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Previous studies have adopted an edge-centric framework to study fine-scale dynamics in human fMRI. To date, however, no studies have applied this same framework to data collected from model organisms. Here, we analyze structural and functional imaging data from lightly anesthetized mice through an edge-centric lens. We find evidence of “bursty” dynamics and events – brief periods of high-amplitude network connectivity. Further, we show that on a per-frame basis events best explain static FC and can be divided into a series of hierarchically-related clusters. The co-fluctuation patterns associated with each centroid link distinct anatomical areas and largely adhere to the boundaries of algorithmically detected functional brain systems. We then investigate the anatomical connectivity undergirding high-amplitude co-fluctuation patterns. We find that events induce modular bipartitions of the anatomical network of inter-areal axonal projections. Finally, we replicate these same findings in a human imaging dataset. In summary, this report recapitulates in a model organism many of the same phenomena observed in previously edge-centric analyses of human imaging data. However, unlike human subjects, the murine nervous system is amenable to invasive experimental perturbations. Thus, this study sets the stage for future investigation into the causal origins of fine-scale brain dynamics and high-amplitude co-fluctuations. Moreover, the cross-species consistency of the reported findings enhances the likelihood of future translation.

The increase of brain dimensions and complexity has characterized the evolution of the genus Homo. According to the available fossil and genetic evidence, a crucial stage came before the divergence of Neanderthals, Denisovans and Homo sapiens, during the Middle Pleistocene. We consider a specimen of about 400 ka, whose phenotype is at the roots of this divergence: Ceprano calvarium (Italy). Here, we show a derived cerebrovascular organization with a mosaic of modern human and primitive features characteristics. Computed microtomography shows vascular variation and ontogenetic defects associated with ventricular and lymphatic involvement while phylogenetic analyzes highlight a dysregulation of the Tet1 gene that shows an accelerated mutation rate between 1.2 Ma and 466 ka, in contrast with the expected neutral evolution of the human genome. These results shed light on the dynamics of cranio-cerebral growth during the encephalization process and on the cerebral vascular and lymphatic system involved in this process. The results of this study could have implications for the research of many of the diseases of the central nervous system that have become predominant in an increasingly structured and long-lived brain system such as that of modern Homo sapiens. One-Sentence Summary: Genetic mutation, anatomical variations and glymphatic system in the process of encephalization towards Homo sapiens.

The mature mammalian brain connectome emerges during development via the extension and pruning of neuronal connections. Glial cells have been identified as key players in the phagocytic elimination of neuronal synapses and projections. Recently, phosphatidylserine has been identified as neuronal “eat-me” signal that guides elimination of unnecessary input sources, but the associated transduction systems involved in such pruning are yet to be described. Here, we identified Xk-related protein 8 (Xkr8), a phospholipid scramblase, as a key factor for the pruning of axons in the developing mammalian brain. We found that mouse Xkr8 is highly expressed immediately after birth and required for phosphatidylserine exposure in the hippocampus. Mice lacking Xkr8 showed excess excitatory nerve terminals, increased density of cortico-cortical and cortico-spinal projections, aberrant electrophysiological profiles of hippocampal neurons, and global brain hyperconnectivity. These data identify phospholipid scrambling by Xkr8 as a central process in the labeling and discrimination of developing neuronal projections for pruning in the mammalian brain.

The macroscale connectome is the network of physical, white-matter tracts between brain areas. The connections are generally weighted and their values interpreted as measures of communication efficacy. In most applications, weights are either assigned based on imaging features--e.g. diffusion parameters--or inferred using statistical models. In reality, the ground-truth weights are unknown, motivating the exploration of alternative edge weighting schemes. Here, we explore a multi-modal (combining diffusion and functional MRI data) regression-based, explanatory model that endows reconstructed fiber tracts with directed and signed weights. Benchmarking this method on Human Connectome Project data, we find that the model fits observed data well, outperforming a suite of null models. The estimated weights are subject-specific and highly reliable, even when fit using relatively few training samples. Next, we analyze the resulting network using graph-theoretic tools from network neuroscience, revealing bilaterally symmetric communities that span cerebral hemispheres. These communities exhibit a clear mapping onto known functional systems. We also study the shortest paths structure of this network, discovering that almost every edge participates in at least one shortest path. We also find evidence of robust asymmetries in edge weights, that the network reconfigures in response to naturalistic stimuli, and that estimated edge weights differ with age. In summary, we offer a simple framework for weighting connectome data, demonstrating both its ease of implementation while benchmarking its utility for typical connectome analyses, including graph theoretic modeling and brain-behavior associations.

Many neurodevelopmental conditions, including autism, affect males more than females. Genomic mechanisms enhancing risk in males may contribute to this sex-bias. The ubiquitin protein ligase E3A gene (Ube3a) exerts pleiotropic effects on cellular homeostasis via control of protein turnover and by acting as transcriptional coactivator with steroid hormone receptors. Overdosage ofUbe3avia duplication or triplication of chromosomal region 15q11-13 causes 1-2% of autistic cases. Here, we test the hypothesis that increased dosage ofUbe3amay influence autism-relevant phenotypes in a sex-biased manner. We report robust sex-biasing effects on brain connectomics and repetitive behaviors in mice with extra copies of Ube3a. These effects were associated with a profound transcriptional dysregulation of several known autism-associated genes (e.g., FMR1, SCN2A, PTEN, MEF2C, SHANK3, TSC2) as well as differentially-expressed genes identified in human 15q duplication and in autistic patients. Notably, increased Ube3a dosage also affects multiple sex-relevant mechanisms, including genes on the X chromosome, genes influenced by sex steroid hormones, downstream targets of the androgen and estrogen receptors, or genes that are sex-differentially regulated by transcription factors. These results suggest thatUbe3aoverdosage can critically contribute to sex-bias in neurodevelopmental conditions via influence on sex-differential mechanisms.

Autism Spectrum Disorder (ASD) is characterized by substantial, yet highly heterogeneous abnormalities in functional brain connectivity. However, the origin and significance of this phenomenon remain unclear. To unravel ASD connectopathy and relate it to underlying etiological heterogeneity, we carried out a bi-center cross-etiological investigation of fMRI-based connectivity in the mouse, in which specific ASD-relevant mutations can be isolated and modeled minimizing environmental contributions. By performing brain-wide connectivity mapping across 16 mouse mutants, we show that different ASD-associated etiologies cause a broad spectrum of connectional abnormalities in which diverse, often diverging, connectivity signatures are recognizable. Despite this heterogeneity, the identified connectivity alterations could be classified into four subtypes characterized by discrete signatures of network dysfunction. Our findings show that etiological variability is a key determinant of connectivity heterogeneity in ASD, hence reconciling conflicting findings in clinical populations. The identification of etiologically-relevant connectivity subtypes could improve diagnostic label accuracy in the non-syndromic ASD population and paves the way for personalized treatment approaches., Molecular Psychiatry, 26 (12), ISSN:1359-4184, ISSN:1476-5578

Brain communication, defined as information transmission through white-matter connections, is at the foundation of the brain’s computational capacities that virtually subtend all aspects of behavior: from sensory perception shared across mammalian species, to complex cognitive functions in humans. How did communication strategies in macroscale brain networks adapted across evolution to accomplish increasingly complex functions? By applying a novel approach to measure information transmission in mouse, macaque and human brains, we found an evolutionary gradient from selective information processing, where brain regions share information through single polysynaptic pathways, to parallel information processing, where regions communicate through multiple parallel pathways. In humans, parallel processing acts as a major connector between unimodal and transmodal systems. Communication strategies are unique to individuals across different mammalian species, pointing at the individual-level specificity of information routing architecture. Our work provides compelling evidence that different communication strategies are tied to the evolutionary complexity of mammalian brain networks.

Neural network models have been instrumental in revealing the foundational principles of whole-brain dynamics. Here we describe a new whole-cortex model of mouse resting-state fMRI (rsfMRI) activity. Our model implements neural input-output nonlinearities and excitatory-inhibitory interactions within areas, as well as a directed connectome obtained with viral tracing to model interareal connections. Our model makes novel predictions about the dynamic organization of rsfMRI activity on a fast scale of seconds, and explains its relationship with the underlying axonal connectivity. Specifically, the simulated rsfMRI activity exhibits rich attractor dynamics, with multiple stationary and oscillatory attractors. Guided by these theoretical predictions, we find that empirical mouse rsfMRI time series exhibit analogous signatures of attractor dynamics, and that model attractors recapitulate the topographical organization and temporal structure of empirical rsfMRI co-activation patterns (CAPs). The richness and complexity of attractor dynamics, as well as its ability to explain CAPs, are lost when the directionality of underlying axonal connectivity is neglected. Finally, complexity of fast dynamics on the scale of seconds was maximal for the values of inter-hemispheric axonal connectivity strength and of inter-areal connectivity sparsity measured in real anatomical mouse data.

Task-free functional connectivity in animal models provides an experimental framework to examine connectivity phenomena under controlled conditions and allows comparison with invasive or terminal procedures. To date, animal acquisitions are performed with varying protocols and analyses that hamper result comparison and integration. We introduce StandardRat, a consensus rat functional MRI acquisition protocol tested across 20 centers. To develop this protocol with optimized acquisition and processing parameters, we initially aggregated 65 functional imaging datasets acquired in rats from 46 centers. We developed a reproducible pipeline for the analysis of rat data acquired with diverse protocols and determined experimental and processing parameters associated with a more robust functional connectivity detection. We show that the standardized protocol enhances biologically plausible functional connectivity patterns, relative to pre-existing acquisitions. The protocol and processing pipeline described here are openly shared with the neuroimaging community to promote interoperability and cooperation towards tackling the most important challenges in neuroscience.

Understanding the population of Central Italy during the 1st millennium BCE is a crucial topic in the biological history of the Mediterranean basin. This period saw the emergence of the Etruscan and Roman cultures which had a significant impact on the bio-cultural history of the region. In this study, we analyse a prehistoric population from Caracupa (Iron Age, Latium, Central Italy). The results suggest an overall good level of health for the population. Despite this, some musculoskeletal changes related to biomechanical stressors were observed, probably as the result of strenuous physical activity. The results of a Simple Matching analysis of intragroup distance distributions suggest potential model of kinship structures and lineages. This may be due to the relative geographic isolation of the Caracupa population. Furthermore, in order to investigate the wider population of Central Italy during the 1st millennium BCE, we have constructed a population pattern using genetic and phenotypic skeletal and dental traits. The comparison between Central Italy and more isolated populations indicated a divergence between the Western and Eastern sides of Central Italy. However, we do not exclude a probable common genetic substratum for all Central Italian populations during the 1st millennium BCE.

There is a consensus that substantial heterogeneity underlies the neurobiology of autism spectrum disorder (ASD). As such, it has become increasingly clear that a dissection of variation at the molecular, cellular, and brain network domains is a prerequisite for identifying biomarkers. Neuroimaging has been widely used to characterize atypical brain patterns in ASD, although findings have varied across studies. This is due, at least in part, to a failure to account for neurobiological heterogeneity. Here, we summarize emerging data-driven efforts to delineate more homogeneous ASD subgroups at the level of brain structure and function—that is, neurosubtyping. We break this pursuit into key methodological steps: the selection of diagnostic samples, neuroimaging features, algorithms, and validation approaches. Although preliminary and methodologically diverse, current studies generally agree that at least 2 to 4 distinct ASD neurosubtypes may exist. Their identification improved symptom prediction and diagnostic label accuracy above and beyond group average comparisons. Yet, this nascent literature has shed light onto challenges and gaps. These include 1) the need for wider and more deeply transdiagnostic samples collected while minimizing artifacts (e.g., head motion), 2) quantitative and unbiased methods for feature selection and multimodal fusion, 3) greater emphasis on algorithms’ ability to capture hybrid dimensional and categorical models of ASD, and 4) systematic independent replications and validations that integrate different units of analyses across multiple scales. Solutions aimed to address these challenges and gaps are discussed for future avenues leading toward a comprehensive understanding of the mechanisms underlying ASD heterogeneity.

Filial imprinting has been used as a powerful ethological paradigm to investigate the neurobiology of early learning that affects lifelong behaviours. When a visually naïve chick is exposed to one of a wide range of conspicuous objects, it may learn its characteristics and subsequently recognises and selectively approaches this stimulus (usually the mother hen and siblings). While the initial phases of memory acquisition have been unravelled, the long-term storage and retrieval components of imprinting memories are still unknown. Here, we used functional MRI in awake newly hatched chicks to identify the long-term storage of imprinting memories in a wide network comprising the hippocampal formation, the medial striatum, the arcopallium, and the prefrontal-like nidopallium caudolaterale. These results provide the first example of non-invasive imaging of the brain in a newborn vertebrate.

Human imaging studies have shown that spontaneous brain activity exhibits stereotypic spatiotemporal reorganization in awake, conscious conditions with respect to minimally conscious states. However, whether and how this phenomenon can be generalized to lower mammalian species, remains unclear. Leveraging a robust protocol for resting-state fMRI (rsfMRI) mapping in non-anesthetized, head-fixed mice, we investigated functional network topography and dynamic structure of spontaneous brain activity in wakeful animals. We found that rsfMRI networks in the awake state, while anatomically comparable to those observed under anesthesia, are topologically configured to maximize interregional communication, departing from the underlying community structure of the mouse axonal connectome. We further report that rsfMRI activity in wakeful animals exhibits unique spatiotemporal dynamics characterized by a state-dependent, dominant occurrence of coactivation patterns encompassing a prominent participation of arousal-related forebrain nuclei, and functional anti-coordination between visual-auditory and polymodal cortical areas. We finally show that rsfMRI dynamics in awake mice exhibits a stereotypical temporal structure, in which state-dominant coactivation patterns are configured as network attractors. These findings suggest that spontaneous brain activity in awake mice is critically shaped by state-specific involvement of basal forebrain arousal systems, and document that its dynamic structure recapitulates distinctive, evolutionarily-relevant principles that are predictive of conscious states in higher mammalian species.

Contains fulltext : 239574.pdf (Publisher’s version ) (Closed access) Open science initiatives are creating opportunities to increase research coordination and impact in nonhuman primate (NHP) imaging. The PRIMatE Data and Resource Exchange community recently developed a collaboration-based strategic plan to advance NHP imaging as an integrative approach for multiscale neuroscience. 5 p.

Postmortem studies have revealed increased density of excitatory synapses in the brains of individuals with autism spectrum disorder (ASD), with a putative link to aberrant mTOR-dependent synaptic pruning. ASD is also characterized by atypical macroscale functional connectivity as measured with resting-state fMRI (rsfMRI). These observations raise the question of whether excess of synapses causes aberrant functional connectivity in ASD. Using rsfMRI, electrophysiology and in silico modelling in Tsc2 haploinsufficient mice, we show that mTOR-dependent increased spine density is associated with ASD -like stereotypies and cortico-striatal hyperconnectivity. These deficits are completely rescued by pharmacological inhibition of mTOR. Notably, we further demonstrate that children with idiopathic ASD exhibit analogous cortical-striatal hyperconnectivity, and document that this connectivity fingerprint is enriched for ASD-dysregulated genes interacting with mTOR or Tsc2. Finally, we show that the identified transcriptomic signature is predominantly expressed in a subset of children with autism, thereby defining a segregable autism subtype. Our findings causally link mTOR-related synaptic pathology to large-scale network aberrations, revealing a unifying multi-scale framework that mechanistically reconciles developmental synaptopathy and functional hyperconnectivity in autism., Autism spectrum disorder (ASD) is characterised by synaptic surplus and atypical functional connectivity. Here, the authors show that synaptic pathology in Tsc2 haploinsufficient mice is associated with autism-like behavior and cortico-striatal hyperconnectivity, and that analogous functional hyperconnectivity signatures can be linked to mTOR-pathway dysfunction in subgroups of children with idiopathic ASD.

To differentially diagnose cranial lesions noted on a medieval skeleton and explore the importance of comorbidity.A skull of an adult female with osteolytic and osteoblastic lesions, edentulism, and an ectopic tooth from an ossuary of the Church of Santa Maria in Vico del Lazio, Frosinone Italy, dating to the Middle Ages.Macroscopic observations of the remains, CT scan, and differential diagnosis was undertaken.A diagnosis of metastatic cancer (potentially breast cancer) or metastatic neuroblastoma (NBL) is offered.Considering the noted comorbidities, this case might represent a rare case of metastatic neuroblastoma.The exploration of comorbidity, in this case the presence of metastatic carcinoma and edentulism, has tremendous potential to expand our knowledge about cancer in the past.Lack of postcranial elements.Clinical and paleopathological investigation of comorbidity in modern and archeological populations to develop an evolutionary perspective on the presence of cancer in the past.

The pathophysiology of autism has been suggested to involve a combination of both macroscale connectome miswiring and microcircuit anomalies. Here, we combine connectome-wide manifold learning with biophysical simulation models to understand associations between global network perturbations and microcircuit dysfunctions in autism. We studied neuroimaging and phenotypic data in 47 individuals with autism and 37 typically developing controls obtained from the Autism Brain Imaging Data Exchange initiative. Our analysis establishes significant differences in structural connectome organization in individuals with autism relative to controls, with strong between-group effects in low-level somatosensory regions and moderate effects in high-level association cortices. Computational models reveal that the degree of macroscale anomalies is related to atypical increases of recurrent excitation/inhibition, as well as subcortical inputs into cortical microcircuits, especially in sensory and motor areas. Transcriptomic association analysis based on postmortem datasets identifies genes expressed in cortical and thalamic areas from childhood to young adulthood. Finally, supervised machine learning finds that the macroscale perturbations are associated with symptom severity scores on the Autism Diagnostic Observation Schedule. Together, our analyses suggest that atypical subcortico-cortical interactions are associated with both microcircuit and macroscale connectome differences in autism., Autism is increasingly recognized to impact multiple scales of neural organization. Here, the authors show alterations in individuals with autism relative to typically developing controls, with findings particularly pointing to atypically organized subcortical-cortical networks.

Complement signaling is thought to serve as an opsonization signal to promote the phagocytosis of synapses by microglia. However, while its role in synaptic remodeling has been demonstrated in the retino-thalamic system, it remains unclear whether complement signaling mediates synaptic pruning in the brain more generally. Here we show that mice lacking the complement 3 receptor (C3r), the major microglia complement receptor, fail to show a deficit in either synaptic pruning or axon elimination in the developing mouse cortex. Instead, mice lacking C3r show a deficit in the perinatal elimination of neurons, both in the retina as well as in the cortex, a deficit that is associated with increased cortical thickness and enhanced functional connectivity in these regions in adulthood. These data demonstrate a preferential role for complement in promoting neuronal elimination in the developing brain and argue for a reconsideration of the role of complement in synaptic pruning.

Abnormal tactile response is an integral feature of Autism Spectrum Disorders (ASDs), and hypo-responsiveness to tactile stimuli is often associated with the severity of ASDs core symptoms. Patients with Phelan-McDermid syndrome (PMS), caused by mutations in the SHANK3 gene, show ASD-like symptoms associated with aberrant tactile responses. The neural underpinnings of these abnormalities are still poorly understood. Here we investigated, in Shank3b−/− adult mice, the neural substrates of whisker-guided behaviors, a key component of rodents’ interaction with the surrounding environment. We assessed whisker-dependent behaviors in Shank3b−/− adult mice and age-matched controls, using the textured novel object recognition (tNORT) and whisker nuisance (WN) test. Shank3b−/− mice showed deficits in whisker-dependent texture discrimination in tNORT and behavioral hypo-responsiveness to repetitive whisker stimulation in WN. Sensory hypo-responsiveness was accompanied by a significantly reduced activation of the primary somatosensory cortex (S1) and hippocampus, as measured by c-fos mRNA induction, a proxy of neuronal activity following whisker stimulation. Moreover, resting-state fMRI showed a significantly reduced S1-hippocampal connectivity in Shank3b mutants, in the absence of altered connectivity between S1 and other somatosensory areas. Impaired crosstalk between hippocampus and S1 might underlie Shank3b−/− hypo-reactivity to whisker-dependent cues, highlighting a potentially generalizable somatosensory dysfunction in ASD.

Abnormal tactile response is considered an integral feature of Autism Spectrum Disorders (ASDs), and hypo-responsiveness to tactile stimuli is often associated with the severity of ASDs core symptoms. Patients with Phelan-McDermid syndrome (PMS), caused by mutations in the SHANK3 gene, show ASD-like symptoms associated with aberrant tactile responses. However, the neural underpinnings of these somatosensory abnormalities are still poorly understood. Here we investigated, in Shank3b−/− adult mice, the neural substrates of whisker-guided behaviors, a key component of rodents’ interaction with the surrounding environment. To this aim, we assessed whisker-dependent behaviors in Shank3b−/− adult mice and age-matched controls, using the textured novel object recognition (tNORT) and whisker nuisance (WN) test. Shank3b−/− mice showed deficits in whisker-dependent texture discrimination in tNORT and behavioral hypo-responsiveness to repetitive whisker stimulation in WN. Notably, sensory hypo-responsiveness was accompanied by a significantly reduced activation of the primary somatosensory cortex (S1) and hippocampus, as measured by c-fos mRNA in situ hybridization, a proxy of neuronal activity following whisker stimulation. Moreover, resting-state fMRI showed a significantly reduced S1-hippocampal connectivity in Shank3b mutant mice. Together, these findings suggest that impaired crosstalk between hippocampus and S1 might underlie Shank3b−/− hypo-reactivity to whisker-dependent cues, highlighting a potentially generalizable form of dysfunctional somatosensory processing in ASD.Significance StatementPatients with Phelan-McDermid syndrome, a syndromic form of ASD caused by mutation of the SHANK3 gene, often show aberrant responses to touch. However, the neural basis of atypical sensory responses in ASD remains undetermined. Here we used Shank3 deficient mice to investigate the neural substrates of behavioral responses to repetitive stimulation of the whiskers, a highly developed sensory organ in mice. We found that mice lacking the Shank3 gene are hypo-responsive to repetitive whisker stimulation. This trait was associated with reduced engagement and connectivity between the primary somatosensory cortex and hippocampus. These results suggest that dysfunctional cortico-hippocampal coupling may underlie somatosensory processing deficits in SHANK3 mutation carriers and related syndromic forms of ASD.