Biology subjects

Bell, F.

Publications and source records attributed to Bell, F..

3 recordsLinked to original sources

bioRxiv2026

A Deterministically Synchronized Widefield Imaging and Virtual Reality Platform for Multimodal Brain Behavior Recording

ObjectiveSimultaneous recording of brain activity, behaviour, and virtual environments is essential for understanding large-scale neural dynamics during behaviour. However, existing systems often rely on software-based synchronization or post hoc alignment, introducing latency, jitter, and drift that obscure fast brain-behavior interactions. ApproachHere, we present a deterministically synchronized widefield calcium imaging platform that unifies neural imaging, high-speed behavioural monitoring, and closed-loop virtual reality (VR) under a shared hardware-defined clock. This system enables millisecond-precision temporal alignment across modalities, including dual-wavelength hemodynamic correction, pupil and orofacial tracking, locomotion sensing, and VR rendering. Main resultsThe platform achieves stable hardware-level synchronization across neural imaging, behavioural recordings, and VR rendering without reliance on software timestamps. It supports widefield imaging rates up to 100 Hz and integrates seamlessly with both ViRMEn and Blender VR engines, exhibiting a mean locomotion-to-VR update latency of [~]1.5 ms. Multimodal recordings during VR navigation demonstrate robust temporal alignment between cortical activity, facial dynamics, pupil signals, and locomotion. SignificanceThis system provides a deterministic multimodal framework for studying brain-behaviour relationships during active behaviour. By enabling millisecond-precision synchronization across neural imaging, behaviour, and virtual environments, this platform enables causal investigation of brain-behaviour interactions at millisecond precision and provides a foundation for next-generation closed-loop neuroengineering experiments.

neuroscience↗

bioRxiv2026

NeuroPupil: A generalization-first framework for scalable and biologically informative cross-species pupillometry

Quantitative pupillometry provides a noninvasive window into brain state and neurological function, but its broader use across experimental and clinical settings is limited by challenges in achieving accurate, scalable, and generalizable measurements. Here, we present NeuroPupil, a deep learning framework for high-throughput, cross-species pupillometry that emphasizes robust generalization across subjects, behavioral contexts, and imaging conditions. Through systematic benchmarking of training strategies and network architectures, we identify pooled multi-subject training combined with an optimized U-Net architecture as a key determinant of reliable and transferable pupil tracking performance. Across diverse mouse and human datasets, NeuroPupil achieves improved accuracy and substantial gains in computational efficiency compared to existing approaches, enabling practical analysis of large-scale datasets. We further demonstrate that improved pupil tracking fidelity enhances downstream biological inference: NeuroPupil-derived pupil features significantly improve prediction of distributed cortical activity in behaving mice and preserve diagnostically relevant temporal structure in human clinical recordings. These findings highlight the importance of precise and scalable measurement for linking pupil dynamics to brain activity and clinical phenotypes. By integrating benchmarking, scalability, and accessible software tools, NeuroPupil provides a reproducible framework for large-scale pupillometry and facilitates its application in systems and translational neuroscience.

neuroscience↗

bioRxiv2021

Territory-level temperature influences settlement decisions, breeding phenology and productivity in three forest passerine birds

Temperature plays an important role in determining breeding phenology of temperate birds, with higher spring temperatures associated with earlier breeding. However, the effect of localised territory-scale temperature variations is poorly understood, with relationships between temperature and breeding phenology mostly studied using coarse-grained climatic indices. Here, we interpolate spring temperatures recorded at 150 m2 grid intersections encompassing 417 ha of forest to examine the influence of territory-scale temperature, and its interaction with mean annual temperature, on territory selection, breeding phenology, clutch size and fledgling success for three co-occurring single-brooded passerine birds using data from 672 nests over four years. All species exhibited significant trends in reproductive traits associated with territory-scale temperature. Pied flycatchers Ficedula hypoleuca settled in cooler territories first, where they raised more fledglings. Blue tits Cyanistes caeruleus laid larger clutches in warmer territories in warm years and always laid earlier at warmer territories irrespective of annual temperature variation. Contrastingly, pied flycatcher and wood warbler Phylloscopus sibilatrix breeding phenology was earlier at warmer territories in cool years and cooler territories in warm years, with wood warbler clutch size responding similarly to this interaction. Greater previous breeding experience and increased higher rates of historical territory occupancy (territory quality) also predicted earlier breeding phenology and higher fledging success for pied flycatchers. We suggest that the migratory pied flycatcher and wood warbler are best synchronised with their prey availability in cooler years at a local population level while resident blue tits match local phenology across all years, which is potentially advantageous under warmer predicted climate change scenarios. We conclude that temperature at the territory scale can be an important driver of settlement and breeding phenology and influence reproductive traits.

ecology↗