arXiv subjects

Chris French

Publications and source records attributed to Chris French.

3 recordsLinked to original sources

arXiv2024

Design and Fabrication of a Low-cost Liquid Optical Waveguide for Augmented Reality

The complexities of fabrication techniques and the demand for high precision have posed significant challenges in the mass production of augmented reality (AR) waveguide combiners. Leveraging the capabilities of Polyjet 3D printing techniques, we have developed a cost-effective method for fabricating liquid geometric waveguide combiners for AR applications, using silicone oil as the medium. During the design phase, we optimized the structure of the waveguide combiner to facilitate easier fabrication. Our proposed method simplifies the production process by removing the need for complicated steps like dicing, layer bonding, and polishing, which are usually involved in traditional manufacturing techniques. We conducted optical simulations and developed a prototype using our patented fabrication method, which successfully demonstrated the integration of virtual images with the real-world environment, thereby confirming its feasibility and potential for cost-effective mass production.

physics.optics↗

arXiv2024

Graph-Based Representation Learning of Neuronal Dynamics and Behavior

Understanding how neuronal networks reorganize in response to external stimuli and give rise to behavior is a central challenge in neuroscience and artificial intelligence. However, existing methods often fail to capture the evolving structure of neural connectivity in ways that capture its relationship to behavior, especially in dynamic, uncertain, or high-dimensional settings with sufficient resolution or interpretability. We introduce the Temporal Attention-enhanced Variational Graph Recurrent Neural Network (TAVRNN), a novel framework that models time-varying neuronal connectivity by integrating probabilistic graph learning with temporal attention mechanisms. TAVRNN learns latent dynamics at the single-unit level while maintaining interpretable population-level representations, to identify key connectivity patterns linked to behavior. TAVRNN generalizes across diverse neural systems and modalities, demonstrating state-of-the-art classification and clustering performance. We validate TAVRNN on three diverse datasets: (1) electrophysiological data from a freely behaving rat, (2) primate somatosensory cortex recordings during a reaching task, and (3) biological neurons in the DishBrain platform interacting with a virtual game environment. Our method outperforms state-of-the-art dynamic embedding techniques, revealing previously unreported relationships between adaptive behavior and the evolving topological organization of neural networks. These findings demonstrate that TAVRNN offers a powerful and generalizable approach for modeling neural dynamics across experimental and synthetic biological systems. Its architecture is modality-agnostic and scalable, making it applicable across a wide range of neural recording platforms and behavioral paradigms.

q-bio.NC↗

arXiv2024

3D Printed Waveguide for Augmented Reality

Mass production of augmented reality (AR) waveguides has been challenging due to the intricate nature of the fabrication technique and the high precision required for its optical characteristics. In this paper, we have presented a novel and low-cost approach for fabricating geometric optical waveguides designed for AR applications utilizing 3D printing techniques. To strike a balance between optical performance and fabrication feasibility, we have optimized the conventional geometric waveguide design to facilitate easier fabrication. It is worth noting that our proposed method does not require molding, dicing, and post-surface polishing after printing. A prototype based on this method has been successfully fabricated, showing the immersion between the virtual image and the real-world scene. The proposed method has great potential for adaptation to mass production in various AR applications.

physics.optics↗