Biology subjects

Liu, Z.

Publications and source records attributed to Liu, Z..

At least 91 records · Page 5Linked to original sources

bioRxiv2026

Foundation Model RNAGAN Enhances Biomedical Insight of Nasopharyngeal Carcinoma Metastasis

RNAGAN (version 2.0, https://github.com/ZhaozhengHou-HKU/RNAGAN-2.0.git) is a published foundation model that analyzes single-cell and bulk-level RNA sequencing samples and enables multiple applications that enhance medical insights. Here we applied this model to Nasopharyngeal Carcinoma (NPC) as in-context few-short format (i.e., the model was never trained with any NPC data). We conducted all four supported functions, which include sample stratification, vectorization, pseudo data generation, and marker identification. The results were then used for identifying metastatic NPC and to investigate mechanisms associated with NPC metastasis. Examination with stratification showed that the accuracy of RNAGAN results for evaluating the metastasis risk in NPC patients are comparable to or outcompeted recently published risk estimation linear prediction model. Vectorization results present consistency across multiple cohorts and RNAGAN model versions. In the task of identifying markers and mechanisms related to NPC metastasis, incorporating pseudo data substantially enhanced the representativeness of single-cohort-based differential expression (DE) analysis. Moreover, RNAGAN identified metastasis-related marker genes based on single cohort, were concordant with the ground truth obtained across multiple cohorts (p=1.05e-9). Regarding biomedical mechanisms, RNAGAN enabled second-order feature extraction, unveiling a remarkable domination of the protective function of adaptive immune responses (as indicated by IL21R levels) over the hazardous function of chronic, non-resolving innate inflammation (as indicated by S100A8 levels) against NPC metastasis after first-line treatment. This association demonstrates a high degree of consistency with the external cohort. This study demonstrates the utility of the foundation model RNAGAN in uncovering therapeutic insights for novel cancer types without extra training. We reveal a critical spatial mechanism preventing distant metastasis via humoral anti-tumor immunity in NPC. High S100A8 expression by innate antigen-presenting cells (APCs) triggers an inflammatory cascade promoting epithelial-mesenchymal transition (EMT) and metastasis. However, when germinal center IL21R+ B cells simultaneously colocalize with these innate signals, they override this suppressive tissue stress. Spatial analysis shows that a high S100A8/IL21R intersection within tumor regions strictly distinguishes treatment responders, whereas non-responders display spatial mismatch or S100A8+ hyper-infiltration. This coordinated innate-adaptive cross-talk sustains functional tertiary lymphoid structures (TLS) that mature IgG-secreting plasma cells, which opsonize and eliminate emerging EMT tumor cells before systemic escape. Consequently, while S100A8 alone is an unreliable prognosticator, its spatial colocalization with IL21R is a robust protective indicator overlooked by conventional bulk analysis methods.

cancer biology↗

bioRxiv2026

Pre-existing levels of pro-survival proteins and induction of BCL-XL dictate cell fate after p53 activation

TP53 (also called TRP53 or p53) is a critical tumour suppressor that prevents cancer development by inducing a transcriptional program which can lead to diverse cellular responses, most prominently, cell proliferation arrest/senescence with survival of cells or cell death by apoptosis. Why distinct cell types undergo different outcomes after p53 activation remains unclear. Using integrated RNA-sequencing, proteomic and functional analyses across a diverse range of murine primary cell types, we demonstrate that cell fate is governed by the balance between pro-survival BCL-2 and pro-apoptotic BH3-only proteins. Cells resistant to apoptosis displays a higher starting ratio of pro-survival BCL-2 to pro-apoptotic BH3-only proteins, along with transcriptional upregulation of the pro-survival gene Bcl2l1, encoding BCL-XL. This control of cell fate is also seen in human wild-type p53 cancer cell lines. These findings reveal the mechanism for understanding p53-driven cell fate decisions, suggest therapeutic strategies to shift p53-induced cell proliferation arrest/senescence toward apoptotic cell death and allowed generation of an RNAseq data-based predictor of outcome for cancer cells after p53 activation.

cancer biology↗

bioRxiv2026

IgG4⁺ plasma cell enrichment and {lambda}-chain-biased BCR remodeling drive low-grade autoimmunity in chronic obstructive pulmonary disease

BackgroundThis study aimed to elucidate B cell subset pathology in COPD, a poorly characterized area, with a focus on its similarities to and differences from classical autoimmune disorders. MethodsThe single-cell RNA-sequencing (scRNA-seq) data from COPD and autoimmune diseases were obtained from Gene Expression Omnibus (GEO) for comparative analyses of B cell subsets and functions via differentially expressed genes (DEGs), KEGG, protein-protein interaction (PPI), and cell-cell communication analyses. Serum IgG4 was measured by ELISA and correlated with clinical parameters. The peripheral blood B cells were sorted by flow cytometry for single-cell B cell receptor (BCR) sequencing. A v-Abl/Bcl2 pro-B cell line was stimulated with cigarette smoke extract (CSE) to assess abnormal development in vitro. ResultsIn lung tissue, IgG4+ plasma cells were enriched and expressed BCR activation/inflammatory genes and TNF/NF-{kappa}B/MAPK pathways. Serum IgG4 concentrations correlated negatively with pre-and post-bronchodilator FEV1/FVC. B cell interacted with monocytes, macrophages, fibroblasts and endothelial cells via IL-1{beta}/IL-6, integrin and chemokine signalling, contributing to chronic inflammation and remodelling. In peripheral blood, transitional T1 B cells were increased, accompanied by {lambda}-chain enrichment and increased IGLV1-47 usage, as well as enrichment of autoimmune pathways. In the bone marrow, the numbers of pre-B I cells were increased while those of small pre-B III cells were reduced, with altered expression of BCR development genes. CSE stimulation of the pro-B cell line reduced {lambda}5 expression in a concentration-dependent manner. ConclusionsThe autoimmune abnormalities in COPD appear more restricted, although IgG4 antibody generation may contribute to immune-mediated lung damage.

immunology↗

bioRxiv2026

Tirzepatide attenuates atherosclerosis through weight loss-independent anti-inflammatory mechanisms

BackgroundAtherosclerosis is a chronic inflammatory vascular disorder with persistent residual inflammation even after standard lipid-lowering therapy. Mounting evidence from bench to bedside suggests that diabetes and obesity accelerate atherosclerosis development. Tirzepatide (TZP), a dual Glucagon-Like Peptide-1 Receptor/Glucose-Dependent Insulinotropic Polypeptide Receptor (GLP-1R/GIPR) agonist approved for treating diabetes and obesity, has demonstrated proven cardiometabolic efficacy in large cardiovascular outcome trials. However, it remains largely uncertain whether TZP attenuates atherosclerosis independent of its anti-diabetic and anti-obese effects through direct actions on the vasculature. MethodsWe established atherosclerotic mouse models under diabetic, obese, and non-diabetic/non-obese conditions. Analysis of covariance (ANCOVA) and pair-feeding experiments were applied to experimentally decouple weight-dependent metabolic improvement from intrinsic vasculoprotection. Molecular and cell biological assays in human umbilical vein endothelial cells (HUVECs) and human aortic endothelial cells (HAECs) were performed to dissect the underlying signaling mechanisms. ResultsTZP markedly reduced aortic plaque burden and inflammation, restrained necrotic core enlargement, and improved plaque stability across all experimental mouse models. Both ANCOVA and pair-feeding experiments confirmed that these atheroprotective effects were independent of food intake and body weight loss. Furthermore, TZP attenuated systemic and vascular inflammation in Tumor Necrosis Factor- (TNF)-treated C57BL/6J mice, and this protection occurred without changes in body weight or blood glucose levels. Mechanistically, TZP directly targeted endothelial cells and activated the cyclic adenosine monophosphate (cAMP)/protein kinase A (PKA)/endothelial nitric oxide synthase (eNOS) pathway, increased eNOS phosphorylation and nitric oxide bioavailability, consequently downregulating the expression of the pro-inflammatory adhesion molecules Vascular Cell Adhesion Molecule-1 (VCAM-1) and Intercellular Adhesion Molecule-1 (ICAM-1). ConclusionsTZP arrests atherosclerosis progression through weight loss-independent anti-inflammatory mechanisms. These findings implicate TZP as a promising therapeutic drug for mitigating residual vascular inflammation in patients with atherosclerotic cardiovascular disease (ASCVD), irrespective of glycemic status or obesity. Clinical PerspectiveO_ST_ABSWhat Is New?C_ST_ABSO_LITirzepatide exerts direct anti-atherosclerotic effects in preclinical mouse models of atherosclerosis under diabetic, obese, and non-obese conditions. C_LIO_LITirzepatide directly targets endothelial GLP-1R/GIPR and downstream cAMP/PKA/eNOS signaling pathway to suppress NF-{kappa}B-driven vascular inflammation, thereby uncovering a previously unrecognized vasculoprotective mechanism underlying its cardiovascular benefits C_LI What Are the Clinical Implications?O_LITirzepatide exerts direct vascular protective effects independent of body weight reduction, suggesting that its cardiovascular benefits may extend beyond glycemic control and obesity management. C_LIO_LITirzepatide may represent a promising therapeutic drug for addressing residual vascular inflammation in ASCVD patients, including those without overt diabetes or obesity C_LI

physiology↗

bioRxiv2026

Lineage-aware stochastic modeling reveals gene-expression dynamics in development and disease

Gene expression changes along cell lineages, but most single-cell RNA-seq analyses treat cells as independent snapshots and ignore their phylogenetic relationships. Here we present LaVOUS, a lineage-aware probabilistic framework for modeling sparse single-cell gene-expression counts on reconstructed lineage trees. LaVOUS couples Brownian motion and Ornstein-Uhlenbeck models of latent transcriptional dynamics with negative-binomial observation models and scalable variational inference, enabling likelihood-based tests for gene-expression heritability, branch-specific expression shifts, and ancestral expression reconstruction. In simulations, LaVOUS improved detection of lineage-associated expression changes over Gaussian phylogenetic models and accurately reconstructed expression histories across expression levels. Applied to lineage-resolved single-cell datasets from metastatic lung cancer, class-switching B cells, and the developing brain, LaVOUS identified expression changes associated with metastatic progression, isotype switching, and neuronal differentiation. LaVOUS provides a general framework for studying single-cell expression dynamics across development and disease.

bioinformatics↗

bioRxiv2026

Parental transport induces a dormant state while maintaining oxytocin recruitment in poison frog tadpoles

Parental care can have pervasive effects on offsprings neurodevelopment. Parent-offspring interactions are often modulated by the neuropeptide oxytocin, which is responsible for the development of social bonds. The development of the oxytocinergic system is dependent on the quality of parental care during the post-natal phase. However, it is yet unknown how post-natal direct interactions can influence the development of the oxytocinergic pathway. Here we tested how an obligate parental care behaviour, tadpole transport in poison frogs, influences the development of the oxytocinergic pathway. To this end, we quantified whole brain expression of oxytocin receptor and oxytocin precursor throughout three developmental stages of A. femoralis tadpoles, before, during and after tadpole transport. Our results show an overall downregulation during tadpole transport, which indicates that during transport tadpoles enter a dormant state to slow down development until they are placed in water. Interestingly, the expression of oxytocin precursor did not vary between the three developmental stages. This might indicate that oxytocin is being recruited during transport, but does not lead to neurodevelopmental changes. In sum, here we present the first evidence of a dormant state during tadpole transport which might be an adaptive response to the terrestrial reproduction in poison frogs.

neuroscience↗

bioRxiv2026

A multi-organ spatial metabolomic atlas of exercising mice reveals neuronal Complex I as a convergent and sufficient axis for tau pathology reduction in PS19

We constructed a spatially resolved metabolomic atlas of long-term exercise across six major organs in wild-type mice: brain, heart, lung, liver, kidney, and skeletal muscle, cataloguing 224 metabolic features and revealing coordinated inter-organ remodeling. Surprisingly, the brain showed particularly pronounced region-specific adaptation. Because pathological tau associates with synaptic mitochondria from early stages of tauopathy, we extended this multi-organ spatial metabolomic approach to PS19 mice and found that exercise reduced over 70% of observable tau pathology in PS19 hippocampus and restored the mitochondrial-related metabolome. Integrated proteomic and spatial metabolomic analyses identified NADH dehydrogenase Complex I as the convergent node. To test this finding biologically, we expressed the yeast NADH dehydrogenase, Ndi1, in PS19 neurons in the absence of exercise. This increased cerebral antioxidants, restored shuttle-linked metabolites, and reduced tau pathology. Increasing NADH dehydrogenase activity through NDI1 reproduces the core anti-tau and metabolic effects of exercise. These findings provide a molecular mechanism for how exercise may prevent or slow tau pathology accumulation, complementing the human-cohort literature linking exercise to delayed cognitive decline.

neuroscience↗

bioRxiv2026

Ancient admixture catalyzes homoploid hybrid speciation and intense genomic erosion in Asian langurs

Ancient admixture catalyzes evolutionary innovation, yet its long-term genomic consequences for newly formed lineages remain poorly understood. Here, based on 53 genomes covering 19 species of the Asian langur genus Trachypithecus, we explore admixtures role in shaping a reticulated radiation. Genome-wide analyses of phylogenomic triplet topologies demonstrate that phylogenetic discordance across this radiation is primarily driven by widespread introgression rather than incomplete lineage sorting. To mitigate historical noise and resolve the ancestral species tree, we anchored our phylogenetic analysis on the X-linked recombination desert (XLRD), which exhibits an 84.5% introgression reduction compared to autosomes. We identify Delacours langur as a clear case of homoploid hybrid speciation, arising from ancient admixture with [~]70:30 genomic contributions from ancestral northern and southern limestone langur lineages. This hybrid species fixed key reproductive isolation loci; notably, alternate inheritance of pigmentation genes (SLC45A4, HPS5, ADCY10) systematically coupled with a fixed RNF175 chimeric allele to drive its diagnostic pelage phenotype. This illustrates how introgressed multi-gene networks rapidly establish prezygotic visual barriers and profound phenotypic divergence. However, subsequent spatial isolation within fragmented karst landscapes forced a major conversion of genetic burden into realized load. Genome-wide, over 82% of loss-of-function variants occur in a homozygous state, reflecting the expression of lethal recessive mutations within long runs of homozygosity. Together, our findings demonstrate that ancient admixture can trigger homoploid hybrid speciation, yet subsequent ecological restriction locks derived lineages into severe, long-term genomic erosion, revealing a fundamental trade-off in reticulate evolutionary radiations.

evolutionary biology↗

bioRxiv2026

Homeobox transcription factor MSX2 down-regulates ERα action to facilitate anti-estrogensensitivity in ERα+ breast cancer

Breast cancer is the most common malignancy among women worldwide. Estrogen receptor (ER)-positive breast cancer is about 70% in the total breast cancer. It has variable prognosis and high recurrent risk, frequently developing resistance to endocrine therapies. Herein, we have identified that a homeobox transcription factor MSX2 downregulated in ER-positive breast cancer is correlated with the advanced grade and poor survival outcomes. Our results have demonstrated that MSX2 interacts with ER to inhibit ER-mediated transactivation. Mechanistically, MSX2 associates with HDAC1/HDAC2 to form a protein complex. MSX2 is required for recruitment of HDAC1/HDAC2 complex to estrogen response elements (EREs) region on ER downstream target genes, reducing histone H3K9ac and H3K27ac levels to inactivate gene transcription. Functionally, ectopic expression of MSX2 suppresses cell growth and enhances the sensitivity to anti-estrogen treatment in ER-positive breast cancer cells. Our results indicate that MSX2 as a novel co-repressor of ER is involved in suppression of ER-positive breast cancer progression. Restoring MSX2 protein may provide a promising strategy to overcome endocrine resistance in ER-positive breast cancer.

Molecular Biology↗

bioRxiv2026

Super-Resolved Single Small Extracellular Vesicle Assay enabled by a Plasmonic Nanohole Array

The accurate quantification of biological nanoparticles, such as small extracellular vesicles (sEVs), is fundamentally hindered by a resolution-coincidence trade-off in digital assays. While physical confinement can isolate single particles, conventional optical readouts remain diffraction-limited, causing multi-particle occupancy to be miscounted as single events and thereby restricting the analytical dynamic range. Here, we report a nanoplasmonic platform that overcomes this limit by introducing a geometry-defined interface that uniquely unifies nanoscale compartmentalisation and near-field-assisted super-resolution imaging. Utilising a gold plasmonic nanohole array, the strict geometric periodicity of the lattice simultaneously serves as a template for single-vesicle confinement and a deterministic grid that generates an array of localised surface plasmon resonance near-field hotspots. This position-deterministic illumination pattern imposes known geometric priors on the excitation field, shifting high-spatial-frequency information into the detectable bandwidth to achieve sub-100 nm lateral resolution. This dual-purpose geometric determinism enables high-fidelity digital readout of individual vesicles with significantly fewer sub-images than stochastic, speckle-based metasurface structured illumination microscopy approaches. The assay achieves an analytical limit of detection of 143 sEVs/{micro}L, matching the performance of state-of-the-art single-EV counting technologies. It successfully differentiates distinct sEV subpopulations based on surface biomarker expression, establishing a clear pathway for future clinical liquid biopsy applications. By replacing stochastic loading and illumination with geometric design, this work establishes a robust framework for precise vesicle interrogation with broad implications for emerging translational applications and fundamental biology.

bioengineering↗

bioRxiv2026

SciCore-Omics: a tri-modal foundation model unifying histology, spatial transcriptomics and language for spatial biology

Histomorphology and spatial transcriptomics capture complementary aspects of tissue biology, but their relationships remain difficult to extract, align, and interpret at scale. Existing foundation models typically connect histology, omics, or language only pairwise, which limits their capacity to jointly infer molecular states, decode spatial tissue organization, and generate biologically grounded explanations. Here, we show SciCore-Omics, the first tri-modal foundation model linking histology images, spatial transcriptomics, and biological language. We constructed a spatially paired image-gene-text dataset comprising 151,182 spots across multiple tissues and performed a three-stage progressive training of SciCore-Omics on this dataset. Across gene expression prediction and spatial domain recognition, SciCore-Omics achieved 23.6-80.9% relative gains in task-specific metrics over the strongest external baselines. It further showed robust zero-shot generalization in histopathology classification, outperforming GPT-5 by 6.16 percentage points in mean accuracy across four benchmarks. Expert evaluation in 10 breast cancer cases confirmed its H&E-only case-level molecular reasoning capability. Together, our method demonstrates that a tri-modal framework can effectively bridge histomorphology and molecular state, providing a more general and interpretable foundation model for computational pathology and omics analysis.

bioinformatics↗

bioRxiv2026

A red-emitting, genetically encoded indicator for two-photon voltage recording in vivo

Genetically encoded voltage indicators (GEVIs) enable minimally invasive, cell-type-specific optical measurements of neuronal membrane potential with millisecond temporal resolution. Red-shifted GEVIs are especially advantageous because they permit spectral multiplexing with complementary sensors and enable all-optical circuit interrogation in combination with blue-light-activated opsins. Despite these advantages, existing red GEVIs remain poorly suited for in vivo use due to limited performance under two-photon (2P) excitation, the predominant modality for deep-tissue imaging. Here, we introduce VADER1, a red GEVI that overcomes this limitation and enables reliable spike detection in vivo under 2P illumination. Under 2P excitation, VADER1 supports extended voltage imaging with both random-access and resonant-scanning microscopy, enables recordings from neurons as deep as cortical layer 5, and allows dual-color imaging with calcium indicators. By filling a critical spectral gap, VADER1 enables integrated optical measurements of fast electrical activity alongside other neural signals and establishes a foundation for two-photon all-optical electrophysiology.

neuroscience↗

bioRxiv2026

Integrating Histology with Spatial Molecular Programs Using a Multimodal Foundation Model

Histopathological assessment remains central to cancer diagnosis and stratification, yet its mechanistic interpretation remains limited without molecular context. To address this, we developed SQUALL, a multimodal foundation model integrating histology with spatial molecular programs. For pretraining, we assembled histMol, a large-scale corpus of 1.76 billion paired histology-spatial transcriptomics spots/bins across 33 tissues and 12 platforms from 3,446 tissue sections. Following pretraining, SQUALL enables transcriptome-wide virtual biomarker profiling, prognostically relevant spatial niches discovery, and integrative disease progression modeling. Leveraging its multimodal embeddings, SQUALL identifies niches associated with tertiary lymphoid structure (TLS) maturation and ovarian cancer relapse, reconstructs molecular trajectories of breast cancer invasion across 325,112 spots, and uncovers underlying transcriptional programs. Applied to whole-slide images from 898 patients, SQUALL outperforms existing pathology foundation models in outcome prediction while enabling interpretable risk stratification. Together, these results establish spatially aligned multimodal pretraining as a new paradigm for extending molecular insights into pathology images.

bioinformatics↗

bioRxiv2026

A multimodal perturbation atlas defines the phenotypic resolution of cellular morphology.

Modeling cellular behavior requires measurements that capture how cells evolve across time, environments, and interventions. Microscopy is uniquely suited to this goal: it is non-destructive and can be applied to living cells in their native context. Yet its phenotypic resolving power remains incompletely characterized relative to molecular assays. Here, we present a multimodal perturbation atlas of 1,000 pooled CRISPR knockouts in A549 cells, profiled by fluorescence microscopy (42 live, 13 fixed markers), label-free quantitative phase imaging of the same live cells (at single timepoints), and single-cell RNA sequencing (scRNA-seq). We develop deep learning frameworks to interpret the rich cell-biological signatures in these ~65M single-cell profiles. At matched reagent cost, phase imaging exceeds the phenotypic resolution of both fluorescence imaging and scRNA-seq, and more reliably recovers higher-order pathway organization. These results establish intrinsic morphology as a high-precision readout of cellular state, and lay a foundation for live-cell profiling of phenotypic trajectories.

systems biology↗

bioRxiv2026

Electrokinetic active grooves for liposome capture, confinement, trajectory analysis and controlled release

Extracellular vesicles (EVs) are attractive candidates for minimally invasive disease monitoring. EV diagnostic signals often reside in low-abundant subpopulations, motivating single-vesicle measurements that can report distributions rather than ensemble averages. In practice, such assays rely on transient migration of a mobile vesicle through a detection region or performing cycled processing/measurement steps on vesicles permanently immobilized on surfaces via affinity-based capture. Single vesicle analysis would benefit from technologies that can combine characteristics of transient detection and surface immobilization to enable controlled capture, fixed time analysis and release of vesicles in a marker-neutral way. Here, we present electrokinetically active (RECON) grooves that provides low-voltage, programmable capture, timed retention, and release of nanoscale vesicles within microscopic grooves under continuous optical access. The platform uses a titanium embedded electrode with thin TiO2 passivation, enabling stable actuation over multi-hour experiments. Using fluorescent, size-defined liposomes as standards, we demonstrate (1) reversible, minute-long confinement at <5 V, (2) size-dependent confinement times, and (3) optical quantification of groove-guided drift velocities. Together, these results establish RECON grooves as a reusable, electrically programmable platform for controlled capture, timed retention, and release, while providing quantitative, trajectory-derived measures of confinement and transport.

biophysics↗

bioRxiv2026

Circadian misalignment underlies immune escape in breast cancer

Circadian regulation shapes tissue physiology, yet how it organizes cellular and molecular dynamics within the tumor microenvironment (TME) and influences tumor immunity remains unclear. Using temporal single-nucleus multiomic profiling of mouse breast tumors, we uncovered extensive circadian programs that are both cell-type-specific and shared across the TME, governing proliferation and immune responses. Notably, cancer epithelial cells exhibited global acrophase misalignment relative to immune populations. This intercellular desynchrony manifests as temporal decoupling between tumor proliferation and immune activation, discordant antigen presentation and T cell recognition with intrinsic activation-exhaustion overlap in T cells, and asynchronous PD-1/PD-L1 oscillations that sustain checkpoint-mediated suppression. Similar patterns were observed in human triple-negative breast cancer (TNBC). Together, these findings establish intercellular circadian misalignment as a mechanism of tumor immune evasion and position the circadian architecture of the tumor-immune ecosystem as a previously underappreciated determinant of tumor development and therapeutic response. HIGHLIGHTSO_LISingle-cell multiomics maps circadian regulation of tumor-immune programs. C_LIO_LICircadian regulation in cancer epithelial cells is misaligned with immune cell populations. C_LIO_LITumor-immune temporal misalignment undermines antitumor immunity. C_LIO_LICircadian misalignment in human TNBC suggests relevance for immunotherapy timing. C_LI

cancer biology↗

bioRxiv2026

Temporal structure of task engagement organizes infra-slow BOLD dynamics

Task-based fMRI has traditionally characterized cognitive engagement through spatial patterns of BOLD activation, leaving open whether tasks also organize activity along the frequency dimension. Here we tested whether temporally structured task engagement reshapes infra-slow BOLD dynamics, asking whether task responses are simply superimposed onto ongoing activity or instead redistribute power across the infra-slow spectrum. Across three independent fMRI datasets, task timing systematically reorganized the BOLD power spectrum. In the main visual attention dataset, periodic stimulation produced sharp stimulus-locked peaks at 0.083 and 0.125 Hz; critically, these gains were matched by a reduction concentrated within the dominant intrinsic infra-slow range (0.01-0.04 Hz), indicating redistribution rather than a simple local increase. Independent auditory and visual-motion datasets showed analogous task-frequency responses at their respective timescales, indicating that this reorganization generalizes across modalities and stimulation frequencies. The peaks were spatially related to GLM-derived activation but persisted after removal of the GLM-modeled response, indicating that this frequency-specific organization is not fully reducible to conventional task-evoked activation. These features were functionally informative: task-imposed frequencies distinguished cognitive states, predicted individual reaction time, and preserved subject-specific signatures across runs more effectively than broader spectral ranges or GLM-derived features. Finally, Jansen-Rit simulations coupled to a Balloon-Windkessel model reproduced the peaks, showing that their expression depends on balanced excitatory, inhibitory, and filter-gain regimes rather than simple amplification of input. Together, these findings indicate that task-fMRI reveals not only where cognition is localized, but how temporally structured engagement redistributes infra-slow dynamics across timescales.

neuroscience↗

bioRxiv2026

A biointegrated living brain stimulator evokes specific neural signalling

Implanted brain stimulators play a crucial role in treating various neurological disorders, including Parkinsons disease (PD), Alzheimers disease, epilepsy, and depression. However, none of the existing implanted brain stimulators can realize specific neuromodulation due to fundamental disparities in signal transmission between electrical signal-induced neuronal responses and neurotransmitter-evoked neural signalling in natural neural circuits, leading to persistent challenges in biosafety and therapeutic effectiveness. Inspired by the dopaminergic neural circuit, we report a biointegrated living brain stimulator (BBS) that integrates ferroelectric bioelectronics, dopaminergic cells, and a gelatin hydrogel matrix, enabling dopamine neurotransmitter-evoked neural signalling. In contrast to conventional brain stimulators, the BBS are capable of programmed secretion of physiological-level dopamine, specifically activating nigral dopamine pathways and restoring motor function in a rodent PD model. By integrating the advantages of both bioelectronics and medicine, this lifelike BBS offers a great promise for next-generation bioelectronics, medicine, and brain-machine interfaces.

bioengineering↗