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Leon, J. J.

Publications and source records attributed to Leon, J. J..

2 recordsLinked to original sources

Temporal stability for individual differences in both habit learning and expression

Actions transition from goal-directed to stimulus-driven habits through repetition. Individual differences in the capacity to learn and control habits are central to current models of psychopathology, which assume that overreliance on habitual control drives maladaptive behaviors. However, whether these tendencies reflect stable, trait-like cognitive processes remains unclear. We examined the temporal stability of individual differences in habit learning and expression. Across two preregistered experiments (total N = 313), we assessed stimulus-response habits using the same stimuli after one day or different stimuli after four months. Evidence for stable individual differences in habit commissions was strong and comparable across experiments, with computational modelling further supporting trait-like tendencies for habit learning and expression. Trait-like tendencies were also reflected in action automatization while practicing stimulus-response associations, which was associated with future habitual behavior. Our findings have theoretical implications for our understanding of habit formation and its role in psychopathology.

neuroscience↗

An open-source, 3D-printable droplet microfluidics platform with strobe-enhanced microscopy

Droplet microfluidics underpins many single-cell, precision biomedical, and nanomaterial techniques. However, implementing these methods reproducibly remains challenging outside specialised laboratories due to high equipment costs, operational inflexibility, mechanical impracticality at the microscope stage, as well as open-source pumping solutions that are inadequately validated for low-flow stability. We present an accessible, research-grade, open-source droplet microfluidics platform integrating a compact, microfluidics-optimised microscopy stage with networked syringe-pump control. Designed for local digital fabrication, primarily 3D printing, and widely available components, the platform supports reproducible builds across diverse settings. This setup enables stable droplet generation, observation of rapid droplet dynamics, and automation-ready networked workflows. The microscopy module uses a Raspberry Pi camera and microsecond stroboscopic illumination to capture sharp images of fast-moving droplets without the need for a high-speed camera. A modular hardware interface and extensible, web-accessible software stack provide a path to integrate additional modules and laboratory automation beyond the configuration evaluated here. For infusion, we introduce an open-source syringe pump optimised for low reliable flow rather than maximum rates, combining gearbox-assisted stepper mechanics with workflow-centric control that enables manual intervention (keypad control) and remote operation (web interface and automation hooks). We benchmark droplet regimes, size tuning, and time-stability under low-flow conditions (between 25 and 2500 uL/h) relevant to advanced assays and demonstrate biomedical readiness through the encapsulation and incubation of cells, beads, and bacteria in monodisperse droplets. The platform has been replicated across laboratories in Latin America and globally, including independent builds, supporting reproducibility. All design files, firmware/software, analysis notebooks, and benchmark datasets are openly released.

bioengineering↗