Biology subjects

Yang, H.

Publications and source records attributed to Yang, H..

At least 469 records · Page 26Linked to original sources

bioRxiv2021

Diversity, function and evolution of marine microbe genomes

Trillions of marine bacterial, archaeal and viral species contribute to the majority diversity of life on Earth. In the current study, we have done a comprehensive review of all the published studies of marine microbiome by re-analyzing most of the available high throughput sequencing data. We collected 17.59 Tb sequencing data from 8,165 metagenomic and prokaryotic samples, and systematically evaluated the genome characters, including genome size, GC content, phylogeny, and the functional and ecological roles of several typical phyla. A genome catalogue of 9,070 high quality genomes and a gene catalogue including 156,209,709 genes were constructed, representing the most integrate marine prokaryotic datasets till now. The genome size of Alphaproteobacteria and Actinobacteria was significant correlated to their GC content. A total of 44,322 biosynthetic gene clusters distributed in 53 types were detected from the reconstructed marine prokaryotic genome catalogue. Phylogenetic annotation of the 8,380 bacterial and 690 archaeal species revealed that most of the known bacterial phyla (99/111), including 62 classes and 181 orders, and four extra unclassified genomes from two candidate novel phyla were detected. In addition, taxonomically unclassified species represented a substantial fraction of 64.56% and 80.29% of the phylogenetic diversity of Bacteria and Archaea respectively. The genomic and ecological features of three groups of Cyanobacteria, luminous bacteria and methane-metabolizing archaea, including inhabitant preference, geolocation distribution and others were through discussed. Our database provides a comprehensive resource for marine microbiome, which would be a valuable reference for studies of marine life origination and evolution, ecology monitor and protection, bioactive compound development.

microbiology↗

bioRxiv2021

Spatiotemporal transcriptome at single-cell resolution reveals key radial glial cell population in axolotl telencephalon development and regeneration

Brain regeneration requires a precise coordination of complex responses in a time- and region-specific manner. Identifying key cell types and molecules that direct brain regeneration would provide potential targets for the advance of regenerative medicine. However, progress in the field has been hampered largely due to limited regeneration capacity of the mammalian brain and understanding of the regeneration process at both cellular and molecular level. Here, using axolotl brain with extrodinary regeneration ability upon injury, and the SpaTial Enhanced REsolution Omics-sequencing (Stereo-seq), we reconstructed the first architecture of axolotl telencephalon with gene expression profiling at single-cell resolution, and fine cell dynamics maps throughout development and regeneration. Intriguingly, we discovered a marked heterogeneity of radial glial cell (RGC) types with distinct behaviors. Of note, one subtype of RGCs is activated since early regeneration stages and proliferates while other RGCs remain dormant. Such RGC subtype appears to be the major cell population involved in early wound healing response and gradually covers the injured area before presumably transformed into the lost neurons. Altogether, our work systematically decoded the complex cellular and molecular dynamics of axolotl telencephalon in development and regeneration, laying the foundation for studying the regulatory mechanism of brain regeneration in the future.

developmental biology↗

bioRxiv2021

Spatially-resolved transcriptomics analyses of invasive fronts in solid tumors

Solid tumors are complex ecosystems, and heterogeneity is the major challenge for overcoming tumor relapse and metastasis. Uncovering the spatial heterogeneity of cell types and functional states in tumors is essential for developing effective treatment, especially in invasive fronts of tumor, the most active region for tumor cells infiltration and invasion. We firstly used SpaTial Enhanced REsolution Omics-sequencing (Stereo-seq) with a nanoscale resolution to characterize the tumor microenvironment of intrahepatic cholangiocarcinoma (ICC). Enrichment of distinctive immune cells, suppressive immune microenvironment and metabolic reprogramming of tumor cells were identified in the 500{micro}m-wide zone centered bilaterally on the tumor boundary, namely invasive fronts of tumor. Furthermore, we found the damaged states of hepatocytes with overexpression of Serum Amyloid A (SAA) in invasive fronts, recruiting macrophages for facilitating further tumor invasion, and thus resulting in a worse prognosis. We also confirmed these findings in hepatocellular carcinoma and other liver metastatic cancers. Our work highlights the remarkable potential of high-resolution-spatially resolved transcriptomic approaches to provide meaningful biological insights for comprehensively dissecting the tumor ecosystem and guiding the development of novel therapeutic strategies for solid tumors.

cancer biology↗

bioRxiv2021

Single-cell Stereo-seq enables cell type-specific spatial transcriptome characterization in Arabidopsis leaves

Understanding the complex functions of plant leaves requires spatially resolved gene expression profiling with single-cell resolution. However, although in situ gene expression profiling technologies have been developed, this goal has not yet been achieved. Here, we present the first in situ single-cell transcriptome profiling in plant, scStereo-seq (single-cell SpaTial Enhanced REsolution Omics-sequencing), which enabled the bona fide single-cell spatial transcriptome of Arabidopsis leaves. We successfully characterized subtle but significant transcriptomic differences between upper and lower epidermal cells. Furthermore, with high-resolution location information, we discovered the cell type-specific spatial gene expression gradients from main vein to leaf edge. By reconstructing those spatial gradients, we show for the first time the distinct spatial developmental trajectories of vascular cells and guard cells. Our findings show the importance of incorporating spatial information for answering complex biological questions in plant, and scStereo-seq offers a powerful single cell spatially resolved transcriptomic strategy for plant biology.

plant biology↗

bioRxiv2021

ADAR2-repressed RNA editing: a novel mechanism contributing to t (8:21) AML leukemogenesis

In the past decade, adenosine to inosine (A-to-I) RNA editing, which is catalyzed by adenosine deaminases acting on RNA (ADAR) family of enzymes ADAR1 and ADAR2, has been shown to contribute to the development and progression of multiple cancers; however, very little is known about its role in acute myeloid leukemia (AML) - the second most common type of leukemia making up 31% of all adult leukemia cases. Here, we found that ADAR2, but not ADAR1 and ADAR3, is specifically downregulated in core binding factor (CBF) AML with t(8;21) or inv(16). In t(8;21) AML, RUNX1-driven transcription of ADAR2 transcripts was found to be repressed by the RUNX1-ETO fusion protein. Forced overexpression of two ADAR2-regulated RNA editing targets COPA and COG3 indeed inhibits clonogenic growth of human t(8;21) AML cells. Further in vivo animal studies confirmed that ADAR2 could suppress leukemogenesis of t(8;21) AML through its RNA binding and editing capabilities. Our results suggest a novel RNA editing-mediated mechanism leading to t(8,12) AML. Key pointsO_LIADAR2, but not ADAR1 and ADAR3, was specifically downregulated in CBF-AML C_LIO_LIRUNX1-ETO suppresses ADAR2 transcription in t(8;21) AML through binding on its promoter C_LIO_LIRNA editing capability of ADAR2 is essential for its repression of leukemogenesis in an AE9a mouse model C_LI

cancer biology↗

bioRxiv2021

Nanocrown electrodes for robust and scalable intracellular recordings of cardiomyocytes for cardiotoxicity screening

Drug-induced cardiotoxicity arises primarily when a compound alters the electrophysiological properties of cardiomyocytes. Features of intracellular action potentials (iAPs) are powerful biomarkers that predict proarrhythmic risks. However, the conventional patch clamp techniques for measuring iAPs are either laborious and low throughput or not suitable for measuring electrically connected cardiomyocytes. In the last decade, a number of vertical nanoelectrodes have been demonstrated to achieve parallel and minimally-invasive iAP recordings. Nanoelectrodes show great promise, but the large variability in success rate, signal strength, and the low throughput of device fabrication have hindered them from being broadly adopted for proarrhythmia drug assessment. In this work, we developed vertically-aligned and semi-hollow nanocrown electrodes that are mechanically robust and made through a scalable fabrication process. Nanocrown electrodes achieve >99% success rates in obtaining intracellular access through electroporation, allowing reliable and simultaneous iAP recordings from up to 57 human pluripotent stem-cell-derived cardiomyocytes (hPSC-CMs). The accuracy of nanocrown electrode recordings is validated by simultaneous patch clamp recording from the same cell. Nanocrown electrodes enable prolonged iAP recording for continual monitoring of the same cells upon the sequential addition of four to five incremental drug doses. In this way, the dose-response data is self-referencing, which avoids the cell-to-cell variations inherent to hPSC-CMs. We are hopeful that this technology development is a step towards establishing an iAP screening assay for preclinical evaluation of drug-induced arrhythmogenicity.

bioengineering↗

bioRxiv2021

Taxonomy Analysis in Bacteria Kingdom based onProtein Domain: A Comparison Study

The taxonomy research on the bacterial kingdom is important and can be usually conducted by the analysis on conserved genes, 16s rRNA, protein domain, and so on. Comparatively, the protein domains maintain a most direct relationship with phenotypes. In this paper, based on the protein domain, we propose a 3-step framework to standardize the classification process of bacteria. Different model candidates are involved and discussed in each step. By comparing the classification results with existing taxonomy, we select the most appropriate candidate to improve the framework, and furthermore, discuss their biological significance. Finally, we put forward taxonomy suggestions based on the best classification results. Significance StatementWe standardize a 3-step framework to carry out bacterial taxonomy research based on protein domain. Furthermore, we filter out the best solution in each step that can together generate the most appropriate classification result, and at the same time, we discuss the biological significant it indicates. Finally, we propose suggestions on NCBI bacterial taxonomy based on the classification results.

bioinformatics↗

bioRxiv2021

A non-bactericidal cathelicidin provides prophylactic efficacy against bacterial infection by driving phagocyte influx

The roles of bactericidal cathelicidins against bacterial infection have been extensively studied. However, the anti-bacterial property and mechanism of action of non-bactericidal cathelicidins are rarely known. Herein, a novel naturally occurring cathelicidin (PopuCATH) from tree frog (Polypedates puerensis) didnt show any direct anti-bacterial activity in vitro. Intriguingly, intraperitoneal injection of PopuCATH before bacterial inoculation significantly reduced the bacterial load in tree frogs and mice, and reduced the inflammatory response induced by bacterial inoculation in mice. PopuCATH pretreatment also increased the survival rates of septic mice induced by a lethal dose of bacterial inoculation or cecal ligation and puncture (CLP). Intraperitoneal injection of PopuCATH significantly drove the leukocyte influx in both frogs and mice. In mice, PopuCATH rapidly drove neutrophil, monocyte/macrophage influx in mouse abdominal cavity and peripheral blood with a negligible impact on T and B lymphocytes, and neutrophils, monocytes/macrophages, but not T and B lymphocytes, were required for the preventive efficacy of PopuCATH. PopuCATH did not directly act as chemoattractant for phagocytes, but PopuCATH obviously drove phagocyte migration when it was cultured with macrophages. PopuCATH significantly elicited chemokine/cytokine production in macrophages through activating p38/ERK mitogen-activated protein kinases (MAPKs) and NF-{kappa}B p65. PopuCATH markedly enhanced neutrophil phagocytosis via promoting the release of neutrophil extracellular traps (NETs). Additionally, PopuCATH showed low side effects both in vitro and in vivo. Collectively, PopuCATH acts as a host-based immune defense regulator that provides prophylactic efficacy against bacterial infection without direct antimicrobial effects. Our findings reveal a non-bactericidal cathelicidin which possesses unique anti-bacterial action, and highlight the potential of PopuCATH to prevent bacterial infection.

immunology↗

bioRxiv2021

Reassortment Network of Influenza A Virus

Influenza A virus (IAV) genomes are composed of eight single-stranded RNA segments. Genetic exchange through reassortment of the segmented genomes often endows IAVs with new genetic characteristics, which may affect transmissibility and pathogenicity of the viruses. However, a comprehensive understanding of the reassortment history of IAVs remains lacking. To this end, we assembled 40296 whole-genome sequences of IAVs for analysis. Using a new clustering method based on Mean Pairwise Distances in the phylogenetic trees, we classified each segment of IAVs into clades. Correspondingly, reassortment events among IAVs were detected by checking the segment clade compositions of related genomes under specific environment factors and time period. We systematically identified 1927 possible reassortment events of IAVs and constructed their reassortment network. Interestingly, minimum spanning tree of the reassortment network reproved that swine act as an intermediate host in the reassortment history of IAVs between avian species and human. Moreover, reassortment patterns among related subtypes constructed in this study are consistent with previous studies. Taken together, our genome-wide reassorment analysis of all the IAVs offers an overview of the leaping evolution of the virus and a comprehensive network representing the relationships of IAVs. AvailabilitySource code freely available for download at https://github.com/ElevenStr/IAVreassortment, implemented in python. Lead Contactbioren@163.com

evolutionary biology↗

bioRxiv2021

Integrating convolution and self-attention improves language model of human genome for interpreting non-coding regions at base-resolution

Interpretation of non-coding genome remains an unsolved challenge in human genetics due to impracticality of exhaustively annotate biochemically active elements in all conditions. Deep learning based computational approaches emerge recently to help interpretating non-coding regions. Here we present LOGO (Language of Genome), a self-attention based contextualized pre-trained language model containing only 2 self-attention layers with 1 million parameters as a substantially light architecture that applies self-supervision techniques to learn bidirectional representations of unlabeled human reference genome. LOGO is then fine-tuned for sequence labelling task, and further extended to variant prioritization task via a special input encoding scheme of alternative alleles followed by adding a convolutional module. Experiments show that LOGO achieves 15% absolute improvement for promoter identification and up to 4.5% absolute improvement for enhancer-promoter interaction prediction. LOGO exhibits state-of-the-art multi-task predictive power on thousands of chromatin features with only 3% parameterization benchmarking against fully supervised model, DeepSEA and 1% parameterization against a recent BERT-based language model for human genome. For allelic-effect prediction, locality introduced by one dimensional convolution shows improved sensitivity and specificity for prioritizing non-coding variants associated with human diseases. In addition, we apply LOGO to interpret type 2 diabetes (T2D) GWAS signals and infer underlying regulatory mechanisms. We make a conceptual analogy between natural language and human genome and demonstrate LOGO is an accurate, fast, scalable, and robust framework to interpret non-coding regions for global sequence labeling as well as for variant prioritization at base-resolution.

bioinformatics↗

bioRxiv2021

DeepConsensus: Gap-Aware Sequence Transformers for Sequence Correction

Pacific BioScience (PacBio) circular consensus sequencing (CCS) generates long (10-25 kb), accurate "HiFi" reads by combining serial observations of a DNA molecule into a consensus sequence. The standard approach to consensus generation uses a hidden Markov model (pbccs). Here, we introduce DeepConsensus, which uses a unique alignment-based loss to train a gap-aware transformer-encoder (GATE) for sequence correction. Compared to pbccs, DeepConsensus reduces read errors in the same dataset by 42%. This increases the yield of PacBio HiFi reads at Q20 by 9%, at Q30 by 27%, and at Q40 by 90%. With two SMRT Cells of HG003, reads from DeepConsensus improve hifiasm assembly contiguity (NG50 4.9Mb to 17.2Mb), increase gene completeness (94% to 97%), reduce false gene duplication rate (1.1% to 0.5%), improve assembly base accuracy (Q43 to Q45), and also reduce variant calling errors by 24%.

bioinformatics↗

bioRxiv2021

Effective Ensemble of Deep Neural Networks Predicts Neural Responses to Naturalistic Videos

This report provides a review of our submissions to the Algonauts Challenge 2021. In this challenge, neural responses in the visual cortex were recorded using functional neuroimaging when participants were watching naturalistic videos. The goal of the challenge is to develop voxel-wise encoding models which predict such neural signals based on the input videos. Here we built an ensemble of models that extract representations based on the input videos from 4 perspectives: image streams, motion, edges, and audio. We showed that adding new modules into the ensemble consistently improved our prediction performance. Our methods achieved state-of-the-art performance on both the mini track and the full track tasks.

neuroscience↗

bioRxiv2021

Overexpression of SHORT-ROOT2 transcription factor enhanced the outgrowth of mature axillary buds in poplar trees

O_LIPlant branching is usually prevented by an actively proliferating apex. In poplars, one GRAS family member, SHORT-ROOT2 (PtSHR2), was preferentially expressed in axillary buds (AXBs) and was inducible during bud maturation and activation. Overexpression of PtSHR2 (PtSHR2OE) in hybrid poplar impaired the apical dominance and simultaneously promoted the outgrowth of axillary branches below the maturation point (BMP), accompanied by regulated expression of genes critical for axillary meristem initiation and bud formation. C_LIO_LIFollowing a detained phenotypic characterization, we compared the IAA and trans-zeatin levels in apical shoots and AXBs of wild-type and PtSHR2OE trees, together with gene expression analyses and defoliation, decapitation, and hormone reapplication assays. C_LIO_LIPtSHR2OE AXBs contained a significantly lower ratio of auxin to cytokinin than wild-type AXBs, particularly in those below the BMP. Decapitation induced a faster bud burst in PtSHR2OE trees than in wild-type plants, and it could be strongly inhibited by exogenously applied auxin and cytokinin biosynthesis inhibitor, but only partially inhibited by N-1-naphthylphthalamic acid (NPA). C_LIO_LIAn impaired basipetal auxin transport, rather than an insufficient auxin biosynthesis or auxin insensitivity, disturbed the local hormonal homeostasis in PtSHR2OE AXBs, which in turn enhanced the axillary bud initiation and promoted the bud release. C_LI HighlightOverexpression of PtSHR2 in poplar impaired the apical dominance and promoted axillary bud outgrowth below the maturation point through disturbing the basipetal auxin transport and auxin and cytokinin homeostasis.

genetics↗

bioRxiv2021

CD49a Identifies Polyfunctional Memory CD8 T cell Subsets that Persist in the Lungs after Influenza Infection

CD8 T cell memory offers critical antiviral protection, even in the absence of neutralizing antibodies. The paradigm is that CD8 T cell memory within the lung tissue consists of a mix of circulating TEM cells and non-circulating TRM cells. However, based on our analysis, the heterogeneity within the tissue is much higher, identifying TCM, TEM, TRM, and a multitude of populations which do not perfectly fit these classifications. Further interrogation of the populations shows that TRM cells that express CD49a, both with and without CD103, have increased and diverse effector potential compared with CD49a negative populations. These populations function as a one-man band, displaying antiviral activity, chemokine production, release of GM-CSF, and the ability to kill specific targets in vitro with delayed kinetics compared with effector CD8 T cells. Together, this study establishes that CD49a defines multiple polyfunctional CD8 memory subsets after clearance of influenza infection, which act to eliminate virus in the absence of direct killing, recruit and mature innate immune cells, and destroy infected cells if the virus persists. Contribution to the fieldProtection from previously seen infections requires specialized immune memory cells properly positioned throughout the body to combat the newly invading pathogen. In the case of re-exposure to influenza virus, CD8 T cells resident within the respiratory tract (TRM) are critical for eliminating the virus. Previously, TRM were viewed as mostly homogenous, with a limited range of immune functions. In this study, lung TRM were compared with circulating memory CD8 T cells transiently present within the lung, to define the breadth of their effector capabilities. Using TRM defining surface proteins CD49a and CD103 to identify different memory CD8 T cell subsets, gene and protein expression were evaluated. In addition to demonstrating higher levels of diversity than previously reported, multiple polyfunctional subsets were identified. This polyfunctionality was primarily associated with cell populations expressing CD49a, and these cells produced multiple antiviral factors, chemokines to recruit other immune cells, a growth factor associated with improved antigen presenting cell function, and cytolytic granules. Functional assays further demonstrated killing of target cells by TRM. This study paints a more holistic, complete picture of the phenotype and functions of lung CD8 T cells after viral infection, revealing CD49a as a marker of cells with high effector capacity.

immunology↗

bioRxiv2021

A network-based approach reveals the dysregulated transcriptional regulation in non-alcohol fatty liver disease

Non-alcohol-related fatty liver disease (NAFLD) is a leading cause of chronic liver disease worldwide. We performed network analysis to investigate the dysregulated biological processes in the disease progression and revealed the molecular mechanism underlying NAFLD. Based on network analysis, we identified a highly conserved disease-associated gene module across three different NAFLD cohorts and highlighted the predominant role of key transcriptional regulators associated with lipid and cholesterol metabolism. In addition, we revealed the detailed metabolic differences between heterogenous NAFLD patients through integrative systems analysis of transcriptomic data and liver-specific genome-scale metabolic model. Furthermore, we identified transcription factors (TFs), including SREBF2, HNF4A, SREBF1, YY1 and KLF13, showing regulation of hepatic expression of genes in the NAFLD-associated modules and validated the TFs using data generated from a mouse NAFLD model. In conclusion, our integrative analysis facilitated our understanding of the regulatory mechanism of these perturbed TFs and associated biological processes.

systems biology↗

bioRxiv2021

Frequency-specific coactivation patterns in resting-state and their alterations in schizophrenia: an fMRI study

The resting-state human brain is a dynamic system that shows frequency-specific characteristics. Coactivation pattern (CAP) analysis has been recently used to identify recurring brain states sharing similar coactivation configurations. However, whether and how CAPs differ across different sub-frequency bands are unknown. In the current study, in addition to the typical low-frequency range (0.01 - 0.08 Hz), the spatial and temporal characteristics of CAPs in four sub-frequency bands, slow-5 (0.01 - 0.027 Hz), slow-4 (0.027 - 0.073 Hz), slow-3 (0.073 - 0.198 Hz), and slow-2 (0.198 - 0.25 Hz), were studied. Six CAP states were obtained for each band., The CAPs from the typical frequency range were spatially largely overlapped with those in slow-5, slow-4 and slow-3 but not with those in slow-2. With the increase of frequency, the CAP state became more unstable and resulted in an overall shorter persistence. The spatial and temporal characteristics of slow-4 and slow-5 were further compared, because they constitute most power of the resting-state fMRI signals. In general, slow-4 showed stronger coactivations or co-deactivations in subcortical regions, while slow-5 showed stronger coactivations or co-deactivations in large-scale cortical networks such as the dorsal attention network. Lastly, frequency-dependent dynamic alterations were also observed in schizophrenia patients. Combining the information obtained from both slow-5 and slow-4 increased the classification accuracy of schizophrenia patients than only using the typical range. In conclusion, our results revealed that the spatial and temporal characteristics of CAP state varied at different frequency bands, which could be helpful for identifying brain alterations in schizophrenia.

neuroscience↗

bioRxiv2021

Neuronal mechanism of a BK channelopathy in absence epilepsy and movement disorders

A growing number of gain-of-function (GOF) BK channelopathy have been identified in patients with epilepsy and paroxysmal movement disorders. Nevertheless, the underlying pathophysiology and corresponding therapeutics remain obscure. Here we utilized a knock-in mouse model carrying human BK-D434G channelopathy to investigate the neuronal mechanism of BK GOF in the pathogenesis of epilepsy and movement disorders. We found that the BK-D434G mice manifest the clinical features of absence epilepsy and exhibit severe motor deficits. BK-D434G mutation causes hyperexcitability of cortical pyramidal neurons and cerebellar Purkinje cells, which contributes to the pathogenesis of absence seizures and the motor defects, respectively. A BK channel blocker paxilline potently suppresses BK-D434G-induced hyperexcitability and effectively mitigates absence seizures in mice. Our study thus uncovered a neuronal mechanism of BK GOF in absence epilepsy and provided the evidence that BK inhibition is a promising therapeutic strategy to mitigate BK GOF-induced neurological disorders. SignificanceDysfunction of BK channels or BK channelopathy has been increasingly implicated in diverse neurological disorders including epilepsy, movement, cognitive and neurodevelopmental disorders. However, precision medicine to treat BK channelopathy is lacking. Here we characterized a mouse model carrying a gain-of-function BK channelopathy D434G from a large family of patients with absence epilepsy and involuntary movement disorders. The BK-D434G mice resemble the clinical manifestations of absence seizures and exhibit severe motor defects. The hyperexcitability in BK-D434G cortical neurons and cerebellar Purkinje cells underscores the neuronal mechanism of BK gain-of-function induced absence epilepsy and movement disorders. The effectiveness of a BK channel blocker on preventing absence seizures suggests that BK inhibition is a promising strategy to treat gain-of-function BK channelopathy.

neuroscience↗

bioRxiv2021

Computational mechanisms for neural representation of words

A critical way for humans to acquire, represent and communicate information is through language, yet the underlying computation mechanisms through which language contributes to our word meaning representations are poorly understood. We compared three major types of word computation mechanisms from large language corpus (simple co-occurrence, graph-space relations and neural-network-vector-embedding relations) in terms of the association of words brain activity patterns, measured by two functional magnetic resonance imaging (fMRI) experiments. Word relations derived from a graph-space representation, and not neural-network-vector-embedding, had unique explanatory power for the neural activity patterns in brain regions that have been shown to be particularly sensitive to language processes, including the anterior temporal lobe (capturing graph-common-neighbors), inferior frontal gyrus, and posterior middle/inferior temporal gyrus (capturing graph-shortest-path). These results were robust across different window sizes and graph sizes and were relatively specific to language inputs. These findings highlight the role of cumulative language inputs in organizing word meaning neural representations and provide a mathematical model to explain how different brain regions capture different types of language-derived information.

neuroscience↗