arXiv preprints from January 1, 2026 through September 5, 2026 — 06:20:24 EST
Functional synapse clusters (FSCs) are synapses with correlated presynaptic activity that are colocalized on the same neuronal dendritic branch. FSCs have been observed after learning in cortical and hippocampal pyramidal neurons. However, previous efforts to ablate FSCs by pharmacologically blocking dendritic nonlinearities to...
Resting-state functional connectivity (FC) is altered in Alzheimer's disease (AD), widely regarded as a distributed network process; whether its FC signature reduces to a few focal sites has not been tested causally, a question central to targeted neuromodulation. We fit subject-specific, cross-subject-identifiable reservoir-computing...
Large ecosystems balance competition and cooperation, yet standard generalized Lotka--Volterra models make mutualism destabilizing by amplifying disorder and driving unbounded growth. We show that Monod-like saturation resolves this paradox: dynamical mean-field theory and random-matrix analysis reveal a broader stable phase and...
Wind plays a crucial role in changing prey defense strategy and predation efficiency. We develop and analyze a prey-predator model that incorporates wind driven environmental effects, prey group defense, and an additional food strategy for the predator. Wind intensity is assumed to modulate predation efficiency, while prey aggregation...
Objective. To develop and evaluate an adaptive electrode-selection method for tracking non-stationary spontaneous activity during long-term high-density microelectrode array (HD-MEA) recordings under a fixed channel budget. Approach. We formulated electrode allocation as a sequential subset-selection problem and used a discounted...
The exponential growth of genomic data, particularly for microbes, has made pangenomic approaches a gold standard for large-scale comparative genomics. By capturing the full genomic diversity of a species rather than relying on a single reference, pangenomics has transformed microbial genomics, revealing the adaptive potential of...
Cell type standardization plays a central role in integrating biological knowledge across single-cell studies. While standardized resources (e.g., Cell Ontology, Nomenclature Frameworks) provide unified vocabularies of cell populations, scientific publications and public datasets continue to use heterogeneous study-specific labels,...
We are studying a new regulator of microtubule homeostasis, wdA, in the fungus Aspergillus nidulans. Mutations in wdA confer cold-sensitive lethal mitotic catastrophe, suggesting an important role in microtubule-based processes. Previous genetic studies showed that deletion of TBCA causes a near-lethal phenotype that is suppressed by...
This paper presents a robust mathematical framework for quantifying antiproliferative effects from noisy in vitro cell viability experiments. The methodology is demonstrated using crystal violet assay measurements of quinolinic acid-induced growth inhibition in B16-F10 murine melanoma, RAW264.7 macrophage, and HaCaT keratinocyte cells...
We consider the spatial spread of epidemic into an unstable, healthy state. When the transmission rate depends on the fraction of infected, the propagating pulse of infection can be either a pulled front or a pushed front. We determined the phase space of parameters for the pulled and pushed regions both by numerically solving the...
Specific mixing or demixing of molecular species is a characteristic feature of condensed intracellular membraneless compartments. How sequence patterns of intrinsically disordered proteins (IDPs) fundamentally impact subcompartmentalization of biomolecular condensates and their role in buffering against concentration fluctuations are...
Gene regulatory network modeling often requires balancing predictive accuracy and mechanistic interpretability. In this work, we compare continuous surrogate models and a discrete mechanistic model on the same \textit{Arabidopsis thaliana} induced systemic resistance (ISR) dataset, using both the raw continuous gene-expression...
We present Loom, a spatial transcriptomics (ST) visual computing system to support the analysis of pseudo-temporal trajectories, comparative investigation across samples and regions of interest, and the examination of spatially structured processes within local microenvironments. ST is a molecular profiling technology that measures...
Additional food sources and predator competition are both known to impact the dynamics of predator-prey models. The Bazykin model of predator competition, with Holling type II functional response, possesses a rich bifurcation structure consisting of a focus-type degenerate Bogdanov-Takens bifurcation of codimension 3, and a degenerate...
Ecological communities are shaped by the interplay between trophic interactions and infectious disease, yet how spatially mediated interactions influence disease-driven ecosystem dynamics remains poorly understood. Here, we develop a gravity-based eco-epidemiological framework for a tri-trophic food chain in which trophic interaction...
We develop an exact finite-population stochastic framework for SIR epidemics evolving under Markovian switching between intervention regimes. The epidemic state is augmented by a finite phase component, allowing transmission, recovery, and direct immunity-acquisition rates to depend on the active regime. Phase-transition intensities...
Single-cell datasets are increasingly costly to store, audit, and reuse for model training. Dimensionality reduction and dataset distillation can reduce this burden, but conventional distillation methods often produce synthetic expression profiles that cannot be traced to an assayed cell. We formulate traceable single-cell data...
Brain-computer interface neurofeedback (BCI-NFT) has shown promise for neuromotor rehabilitation, but its clinical adoption -- particularly in pediatric populations -- remains limited in part by the lengthy calibration required before each therapy session. This study developed and evaluated a deep-learning framework to reduce...
Neuronal communication is mediated in part by changes in neuronal firing rates. The time interval between successive neuronal firings is referred to as the inter-spike interval (ISI), and quantifying its statistics is important for understanding neuronal communication. This paper studies the ISI statistics of a postsynaptic neuron...
We develop an exact finite-population stochastic framework for SIR epidemics evolving under Markovian switching between intervention regimes. The epidemic state is augmented by a finite phase component, allowing transmission, recovery, and direct immunity-acquisition rates to depend on the active regime. Phase-transition intensities...
Gene regulatory network (GRN) models are widely used to investigate gene-expression dynamics in biological systems. evolutionary GRN model proposed by Kaneko (2007), which investigated the relationship between robustness to nongenetic phenotypic noise and robustness to mutation. We explicitly reconstruct the simulation protocol by...
Ecological communities are shaped by the interplay between trophic interactions and infectious disease, yet how spatially mediated interactions influence disease-driven ecosystem dynamics remains poorly understood. Here, we develop a gravity-based eco-epidemiological framework for a tri-trophic food chain in which trophic interaction...
In vitro transcription using bacteriophage T7 RNA polymerase (T7 RNAP) is the gold-standard platform for RNA production in both research and therapeutic applications. Despite its high processivity and promoter specificity, T7 RNAP generates multiple RNA by-products, including double-stranded RNA, 3'-extended transcripts, abortive...
Humans have always externalized thought onto tools, from the tally and the abacus to the map and, now, large language models. I model the agent, the tool, and the task as one dynamical system in which competence (what the user retains) and reliance (what the user outsources) co-evolve, and find that the outcome is bistable. Above a...
Reconstructing the energy profile of DNA-binding proteins along the genome requires an algorithm that quantifies efficiently the binding free energy. We assembled a dataset of protein structures and DNA binding sites, together with their binding energies, and used it to train a machine-learning algorithm that learns a latent invariant...