Area-Specificity and Plasticity of History-Dependent Value Coding During Learning.

Decision making is often driven by the subjective value of available options, a value which is formed through experience. To support this fundamental behavior, the brain must encode and maintain the subjective value. To investigate the area specificity and plasticity of value coding, we trained mice in a value-based decision task and imaged neural activity in 6 cortical areas with cellular resolution. History- and value-related signals were widespread across areas, but their strength and temporal patterns differed. In expert mice, the retrosplenial cortex (RSC) uniquely encoded history- and value-related signals with persistent population activity patterns across trials. This unique encoding of RSC emerged during task learning with a strong increase in more distant history signals. Acute inactivation of RSC selectively impaired the reward-history-based behavioral strategy. Our results indicate that RSC flexibly changes its history coding and persistently encodes value-related signals to support adaptive behaviors.

H3 K27M and EZHIP Impede H3K27-Methylation Spreading by Inhibiting Allosterically Stimulated PRC2.

Diffuse midline gliomas and posterior fossa type A ependymomas contain the recurrent histone H3 lysine 27 (H3 K27M) mutation and express the H3 K27M-mimic EZHIP (CXorf67), respectively. H3 K27M and EZHIP are competitive inhibitors of Polycomb Repressive Complex 2 (PRC2) lysine methyltransferase activity. In vivo, these proteins reduce overall H3 lysine 27 trimethylation (H3K27me3) levels; however, residual peaks of H3K27me3 remain at CpG islands (CGIs) through an unknown mechanism. Here, we report that EZHIP and H3 K27M preferentially interact with PRC2 that is allosterically activated by H3K27me3 at CGIs and impede its spreading. Moreover, H3 K27M oncohistones reduce H3K27me3 in trans, independent of their incorporation into the chromatin. Although EZHIP is not found outside placental mammals, expression of human EZHIP reduces H3K27me3 in Drosophila melanogaster through a conserved mechanism. Our results provide mechanistic insights for the retention of residual H3K27me3 in tumors driven by H3 K27M and EZHIP.

Sall4 regulates posterior trunk mesoderm development by promoting mesodermal gene expression and repressing neural genes in the mesoderm.

The trunk axial skeleton develops from paraxial mesoderm cells. Our recent study demonstrated that conditional knockout of the stem cell factor Sall4 in mice by TCre caused tail truncation and a disorganized axial skeleton posterior to the lumbar level. Based on this phenotype, we hypothesized that, in addition to the previously reported role of Sall4 in neuromesodermal progenitors, Sall4 is involved in the development of the paraxial mesoderm tissue. Analysis of gene expression and SALL4 binding suggests that Sall4 directly or indirectly regulates genes involved in presomitic mesoderm differentiation, somite formation and somite differentiation. Furthermore, ATAC-seq in TCre; Sall4 mutant posterior trunk mesoderm shows that Sall4 knockout reduces chromatin accessibility. We found that Sall4-dependent open chromatin status drives activation and repression of WNT signaling activators and repressors, respectively, to promote WNT signaling. Moreover, footprinting analysis of ATAC-seq data suggests that Sall4-dependent chromatin accessibility facilitates CTCF binding, which contributes to the repression of neural genes within the mesoderm. This study unveils multiple mechanisms by which Sall4 regulates paraxial mesoderm development by directing activation of mesodermal genes and repression of neural genes.

Different roles of response covariability and its attentional modulation in the sensory cortex and posterior parietal cortex.

The covariability of neural responses in the neuron population is highly relevant to the information encoding. Cognitive processes, such as attention, are found to modulate the covariability in the visual cortex to improve information encoding, suggesting the computational advantage of covariability modulation in the neural system. However, is the covariability modulation a general mechanism for enhanced information encoding throughout the information processing pathway, or only adopted in certain processing stages, depending on the property of neural representation? Here, with ultrahigh-field MRI, we examined the covariability, which was estimated by noise correlation, in different attention states in the early visual cortex and posterior parietal cortex (PPC) of the human brain, and its relationship to the quality of information encoding. Our results showed that while attention decreased the covariability to improve the stimulus encoding in the early visual cortex, covariability modulation was not observed in the PPC, where covariability had little impact on information encoding. Further, attention promoted the information flow between the early visual cortex and PPC, with an apparent emphasis on a flow from high- to low-dimensional representations, suggesting the existence of a reduction in the dimensionality of neural representation from the early visual cortex to PPC. Finally, the neural response patterns in the PPC could predict the amplitudes of covariability change in the early visual cortex, indicating a top-down control from the PPC to early visual cortex. Our findings reveal the specific roles of the sensory cortex and PPC during attentional modulation of covariability, determined by the complexity and fidelity of the neural representation in each cortical region.

Structural basis for binding of Drosophila Smaug to the GPCR Smoothened and to the germline inducer Oskar.

Drosophila Smaug and its orthologs comprise a family of mRNA repressor proteins that exhibit various functions during animal development. Smaug proteins contain a characteristic RNA-binding sterile-α motif (SAM) domain and a conserved but uncharacterized N-terminal domain (NTD). Here, we resolved the crystal structure of the NTD of the human SAM domain-containing protein 4A (SAMD4A, a.k.a. Smaug1) to 1.6 Å resolution, which revealed its composition of a homodimerization D subdomain and a subdomain with similarity to a pseudo-HEAT-repeat analogous topology (PHAT) domain. Furthermore, we show that Drosophila Smaug directly interacts with the Drosophila germline inducer Oskar and with the Hedgehog signaling transducer Smoothened through its NTD. We determined the crystal structure of the NTD of Smaug in complex with a Smoothened α-helical peptide to 2.0 Å resolution. The peptide binds within a groove that is formed by both the D and PHAT subdomains. Structural modeling supported by experimental data suggested that an α-helix within the disordered region of Oskar binds to the NTD of Smaug in a mode similar to Smoothened. Together, our data uncover the NTD of Smaug as a peptide-binding domain.

Suspending the Embodied Self in Meditation Attenuates Beta Oscillations in the Posterior Medial Cortex.

Human experience is imbued by the sense of being an embodied agent. The investigation of such basic self-consciousness has been hampered by the difficulty of comprehensively modulating it in the laboratory while reliably capturing ensuing subjective changes. The present preregistered study fills this gap by combining advanced meditative states with principled phenomenological interviews: 46 long-term meditators (19 female, 27 male) were instructed to modulate and attenuate their embodied self-experience during magnetoencephalographic monitoring. Results showed frequency-specific (high-beta band) activity reductions in frontoparietal and posterior medial cortices (PMC). Importantly, PMC reductions were driven by a subgroup describing radical embodied self-disruptions, including suspension of agency and dissolution of a localized first-person perspective. Neural changes were correlated with lifetime meditation and interview-derived experiential changes, but not with classical self-reports. The results demonstrate the potential of integrating in-depth first-person methods into neuroscientific experiments. Furthermore, they highlight neural oscillations in the PMC as a central process supporting the embodied sense of self.

Mixed Selectivity Coding of Content-Temporal Detail by Dorsomedial Posterior Parietal Neurons.

The dorsomedial posterior parietal cortex (dmPPC) is part of a higher-cognition network implicated in elaborate processes underpinning memory formation, recollection, episode reconstruction, and temporal information processing. Neural coding for complex episodic processing is however under-documented. Here, we recorded extracellular neural activities from three male rhesus macaques (Macaca mulatta) and revealed a set of neural codes of "neuroethogram" in the primate parietal cortex. Analyzing neural responses in macaque dmPPC to naturalistic videos, we discovered several groups of neurons that are sensitive to different categories of ethogram items, low-level sensory features, and saccadic eye movement. We also discovered that the processing of category and feature information by these neurons is sustained by the accumulation of temporal information over a long timescale of up to 30 s, corroborating its reported long temporal receptive windows. We performed an additional behavioral experiment with additional two male rhesus macaques and found that saccade-related activities could not account for the mixed neuronal responses elicited by the video stimuli. We further observed monkeys' scan paths and gaze consistency are modulated by video content. Taken altogether, these neural findings explain how dmPPC weaves fabrics of ongoing experiences together in real time. The high dimensionality of neural representations should motivate us to shift the focus of attention from pure selectivity neurons to mixed selectivity neurons, especially in increasingly complex naturalistic task designs.

Insula→Amygdala and Insula→Thalamus Pathways Are Involved in Comorbid Chronic Pain and Depression-Like Behavior in Mice.

The comorbidity of chronic pain and depression poses tremendous challenges for the treatment of either one because they exacerbate each other with unknown mechanisms. As the posterior insular cortex (PIC) integrates multiple somatosensory and emotional information and is implicated in either chronic pain or depression, we hypothesize that the PIC and its projections may contribute to the pathophysiology of comorbid chronic pain and depression. We show that PIC neurons were readily activated by mechanical, thermal, aversive, and stressful and appetitive stimulation in naive and neuropathic pain male mice subjected to spared nerve injury (SNI). Optogenetic activation of PIC neurons induced hyperalgesia and conditioned place aversion in naive mice, whereas inhibition of these neurons led to analgesia, conditioned place preference (CPP), and antidepressant effect in both naive and SNI mice. Combining neuronal tracing, optogenetics, and electrophysiological techniques, we found that the monosynaptic glutamatergic projections from the PIC to the basolateral amygdala (BLA) and the ventromedial nucleus (VM) of the thalamus mimicked PIC neurons in pain modulation in naive mice; in SNI mice, both projections were enhanced accompanied by hyperactivity of PIC, BLA, and VM neurons and inhibition of these projections led to analgesia, CPP, and antidepressant-like effect. The present study suggests that potentiation of the PIC→BLA and PIC→VM projections may be important pathophysiological bases for hyperalgesia and depression-like behavior in neuropathic pain and reversing the potentiation may be a promising therapeutic strategy for comorbid chronic pain and depression.

The Expected Behaviors of Posterior Predictive Tests and Their Unexpected Interpretation.

Poor fit between models of sequence or trait evolution and empirical data is known to cause biases and lead to spurious conclusions about evolutionary patterns and processes. Bayesian posterior prediction is a flexible and intuitive approach for detecting such cases of poor fit. However, the expected behavior of posterior predictive tests has never been characterized for evolutionary models, which is critical for their proper interpretation. Here, we show that the expected distribution of posterior predictive P-values is generally not uniform, in contrast to frequentist P-values used for hypothesis testing, and extreme posterior predictive P-values often provide more evidence of poor fit than typically appreciated. Posterior prediction assesses model adequacy under highly favorable circumstances, because the model is fitted to the data, which leads to expected distributions that are often concentrated around intermediate values. Nonuniform expected distributions of P-values do not pose a problem for the application of these tests, however, and posterior predictive P-values can be interpreted as the posterior probability that the fitted model would predict a dataset with a test statistic value as extreme as the value calculated from the observed data.

Partitioning gene-level contributions to complex-trait heritability by allele frequency identifies disease-relevant genes.

Recent works have shown that SNP heritability-which is dominated by low-effect common variants-may not be the most relevant quantity for localizing high-effect/critical disease genes. Here, we introduce methods to estimate the proportion of phenotypic variance explained by a given assignment of SNPs to a single gene ("gene-level heritability"). We partition gene-level heritability by minor allele frequency (MAF) to find genes whose gene-level heritability is explained exclusively by "low-frequency/rare" variants (0.5% ≤ MAF < 1%). Applying our method to ∼16K protein-coding genes and 25 quantitative traits in the UK Biobank (N = 290K "White British"), we find that, on average across traits, ∼2.5% of nonzero-heritability genes have a rare-variant component and only ∼0.8% (327 gene-trait pairs) have heritability exclusively from rare variants. Of these 327 gene-trait pairs, 114 (35%) were not detected by existing gene-level association testing methods. The additional genes we identify are significantly enriched for known disease genes, and we find several examples of genes that have been previously implicated in phenotypically related Mendelian disorders. Notably, the rare-variant component of gene-level heritability exhibits trends different from those of common-variant gene-level heritability. For example, while total gene-level heritability increases with gene length, the rare-variant component is significantly larger among shorter genes; the cumulative distributions of gene-level heritability also vary across traits and reveal differences in the relative contributions of rare/common variants to overall gene-level polygenicity. While nonzero gene-level heritability does not imply causality, if interpreted in the correct context, gene-level heritability can reveal useful insights into complex-trait genetic architecture.

Calibration of computational tools for missense variant pathogenicity classification and ClinGen recommendations for PP3/BP4 criteria.

Recommendations from the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) for interpreting sequence variants specify the use of computational predictors as "supporting" level of evidence for pathogenicity or benignity using criteria PP3 and BP4, respectively. However, score intervals defined by tool developers, and ACMG/AMP recommendations that require the consensus of multiple predictors, lack quantitative support. Previously, we described a probabilistic framework that quantified the strengths of evidence (supporting, moderate, strong, very strong) within ACMG/AMP recommendations. We have extended this framework to computational predictors and introduce a new standard that converts a tool's scores to PP3 and BP4 evidence strengths. Our approach is based on estimating the local positive predictive value and can calibrate any computational tool or other continuous-scale evidence on any variant type. We estimate thresholds (score intervals) corresponding to each strength of evidence for pathogenicity and benignity for thirteen missense variant interpretation tools, using carefully assembled independent data sets. Most tools achieved supporting evidence level for both pathogenic and benign classification using newly established thresholds. Multiple tools reached score thresholds justifying moderate and several reached strong evidence levels. One tool reached very strong evidence level for benign classification on some variants. Based on these findings, we provide recommendations for evidence-based revisions of the PP3 and BP4 ACMG/AMP criteria using individual tools and future assessment of computational methods for clinical interpretation.

Self-organizing in vitro mouse neural tube organoids mimic embryonic development.

The embryonic neural tube is the origin of the entire adult nervous system, and disturbances in its development cause life-threatening birth defects. However, the study of mammalian neural tube development is limited by the lack of physiologically realistic three-dimensional (3D) in vitro models. Here, we report a self-organizing 3D neural tube organoid model derived from single mouse embryonic stem cells that exhibits an in vivo-like tissue architecture, cell type composition and anterior-posterior (AP) patterning. Moreover, maturation of the neural tube organoids showed the emergence of multipotent neural crest cells and mature neurons. Single-cell transcriptome analyses revealed the sequence of transcriptional events in the emergence of neural crest cells and neural differentiation. Thanks to the accessibility of this model, phagocytosis of migrating neural crest cells could be observed in real time for the first time in a mammalian model. We thus introduce a tractable in vitro model to study some of the key morphogenetic and cell type derivation events during early neural development.

Shared cis-regulatory modules control expression of the tandem paralogs midline and H15 in the follicular epithelium.

The posterior end of the follicular epithelium is patterned by midline (MID) and its paralog H15, the Drosophila homologs of the mammalian Tbx20 transcription factor. We have previously identified two cis-regulatory modules (CRMs) that recapitulate the endogenous pattern of mid in the follicular epithelium. Here, using CRISPR/Cas9 genome editing, we demonstrate redundant activity of these mid CRMs. Although the deletion of either CRM alone generated marginal change in mid expression, the deletion of both CRMs reduced expression by 60%. Unexpectedly, the deletion of the 5' proximal CRM of mid eliminated H15 expression. Interestingly, expression of these paralogs in other tissues remained unaffected in the CRM deletion backgrounds. These results suggest that the paralogs are regulated by a shared CRM that coordinates gene expression during posterior fate determination. The consistent overlapping expression of mid and H15 in various tissues may indicate that the paralogs could also be under shared regulation by other CRMs in these tissues.

Sequential Bayesian Phylogenetic Inference.

The ideal approach to Bayesian phylogenetic inference is to estimate all parameters of interest jointly in a single hierarchical model. However, this is often not feasible in practice due to the high computational cost. Instead, phylogenetic pipelines generally consist of sequential analyses, whereby a single point estimate from a given analysis is used as input for the next analysis (e.g., a single multiple sequence alignment is used to estimate a gene tree). In this framework, uncertainty is not propagated from step to step, which can lead to inaccurate or spuriously confident results. Here, we formally develop and test a sequential inference approach for Bayesian phylogenetic inference, which uses importance sampling to generate observations for the next step of an analysis pipeline from the posterior distribution produced in the previous step. Our sequential inference approach presented here not only accounts for uncertainty between analysis steps, but also allows for greater flexibility in software choice (and hence model availability) and can be computationally more efficient than the traditional joint inference approach when multiple models are being tested. We show that our sequential inference approach is identical in practice to the joint inference approach only if sufficient information in the data is present (a narrow posterior distribution) and/or sufficiently many importance samples are used. Conversely, we show that the common practice of using a single point estimate can be biased, e.g., a single phylogeny estimate to transform an unrooted phylogeny into a time-calibrated phylogeny. We demonstrate the theory of sequential Bayesian inference using both a toy example and an empirical case study of divergence-time estimation in insects using a relaxed clock model from transcriptome data. In the empirical example, we estimate three posterior distributions of branch lengths from the same data (DNA character matrix with a GTR+Γ+I substitution model, an amino acid data matrix with empirical substitution models, and an amino acid data matrix with the PhyloBayes CAT-GTR model). Finally, we apply three different node-calibration strategies and show that divergence-time estimates are affected by both the data source and underlying substitution process to estimate branch lengths as well as the node-calibration strategies. Thus, our new sequential Bayesian phylogenetic inference provides the opportunity to efficiently test different approaches for divergence time estimation, including branch-length estimation from other software.

Posterior parietal cortex is causally involved in reward valuation but not in probability weighting during risky choice.

This study provides evidence that the posterior parietal cortex is causally involved in risky decision making via the processing of reward values but not reward probabilities. In the within-group experimental design, participants performed a binary lottery choice task following transcranial magnetic stimulation of the right posterior parietal cortex, left posterior parietal cortex, and a right posterior parietal cortex sham (placebo) stimulation. The continuous theta-burst stimulation protocol supposedly downregulating the cortical excitability was used. Both, mean-variance and the prospect theory approach to risky choice showed that the posterior parietal cortex stimulation shifted participants toward greater risk aversion compared with sham. On the behavioral level, after the posterior parietal cortex stimulation, the likelihood of choosing a safer option became more sensitive to the difference in standard deviations between lotteries, compared with sham, indicating greater risk avoidance within the mean-variance framework. We also estimated the shift in prospect theory parameters of risk preferences after posterior parietal cortex stimulation. The hierarchical Bayesian approach showed moderate evidence for a credible change in risk aversion parameter toward lower marginal reward value (and, hence, lower risk tolerance), while no credible change in probability weighting was observed. In addition, we observed anecdotal evidence for a credible increase in the consistency of responses after the left posterior parietal cortex stimulation compared with sham.

Functionality of arousal-regulating brain circuitry at rest predicts human cognitive abilities.

Arousal state is regulated by subcortical neuromodulatory nuclei, such as locus coeruleus, which send wide-reaching projections to cortex. Whether higher-order cortical regions have the capacity to recruit neuromodulatory systems to aid cognition is unclear. Here, we hypothesized that select cortical regions activate the arousal system, which, in turn, modulates large-scale brain activity, creating a functional circuit predicting cognitive ability. We utilized the Human Connectome Project 7T functional magnetic resonance imaging dataset (n = 149), acquired at rest with simultaneous eye tracking, along with extensive cognitive assessment for each subject. First, we discovered select frontoparietal cortical regions that drive large-scale spontaneous brain activity specifically via engaging the arousal system. Second, we show that the functionality of the arousal circuit driven by bilateral posterior cingulate cortex (associated with the default mode network) predicts subjects' cognitive abilities. This suggests that a cortical region that is typically associated with self-referential processing supports cognition by regulating the arousal system.

Switching off: disruptive TMS reveals distinct contributions of the posterior middle temporal gyrus and angular gyrus to bilingual speech production.

The role of the left temporoparietal cortex in speech production has been extensively studied during native language processing, proving crucial in controlled lexico-semantic retrieval under varying cognitive demands. Yet, its role in bilinguals, fluent in both native and second languages, remains poorly understood. Here, we employed continuous theta burst stimulation to disrupt neural activity in the left posterior middle-temporal gyrus (pMTG) and angular gyrus (AG) while Italian-Friulian bilinguals performed a cued picture-naming task. The task involved between-language (naming objects in Italian or Friulian) and within-language blocks (naming objects ["knife"] or associated actions ["cut"] in a single language) in which participants could either maintain (non-switch) or change (switch) instructions based on cues. During within-language blocks, cTBS over the pMTG entailed faster naming for high-demanding switch trials, while cTBS to the AG elicited slower latencies in low-demanding non-switch trials. No cTBS effects were observed in the between-language block. Our findings suggest a causal involvement of the left pMTG and AG in lexico-semantic processing across languages, with distinct contributions to controlled vs. "automatic" retrieval, respectively. However, they do not support the existence of shared control mechanisms within and between language(s) production. Altogether, these results inform neurobiological models of semantic control in bilinguals.

Dynamical changes of interaction across functional brain communities during propofol-induced sedation.

It is crucial to understand how anesthetics disrupt information transmission within the whole-brain network and its hub structure to gain insight into the network-level mechanisms underlying propofol-induced sedation. However, the influence of propofol on functional integration, segregation, and community structure of whole-brain networks were still unclear. We recruited 12 healthy subjects and acquired resting-state functional magnetic resonance imaging data during 5 different propofol-induced effect-site concentrations (CEs): 0, 0.5, 1.0, 1.5, and 2.0 µg/ml. We constructed whole-brain functional networks for each subject under different conditions and identify community structures. Subsequently, we calculated the global and local topological properties of whole-brain network to investigate the alterations in functional integration and segregation with deepening propofol sedation. Additionally, we assessed the alteration of key nodes within the whole-brain community structure at each effect-site concentrations level. We found that global participation was significantly increased at high effect-site concentrations, which was mediated by bilateral postcentral gyrus. Meanwhile, connector hubs appeared and were located in posterior cingulate cortex and precentral gyrus at high effect-site concentrations. Finally, nodal participation coefficients of connector hubs were closely associated to the level of sedation. These findings provide valuable insights into the relationship between increasing propofol dosage and enhanced functional interaction within the whole-brain networks.

Multi-Cell Line Analysis of Lysosomal Proteomes Reveals Unique Features and Novel Lysosomal Proteins.

Lysosomes, the main degradative organelles of mammalian cells, play a key role in the regulation of metabolism. It is becoming more and more apparent that they are highly active, diverse, and involved in a large variety of processes. The essential role of lysosomes is exemplified by the detrimental consequences of their malfunction, which can result in lysosomal storage disorders, neurodegenerative diseases, and cancer. Using lysosome enrichment and mass spectrometry, we investigated the lysosomal proteomes of HEK293, HeLa, HuH-7, SH-SY5Y, MEF, and NIH3T3 cells. We provide evidence on a large scale for cell type-specific differences of lysosomes, showing that levels of distinct lysosomal proteins are highly variable within one cell type, while expression of others is highly conserved across several cell lines. Using differentially stable isotope-labeled cells and bimodal distribution analysis, we furthermore identify a high confidence population of lysosomal proteins for each cell line. Multi-cell line correlation of these data reveals potential novel lysosomal proteins, and we confirm lysosomal localization for six candidates. All data are available via ProteomeXchange with identifier PXD020600.

Hinge point emergence in mammalian spinal neurulation.

Neurulation is the process in early vertebrate embryonic development during which the neural plate folds to form the neural tube. Spinal neural tube folding in the posterior neuropore changes over time, first showing a median hinge point, then both the median hinge point and dorsolateral hinge points, followed by dorsolateral hinge points only. The biomechanical mechanism of hinge point formation in the mammalian neural tube is poorly understood. Here we employ a mechanical finite element model to study neural tube formation. The computational model mimics the mammalian neural tube using microscopy data from mouse and human embryos. While intrinsic curvature at the neural plate midline has been hypothesized to drive neural tube folding, intrinsic curvature was not sufficient for tube closure in our simulations. We achieved neural tube closure with an alternative model combining mesoderm expansion, nonneural ectoderm expansion, and neural plate adhesion to the notochord. Dorsolateral hinge points emerged in simulations with low mesoderm expansion and zippering. We propose that zippering provides the biomechanical force for dorsolateral hinge point formation in settings where the neural plate lateral sides extend above the mesoderm. Together, these results provide a perspective on the biomechanical and molecular mechanism of mammalian spinal neurulation.