specific parcels was significantly more homogeneous than that based on the group atlas. We found that the position, size, and topography of these anatomical parcels were highly variable across individuals and demonstrated nonredundant information about individual differences. Finally, we found that intersubject variability in anatomical connectivity was correlated with the diversity of anatomical connectivity patterns. Overall, we identified cortical parcels that show homogeneous anatomical connectivity patterns. These parcels displayed marked intersubject spatial variability, which may be used in future functional studies to reveal structure-function relationships in the human brain.

An Adult Brain Atlas Reveals Broad Neuroanatomical Changes in Independently Evolved Populations of Mexican Cavefish

A shift in environmental conditions impacts the evolution of complex developmental and behavioral traits. The Mexican cavefish, Astyanax mexicanus, is a powerful model for examining the evolution of development, physiology, and behavior because multiple cavefish populations can be compared to an extant, ancestral-like surface population of the same species. Many behaviors have diverged in cave populations of A. mexicanus, and previous studies have shown that cavefish have a loss of sleep, reduced stress, an absence of social behaviors, and hyperphagia. Despite these findings, surprisingly little is known about the changes in neuroanatomy that underlie these behavioral phenotypes. Here, we use serial sectioning to generate brain atlases of surface fish and three independent cavefish populations. Volumetric reconstruction of serial-sectioned brains confirms convergent evolution on reduced optic tectum volume in all cavefish populations tested. In addition, we quantified volumes of specific neuroanatomical loci within several brain regions that have previously been implicated in behavioral regulation, including the hypothalamus, thalamus, and habenula. These analyses reveal an enlargement of the hypothalamus in all cavefish populations relative to surface fish, as well as subnuclei-specific differences within the thalamus and prethalamus. Taken together, these analyses support the notion that changes in environmental conditions are accompanied by neuroanatomical changes in brain structures associated with behavior. This atlas provides a resource for comparative neuroanatomy of additional brain regions and the opportunity to associate brain anatomy with evolved changes in behavior.

A probabilistic atlas of the human motion complex built from large-scale functional localizer data

Accurate motion perception is critical to dealing with the changing dynamics of our visual world. A cluster known as the human MT+ complex (hMT+) has been identified as a core region involved in motion perception. Several atlases defined based on cytoarchitecture, retinotopy, connectivity, and multimodal features include homologs of the hMT+. However, an hMT+ atlas defined directly based on this region's response for motion is still lacking. Here, we identified the hMT+ based on motion responses from functional magnetic resonance imaging (fMRI) localizer data in 509 participants and then built a probabilistic atlas of the hMT+. As a result, four main findings were revealed. First, the hMT+ showed large interindividual variability across participants. Second, the atlases stabilized when the number of participants used to build the atlas was more than 100. Third, the functional hMT+ showed good agreement with the hMT+ atlases built based on cytoarchitecture, retinotopy, and connectivity, suggesting a good structural-functional correspondence. Fourth, tests on multiple fMRI data sets acquired from independent participants, imaging parameters and paradigms revealed that the functional hMT+ showed higher sensitivity than all other atlases in ROI analysis except that connectivity and multimodal hMT+ atlases in the left hemisphere could infrequently attain comparable sensitivity to the functional atlas. Taken together, our findings reveal the benefit of using large-scale functional localizer data to build a reliable and representative hMT+ atlas. Our atlas is freely available for download; it can be used to localize the hMT+ in individual participants when functional localizer data are not available.

Brain-wide cellular resolution imaging of Cre transgenic zebrafish lines for functional circuit-mapping

Decoding the functional connectivity of the nervous system is facilitated by transgenic methods that express a genetically encoded reporter or effector in specific neurons; however, most transgenic lines show broad spatiotemporal and cell-type expression. Increased specificity can be achieved using intersectional genetic methods which restrict reporter expression to cells that co-express multiple drivers, such as Gal4 and Cre. To facilitate intersectional targeting in zebrafish, we have generated more than 50 new Cre lines, and co-registered brain expression images with the Zebrafish Brain Browser, a cellular resolution atlas of 264 transgenic lines. Lines labeling neurons of interest can be identified using a web-browser to perform a 3D spatial search (zbbrowser.com). This resource facilitates the design of intersectional genetic experiments and will advance a wide range of precision circuit-mapping studies.

Automated Generation of Radiologic Descriptions on Brain Volume Changes From T1-Weighted MR Images: Initial Assessment of Feasibility

Purpose: To examine the feasibility and potential difficulties of automatically generating radiologic reports (RRs) to articulate the clinically important features of brain magnetic resonance (MR) images.

Materials and Methods: We focused on examining brain atrophy by using magnetization-prepared rapid gradient-echo (MPRAGE) images. The technology was based on multi-atlas whole-brain segmentation that identified 283 structures, from which larger superstructures were created to represent the anatomic units most frequently used in RRs. Through two layers of data-reduction filters, based on anatomic and clinical knowledge, raw images (~10 MB) were converted to a few kilobytes of human-readable sentences. The tool was applied to images from 92 patients with memory problems, and the results were compared to RRs independently produced by three experienced radiologists. The mechanisms of disagreement were investigated to understand where machine–human interface succeeded or failed.

Results: The automatically generated sentences had low sensitivity (mean: 24.5%) and precision (mean: 24.9%) values; these were significantly lower than the inter-rater sensitivity (mean: 32.7%) and precision (mean: 32.2%) of the radiologists. The causes of disagreement were divided into six error categories: mismatch of anatomic definitions (7.2 ± 9.3%), data-reduction errors (11.4 ± 3.9%), translator errors (3.1 ± 3.1%), difference in the spatial extent of used anatomic terms (8.3 ± 6.7%), segmentation quality (9.8 ± 2.0%), and threshold for sentence-triggering (60.2 ± 16.3%).

Conclusion: These error mechanisms raise interesting questions about the potential of automated report generation and the quality of image reading by humans. The most significant discrepancy between the human and automatically generated RRs was caused by the sentence-triggering threshold (the degree of abnormality), which was fixed to z-score >2.0 for the automated generation, while the thresholds by radiologists varied among different anatomical structures.

Atlas of the telencephalon based on cytoarchitecture, neurochemical markers, and gene expressions in Rhinogobius flumineus [Mizuno, 1960]

Gobiida is a basal subseries of percomorphs in teleost fishes, holding a useful position for comparisons with other orders of Percomorpha as well as other cohort of teleosts. Here, we describe a telencephalic atlas of a Gobiida species Rhinogobius flumineus (Mizuno, Memoirs of the College of Science, University of Kyoto, Series B: Biology, 1960; 27, 3), based on cytoarchitectural observations, combined with analyses of the distribution patterns of neurochemical markers and transcription factors. The telencephalon of R. flumineus shows a number of features distinct from those of other teleosts. Among others, the followings were of special note. (a) The lateral part of dorsal telencephalon (Dl), which is known as a visual center in other teleosts, is composed of as many as seven regions, some of which are conspicuous, circumscribed by cell plates. These subdivisions of the Dl can be differentiated clearly by differential soma size and color with Nissl-staining, and distribution patterns of neural markers. (b) Cell populations continuous with the ventral region of dorsal part of ventral telencephalon (vVd) exhibit extensive dimension. Especially, portion 1 of the central part of ventral telencephalon appears to represent a cell population laterally translocated from the vVd, forming a large cluster of small cells that penetrate deep into the central part of dorsal telencephalon. (c) The magnocellular subdivision of dorsal part of dorsal telencephalon (Ddmg) contains not only large cells but also vglut2a-positive clusters of small cells that cover a wide range of the caudal Ddmg. Such clusters of small cells have not been observed in the Ddmg of other teleosts.

Navigating the Murine Brain: Toward Best Practices for Determining and Documenting Neuroanatomical Locations in Experimental Studies

In experimental neuroscientific research, anatomical location is a key attribute of experimental observations and critical for interpretation of results, replication of findings, and comparison of data across studies. With steadily rising numbers of publications reporting basic experimental results, there is an increasing need for integration and synthesis of data. Since comparison of data relies on consistently defined anatomical locations, it is a major concern that practices and precision in the reporting of location of observations from different types of experimental studies seem to vary considerably. To elucidate and possibly meet this challenge, we have evaluated and compared current practices for interpreting and documenting the anatomical location of measurements acquired from murine brains with different experimental methods. Our observations show substantial differences in approach, interpretation and reproducibility of anatomical locations among reports of different categories of experimental research, and strongly indicate that ambiguous reports of anatomical location can be attributed to missing descriptions. Based on these findings, we suggest a set of minimum requirements for documentation of anatomical location in experimental murine brain research. We furthermore demonstrate how these requirements have been applied in the EU Human Brain Project to optimize workflows for integration of heterogeneous data in common reference atlases. We propose broad adoption of some straightforward steps for improving the precision of location metadata and thereby facilitating interpretation, reuse and integration of data.

MultiMap: A Tool to Automatically Extract and Analyse Spatial Microscopic Data From Large Stacks of Confocal Microscopy Images

The development of 3D visualization and reconstruction methods to analyse microscopic structures at different levels of resolutions is of great importance to define brain microorganization and connectivity. MultiMap is a new tool that allows the visualization, 3D segmentation and quantification of fluorescent structures selectively in the neuropil from large stacks of confocal microscopy images. The major contribution of this tool is the posibility to easily navigate and create regions of interest of any shape and size within a large brain area that will be automatically 3D segmented and quantified to determine the density of puncta in the neuropil. As a proof of concept, we focused on the analysis of glutamatergic and GABAergic presynaptic axon terminals in the mouse hippocampal region to demonstrate its use as a tool to provide putative excitatory and inhibitory synaptic maps. The segmentation and quantification method has been validated over expert labeled images of the mouse hippocampus and over two benchmark datasets, obtaining comparable results to the expert detections.

A Spotlight on Bridging Microscale and Macroscale Human Brain Architecture

We place a spotlight on the emerging trend of jointly studying the micro- and macroscale organization of nervous systems. We discuss the pioneering studies of Ding et al. (2016) and Glasser et al. (2016) in the context of growing efforts to combine and integrate multiple features of brain organization into a multi-modal and multi-scale examination of the human brain.

Comprehensive cellular-resolution atlas of the adult human brain

Detailed anatomical understanding of the human brain is essential for unraveling its functional architecture, yet current reference atlases have major limitations such as lack of whole‐brain coverage, relatively low image resolution, and sparse structural annotation. We present the first digital human brain atlas to incorporate neuroimaging, high‐resolution histology, and chemoarchitecture across a complete adult female brain, consisting of magnetic resonance imaging (MRI), diffusion‐weighted imaging (DWI), and 1,356 large‐format cellular resolution (1 µm/pixel) Nissl and immunohistochemistry anatomical plates. The atlas is comprehensively annotated for 862 structures, including 117 white matter tracts and several novel cyto‐ and chemoarchitecturally defined structures, and these annotations were transferred onto the matching MRI dataset. Neocortical delineations were done for sulci, gyri, and modified Brodmann areas to link macroscopic anatomical and microscopic cytoarchitectural parcellations. Correlated neuroimaging and histological structural delineation allowed fine feature identification in MRI data and subsequent structural identification in MRI data from other brains. This interactive online digital atlas is integrated with existing Allen Institute for Brain Science gene expression atlases and is publicly accessible as a resource for the neuroscience community. J. Comp. Neurol. 524:3127–3481, 2016. © 2016 The Authors The Journal of Comparative Neurology Published by Wiley Periodicals, Inc.

Catlas: An magnetic resonance imaging-based three-dimensional cortical atlas and tissue probability maps for the domestic cat (Felis catus)

Brain atlases play an important role in effectively communicating results from neuroimaging studies in a standardized coordinate system. Furthermore, brain atlases extend analysis of functional magnetic resonance imaging (MRI) data by delineating regions of interest over which to evaluate the extent of functional activation as well as measures of inter-regional connectivity. Here, we introduce a three-dimensional atlas of the cat cerebral cortex based on established cytoarchitectonic and electrophysiological findings. In total, 71 cerebral areas were mapped onto the gray matter (GM) of an averaged T1-weighted structural MRI acquired at 7 T from eight adult domestic cats. In addition, a nonlinear registration procedure was used to generate a common template brain as well as GM, white matter, and cerebral spinal fluid tissue probability maps to facilitate tissue segmentation as part of the standard preprocessing pipeline for MRI data analysis. The atlas and associated files can also be used for planning stereotaxic surgery and for didactic purposes.

Macroanatomical Landmarks Featuring Junctions of Major Sulci and Fissures and Scalp Landmarks Based on the International 10-10 System for Analyzing Lateral Cortical Development of Infants

The topographic relationships between the macroanatomical structure of the lateral cortex, including sulci and fissures, and anatomical landmarks on the external surface of the head are known to be consistent. This allows the coregistration of EEG electrodes or functional near-infrared spectroscopy over the scalp with underlying cortical regions. However, limited information is available as to whether the topographic relationships are maintained in rapidly developing infants, whose brains and heads exhibit drastic growth. We used MRIs of infants ranging in age from 3 to 22 months old, and identified 20 macroanatomical landmarks, featuring the junctions of major sulci and fissures, as well as cranial landmarks and virtually determined positions of the international 10-20 and 10-10 systems. A Procrustes analysis revealed developmental trends in changes of shape in both the cortex and head. An analysis of Euclidian distances between selected pairs of cortical landmarks at standard stereotactic coordinates showed anterior shifts of the relative positions of the premotor and parietal cortices with age. Finally, cortical landmark positions and their spatial variability were compared with 10-10 landmark positions. The results indicate that variability in the distribution of each macroanatomical landmark was much smaller than the pitch of the 10-10 landmarks. This study demonstrates that the scalp-based 10-10 system serves as a good frame of reference in infants not only for assessing the development of the macroanatomy of the lateral cortical structure, but also for functional studies of cortical development using transcranial modalities such as EEG and fNIRS.

ATPP: A Pipeline for Automatic Tractography-Based Brain Parcellation

There is a longstanding effort to parcellate brain into areas based on micro-structural, macro-structural, or connectional features, forming various brain atlases. Among them, connectivity-based parcellation gains much emphasis, especially with the considerable progress of multimodal magnetic resonance imaging in the past two decades. The Brainnetome Atlas published recently is such an atlas that follows the framework of connectivity-based parcellation. However, in the construction of the atlas, the deluge of high resolution multimodal MRI data and time-consuming computation poses challenges and there is still short of publically available tools dedicated to parcellation. In this paper, we present an integrated open source pipeline (https://www.nitrc.org/projects/atpp), named Automatic Tractography-based Parcellation Pipeline (ATPP) to realize the framework of parcellation with automatic processing and massive parallel computing. ATPP is developed to have a powerful and flexible command line version, taking multiple regions of interest as input, as well as a user-friendly graphical user interface version for parcellating single region of interest. We demonstrate the two versions by parcellating two brain regions, left precentral gyrus and middle frontal gyrus, on two independent datasets. In addition, ATPP has been successfully utilized and fully validated in a variety of brain regions and the human Brainnetome Atlas, showing the capacity to greatly facilitate brain parcellation.

Brain Vascular Imaging Techniques

Recent major improvements in a number of imaging techniques now allow for the study of the brain in ways that could not be considered previously. Researchers today have well-developed tools to specifically examine the dynamic nature of the blood vessels in the brain during development and adulthood; as well as to observe the vascular responses in disease situations in vivo. This review offers a concise summary and brief historical reference of different imaging techniques and how these tools can be applied to study the brain vasculature and the blood-brain barrier integrity in both healthy and disease states. Moreover, it offers an overview on available transgenic animal models to study vascular biology and a description of useful online brain atlases.

The Brain of the Archerfish Toxotes chatareus: A Nissl-Based Neuroanatomical Atlas and Catecholaminergic/Cholinergic Systems

Over recent years, the seven-spot archerfish (Toxotes chatareus) has emerged as a new model for studies in visual and behavioral neuroscience thanks to its unique hunting strategy. Its natural ability to spit at insects outside of water can be used in the laboratory for well controlled behavioral experiments where the fish is trained to aim at targets on a screen. The need for a documentation of the neuroanatomy of this animal became critical as more research groups use it as a model. Here we present an atlas of adult T. chatareus specimens caught in the wild in South East Asia. The atlas shows representative sections of the brain and specific structures revealed by a classic Nissl staining as well as corresponding schematic drawings. Additional immunostainings for catecholaminergic and cholinergic systems were conducted to corroborate the identification of certain nuclei and the data of a whole brain scanner is available online. We describe the general features of the archerfish brain as well as its specificities, especially for the visual system and compare the neuroanatomy of the archerfish with other teleosts. This atlas of the archerfish brain shows all levels of the neuraxis and intends to provide a solid basis for further neuroscientific research on T. chatareus, in particular electrophysiological studies.

The Human Brainnetome Atlas: A New Brain Atlas Based on Connectional Architecture

The human brain atlases that allow correlating brain anatomy with psychological and cognitive functions are in transition from ex vivo histology-based printed atlases to digital brain maps providing multimodal in vivo information. Many current human brain atlases cover only specific structures, lack fine-grained parcellations, and fail to provide functionally important connectivity information. Using noninvasive multimodal neuroimaging techniques, we designed a connectivity-based parcellation framework that identifies the subdivisions of the entire human brain, revealing the in vivo connectivity architecture. The resulting human Brainnetome Atlas, with 210 cortical and 36 subcortical subregions, provides a fine-grained, cross-validated atlas and contains information on both anatomical and functional connections. Additionally, we further mapped the delineated structures to mental processes by reference to the BrainMap database. It thus provides an objective and stable starting point from which to explore the complex relationships between structure, connectivity, and function, and eventually improves understanding of how the human brain works. The human Brainnetome Atlas will be made freely available for download at http://atlas.brainnetome.org, so that whole brain parcellations, connections, and functional data will be readily available for researchers to use in their investigations into healthy and pathological states.