Biology subjects

Wang, Z.

Publications and source records attributed to Wang, Z..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

PigGPA: A Domain-Constrained Agent for Porcine Genomic Breeding with Verifiable Tool Execution

Large language model agents can plan and execute scientific analyses, but successful task completion does not establish whether analytical decisions remain consistent across independent sessions or whether computations follow the parameters specified beforehand. We investigated these limitations using four genomic analysis tasks. General-purpose agents showed limited consistency in analytical decisions across repeated sessions (57.5-58.8%). Incorporating domain knowledge improved analytical performance, with reusable skills increasing mean evaluation scores from 73.44 to 89.06/100 , but did not resolve decision variability or ensure agreement between specified and executed parameters. To address these limitations, we developed an approach combining domain-constrained analytical skills with call-level execution contracts. Each tool invocation is linked to a pre-execution parameter declaration through SHA-256 hashing, with actual command-line arguments and execution records subsequently checked against the declared parameters. We implemented this approach in PigGPA, an autonomous agent for porcine genomic breeding that integrates statistical genetics, sequence-based functional prediction and multi-omics annotation. PigGPA completed all benchmark tasks with full agreement between declared and executed parameters, while its core quantitative-genetic results closely matched established software (r = 0.999-1.000). An application to loin muscle depth further demonstrated an integrated workflow from genetic association analysis to functional interpretation. These findings show that domain knowledge improves analytical performance, while direct verification of tool execution provides an additional basis for reproducible scientific computation.

bioinformatics↗

bioRxiv2026

Hierarchical distribution matching enables comprehensive characterization of common and condition-specific cell niches in spatial omics data

Deciphering cell niches in complex tissues is essential for understanding tissue structure and disease. Recent advances in spatial omics have enabled subcellular resolution and accurate cell identity mapping. However, robust delineation of cell niches and disease-associated spatial patterns remains difficult. We introduce Harmonics, a novel computational framework that systematically identifies both common and condition-specific cell niches from spatial omics data through hierarchical distribution matching. Harmonics also includes a suite of downstream modules that facilitate comprehensive niche characterization. We demonstrate its scalability, accuracy and generalizability across datasets spanning diverse species, tissues, diseases, spatial modalities, and technological platforms. For condition-agnostic datasets, Harmonics outperforms baseline methods in both accuracy and robustness, and further demonstrates the capability to resolve niche structures at finer granularity. Across diverse diseases including pulmonary fibrosis, triple-negative breast cancer, and colorectal cancer, Harmonics enables precise identification of condition-specific niches and reveals disease-associated dynamics, subtype-specific spatial patterns, and structured immune architectures. We envision Harmonics as a practical and versatile tool for spatial niche analysis that can be applied across a wide range of biological contexts and seamlessly integrated with existing spatial omics workflows.

bioinformatics↗

bioRxiv2026

DeepD enables efficient genome modeling and controllable long-context sequence generation across domains of life

Genome foundation models hold great potential for advancing biological research, but modeling diverse complex genomes and generating controllable genome-scale sequences remain challenging. We present DeepD, a phylogeny-informed sparse mixture-of-experts model operating at single-nucleotide resolution over a 1-million-token context while reducing active computation. Pretrained on unselected whole-genome sequences across all domains of life, DeepD learns genic and intergenic sequence features and supports broad sequence-to-function prediction across species. DeepD performs well in human protein fitness and disease variants effect prediction, such as BRCA1 and BRCA2, with particular strength in regulatory regions, such as promoter and transcription-factor binding sites. Expert routing captures exon-intron boundaries, transposable elements, and distal cis-regulatory elements. DeepD also generates experimentally validated core promoters with specified transcriptional strengths. Finally, the Context-Anchor-Body strategy enables generation of complete yeast chromosome sequences and megabase-scale Arabidopsis segments, preserving gene structure and order while introducing variations within natural ranges. Together, DeepD is an efficient genome foundation model that unifies accurate sequence-to-function prediction with controllable genome-scale generation, advancing predictive and generative design of complex genomes.

bioinformatics↗

bioRxiv2026

MOFI reveals dynamic multi-omics coordination during cell fate progression

Cell fate decisions are shaped by dynamic coordination across transcriptomic, chromatin, and protein layers. Time-series single-cell multi-omics assays now enable these molecular layers to be profiled across developmental stages, yet each cell is still observed only once, and the continuous multi-omics trajectories connecting discrete snapshots remain unresolved. A central challenge is therefore to jointly integrate paired omics measurements while reconstructing their shared developmental progression. Here we present Multi-Omics Fate Inference (MOFI), a dynamically constrained multi-omics integration framework designed to reconstruct continuous cell fate transitions from paired multi-omics snapshots sampled across multiple time points. MOFI jointly models omics-specific state dynamics, cross-omics correspondence, and shared population growth within a unified framework, enabling cross-omics perturbation response analysis and identification of candidate cross-omics transformation programs. Across simulated benchmarks and paired RNA-ATAC/RNA-protein time-series datasets, MOFI reconstructed continuous fate transitions, population dynamics and cross-omics changes consistent with observed measurements. In kidney organoids, MOFI captured coordinated RNA-ATAC progression of nephron lineage specification. In hematopoietic progenitors, MOFI predicted perturbation-responsive lineage redistribution and nominated multi-omics transformation programs linking transcriptional modules with protein-level responses. In neural developmental systems, MOFI resolved gradual brain organoid maturation and interneuron lineage allocation during human cortical development. Together, MOFI provides a dynamics-grounded method for converting discrete paired multi-omics snapshots into interpretable models of cell fate progression, perturbation response, and cross-omics transformation analysis.

bioinformatics↗

bioRxiv2026

Live imaging reveals oocyte membrane pre-remodeling forming permissive space for asymmetric division

Abstract Successful oocyte maturation requires first polar body (PB1) extrusion, yet how the oocyte prepares for this asymmetric event remains unclear. Live membrane imaging of mouse oocytes reveals pronounced regional heterogeneity in plasma-membrane dynamics, generating an early polarized pattern across the surface. Whereas most of the oocyte surface and its microvilli remain relatively stable, a discrete membrane domain collapses and retracts around germinal vesicle breakdown (GVBD), separating from the zona pellucida to establish a pre-extrusion space (PES). Transient oocyte comb-like protrusions arise within the PES and subsequently collapse, converting the protrusion-filled region into an open cavity before PB1 extrusion. Mechanistically, early ERK28 dependent dissociation of the cortical scaffold ZO-1 is required for this space to form. ERK2 phosphorylates ZO-1, suppresses its phase separation, and promotes its removal from the cortex. Blocking MEK-ERK signaling prevents ZO-1 dissociation, abolishes pre-extrusion space formation, and impairs PB1 extrusion, whereas ERK activation restores these events in aged oocytes. Together, our findings identify a membrane collapse-based pre-remodeling mechanism that licenses PB1 extrusion and reveal ERK-ZO-1 signaling as a key regulator of oocyte maturation.

cell biology↗

bioRxiv2026

PatientPheX: A Full-Text Biomedical Corpus for Patient-Specific Phenotype Information Extraction

Patient-specific phenotype information extraction identifiers and normalizes phenotype entities and links them with individual patients, supporting rare disease research and genotype-phenotype analysis. However, existing datasets rarely combine full-text biomedical content with detailed annotations of patients, phenotypes, related entities, and their associations. In this work, we present PatientPheX, a corpus for patient-specific phenotype information extraction comprising 200 full-text articles, primarily case reports and case series. The corpus provides mention annotations and normalization for seven biomedical entity types, together with explicit associations between patients and entities across sentences, paragraphs, and sections. Negated findings and composite phenotype mentions are also annotated. Corpus construction combines automated pre-annotation, large language model (LLM)-assisted verification, and manual review and adjudication. Benchmarks cover entity recognition and normalization and patient-phenotype association extraction using gold-standard and predicted entities. The overall document-level entity F1 was 86.95%, while phenotype F1 was 79.33%. The best relation extraction macro-F1 decreased from 84.14% with gold-standard entities to 54.98% with predicted entities, highlighting the combined challenges of phenotype extraction and patient attribution. PatientPheX provides a resource for developing and evaluating patient-centered information extraction methods and supports the construction of structured patient-level knowledge resources for phenotype-driven biomedical research.

bioinformatics↗

bioRxiv2026

Structural Basis of γδ T-Cell Receptor Crosslinking and Activation by a Spontaneously Dimerized Fab

The gamma delta T-cell receptor ({gamma}{delta} TCR) mediates {gamma}{delta} T-cell responses that are crucial for immune defense, tissue surveillance, and homeostasis. While recent studies suggest that {gamma}{delta} TCRs engage ligands multivalently, how multivalent engagement activates the {gamma}{delta} TCR remains elusive. Here, we present the structures of the V{gamma}9V{delta}2 (clone G115) TCR in both the inactive and the agonist-crosslinked active states. In the {gamma}{delta} TCR lipoprotein complex, cholesterol and phospholipids form a "barrier" that isolates CD3{zeta}{zeta} from the other subunits and likely prevents autoactivation. As an agonist, the Fab fragment of the UCHT1 antibody dimerizes upon binding the V{gamma}9V{delta}2 TCR, thereby crosslinking and activating the receptor. Cryo-EM analysis of Fab-crosslinked V{gamma}9V{delta}2 TCR identifies three Fab dimer interfaces, one between the two light chains and the other two between light and heavy chains. These Fab-Fab interfaces, together with the Fab-CD3{epsilon} interface, mediate the assembly of the V{gamma}9V{delta}2 TCR and UCHT1 Fab into 2:2 tetramers. Upon activation, the V{gamma}9V{delta}2 TCR becomes conformationally plastic and loses enriched lipids, including cholesterol and phosphatidylethanolamine. Our findings reveal a dimerization-driven activation mechanism, inform the design of rigid TCR-crosslinking agonists, and suggest multivalency-induced clustering as a general paradigm for {gamma}{delta} TCR activation.

immunology↗

bioRxiv2026

Co-targeting KRAS and BCL-2 induces pyroptosis and antitumor tertiary lymphoid structures

Mutant KRAS drives lung tumorigenesis through both cell-intrinsic and cell-extrinsic mechanisms, yet mutation subtype-specific differences in metabolic regulation and immune evasion remain incompletely understood. Here we show that the KRAS G12D mutation, particularly in the KRAS/STK11 co-mutant (KL) context, is associated with poor prognosis and a suppressed immune microenvironment characterized by impaired antigen presentation. At the cell-intrinsic level, G12D exhibits weakened interaction with hexokinase 1 (HK1), reduced spare respiratory capacity, and diminished mitochondrial stress resistance compared with G12C. Based on this mitochondrial vulnerability, we screened a panel of clinically available agents that induce mitochondrial stress and identified that co-targeting KRAS and BCL-2 synergistically triggers GSDME-mediated pyroptosis predominantly in G12D tumors. This combination further induces functional tertiary lymphoid structures (TLS) in vivo. Immune cell depletion experiments further demonstrate that the antitumor efficacy is dramatically dependent on B cells. Moreover, this treatment strategy induced membrane attack complex (MAC) deposition in situ and elicited memory antitumor responses. Collectively, these findings establish that combined KRAS and BCL-2 inhibition elicits pyroptosis and TLS formation, leading to B-cell-dependent in situ and memory antitumor immunity, providing a mechanistic rationale for targeting mitochondrial-immune crosstalk in KRAS G12D-mutant lung cancer.

cancer biology↗

bioRxiv2026

PIEZO1 marks a low neuroendocrine state and supports cisplatin tolerance in small cell lung cancer

Small cell lung cancer (SCLC) is initially sensitive to platinum chemotherapy, yet resistant disease frequently develops with altered neuroendocrine (NE) identity. The mechanisms linking these cell states to treatment tolerance remain incompletely understood. Here, we integrate chemoresistant cell models with patient bulk multiomics, single-cell and spatial transcriptomic data to investigate the mechanosensitive channel PIEZO1. In H69AR cells, PIEZO1 upregulation accompanied loss of NE markers and enrichment of mesenchymal programmes; increased PIEZO1 expression and reduced cisplatin sensitivity were also observed in H446DDP cells. Across patient-derived data sources, PIEZO1 was associated with low NE activity within malignant populations, despite its substantially higher abundance in vascular and stromal cells. State-blind CNV analyses and cross-sectional state ordering supported a cell-state association that was only weakly explained by detectable subclones and varied with hypoxia across models. Spatial analyses localized PIEZO1-rich signals to stromal and vascular interface regions, while composition-adjusted tumour-core analyses showed little residual covariance with tumour programmes. PIEZO1 depletion reduced intracellular calcium-associated signals and cisplatin IC50 and increased drug-induced apoptosis. Conversely, Yoda1 increased calcium signals and cisplatin tolerance in parental cells. Patient light-chain phosphorylation, YAP localization and partial pharmacological reversal by verteporfin supported an actomyosin-YAP-linked mechanism. PIEZO1 depletion also reduced SMAD2/3 and mesenchymal-associated readouts. Finally, transcript enrichment profiles and PIEZO1-IGF2BP2 covariation nominated a potential m6A regulatory layer. Together, these findings identify PIEZO1 as a low-NE state-associated marker and contributor to cisplatin tolerance, and motivate a calcium-cytoskeleton-YAP model for further mechanistic testing.

cancer biology↗

bioRxiv2026

Filling the Missing Puzzle: Integrating Interaction and Evolutionary Information to Enhance Protein Fitness Prediction in Inverse Folding

Protein inverse folding, which infers compatible amino acid sequences from a given backbone structure, is central to rational protein design. Current methods rely largely on sequence recovery rate as the evaluation metric, emphasizing structural compatibility but seldom addressing function. Yet functional activity depends on the proper network of non-covalent interactions-protein-ligand contacts being a prime example. We argue that function-oriented protein design is governed by three complementary constraints: structural, interaction, and evolutionary, none of which are handled in a unified manner by existing pretrained models. To bridge this gap, we introduce zPolaron, a graph neural network built on protein-ligand complexes for functional protein design. zPolaron represents residues and ligand atoms as a heterogeneous graph and jointly encodes structural, interaction, and evolutionary information by fusing physical-interaction-enhanced graph representations with ESM-2 embeddings. Across multiple fitness prediction benchmarks, zPolaron outperforms all baselines, with gains evident across structural, interaction, and evolutionary dimensions. Wet-lab experiments further confirm its utility in functional enzyme screening and design: the optimized CalA6-D205A-S160G mutant achieves a 17.84-fold improvement in activity, while the CalB-I121M mutant yields a 1.91-fold increase. Together, these results show that integrating interaction and evolutionary information fills the missing puzzle of inverse folding, enhancing protein fitness prediction beyond structural compatibility. zPolaron is available at https://github.com/zelixirSH/zPolaron.

bioinformatics↗

bioRxiv2026

Disrupted chromatin architecture blocks B lymphopoiesis in Down syndrome

Human fetal haematopoiesis requires developmental potential to be encoded before lineage identity becomes transcriptionally apparent, but whether three-dimensional genome architecture provides such information is unknown. Here we develop ChromE-seq, a scalable single-cell assay that jointly profiles chromatin conformation and transcription, and integrate it with chromatin accessibility and DNA methylation to generate a multimodal atlas of ~400,000 haematopoietic cells from disomic and trisomy 21 (T21) human fetal liver. Chromatin contacts frequently preceded lineage-specific transcription or persisted after transcription declined, revealing 3D chromatin priming and memory. Unexpectedly, B-lineage and erythroid differentiation followed opposing architectural trajectories, with progressive loss and gain of chromatin connectivity, respectively. T21 disproportionately disrupted B-lineage architecture, redistributed interactions towards shorter genomic distances and weakened an EBF1-centred regulatory circuit. Deletion of a T21-sensitive EBF1 loop anchor reproduced the CLP-to-B-progenitor bottleneck observed in T21. These findings establish 3D genome architecture as an organizing layer of human fetal haematopoiesis that links developmental potential with lineage-specific vulnerability to genomic perturbation.

genomics↗

bioRxiv2026

Chain of Structures: Connecting Reasoning and Generation for Protein Design

Scientific design requires reasoning in scientific spaces that represent the objects being designed. Building on Scinetics' Chain of Science Tokens, we present chain-of-structures (COS) as a concrete protein-design case study that connects reasoning and generation through explicit structural states. In this technical report, we apply COS to enzyme design, where catalytic function requires precise local geometry within a compatible global fold, making it a demanding test of reasoning from chemical requirements to protein structure. Starting from a reaction specification and target length, COS couples a language reasoning expert with an all-atom generation expert across four rounds: catalytic core, active site, global backbone, and complete sequence and structure. Each reasoning state directly conditions generation, and the resulting structure becomes context for the next decision. Discrete residue constraints and continuous latents connect the two experts, enabling structural supervision of the reasoning interface. On the evaluated benchmark, COS leads the compared baselines on five of six metrics, achieving 57.0% EC3 agreement and a TM-score of 0.729.

bioinformatics↗

bioRxiv2026

Reversion to the Meta Body Form of Life after Complete Cell Death in Pure Liquid Water

The prevailing view holds that simpler animate beings predating the dawn of cellular life once existed, yet they have long since vanished from the present-day Earth. Our hypothesis posits that these animate beings persist to this day. To this end, we devised a long-term experiment spanning over a decade, keeping Staphylococcus aureus (S. aureus) within a sealed aqueous system of pure water. The findings illustrated that, upon the complete cell death (CCD) of the S. aureus, as cellular remnants progressively succumbed to dissolution, the aqueous solution underwent self-purification, bringing forth a class of lipid bilayer membrane microspheres containing RNA and proteins. These structures maintained long-term sustainable stability within the thermodynamic storm of water molecules and underwent dynamic size fluctuations over time - collectively exhibited phenomena indicative of being "alive". This study reveals that the cell, upon complete cell death, undergoes reversion to a living entity simpler than the cell itself - the Meta Body (MB). The discovery of MB opens an entire re-conceptualization of what death ultimately brings.

biophysics↗

bioRxiv2026

Land use and climate warming interact to reshape global avian biodiversity through ecological filtering and homogenisation

Land-use and climate change are dominant drivers of terrestrial biodiversity change, yet are usually analysed separately although they co-occur and may interact. We integrated global bird assemblage records from PREDICTS with temperature anomalies and species' ecological characteristics to test how land use modifies biodiversity responses to climate warming across three dimensions: local abundance and richness, compositional dissimilarity among assemblages, and species occurrence across ecological groups. Land use modified warming associations for both abundance and richness. Relative to primary vegetation, warming associations were more positive in low-intensity agriculture for both responses, but more negative for richness in high-intensity agriculture and urban land. Predicted richness remained below the reference, defined as primary vegetation at temperature anomaly 0, across all modified land uses, with the largest declines in high-intensity agriculture (-17.9%) and urban land (-21.8%). Within land-use classes, greater warming exposure was generally associated with higher compositional similarity, consistent with warming associated biotic homogenisation. Occurrence models revealed ecological filtering: broad-niched generalists were favoured in warmer modified habitats, whereas range-restricted habitat specialists were filtered out under intensive land use and warming. Conservation assessments should therefore integrate land-use-warming interactions with changes in assemblage composition and ecological strategies, particularly in agricultural and urban landscapes where warming further disadvantaged range-restricted specialists.

ecology↗

bioRxiv2026

In situ architecture of the basal body reveals regionalized assembly and central pair microtubules nucleation

The basal body (BB) is essential for axoneme assembly and ciliary function, and its defects are associated with ciliogenesis disorders and ciliopathies (1,2). However, the molecular basis of the BB's region-specific transitions along the proximal-distal axis, and the mechanism by which ciliary central pair (CP) microtubules are nucleated during ciliogenesis, have remained largely unknown. Here, we resolve the subnanometer architecture of native BBs in mammalian multiciliated cells using cryo-electron tomography and subtomogram averaging, and identify 11 ciliary-base microtubule-associated proteins (CMAPs), including 5 previously uncharacterized core components. These CMAPs localize specifically along ciliary base that facilitate the triplet-to-doublet microtubule transition. We further identify luminal gamma-tubulin ring complexes (gamma-TuRCs) anchored to the microtubule wall via the augmin complex, and propose that they may serve as candidate nucleation sites for CP microtubules biogenesis. Together, these findings define a molecular blueprint of the BB and provide a structural framework for understanding how regional architectural specialization and luminal nucleation collectively drive ciliary assembly and how their dysfunction causes ciliopathies.

cell biology↗

bioRxiv2026

Mechanophenotype of synovial fibroblasts correlates with patients' pathotypes and treatment response in Rheumatoid Arthritis

The mechanical features of synovial fibroblasts may encode clinically relevant information for the management of rheumatoid arthritis. Indeed, it remains poorly understood the links between cellular and microenvironment mechanics with patient stratification and therapeutic response. Here we show that combining organotypic synovial cultures with multimodal mechanophenotyping and transcriptomics identifies distinct ''soft'' and ''stiff'' fibroblast states. Healthy and rheumatoid arthritis fibroblasts were cultured in two or three dimensions (organotypic cell cultures), alone or with endothelial cells, and characterized by high-throughput nanoindentation, picobalance measurements, digital holographic microscopy, Brillouin microscopy and RNA sequencing. Three-dimensional culture reduced single-cell Young's modulus and total mass while increasing dry-mass surface density; endothelial co-culture increased fibroblast stiffness and the longitudinal modulus of intact organotypic cultures. Stiffness-based grouping revealed transcriptional programmes related to extracellular-matrix remodelling, cytoskeletal contractility, and TGF-beta, WNT, and Hippo signalling. Mapping these signatures to publicly available rheumatoid arthritis clinical transcriptomic datasets associated the ''stiff'' state with fibrotic and myeloid-fibrotic pathotypes and treatment-refractory programmes, whereas the ''soft'' state aligned with lymphoid pathotypes and rituximab- or tocilizumab-responsive programmes. These findings support mechanophenotype-associated transcriptional signatures as potential biomarkers for rheumatoid arthritis stratification.

biophysics↗

bioRxiv2026

Priority effects influence bacterial community assembly on temperate deciduous tree leaves

Microbial community assembly on leaves (the phyllosphere) is influenced by deterministic, stochastic, and historical processes. However, the importance of historical processes such as priority effects, where the timing and order of colonization influence community assembly, has not been extensively investigated in field-based phyllosphere studies. We designed a field experiment in a temperate forest in Quebec where we inoculated five strains of Methylobacterium onto the leaves of red maple and American beech trees, either early or late during the growing season. We quantified microbial community structure throughout the season using metabarcoding of a Methylobacterium-targeting rpoB primer as well as a 16S rRNA primer targeting the entire bacterial community. We show that the effects of inoculation on bacterial communities depend on inoculation timing: early-season inoculation led to strain-specific shifts in community composition, while late-season inoculation had no significant effect. Although the effect of early-season inoculation weakened over time, early- and late-season inoculation still led to different community compositions at the end of the growing season. Our study demonstrates that priority effects contribute to the assembly of phyllosphere bacterial communities under field conditions, with arrival timing and strain identity shaping community trajectories. Considering historical processes will thus be crucial for successful microbiome management.

ecology↗

bioRxiv2026

Toward A Whole-Brain Interface Enabled by High-Resolution Surface Electrophysiology

The goal of building a whole-brain interface - capable of generating a real-time digital representation of the state of the entire central nervous system - has long been framed as a hardware challenge of recording simultaneously from ever-larger numbers of microelectrodes. Advances in high-resolution neural interfaces now enable electrophysiologic interaction with the human nervous system at spatial and temporal resolutions previously unattainable without disrupting tissue architecture or physiology. These capabilities create new opportunities for mechanistic neuroscience, neuroprosthetics, and precision-guided neurosurgery. With the advent of modern microelectrode array technology, however, the whole-brain interface has also become a data challenge. Rather than pursuing large-scale human brain recording purely through a single device placed in a single patient, we demonstrate here that systematic multi-subject aggregation, across brain regions and behavioral paradigms, in a common anatomical framework, can achieve something functionally similar to a whole-brain interface. Here we present an approach to a functional atlas of the human central nervous system derived from high-resolution surface electrophysiology recordings obtained in the first 70 patients implanted with an anatomically conformal, thin-film neural interface positioned in more than 100 locations. The atlas comprises >100,000 electrode deployments and catalogs placement across a broad range of neuroanatomic targets spanning the motor, sensory, language, auditory, and associative domains, as well as brainstem and spinal cord structures that have historically been difficult to access at high electrophysiologic resolution. Across participants, aggregated recordings reveal somatotopic organization, including digit representations that follow a lateral-to-medial ordering consistent with classical homuncular maps, with transitions between adjacent representations occurring over spatial scales of approximately 0.8 - 2.0 mm; canonical frequency-band signatures, such as movement-related beta-band suppression and focal high-gamma (70 - 200 Hz) increases during motor and speech behaviors; and task-modulated population dynamics in both evoked and spontaneous activity across cortical, brainstem, and spinal cord regions. These findings yield insight into patterns of mesoscale electrophysiological dynamics conserved across the entire human central nervous system, suggesting that fine-scale functional organization is preserved across individuals when aligned to common anatomical landmarks. We further demonstrate several applications of these high-resolution recordings, including real-time neural decoding from upper extremity motor cortex to enable real-time neuroprosthetic control, and from ventrolateral cortex to decode cortical correlates of spoken language, facial movements, and complex facial expressions of emotion, supporting initial feasibility of combined verbal and nonverbal communication interfaces. Together, these results establish a paradigm for approaching large-scale interfaces with the human brain, as well as a starting point for a scalable, extensible atlas of human electrophysiologic function designed to accelerate discovery across basic neuroscience, translational research, and clinical neurotechnology.

neuroscience↗