synaptic & neural circuits

This paper introduces DyCoM, a framework that unifies dynamic connectivity analysis in neuroimaging by decomposing estimators into fundamental operations, revealing distinct biological interpretations from different computational choices.

This study shows that brain geometry and cognitive inputs shape neural dynamics and topology, with bioRNNs capturing empirical brain activity and spatial patterns.

The paper examines how kinship, acoustic signaling, and socio-spatial structure affect decision-making and social influence in white-nosed coatis, finding that majority support and proximity to leaders shape group decisions.

The paper uses simulations to explain conflicting experimental results on ephaptic coupling in cardiomyocytes by analyzing geometric configurations.

The paper develops a data-driven method to identify individualized disordered connectivity patterns from fMRI data, revealing diverse neurobiological mechanisms underlying transdiagnostic psychiatric symptoms.

This study uses a spatial agent-based model to show that resource heterogeneity and bachelor threat jointly shape intergroup tolerance by promoting aggregation and familiarity through encounter histories.

This study investigates the dose-dependent fMRI response to transcranial photobiomodulation in humans, showing non-local effects and parameter-dependent responses.

The paper demonstrates subthreshold asynchronous computations in biophysically detailed neuron networks using graded synaptic transmission without spiking.

This paper shows that cross-feeding in microbial communities can evolve from energy acquisition alone, without requiring specific metabolic trade-offs or exchange mechanisms.

This study uses an agent-based model to explore eco-evolutionary dynamics of plastic and non-plastic genotypes in nematodes under fluctuating environments, revealing how costs of plasticity and environmental stability influence phenotypic strategies.

This paper extends a computational model of time compaction theory to account for waiting and speed modulation in dynamic environments, demonstrating its ability to generate adaptive behavior in simulated football scenarios.

This paper develops a coupled Maxwell-electromagnetic cable framework to model action potential propagation in branched axons, showing electromagnetic effects significantly impact conduction and bifurcation transmission.

This paper introduces blood-mediated optoacoustic stimulation (BOAS) for precise brain cortex stimulation, showing it can trigger neuronal activity comparable to natural visual stimulation and is more efficient than photothermal methods.

This paper introduces a single-channel strongly-coupled geometry surface coil for rodent whole-brain fMRI, showing improved depth sensitivity and consistent signal-to-noise ratio across loading conditions.

The paper determines high-resolution structures of adenovirus particles at different proteolytic stages, revealing how protease-driven remodeling affects capsid stability and maturation.

This paper introduces a high-channel-count neural recording and stimulation platform with 5,376 channels, demonstrating its use in high-resolution cortical mapping in rat brains.

This paper develops a Bayesian dynamical IPM framework that integrates population density and individual growth data to improve predictions of size-structured population dynamics under global change.

The paper develops a 3D model of social coordination in fish using real behavior data and validates it through a closed-loop virtual reality system.

This study shows Bombus terrestris workers can learn to associate novel odors with queen context, influencing their social and reproductive behavior.

This paper introduces a wearable OPM-MEG system that enables brain activity localization in an open environment without magnetic shielding.

This paper introduces an enzyme-free DNA-based templated dimerization reaction controlled by a fuel strand that displaces product to overcome inhibition, enabling information propagation from templates.

This paper introduces LATeNT, a light-activated tetanus neurotoxin that enables conditional proteolysis and inducible synaptic inhibition in vivo, with applications in neuroscience and beta cell function.

This paper introduces alphaKL, a new RNA connector that enables edge-to-edge assembly of RNA nanostructures, expanding their structural design space.

The paper reports an in vitro system of lipid kinases and phosphatases that self-organize into dynamic spatiotemporal patterns on model membranes.

This paper introduces Neural SS-DMP, a method that improves neural decoding by reframing it as structured control inference with behavior priors, achieving better accuracy and trajectory smoothness in ECoG and spiking data.

The paper shows that structured scene descriptions, not just object co-occurrence, predict high-level visual cortex responses better, and language-aligned models capture this structure.

This paper develops two hybrid calcium indicators, HyBRIC and HyBRIC2, that use luciferase activation and BRET for high-contrast red-window calcium imaging with improved brightness and responsiveness.

This study investigates how auditory-motor learning adapts to changing mappings, finding rapid short-term adjustments and slower long-term learning through targeted training.

This paper develops a method to create stable, size-controlled membraneless organelles using surfactant-like peptides and pH-responsive polypeptides, enhancing enzymatic reactions in synthetic cells.