synaptic & neural circuits

This paper introduces a fictive learning rule in model-based reinforcement learning that generalizes reward prediction errors to unvisited states and actions, explaining behavioral phenomena in the two-step task.

The paper determines the cryo-EM structure of a Shaker K+ channel mutant and shows that voltage sensing domain activation induces a dynamic shift in the linker population equilibrium rather than directly pulling the gate open.

The paper develops and validates a multiscale cortical circuit model to simulate TMS-evoked responses, revealing mechanisms of cortical activation and inhibition.

The paper shows that short disordered peptides can convert proteins into mechanosensors that respond to cellular forces, expanding the known mechanisms of mechanosensing.

The paper shows that inhibitory neurons can suppress excess synchrony caused by over-represented excitatory di-synaptic motifs in neural networks.

This paper introduces a state-dependent framework for drift diffusion models to better capture sequential decision-making in natural environments.

This study tracks Syb2-containing extracellular vesicles in neurons to reveal their endocytic pathways and rapid incorporation into synaptic vesicles.

This study develops a microfluidic device to simultaneously image neural activity and behavior in chemically stimulated, head-fixed C. elegans, showing that greater movement freedom leads to more naturalistic responses.

This paper introduces a biodegradable ECoG array with high electrode density and fidelity, demonstrating its ability to map cortical seizures and classify seizure stages with high accuracy in vivo.

This study screens all human paralog pairs to identify synthetic lethal interactions and finds that their strength depends on shared protein interaction networks and cellular context.

The paper models how arousal drives behavioural state transitions in mice using a dynamical systems approach, showing arousal affects engagement in a visual decision-making task.

This paper introduces a graphene-based probe for high-density, long-term neuronal recording at neuronal density, demonstrating reliable signal capture and connectivity analysis in vivo.

This study shows rats balance food and leisure by adjusting their time allocation based on switching costs, following rational decision-making principles similar to foraging models.

This paper introduces a multiscale GCN framework for brain network analysis that integrates structural and functional connectivity data, achieving 71.59% accuracy in schizophrenia classification with explainable insights.

This study determines the cryo-EM structure of the Drosophila Alka channel, revealing a lysine residue as a molecular switch for alkaline pH sensing and identifying hydroxide ions as a new class of ion channel ligands.

This paper introduces a DNA framework vesicle nanoreactor that enables programmable and quantifiable membrane fusion by controlling geometry and kinetics.

This study examines how RNN capacity affects exploration strategies in reinforcement learning, finding that higher capacity networks exhibit more human-like strategies but still differ in perseveration and switch rates.

The paper investigates how phenotypic switching strategies affect expansion speed in spatial populations, showing optimal switching rates and the impact of adaptation lags and spatial structure.

The paper examines behavior choices in Drosophila between grooming, feeding, and courting, finding contextual flexibility rather than an absolute hierarchy of needs.

This study shows that combining differential adhesion with cell signaling avoids kinetic traps, enabling robust multicellular self-organization in synthetic systems.

This paper introduces a dual-channel magnetic chamber for high-frequency magnetic neuromodulation in mice, capable of generating two independent magnetic fields with minimal interference and real-time behavioral monitoring.

This study establishes the formyl phosphate route for formate assimilation in E. coli through adaptive evolution and rational engineering, enabling formate-dependent growth.

AdapSkin improves neural signal accuracy and consistency in aging populations through adaptive, stretchable electronics and machine learning.

This paper introduces an allocentric framework for modeling collective motion, showing that coherent group behavior can emerge from navigational circuits without explicit alignment rules.

This paper introduces a hybrid SEIR-FitzHugh-Nagumo model to simulate information flow in neural networks, showing improved directional information flow and reduced latency compared to conventional models.

This paper describes a system using DNA origami to control directional membrane budding, mimicking virus assembly and producing DNA-shelled vesicles with applications in drug delivery and synthetic biology.

The paper examines neural dynamics in macaque medial premotor cortex during a task involving attention and tapping to a metronome, identifying low-dimensional manifolds that capture behavioral transitions.

The paper shows that strain-specific individual behaviours in C. elegans predict collective aggregation in mixed groups without altering individual movement patterns.

This study shows that the C610S mutation in GC1 disrupts endothelium-dependent vascular relaxation by impairing S-nitrosation, despite normal NO-cGMP signaling.

The paper studies adaptive control of neural synchrony in modified FHN networks with variance-driven coupling, showing topology-dependent effects on synchrony and introducing a feedback controller for desynchronization.