Biology subjects

Chen, Z.

Publications and source records attributed to Chen, Z..

At least 109 records · Page 6Linked to original sources

bioRxiv2026

Decoding Immune Reconstitution Failure in People Living with HIV through Single-cell Genomics

Immune non-responders (INRs), a subset of people living with HIV (PLWH), fail to achieve full immune reconstitution and remain at increased risk of morbidity, mortality, and non-AIDS-related illnesses. As the mechanisms underlying this impaired immune recovery remain poorly understood, we performed single-cell multi-omics profiling on peripheral blood mononuclear cells from 43 INRs, 47 immune responders and 53 healthy donors. Our dataset comprises 2,744,009 transcriptomes and 1,226,658 chromatin-accessibility profiles across 58 identified immune cell types. INRs exhibited markedly elevated inflammatory signaling, increased apoptotic activity, and dysregulation of immune-activating ligand-receptor interactions. Additionally, we identified 2,996 interaction cis-eGenes and 5,938 cis-caPeaks, and validated key cell type-specific cis-xQTL effects associated with immune reconstitution failure. Furthermore, we identified 3,551 sc-eQTLs and 872 cell-state interaction eQTLs (ieQTLs) in CD4+ T cells. A genotype-specific upregulation of OAS3 in INRs, likely regulated by STAT1, was identified based on these results. We developed scPRISM (single cell Predictive Reconstitution Immune Status Model), a multi-modal framework that integrates scRNA-seq and scATAC-seq data to perform the dual tasks of differentiating disease states and predicting gene expression from chromatin accessibility, thereby deciphering the cell type-specific cis-regulatory basis of the disease. Our study delineates the transcriptional and epigenomic landscape of immune dysregulation in INRs and provides new genetic insights into HIV-associated immune reconstitution failure. These findings offer a foundation for developing biomarkers and precision therapies to restore immune function in PLWH.

genetics↗

bioRxiv2026

FBXL21 regulates diurnal proteostasis and stress response by targeting DNAJB6 and client proteins

Circadian regulation of proteostasis, a key determinant of muscle health, remains poorly understood. Here, we identified DNAJB6, an Hsp40 (DnaJ) co-chaperone, as a substrate of the circadian E3 ligase FBXL21. FBXL21 mediated the ubiquitination-dependent proteasomal degradation of both DNAJB6 and its client proteins including Desmin; causative mutations of DNAJB6 in myopathies, however, rendered resistance to FBXL21-directed degradation. Fbxl21 KO C2C12 cells displayed aberrant accumulation of Desmin, and showed aggravated cytoplasmic accumulation of TDP-43, another DNAJB6 client protein, in heat shock response. Under timed exercise as a physiological stressor, WT mice displayed robust diurnal rhythms in the levels of stress granule markers (G3BP1 and FUS) and TDP-43 as a function of exercise timing. In contrast, the Fbxl21 hypomorph Psttm mutant mice showed elevated expression of these proteins without exercise, which was exacerbated under exercise-induced stress conditions; importantly, these abnormalities were rescued by skeletal muscle-specific FBXL21 expression. Our study elucidates a novel diurnal regulatory mechanism of skeletal muscle proteostasis via FBXL21 as a chaperone-linked E3 ligase, highlighting the FBXL21-DNAJB6 axis as a potential therapeutic target for myopathies.

cell biology↗

bioRxiv2026

DHHC3-dependent S-Acylation of CRY1 regulates its subcellular localization and repressor function in the circadian clock

The circadian clock is essential for maintaining cellular homeostasis and physiological fitness. At the molecular level, core clock proteins function via transcriptional-translational feedback loops in the cellular oscillator, and are highly regulated by post-translational modifications. Our unbiased screening of core clock proteins revealed that Cryptochrome 1 (CRY1), the central transcriptional repressor in the circadian clock, undergoes a novel post-translational modification known as S-acylation. We show that this reversible lipidation of CRY1 is required for its nuclear import and interaction with key clock components. Further, we mapped four cysteine residues as CRY1 S-acylation sites and identified DHHC3 as the primary protein acyltransferase for CRY1. Importantly, loss of CRY1 S-acylation, either via cysteine mutagenesis or genetic deletion of DHHC3, impaired CRY1 repressor function and consequently cellular circadian rhythms, suggesting that dynamic S-acylation couples cytoplasmic regulation of CRY1 and its transcriptional repressor function in the nucleus. Together, our findings identify S-acylation as a previously unknown post-translational modification of CRY1 critical for circadian clock function and establish DHHC3 as a pivotal circadian regulatory enzyme. Targeting CRY1 S-acylation or its regulatory enzymes may constitute an innovative therapeutic approach against clock-associated diseases.

biochemistry↗

bioRxiv2026

Cryptochrome Loss Drives COPD-like Lung Pathology through Disrupted Alveolar Epithelial Proliferation and Immune Homeostasis

Chronic obstructive pulmonary disease (COPD) is a progressive lung disease characterized by alveolar destruction, impaired epithelial regeneration and chronic inflammation. While circadian disruption has been linked to COPD pathogenesis, the cellular mechanisms remain unclear. Here, we identify the core clock components Cryptochrome 1 and 2 (Cry1/2) as essential regulators of alveolar epithelial cell proliferation and pulmonary immune homeostasis. Cry1/2 double knockout (dKO) mice exhibit spontaneous emphysema-like pathology, including airspace enlargement, increased lung compliance, and inflammatory cell infiltration without environmental insults. Mechanistically, Cry1/2-deficient alveolar epithelial cells display reduced proliferative capacity, and transcriptomic profiling revealed a pronounced shift toward a more proximal airway-like phenotype. Notably, these cells share a gene signature with human COPD lungs in pathways involving immune regulation. Furthermore, Cry1/2-deficient macrophages show elevated responsiveness to LPS. Bone marrow (BM) transplantation revealed that mice receiving Cry1/2 dKO BM suffer from enhanced lung inflammation without airspace enlargement, supporting a critical role of epithelial Cry1/2 in maintaining alveolar integrity. Importantly, treatment with Nobiletin, a circadian rhythm-modulating compound, mitigates NF-{kappa}B activation and ameliorates lung inflammation and structural damage in Cry1/2 dKO mice. These findings establish CRY1/2 as critical circadian regulators of epithelial cell proliferation and immune homeostasis, and highlight the therapeutic potential of targeting circadian pathways in COPD.

genetics↗

bioRxiv2026

In situ molecular architecture of the mammalian sperm nuclear vacuole

Direct identification of macromolecular complexes in their native context remains a major barrier to unbiased biological discovery. This challenge is particularly acute in mammalian sperm nuclei, in which condensed chromatin is interspersed with poorly understood phase-separated compartments termed nuclear vacuoles. Vacuoles are associated with reduced fertilization efficiency, yet their composition remains unclear. Here we combine high-resolution in situ cryo-electron tomography (cryo-ET) with AlphaFold docking to identify vacuole components as proteasomes, the proteasome activator PA200, and ferritin. In situ structures at resolutions up to 3.8 [A] reveal distinct proteasome-PA200 associations and gating states, consistent with a stepwise activation mechanism. Ferritin assemblies exhibit heterogeneous mineralization states and directly contact chromatin. Together, these findings establish the molecular organization of sperm nuclear vacuoles and implicate protein turnover and metal homeostasis in shaping the nuclear landscape, while demonstrating the power of in situ cryo-ET to resolve protein identity and conformational dynamics in native cellular environments.

biochemistry↗

bioRxiv2026

Astrocytic D1 Dopamine-Signaling Regulates Synaptic Remodeling and Cocaine Seeking

D1-type receptor (D1R)-mediated dopaminergic signaling within the nucleus accumbens shell (NAcSh) is essential for forming adaptive circuit changes that embed persistent memories associated with drug seeking and craving. While D1R is expressed in both NAcSh neurons and astrocytes, the specific contribution of astrocytic D1R to drug-related circuit plasticity remains poorly understood. Here, we demonstrate in mouse NAcSh slices that D1R agonists increase astrocytic Ca2+ activity, an effect that is attenuated by astrocyte-specific D1R knockdown. Furthermore, selective knockdown of astrocytic D1R in the NAcSh prior to cocaine self-administration inhibits cocaine-induced generation of silent synapses, therefore hampering the associated remodeling of NAcSh circuits. Behaviorally, knockdown of NAcSh astrocytic D1R expedites the extinction of cocaine seeking and reduces cue-induced reinstatement. These results identify astrocytic D1R as a fundamental component of NAcSh dopamine signaling during cocaine experience that remodels synaptic connections and neural networks underlying drug seeking and relapse.

neuroscience↗

bioRxiv2026

Automated assembly of protein complexes from cryo-EM maps with structure-informed Monte Carlo Tree Search

Structural cell biology aims to visualize functional molecules as they carry out their biological roles in their native cellular context. However, macromolecular complexes in situ have thus far been resolved predominantly at intermediate resolutions, complicating protein identification and structural modeling due to the vast combinatorial space of possible components within a proteome. Here, we developed Cryosearch, a GPU-accelerated framework for automated assembly of macromolecular complexes from proteome-scale monomer libraries. Cryosearch implements Monte Carlo tree search with correlation-based rewards to identify combinations of protein domains that collectively best explain density maps. This approach enables autonomous de novo assembly of molecular complexes from intermediate-resolution maps.

bioinformatics↗

bioRxiv2026

conMItion: an R package adjusting confounding factors for associations in multi-omics

SummaryAssociation measurements, such as mutual information (MI), are fundamental in the analysis of cancer multi-omics data for identifying cancer-related genes, gene signatures, and gene regulatory networks, thereby shedding light on tumor development, progression, and treatment. Confounding factors, including tumor purity and mutation burden, can bias association measurements in MI, potentially leading to the misclassification of passenger events as drivers. Conditional mutual information (CMI) provides a robust framework for assessing both linear and non-linear associations while effectively accounting for different confounding factors. An R package called conMItion is introduced to estimate CMI and its statistical significance for multi-omics data, with flexibility to adjust for one or two confounding factors. We demonstrated the utilization of conMItion through two use cases. First, we identified co-occurring somatic alterations in bladder cancer genomic data. Second, we applied conMItion to a single-cell RNA sequencing dataset of lung cancer patients and identified positively or negatively associated cell types within the lung cancer tumor microenvironment. Availability and ImplementationThe conMItion package is freely available on CRAN at https://CRAN.R-project.org/package=conMItion. The two use cases described in the paper can be accessed at https://github.com/GJYWang/conMItion. A supplementary document is available online.

bioinformatics↗

bioRxiv2026

Towards Continuous Home Monitoring for Dementia: A Real-Time mmWave Radar Framework for Activity Classification and Tracking

Millimeter-wave radar can quietly monitor health and behavior at home, which is vital for supporting people living with dementia. Most studies, however, remain limited to short-term testing in controlled spaces. Real-world deployment requires robust activity classification as a prerequisite: vital-sign and behavioral sensing require fundamentally different processing pipelines, and absent periods need to be reliably distinguished from stationary states. Bridging the critical gap between controlled laboratory demonstrations and continuous home monitoring, this paper introduces a self-adapting radar framework that extracts meaningful behavioral segments from massive, unconstrained real-world data. The system performs continuous real-time activity classification (stationary, walking, and absent) and target localization, selectively directing downstream processing to the most informative segments. It addresses key real-world deployment challenges including adaptive thresholding across subjects and environments, and walking detection under naturalistic activity conditions. Prior to integration with the Minder platform, the system was validated in a fully instrumented studio apartment against ground truth. Across 12 subjects, the system achieved an overall classification accuracy of 0.98, with F1 scores of 0.99 for absence and stationary states, and 0.95 for walking. Event-based evaluation yielded a per-subject walking sensitivity of 0.916{+/-} 0.058 and F1 score of 0.935 {+/-}0.030. Localization root mean square error during movement was 0.40 m. The results demonstrate reliable performance suitable for transitioning to long-term real-world home deployment.

bioengineering↗

bioRxiv2026

Dependencies in heterogeneous, lineage plastic patient-derived prostate cancer organoids revealed through integrated single-cell multiomics and CRISPR screening

Lineage plasticity and tumor heterogeneity limit the effectiveness of targeted therapies, yet the functional dependencies used to nominate therapeutic targets are often derived from homogeneous systems that fail to capture this complexity. Here, we establish a framework to resolve state-specific genetic vulnerabilities by integrating single-cell multiomics (RNA and ATAC) with pooled CRISPR-Cas9 screening across a large panel of patient-derived organoids (PDOs) from castrate-resistant prostate cancer (CRPC) and neuroendocrine prostate cancer (NEPC). We generate a single-cell multiome atlas spanning >190,000 cells across 22 PDOs, defining seven lineage states--including intermediate and plastic populations not resolved by bulk profiling--and demonstrate that these lineage programs robustly classify independent transcriptomic datasets from prostate cancer patient tumors. By systematically coupling this atlas to subtype-resolved CRISPR screens, we construct a functional dependency map linking cell state in heterogeneous 3D human tumor models. We show that intratumoral heterogeneity fundamentally reshapes the interpretation of gene essentiality, whereby gene-level depletion reflects the composite behavior of co-existing subpopulations, and identify a general principle in which resistant "limiting" populations disproportionately determine aggregate fitness effects. This framework reveals both canonical and previously unrecognized lineage-restricted dependencies within highly plastic tumor and NEPC states, including a therapeutically targetable dependency on the aryl hydrocarbon receptor (AHR) in a novel hybrid stem-like/ASCL1 population. Together, these data establish an extensive multi-dimensional prostate cancer resource, identify novel lineage-resolved biology, and provide a generalizable strategy for interpreting functional genomics in heterogeneous human tumors.

cancer biology↗

bioRxiv2026

DNA methylation in Escherichia coli changes in response to growth conditions

Bacteria require rapid adaptation under fluctuating environmental conditions. Commonly recognized global regulators enable bacteria to respond promptly to external changes, though they are either restricted to specific bacterial taxonomies or physiological statuses, suggesting that additional regulators are required for adaptation. DNA methylation is a reversible modification affecting bacterial gene regulation. However, conventional methods can only detect one DNA methylation form each round, leaving the understanding of DNA methylation in bacterial adaptation mostly unknown. This study aimed to identify genome-wide DNA methylation variation (N6-methyladenine, N4-methylcytosine, and 5-methylcytosine) in Escherichia coli under different culture conditions using Oxford Nanopore sequencing. DNA samples from six conditions (normal, low oxygen, low pH, high temperature, high salt, and recovery after low pH exposure) during the exponential and stationary phases were extracted. When culture conditions were compared to the normal condition, E. coli exhibited more differentially methylated sites during the exponential phase than in the stationary phase. During the exponential phase, the genes differentially methylated in all conditions were involved in cellular activities, such as cellular and metabolic processes. During the stationary phase, universally differentially methylated genes were associated with oxidation responses. Subsequent analysis found that although DNA methylation analysis was affected by batch effects, some genes (e.g. rpoS) showed consistently differential methylation across datasets. Our findings suggest that the E. coli DNA methylation profile was affected by growth phases and conditions, and DNA methylation profiling by Oxford Nanopore sequencing could be a potential approach for gene activity estimation in environmental samples. ImportanceBacterial DNA methylation is a reversible genetic modification affecting gene regulation, enabling rapid adaptation. Three major forms in bacteria are N6-methyladenine, N4-methylcytosine, and 5-methylcytosine. Using Oxford Nanopore sequencing, we characterized genome-wide variation in these methylation types in Escherichia coli under six conditions (normal, low oxygen, low pH, high temperature, high salt, and recovery after low pH exposure). DNA methylation signatures in E. coli varied with growth conditions. Using the normal condition as a baseline, E. coli during the exponential phase exhibited more differentially methylated genomic loci under stress conditions compared to the stationary phase. Under stress conditions, genes with differential methylation were associated with cellular processes or oxidative responses, depending on the growth phase. Our findings reveal that the DNA methylation signature in E. coli was affected by growth phases and conditions, and Oxford Nanopore-based DNA methylation profiling could be a potential approach for gene activity estimation in environmental samples.

microbiology↗

bioRxiv2026

Multidimensional dynamics of object representations in the human visual system

AO_SCPLOWBSTRACTC_SCPLOWNatural image representations are distributed across many dimensions of visual cortex activity, but little is known about how the multidimensional structure of these representations evolves over time following stimulus onset. Here we examined the temporal dynamics and latent dimensional structure of natural object representations in large-scale EEG and MEG data. We also compared these data with leading representational models derived from large-scale human similarity judgments and deep neural networks. Our findings reveal a rapid expansion of stimulus dimensionality in the brain, which peaks within 100 milliseconds and gradually decays over hundreds of milliseconds. The dynamics of these dimensionality changes tracked the decoding accuracy for both behavioral embeddings and neural network features, suggesting that dimensionality may be a general indicator of representational expressivity. Interestingly, the dimensionality of the neural representations could not be fully explained by leading behavior-based or neural network models. Follow-up experiments showed that the remaining neural variance carried additional perceptually relevant information not yet explained by leading models. Together, these findings reveal previously unrecognized complexity in measurements of dynamic human brain responses to natural objects.

neuroscience↗

bioRxiv2026

EnzCast: Prediction of Patient-Specific Enzymatic Kinetics through Multi-Modal Deep Learning and Isoform-Resolved Bayesian Inference based on Single-Cell Transcriptomics

Enzyme kinetic parameters underpin mechanistic biology but remain sparse in physiological context. We present EnzCast, a multi-modal framework jointly predicting Km, kcat, kcat/Km, and Ki from protein sequence, 3D structure, substrate chemistry, and experimental conditions, paired with IsoKin, an isoform-resolved Bayesian framework converting EnzCast priors into patient-specific in vivo kinetics. Trained on KinBench, the largest curated kinetics database, task-adaptive EnzCast achieved R2 = 0.413, 0.455, 0.227, and 0.105 for Km, Ki, kcat, and kcat/Km, surpassing all baselines on catalytic tasks. Systematic condition scans recovered compartment-specific pH direction inversion and pathway-level temperature responses. In a 20-patient colorectal cancer single-cell cohort, IsoKin reduced posterior uncertainty by 73.3% and 77.3%, revealing cell-type-specific rewiring. Orthogonal validation--scFEA flux, DepMap essentiality (permutation P = 0.0008) and TCGA survival-- provided mixed but directionally consistent support. Together, EnzCast and IsoKin bridge in vitro prediction, condition-aware biochemical interrogation and patient-resolved in vivo inference.

bioinformatics↗

bioRxiv2026

Mapping fibrotic microenvironments: single-cell and spatial profiling of Schistosoma mansoni-induced tissue fibrosis

Schistosoma-induced tissue fibrosis, driven by immune response to trapped schistosome eggs, is the principal cause of pathology and schistosomiasis-related morbidity. While praziquantel effectively clears adult parasites, no therapies exist to target eggs or egg-induced tissue fibrosis. Here, we utilise single-cell spatial transcriptomics to define the high-resolution molecular architecture of the fibrotic niche in Schistosoma mansoni-infected mice at 8 weeks post-infection. Our data reveal that the host executes divergent, organ-specific biological programs: constructing a rigid, concentric fibrotic granuloma for permanent egg sequestration in the liver while building a flexible, discontinuous collagen architecture in the intestine to facilitate egg transit. Spatially resolved cell-cell interaction analysis, unprecedented in schistosome-induced fibrosis, identifies the strongest cellular interactions between macrophages and collagen-producing cells, with TGF-{beta}-dominant ligand-receptor pairs in the hepatic niche and integrin-centered pairs in the intestine. Despite this architectural divergence, we detected a core signature of five ligand-receptor pairs shared across both tissues, suggesting shared signalling interactions that could be leveraged for pan-tissue therapeutics for treating schistosome-induced fibrosis. Together, these findings provide the first high-resolution spatial atlas of schistosomiasis-associated fibrosis and provide a foundational framework for discovering novel drug targets capable of reversing established tissue damage, addressing a critical clinical gap where current therapies fail.

molecular biology↗

bioRxiv2026

Prenatal THC exposure disrupts mitochondrial respiratory gene programs and delays medium spiny neuron maturation in the nucleus accumbens

Prenatal cannabis exposure (PCE) is increasingly prevalent and has been associated with adverse neurodevelopmental outcomes, yet its molecular impact on brain reward circuitry remains poorly defined. Here, we investigated transcriptional and epigenomic alterations in the nucleus accumbens (NAc) following prenatal {Delta}9-tetrahydrocannabinol exposure in a rat model using snRNA-seq and snATAC-seq analyses. PCE markedly suppressed the expression of genes involved in mitochondrial oxidative phosphorylation (OXPHOS) in the NAc on postnatal day 24 (P24), indicating reduced mitochondrial respiration capacity. This disrupted mitochondrial respiratory gene programming was accompanied by coordinated alterations in ribosomal and proteasomal pathways regulating protein homeostasis in NAc medium spiny neurons (MSNs), suggesting coupled disruption of cellular metabolism and neuronal maturation. snATAC-seq analysis revealed altered chromatin accessibility at promoter regions enriched for Nrf1 and Yy2 binding motifs, implicating Hrf1- and Yy2-associated transcriptional regulation of mitochondrial genes in MSNs following PCE. Moreover, an acute THC challenge in PCE offspring at P24 further exacerbated the suppression of genes involved in mitochondrial OXPHOS and MSN maturation. Together, these findings define a transcriptional and epigenetic framework through which PCE may perturb mitochondrial function and impair MSN maturation trajectories in the NAc, providing mechanistic insights into how PCE may alter the development of reward circuitry.

neuroscience↗

bioRxiv2026

Coenzyme A is a redox sensing cofactor for malic enzyme 2 regulating oxidative stress and mitochondrial metabolism

Coenzyme A (CoA) is an essential cofactor required for numerous metabolic reactions, yet its ability to bind and regulate proteins remains poorly defined. Using a proteomic approach, we identified malic enzyme 2 (ME2) as a CoA-binding protein. ME2 uses NAD(P)+ to convert malate to pyruvate, generating NAD(P)H to support energy production and redox homeostasis. ME2 binds CoA at an allosteric site previously thought to bind NAD(P)+. Reduced CoA has minimal effect on ME2 activity, but the oxidized form, CoA disulfide, strongly activates ME2 by promoting ME2 tetramerization and a catalytically efficient closed conformation. Under oxidative stress, ME2 facilitates CoA disulfide formation, enhancing NADPH production and cellular defense against reactive oxygen species (ROS). Mice with ME2 mutation that cannot bind CoA show impaired muscle performance, elevated ROS, and mitochondrial dysfunction. These findings establish CoA as a redox-sensing cofactor, allowing cells to respond to ROS and promote mitochondrial metabolism, and expanding the function of this essential cofactor.

biochemistry↗

bioRxiv2026

Generation of High-Affinity Anti-GIPR Antagonist Antibodies with Sustained and Non-rebound Weight Loss in DIO Mice by AlfaBodY

The glucose-dependent insulinotropic polypeptide receptor (GIPR) is an attractive therapeutic target for metabolic disorders, with GIPR antagonism emerging as a promising strategy for obesity and type 2 diabetes. However, developing functional antibodies against GPCRs remains challenging due to their complex architecture and conformational dynamics. Here, we employed AlfaBodY, an iterative active learning platform integrating structural and sequence information, to in silico design human anti-GIPR antibodies. Through four rounds of optimization, we generated antibodies with high binding affinities. Lead candidates AB106-131 (KD 1.2 nM) and AB106-156 (KD 1.7 nM) exhibited 7 to 10-fold higher affinity than 2G10 (KD 12 nM) while maintaining comparable antagonistic activity in a cAMP reporter assay (IC50 4[~]5 nM). In diet-induced obese mice, AB106-156 alone induced weight loss comparable to that of semaglutide ([~] -15%), while preserving lean mass and achieving sustained weight control after treatment withdrawal. Co-administration with the GLP-1 receptor agonist semaglutide produced synergistic weight reduction (-25.4%) and markedly attenuated the fat-mass rebound observed with semaglutide alone. Our results demonstrate that AI-driven design can generate potent anti-GIPR antibodies with favourable in vivo efficacy, supporting further development of GIPR antagonist for obesity and related metabolic disorders. The AlfaBodY platform enables faster development of more efficacious biologic drugs.

pharmacology and toxicology↗

bioRxiv2026

Aligned recordings of neural spiking activity and licking behavior in thirsty mice

Electrophysiological data, which serve as a biological signal that bridges neural activity and behavioral tasks, provide an innovative approach to neuroscience research. In this study, we constructed a dataset that contains over 2000 neurons across 117 days recorded in 20 mice containing 28,573 trials. Data for 5 mice were collected from the Secondary Motor Cortex (M2) region 8 mice was derived from the Ventrolateral Striatum (VLS) and 7 mice were from Substantia Nigra pars Reticulata (SNR). We induced licking behavior in head-fixed mice by periodically delivering water through a spout while simultaneously recording spiking activity from three brain regions and behavior related electrical signals. This dataset ensures precise temporal alignment between neural activity and behavioral events, offering a robust foundation for investigating neural encoding mechanisms and simulation of neural activities. This dataset establishes a precise spike-to-event mapping, which enables high decoding accuracy using Multilayer Perceptron (MLP) and Support Vector Machine (SVM). It can serve as a high-quality benchmark for developing encoding and decoding algorithms in neural networks, particularly Spiking Neural Networks (SNNs).

neuroscience↗