MECP2 Duplication Causes Aberrant GABA Pathways, Circuits and Behaviors in Transgenic Monkeys: Neural Mappings to Patients with Autism

State-specific Regulation of Electrical Stimulation in the Intralaminar Thalamus of Macaque Monkeys: Network and Transcriptional Insights into Arousal

Long-range thalamocortical communication is central to anesthesia-induced loss of consciousness and its reversal. However, isolating the specific neural networks connecting thalamic nuclei with various cortical regions for state-specific anesthesia regulation is challenging, with the biological underpinnings still largely unknown. Here, simultaneous electroencephalogram-fuctional magnetic resonance imaging (EEG-fMRI) and deep brain stimulation are applied to the intralaminar thalamus in macaques under finely-tuned propofol anesthesia. This approach led to the identification of an intralaminar-driven network responsible for rapid arousal during slow-wave oscillations. A network-based RNA-sequencing analysis is conducted of region-, layer-, and cell-specific gene expression data from independent transcriptomic atlases and identifies 2489 genes preferentially expressed within this arousal network, notably enriched in potassium channels and excitatory, parvalbumin-expressing neurons, and oligodendrocytes. Comparison with human RNA-sequencing data highlights conserved molecular and cellular architectures that enable the matching of homologous genes, protein interactions, and cell types across primates, providing novel insight into network-focused transcriptional signatures of arousal.

Gating of Social Behavior by Inhibitory Inputs from Hippocampal CA1 to Retrosplenial Agranular Cortex

The retrosplenial cortex has been implicated in processing sensory information and spatial learning, with abnormal neural activity reported in association with psychedelics and in mouse and non-human primate models of autism spectrum disorders (ASDs). The direct role of the retrosplenial cortex in regulating social behaviors remains unclear. In this work, we reveal that neural activity in the retrosplenial agranular cortex (RSA), a subregion of the retrosplenial cortex, is initially activated, then quickly suppressed upon social contact. This up-down phase of RSA neurons is crucial for normal social behaviors. Parvalbumin-positive GABAergic neurons in the hippocampal CA1 region were found to send inhibitory projections to the RSA. Blocking these CA1-RSA inhibitory inputs significantly impaired social behavior. Notably, enhancing the CA1-RSA inhibitory input rescued the social behavior defects in an ASD mouse model. This work suggests a neural mechanism for the salience processing of social behavior and identifies a potential target for ASD intervention using neural modulation approaches.

Tug-of-Peace: Visual Rivalry and Atypical Visual Motion Processing in MECP2 Duplication Syndrome of Autism

Extracting common patterns of neural circuit computations in the autism spectrum and confirming them as a cause of specific core traits of autism is the first step toward identifying cell-level and circuit-level targets for effective clinical intervention. Studies in humans with autism have identified functional links and common anatomic substrates between core restricted behavioral repertoire, cognitive rigidity, and overstability of visual percepts during visual rivalry. To study these processes with single-cell precision and comprehensive neuronal population coverage, we developed the visual bistable perception paradigm for mice based on ambiguous moving plaid patterns consisting of two transparent gratings drifting at an angle of 120°. This results in spontaneous reversals of the perception between local component motion (plaid perceived as two separate moving grating components) and integrated global pattern motion (plaid perceived as a fused moving texture). This robust paradigm does not depend on the explicit report of the mouse, since the direction of the optokinetic nystagmus (OKN) is used to infer the dominant percept. Using this paradigm, we found that the rate of perceptual reversals between global and local motion interpretations is reduced in the methyl-CpG-binding protein 2 duplication syndrome (MECP2-ds) mouse model of autism. Moreover, the stability of local motion percepts is greatly increased in MECP2-ds mice at the expense of global motion percepts. Thus, our model reproduces a subclass of the core features in human autism (reduced rate of visual rivalry and atypical perception of visual motion). This further offers a well-controlled approach for dissecting neuronal circuits underlying these core features.

Mapping and comparing fMRI connectivity networks across species

Technical advances in neuroimaging, notably in fMRI, have allowed distributed patterns of functional connectivity to be mapped in the human brain with increasing spatiotemporal resolution. Recent years have seen a growing interest in extending this approach to rodents and non-human primates to understand the mechanism of fMRI connectivity and complement human investigations of the functional connectome. Here, we discuss current challenges and opportunities of fMRI connectivity mapping across species. We underscore the critical importance of physiologically decoding neuroimaging measures of brain (dys)connectivity via multiscale mechanistic investigations in animals. We next highlight a set of general principles governing the organization of mammalian connectivity networks across species. These include the presence of evolutionarily conserved network systems, a dominant cortical axis of functional connectivity, and a common repertoire of topographically conserved fMRI spatiotemporal modes. We finally describe emerging approaches allowing comparisons and extrapolations of fMRI connectivity findings across species. As neuroscientists gain access to increasingly sophisticated perturbational, computational and recording tools, cross-species fMRI offers novel opportunities to investigate the large-scale organization of the mammalian brain in health and disease.

Metabolic and functional substrates of impulsive decision-making in individuals with heroin addiction after prolonged methadone maintenance treatment

Elevated impulsivity has been frequently reported in individuals with opioid addiction receiving methadone maintenance therapy (MMT), but the underlying neural mechanisms and cognitive subprocesses are not fully understood. We acquired functional magnetic resonance imaging (fMRI) data from 37 subjects with heroin addiction receiving long-term MMT and 33 healthy controls who performed a probabilistic reversal learning task, and measured their resting-state brain glucose using fluorine-18-fluorodeoxyglucose positron emission tomography (18F-FDG PET). Subjects receiving MMT exhibited significantly elevated self-reported impulsivity, and computational modeling revealed a marked impulsive decision bias manifested as switching more frequently without available evidence. Moreover, this impulsive decision bias was associated with the dose and duration of methadone use, irrelevant to the duration of heroin use. During the task, the switch-related hypoactivation in the left rostral middle frontal gyrus was correlated with the impulsive decision bias while the function of reward sensitivity was intact in subjects receiving MMT. Using prior brain-wide receptor density data, we found that the highest variance of regional metabolic abnormalities was explained by the spatial distribution of μ-opioid receptors among 10 types of neurotransmitter receptors. Heightened impulsivity in individuals receiving prolonged MMT is manifested as atypical choice bias and noise in decision-making processes, which is further driven by deficits in top-down cognitive control, other than reward sensitivity. Our findings uncover multifaceted mechanisms underlying elevated impulsivity in subjects receiving MMT, which might provide insights for developing complementary therapies to improve retention during MMT.

Identification of de novo Mutations in the Chinese Autism Spectrum Disorder Cohort via Whole-Exome Sequencing Unveils Brain Regions Implicated in Autism

Autism spectrum disorder (ASD) is a highly heritable neurodevelopmental disorder characterized by deficits in social interactions and repetitive behaviors. Although hundreds of ASD risk genes, implicated in synaptic formation and transcriptional regulation, have been identified through human genetic studies, the East Asian ASD cohorts are still under-represented in genome-wide genetic studies. Here, we applied whole-exome sequencing to 369 ASD trios including probands and unaffected parents of Chinese origin. Using a joint-calling analytical pipeline based on GATK toolkits, we identified numerous de novo mutations including 55 high-impact variants and 165 moderate-impact variants, as well as de novo copy number variations containing known ASD-related genes. Importantly, combined with single-cell sequencing data from the developing human brain, we found that the expression of genes with de novo mutations was specifically enriched in the pre-, post-central gyrus (PRC, PC) and banks of the superior temporal (BST) regions in the human brain. By further analyzing the brain imaging data with ASD and healthy controls, we found that the gray volume of the right BST in ASD patients was significantly decreased compared to healthy controls, suggesting the potential structural deficits associated with ASD. Finally, we found a decrease in the seed-based functional connectivity between BST/PC/PRC and sensory areas, the insula, as well as the frontal lobes in ASD patients. This work indicated that combinatorial analysis with genome-wide screening, single-cell sequencing, and brain imaging data reveal the brain regions contributing to the etiology of ASD.

Noncoding transcripts are linked to brain resting-state activity in non-human primates

Brain-derived transcriptomes are known to correlate with resting-state brain activity in humans. Whether this association holds in nonhuman primates remains uncertain. Here, we search for such molecular correlates by integrating 757 transcriptomes derived from 100 macaque cortical regions with resting-state activity in separate conspecifics. We observe that 150 noncoding genes explain variations in resting-state activity at a comparable level with protein-coding genes. In-depth analysis of these noncoding genes reveals that they are connected to the function of nonneuronal cells such as oligodendrocytes. Co-expression network analysis finds that the modules of noncoding genes are linked to both autism and schizophrenia risk genes. Moreover, genes associated with resting-state noncoding genes are highly enriched in human resting-state functional genes and memory-effect genes, and their links with resting-state functional magnetic resonance imaging (fMRI) signals are altered in the brains of patients with autism. Our results highlight the potential for noncoding RNAs to explain resting-state activity in the nonhuman primate brain.

Brain-wide and cell-specific transcriptomic insights into MRI-derived cortical morphology in macaque monkeys

Integrative analyses of transcriptomic and neuroimaging data have generated a wealth of information about biological pathways underlying regional variability in imaging-derived brain phenotypes in humans, but rarely in nonhuman primates due to the lack of a comprehensive anatomically-defined atlas of brain transcriptomics. Here we generate complementary bulk RNA-sequencing dataset of 819 samples from 110 brain regions and single-nucleus RNA-sequencing dataset, and neuroimaging data from 162 cynomolgus macaques, to examine the link between brain-wide gene expression and regional variation in morphometry. We not only observe global/regional expression profiles of macaque brain comparable to human but unravel a dorsolateral-ventromedial gradient of gene assemblies within the primate frontal lobe. Furthermore, we identify a set of 971 protein-coding and 34 non-coding genes consistently associated with cortical thickness, specially enriched for neurons and oligodendrocytes. These data provide a unique resource to investigate nonhuman primate models of human diseases and probe cross-species evolutionary mechanisms.

HC-Net: A hybrid convolutional network for non-human primate brain extraction

Brain extraction (skull stripping) is an essential step in the magnetic resonance imaging (MRI) analysis of brain sciences. However, most of the current brain extraction methods that achieve satisfactory results for human brains are often challenged by non-human primate brains. Due to the small sample characteristics and the nature of thick-slice scanning of macaque MRI data, traditional deep convolutional neural networks (DCNNs) are unable to obtain excellent results. To overcome this challenge, this study proposed a symmetrical end-to-end trainable hybrid convolutional neural network (HC-Net). It makes full use of the spatial information between adjacent slices of the MRI image sequence and combines three consecutive slices from three axes for 3D convolutions, which reduces the calculation consumption and promotes accuracy. The HC-Net consists of encoding and decoding structures of 3D convolutions and 2D convolutions in series. The effective use of 2D convolutions and 3D convolutions relieves the underfitting of 2D convolutions to spatial features and the overfitting of 3D convolutions to small samples. After evaluating macaque brain data from different sites, the results showed that HC-Net performed better in inference time (approximately 13 s per volume) and accuracy (mean Dice coefficient reached 95.46%). The HC-Net model also had good generalization ability and stability in different modes of brain extraction tasks.

Aberrant brain functional and structural developments in MECP2 duplication rats

Transgenic animal models with homologous etiology provide a promising way to pursue the neurobiological substrates of the behavioral deficits in autism spectrum disorder (ASD). Gain-of-function mutations of MECP2 cause MECP2 duplication syndrome, a severe neurological disorder with core symptoms of ASD. However, abnormal brain developments underlying the autistic-like behavioral deficits of MECP2 duplication syndrome are rarely investigated. To this end, a human MECP2 duplication (MECP2-DP) rat model was created by the bacterial artificial chromosome transgenic method. Functional and structural magnetic resonance imaging (MRI) with high-field were performed on 16 male MECP2-DP rats and 15 male wildtype rats at postnatal 28 days, 42 days, and 56 days old. Multimodal fusion analyses guided by locomotor-relevant metrics and social novelty time separately were applied to identify abnormal brain networks associated with diverse behavioral deficits induced by MECP2 duplication. Aberrant functional developments of a core network primarily composed of the dorsal medial prefrontal cortex (dmPFC) and retrosplenial cortex (RSP) were detected to associate with diverse behavioral phenotypes in MECP2-DP rats. Altered developments of gray matter volume were detected in the hippocampus and thalamus. We conclude that gain-of-function mutations of MECP2 induce aberrant functional activities in the default-mode-like network and aberrant volumetric changes in the brain, resulting in autistic-like behavioral deficits. Our results gain critical insights into the biomarker of MECP2 duplication syndrome and the neurobiological underpinnings of the behavioral deficits in ASD.

Mapping brain-wide excitatory projectome of primate prefrontal cortex at submicron resolution and comparison with diffusion tractography

Resolving trajectories of axonal pathways in the primate prefrontal cortex remains crucial to gain insights into higher-order processes of cognition and emotion, which requires a comprehensive map of axonal projections linking demarcated subdivisions of prefrontal cortex and the rest of brain. Here, we report a mesoscale excitatory projectome issued from the ventrolateral prefrontal cortex (vlPFC) to the entire macaque brain by using viral-based genetic axonal tracing in tandem with high-throughput serial two-photon tomography, which demonstrated prominent monosynaptic projections to other prefrontal areas, temporal, limbic, and subcortical areas, relatively weak projections to parietal and insular regions but no projections directly to the occipital lobe. In a common 3D space, we quantitatively validated an atlas of diffusion tractography-derived vlPFC connections with correlative green fluorescent protein-labeled axonal tracing, and observed generally good agreement except a major difference in the posterior projections of inferior fronto-occipital fasciculus. These findings raise an intriguing question as to how neural information passes along long-range association fiber bundles in macaque brains, and call for the caution of using diffusion tractography to map the wiring diagram of brain circuits.

In the brain is a web of interconnected nerve cells that send messages to one another via spindly projections called axons. These axons join together at junctions called synapses to create circuits of nerve cells which connect neighboring or distant brain regions. Notably, long-range neural connections underpin higher-order cognitive skills (such as planning and emotion regulation) which make humans distinct from our primate relatives. Only by untangling these far-reaching networks can researchers begin to delineate what sets the human brain apart from other species.

Researchers deploy a range of imaging techniques to map neural networks: scanning entire brains using MRI machines, or imaging thin slices of fluorescently labelled brain tissue using powerful microscopes. However, tracing long-range axons at a high resolution is challenging, and has stirred up debate about whether some neural tracts, such as the inferior fronto-occipital fasciculus, are present in all primates or only humans.

To address these discrepancies, Yan, Yu et al. employed a two-pronged approach to map neural circuits in the brains of macaques. First, two techniques – called viral tracing and two-photon microscopy – were used to create a three-dimensional, fine-grain map showing how the ventrolateral prefrontal cortex (vlPFC), which regulates complex behaviors, connects to the rest of the brain. This revealed prominent axons from the vlPFC projecting via a single synapse to distant brain regions involved in higher-order functions, such as encoding memories and processing emotion. However, there were no direct, monosynaptic connections between the vlPFC and the occipital lobe, the brain’s visual processing center at the back of the head.

Next, Yan, Yu et al. used a specialized MRI scanner to create an atlas of neural circuits connected to the vlPFC, and compared these results to a technique tracing axons stained with a fluorescent dye. In general, there was good agreement between the two methods, except for major differences in the rear-end projections that typically form the inferior fronto-occipital fasciculus. This suggests that this long-range neural pathway exists in monkeys, but it connects via multiple synapses instead of a single junction as was previously thought.

The findings of Yan, Yu et al. provide new insights on the far-reaching neural pathways connecting distant parts of the macaque brain. It also suggests that atlases of neural circuits from whole brain scans should be taken with caution and validated using neural tracing experiments.

Ultrasound modulation of macaque prefrontal cortex selectively alters credit assignment-related activity and behavior

Credit assignment is the association of specific instances of reward to the specific events, such as a particular choice, that caused them. Without credit assignment, choice values reflect an approximate estimate of how good the environment was when the choice was made—the global reward state—rather than exactly which outcome the choice caused. Combined transcranial ultrasound stimulation (TUS) and functional magnetic resonance imaging in macaques demonstrate credit assignment–related activity in prefrontal area 47/12o, and when this signal was disrupted with TUS, choice value representations across the brain were impaired. As a consequence, behavior was no longer guided by choice value, and decision-making was poorer. By contrast, global reward state–related activity in the adjacent anterior insula remained intact and determined decision-making after prefrontal disruption.

Embryo-Engineered Nonhuman Primate Models: Progress and Gap to Translational Medicine

Animal models of human diseases are vital in better understanding the mechanism of pathogenesis and essential for evaluating and validating potential therapeutic interventions. As close relatives of humans, nonhuman primates (NHPs) play an increasingly indispensable role in advancing translational medicine research. In this review, we summarized the progress of NHP models generated by embryo engineering, analyzed their unique advantages in mimicking clinical patients, and discussed the remaining gap between basic research of NHP models to translational medicine.

Brain imaging-based machine learning in autism spectrum disorder: methods and applications

Autism spectrum disorder (ASD) is a neurodevelopmental condition with early childhood onset and high heterogeneity. As the pathogenesis is still elusive, ASD diagnosis is comprised of a constellation of behavioral symptoms. Non-invasive brain imaging techniques, such as magnetic resonance imaging (MRI), provide a valuable objective measurement of the brain. Many efforts have been devoted to developing imaging-based diagnostic tools for ASD based on machine learning (ML) technologies. In this survey, we review recent advances that utilize machine learning approaches to classify individuals with and without ASD. First, we provide a brief overview of neuroimaging-based ASD classification studies, including the analysis of publications and general classification pipeline. Next, representative studies are highlighted and discussed in detail regarding different imaging modalities, methods and sample sizes. Finally, we highlight several common challenges and provide recommendations on future directions. In summary, identifying discriminative biomarkers for ASD diagnosis is challenging, and further establishing more comprehensive datasets and dissecting the individual and group heterogeneity will be critical to achieve better ADS diagnosis performance. Machine learning methods will continue to be developed and are poised to help advance the field in this regard.

Sleep Disorders in Children With Autism Spectrum Disorder: Insights From Animal Models, Especially Non-human Primate Model

Autism Spectrum Disorder (ASD) is a heterogeneous neurodevelopmental disorder with deficient social skills, communication deficits and repetitive behaviors. The prevalence of ASD has increased among children in recent years. Children with ASD experience more sleep problems, and sleep appears to be essential for the survival and integrity of most living organisms, especially for typical synaptic development and brain plasticity. Many methods have been used to assess sleep problems over past decades such as sleep diaries and parent-reported questionnaires, electroencephalography, actigraphy and videosomnography. A substantial number of rodent and non-human primate models of ASD have been generated. Many of these animal models exhibited sleep disorders at an early age. The aim of this review is to examine and discuss sleep disorders in children with ASD. Toward this aim, we evaluated the prevalence, clinical characteristics, phenotypic analyses, and pathophysiological brain mechanisms of ASD. We highlight the current state of animal models for ASD and explore their implications and prospects for investigating sleep disorders associated with ASD.

Brain connectivity abnormalities and treatment-induced restorations in patients with cervical dystonia

BACKGROUND

The relationship between brain abnormalities and phenotypic characteristics in cervical dystonia (CD) patients has not been fully established, and little is known about the neuroplastic changes induced by botulinum toxin type A (BoNT-A) treatment.

METHODS

Ninety-two CD patients presenting with rotational torticollis and 45 healthy controls from our database were retrospectively screened. After clinical assessment, the 92 patients underwent baseline magnetic resonance imaging (MRI) followed by a single-dose injection of BoNT-A. Four weeks later, 76 out of the 92 patients were re-evaluated with the Tsui scale for dystonia severity, and 33 out of 76 patients completed post-treatment MRI scanning. Data-driven global brain connectivity and regional homogeneity in tandem with seed-based connectivity analyses were used to examine the functional abnormalities in CD and longitudinal circuit alterations that scaled with clinical response to BoNT-A. Multiple regression models were employed for the prediction analysis of treatment efficacy.

RESULTS

Cervical dystonia patients exhibited elevated baseline connectivity of the right postcentral gyrus with the left dorsomedial prefrontal cortex and right caudate nucleus, which was associated with their symptom severity. BoNT-A reduced excessive functional connectivity between the sensorimotor cortex and right superior frontal gyrus, which was significantly correlated with changes in Tsui score. Moreover, pre-treatment regional homogeneity of the left middle frontal gyrus was linearly related to varied response to treatment.

CONCLUSIONS

Our findings unravel dissociable connectivity of the sensorimotor cortex underlying the pathology of CD and central effects of BoNT-A therapy. Furthermore, baseline regional homogeneity with the left middle frontal gyrus may represent a potential evidence-based marker of patient stratification for BoNT-A therapy in CD.

Excessive Formation and Stabilization of Dendritic Spine Clusters in the MECP2-Duplication Syndrome Mouse Model of Autism

Autism-associated genetic mutations may perturb the balance between stability and plasticity of synaptic connections in the brain. Here, we report an increase in the formation and stabilization of dendritic spines in the cerebral cortex of the mouse model of MECP2-duplication syndrome, a high-penetrance form of syndromic autism. Increased stabilization is mediated entirely by spines that form cooperatively in 10-μm clusters and is observable across multiple cortical areas both spontaneously and following motor training. Excessive stability of dendritic spine clusters could contribute to behavioral rigidity and other phenotypes in syndromic autism.

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.

Risky decision-making following prefrontal D1 receptor manipulation

The prefrontal dopamine D1 receptor (D1R) is involved in cognitive processes. Viral overexpression of this receptor in rats further increases the reward-related behaviors and even its termination induces anhedonia and helplessness. In this study, we investigated the risky decision-making during D1R overexpression and its termination. Rats conducted the rodent version of the Iowa gambling task daily. In addition, the methyl CpG–binding protein-2 (MeCP2), one regulator connecting the dopaminergic system, cognitive processes, and mood-related behavior, was investigated after completion of the behavioral tasks. D1R overexpressing subjects exhibited maladaptive risky decision-making and risky decisions returned to control levels following termination of D1R overexpression; however, after termination, animals earned less reward compared to control subjects. In this phase, MeCP2-positive cells were elevated in the right amygdala. Our results extend the previously reported behavioral changes in the D1R-manipulated animal model to increased risk-taking and revealed differential MeCP2 expression adding further evidence for a bipolar disorder-like phenotype of this model.