Gene expression in the primate orbitofrontal cortex related to anxious temperament.

Anxiety disorders are among the most prevalent psychiatric disorders, causing significant suffering and disability. Relative to other psychiatric disorders, anxiety disorders tend to emerge early in life, supporting the importance of developmental mechanisms in their emergence and maintenance. Behavioral inhibition (BI) is a temperament that emerges early in life and, when stable and extreme, is linked to an increased risk for the later development of anxiety disorders and other stress-related psychopathology. Understanding the neural systems and molecular mechanisms underlying this dispositional risk could provide insight into treatment targets for anxiety disorders. Nonhuman primates (NHPs) have an anxiety-related temperament, called anxious temperament (AT), that is remarkably similar to BI in humans, facilitating the design of highly translational models for studying the early risk for stress-related psychopathology. Because of the recent evolutionary divergence between humans and NHPs, many of the anxiety-related brain regions that contribute to psychopathology are highly similar in terms of their structure and function, particularly with respect to the prefrontal cortex. The orbitofrontal cortex plays a critical role in the flexible encoding and regulation of threat responses, in part through connections with subcortical structures like the amygdala. Here, we explore individual differences in the transcriptional profile of cells within the region, using laser capture microdissection and single nuclear sequencing, providing insight into the molecules underlying individual differences in AT-related function of the pOFC, with a particular focus on previously implicated cellular systems, including neurotrophins and glucocorticoid signaling.

Real-time trajectory guide tracking for intraoperative MRI-guided neurosurgery.

PURPOSE: In current intraoperative MRI (IMRI) methods, an iterative approach is used to aim trajectory guides at intracerebral targets: image MR-visible features, determine current aim by fitting model to image, manipulate device, repeat. Infrequent updates are produced by such methods, compared to rapid optically tracked stereotaxy used in the operating room. Our goal was to develop a real-time interactive IMRI method for aiming. METHODS: The current trajectory was computed from two points along the guide's central axis, rather than by imaging the entire device. These points were determined by correlating one-dimensional spokes from a radial sequence with the known cross-sectional projection of the guide. The real-time platform RTHawk was utilized to control MR sequences and data acquisition. On-screen updates were viewed by the operator while simultaneously manipulating the guide to align it with the planned trajectory. Accuracy was quantitated in a phantom, and in vivo validation was demonstrated in nonhuman primates undergoing preclinical gene ( n = 5 $$ n=5 $$ ) and cell ( n = 4 $$ n=4 $$ ) delivery surgeries. RESULTS: Updates were produced at 5 Hz In 10 phantom experiments at a depth of 48 mm, the cannula tip was placed with radial error of (min, mean, max) = (0.16, 0.29, 0.68) mm. Successful in vivo delivery of payloads to all 14 targets was demonstrated across nine surgeries with depths of (min, mean, max) = (33.3, 37.9, 42.5) mm. CONCLUSION: A real-time interactive update rate was achieved, reducing operator fatigue without compromising accuracy. Qualitative interpretation of images during aiming was rendered unnecessary by objectively computing device alignment.

Longitudinal assessment of early-life white matter development with quantitative relaxometry in nonhuman primates.

Alterations in white matter (WM) development are associated with many neuropsychiatric and neurodevelopmental disorders. Most MRI studies examining WM development employ diffusion tensor imaging (DTI), which relies on estimating diffusion patterns of water molecules as a reflection of WM microstructure. Quantitative relaxometry, an alternative method for characterizing WM microstructural changes, is based on molecular interactions associated with the magnetic relaxation of protons. In a longitudinal study of 34 infant non-human primates (NHP) (Macaca mulatta) across the first year of life, we implement a novel, high-resolution, T1-weighted MPnRAGE sequence to examine WM trajectories of the longitudinal relaxation rate (qR1) in relation to DTI metrics and gestational age at scan. To the best of our knowledge, this is the first study to assess developmental WM trajectories in NHPs using quantitative relaxometry and the first to directly compare DTI and relaxometry metrics during infancy. We demonstrate that qR1 exhibits robust logarithmic growth, unfolding in a posterior-anterior and medial-lateral fashion, similar to DTI metrics. On a within-subject level, DTI metrics and qR1 are highly correlated, but are largely unrelated on a between-subject level. Unlike DTI metrics, gestational age at birth (time in utero) is a strong predictor of early postnatal qR1 levels. Whereas individual differences in DTI metrics are maintained across the first year of life, this is not the case for qR1. These results point to the similarities and differences in using quantitative relaxometry and DTI in developmental studies, providing a basis for future studies to characterize the unique processes that these measures reflect at the cellular and molecular level.

Evidence in primates supporting the use of chemogenetics for the treatment of human refractory neuropsychiatric disorders.

Non-human primate (NHP) models are essential for developing and translating new treatments that target neural circuit dysfunction underlying human psychopathology. As a proof-of-concept for treating neuropsychiatric disorders, we used a NHP model of pathological anxiety to investigate the feasibility of decreasing anxiety by chemogenetically (DREADDs [designer receptors exclusively activated by designer drugs]) reducing amygdala neuronal activity. Intraoperative MRI surgery was used to infect dorsal amygdala neurons with AAV5-hSyn-HA-hM4Di in young rhesus monkeys. In vivo microPET studies with [11C]-deschloroclozapine and postmortem autoradiography with [3H]-clozapine demonstrated selective hM4Di binding in the amygdala, and neuronal expression of hM4Di was confirmed with immunohistochemistry. Additionally, because of its high affinity for DREADDs, and its approved use in humans, we developed an individualized, low-dose clozapine administration strategy to induce DREADD-mediated amygdala inhibition. Compared to controls, clozapine selectively decreased anxiety-related freezing behavior in the human intruder paradigm in hM4Di-expressing monkeys, while coo vocalizations and locomotion were unaffected. These results are an important step in establishing chemogenetic strategies for patients with refractory neuropsychiatric disorders in which amygdala alterations are central to disease pathophysiology.

Spatiotemporal dynamics of nonhuman primate white matter development during the first year of life.

White matter (WM) development early in life is a critical component of brain development that facilitates the coordinated function of neuronal pathways. Additionally, alterations in WM have been implicated in various neurodevelopmental disorders, including psychiatric disorders. Because of the need to understand WM development in the weeks immediately following birth, we characterized changes in WM microstructure throughout the postnatal macaque brain during the first year of life. This is a period in primates during which genetic, developmental, and environmental factors may have long-lasting impacts on WM microstructure. Studies in nonhuman primates (NHPs) are particularly valuable as a model for understanding human brain development because of their evolutionary relatedness to humans. Here, 34 rhesus monkeys (23 females, 11 males) were imaged longitudinally at 3, 7, 13, 25, and 53 weeks of age with T1-weighted (MPnRAGE) and diffusion tensor imaging (DTI). With linear mixed-effects (LME) modeling, we demonstrated robust logarithmic growth in FA, MD, and RD trajectories extracted from 18 WM tracts across the brain. Estimated rate of change curves for FA, MD, and RD exhibited an initial 10-week period of exceedingly rapid WM development, followed by a precipitous decline in growth rates. K-means clustering of raw DTI trajectories and rank ordering of LME model parameters revealed distinct posterior-to-anterior and medial-to-lateral gradients in WM maturation. Finally, we found that individual differences in WM microstructure assessed at 3 weeks of age were significantly related to those at 1 year of age. This study provides a quantitative characterization of very early WM growth in NHPs and lays the foundation for future work focused on the impact of alterations in early WM developmental trajectories in relation to human psychopathology.

U-net model for brain extraction: Trained on humans for transfer to non-human primates.

Brain extraction (a.k.a. skull stripping) is a fundamental step in the neuroimaging pipeline as it can affect the accuracy of downstream preprocess such as image registration, tissue classification, etc. Most brain extraction tools have been designed for and applied to human data and are often challenged by non-human primates (NHP) data. Amongst recent attempts to improve performance on NHP data, deep learning models appear to outperform the traditional tools. However, given the minimal sample size of most NHP studies and notable variations in data quality, the deep learning models are very rarely applied to multi-site samples in NHP imaging. To overcome this challenge, we used a transfer-learning framework that leverages a large human imaging dataset to pretrain a convolutional neural network (i.e. U-Net Model), and then transferred this to NHP data using a small NHP training sample. The resulting transfer-learning model converged faster and achieved more accurate performance than a similar U-Net Model trained exclusively on NHP samples. We improved the generalizability of the model by upgrading the transfer-learned model using additional training datasets from multiple research sites in the Primate Data-Exchange (PRIME-DE) consortium. Our final model outperformed brain extraction routines from popular MRI packages (AFNI, FSL, and FreeSurfer) across a heterogeneous sample from multiple sites in the PRIME-DE with less computational cost (20 s~10 min). We also demonstrated the transfer-learning process enables the macaque model to be updated for use with scans from chimpanzees, marmosets, and other mammals (e.g. pig). Our model, code, and the skull-stripped mask repository of 136 macaque monkeys are publicly available for unrestricted use by the neuroimaging community at https://github.com/HumanBrainED/NHP-BrainExtraction.

Social media recruitment for mental health research: A systematic review.

BACKGROUND: Social media holds exciting promise for advancing mental health research recruitment, however, the extent and efficacy to which these platforms are currently in use are underexplored. OBJECTIVE: A systematic review was conducted to characterize the current use and efficacy of social media in recruiting participants for mental health research. METHOD: A literature review was performed using MEDLINE, EMBASE, and PsychINFO. Only non-duplicative manuscripts written in the English language and published between 1/1/2004-3/31/2019 were selected for further screening. Data extracted included study type and design, participant inclusion criteria, social media platform, advertising strategy, final recruited sample size, recruitment location, year, monetary incentives, comparison to other recruitment methods if performed, and final cost per participant. RESULTS: A total of 176 unique studies that used social media for mental health research recruitment were reviewed. The majority of studies were cross-sectional (62.5%) in design and recruited adults. Facebook was overwhelmingly the recruitment platform of choice (92.6%), with the use of paid advertisements being the predominant strategy (60.8%). Of the reviewed studies, substance abuse (43.8%) and mood disorders (15.3%) were the primary subjects of investigation. In 68.3% of studies, social media recruitment performed as well as or better than traditional recruitment methods in the number and cost of final enrolled participants. The majority of studies used Facebook for recruitment at a median cost per final recruited study participant of $19.47. In 55.6% of the studies, social media recruitment was the more cost-effective recruitment method when compared to traditional methods (e.g., referrals, mailing). CONCLUSION: Social media appears to be an effective and economical recruitment tool for mental health research. The platform raises methodological and privacy concerns not covered in current research regulations that warrant additional consideration.

Functional Connectivity within the Primate Extended Amygdala Is Heritable and Associated with Early-Life Anxious Temperament.

Children with an extremely inhibited, anxious temperament (AT) are at increased risk for anxiety disorders and depression. Using a rhesus monkey model of early-life AT, we previously demonstrated that metabolism in the central extended amygdala (EAc), including the central nucleus of the amygdala (Ce) and bed nucleus of the stria terminalis (BST), is associated with trait-like variation in AT. Here, we use fMRI to examine relationships between Ce-BST functional connectivity and AT in a large multigenerational family pedigree of rhesus monkeys (n = 170 females and 208 males). Results demonstrate that Ce-BST functional connectivity is heritable, accounts for a significant but modest portion of the variance in AT, and is coheritable with AT. Interestingly, Ce-BST functional connectivity and AT-related BST metabolism were not correlated and accounted for non-overlapping variance in AT. Exploratory analyses suggest that Ce-BST functional connectivity is associated with metabolism in the hypothalamus and periaqueductal gray. Together, these results suggest the importance of coordinated function within the EAc for determining individual differences in AT and metabolism in brain regions associated with its behavioral and neuroendocrine components.SIGNIFICANCE STATEMENT Anxiety disorders directly impact the lives of nearly one in five people, accounting for substantial worldwide suffering and disability. Here, we use a nonhuman primate model of anxious temperament (AT) to understand the neurobiology underlying the early-life risk to develop anxiety disorders. Leveraging the same kinds of neuroimaging measures routinely used in human studies, we demonstrate that coordinated activation between the central nucleus of the amygdala and the bed nucleus of the stria terminalis is correlated with, and coinherited with, early-life AT. Understanding how these central extended amygdala regions work together to produce extreme anxiety provides a neural target for early-life interventions with the promise of preventing lifelong disability in at-risk children.

Ultrastructural localization of DREADDs in monkeys.

Designer receptors exclusively activated by designer drugs (DREADDs) are extensively used to modulate neuronal activity in rodents, but their use in primates remains limited. An essential need that remains is the demonstration that DREADDs are efficiently expressed on the plasma membrane of primate neurons. To address this issue, electron microscopy immunogold was used to determine the subcellular localization of the AAV vector-induced DREADDs hM4Di and hM3Dq fused to different tags in various brain areas of rhesus monkeys and mice. When hM4Di was fused to mCherry, the immunogold labelling was mostly confined to the intracellular space, and poorly expressed at the plasma membrane in monkey dendrites. In contrast, the hM4Di-mCherry labelling was mostly localized to the dendritic plasma membrane in mouse neurons, suggesting species differences in the plasma membrane expression of these exogenous proteins. The lack of hM4Di plasma membrane expression may limit the functional effects of systemic administration of DREADD-actuators in monkey neurons. Removing the mCherry and fusing of hM4Di with the haemagglutinin (HA) tag resulted in strong neuronal plasma membrane immunogold labelling in both monkeys and mice neurons. Finally, hM3Dq-mCherry was expressed mostly at the plasma membrane in monkey neurons, indicating that the fusion of mCherry with hM3Dq does not hamper membrane incorporation of this specific DREADD. Our results suggest that the pattern of ultrastructural expression of DREADDs in monkey neurons depends on the DREADD/tag combination. Therefore, a preliminary characterization of plasma membrane expression of specific DREADD/tag combinations is recommended when using chemogenetic approaches in primates.

Bayesian convolutional neural network based MRI brain extraction on nonhuman primates.

Brain extraction or skull stripping of magnetic resonance images (MRI) is an essential step in neuroimaging studies, the accuracy of which can severely affect subsequent image processing procedures. Current automatic brain extraction methods demonstrate good results on human brains, but are often far from satisfactory on nonhuman primates, which are a necessary part of neuroscience research. To overcome the challenges of brain extraction in nonhuman primates, we propose a fully-automated brain extraction pipeline combining deep Bayesian convolutional neural network (CNN) and fully connected three-dimensional (3D) conditional random field (CRF). The deep Bayesian CNN, Bayesian SegNet, is used as the core segmentation engine. As a probabilistic network, it is not only able to perform accurate high-resolution pixel-wise brain segmentation, but also capable of measuring the model uncertainty by Monte Carlo sampling with dropout in the testing stage. Then, fully connected 3D CRF is used to refine the probability result from Bayesian SegNet in the whole 3D context of the brain volume. The proposed method was evaluated with a manually brain-extracted dataset comprising T1w images of 100 nonhuman primates. Our method outperforms six popular publicly available brain extraction packages and three well-established deep learning based methods with a mean Dice coefficient of 0.985 and a mean average symmetric surface distance of 0.220 mm. A better performance against all the compared methods was verified by statistical tests (all p-values < 10-4, two-sided, Bonferroni corrected). The maximum uncertainty of the model on nonhuman primate brain extraction has a mean value of 0.116 across all the 100 subjects. The behavior of the uncertainty was also studied, which shows the uncertainty increases as the training set size decreases, the number of inconsistent labels in the training set increases, or the inconsistency between the training set and the testing set increases.