Biology subjects

Pun, S. H.

Publications and source records attributed to Pun, S. H..

4 recordsLinked to original sources

bioRxiv2024

Sapphire-Based Optrode for Low Noise Neural Recording and Optogenetic Manipulation

Electrophysiological recordings of neurons in deep brain regions using optogenetic stimulation are essential to understanding and regulating the role of complex neural activity in biological behavior and cognitive function. Optogenetic techniques have significantly advanced neuroscience research by enabling the optical manipulation of neural activities. Because of the significance of the technique, constant advancements in implantable optrodes that integrate optical stimulation with low-noise, large-scale electrophysiological recording are in demand to improve the spatiotemporal resolution for various experimental designs and future clinical applications. However, robust and easy-to-use neural optrodes that integrate neural recording arrays with high-intensity light emitting diodes (LEDs) are still lacking. Here, we propose a neural optrode based on Gallium Nitride (GaN) on sapphire technology, which integrates a high-intensity blue LED with a 5x2 recording array monolithically for simultaneous neural recording and optogenetic manipulation. To reduce the noise interference between the recording electrodes and the LED, which is in close physical proximity, three metal grounding interlayers were incorporated within the optrode, and their ability to reduce LED-induced artifacts during neural recording was confirmed through both electromagnetic simulations and experimental demonstrations. The capability of the sapphire optrode to record action potentials has been demonstrated by recording the firing of mitral/tuft cells in the olfactory bulbs of mice in vivo. Additionally, the elevation of action potential firing due to optogenetic stimulation observed using the sapphire probe in medial superior olive (MSO) neurons of the gerbil auditory brainstem confirms the capability of this sapphire optrode to precisely access neural activities in deep brain regions under complex experimental designs.

neuroscience↗

bioRxiv2021

Predicting the Influence of Axon Myelination on Sound Localization Precision Using a Spiking Neural Network Model of Auditory Brainstem

Spatial hearing allows animals to rapidly detect and localize auditory events in the surrounding environment. The auditory brainstem plays a central role in processing and extracting binaural spatial cues through microsecond-precise binaural integration, especially for detecting interaural time differences (ITDs) of low-frequency sounds at the medial superior olive (MSO). A series of mechanisms exist in the underlying neural circuits for preserving accurate action potential timing across multiple fibers, synapses and nuclei along this pathway. One of these is the myelination of afferent fibers that ensures reliable and temporally precise action potential propagation in the axon. There are several reports of fine-tuned myelination patterns in the MSO circuit, but how specifically myelination influences the precision of sound localization remains incompletely understood. Here we present a spiking neural network model of the auditory brainstem with myelinated axons to investigate whether different axon myelination thicknesses alter the sound localization process. Our model demonstrates that axon myelin thickness along the contralateral pathways can substantially modulate ITD detection. Furthermore, optimal ITD sensitivity is reached when the MSO receives contralateral inhibition via thicker myelinated axons compared to contralateral excitation, a result that is consistent with previously reported experimental observations. Our results suggest specific roles of axon myelination for extracting temporal dynamics in ITD perception, especially in the pathway of the contralateral inhibition.

neuroscience↗

bioRxiv2020

Robotic Stereotaxic System based on 3D skull reconstruction to improve surgical accuracy and speed

Some experimental approaches in neuroscience research require the precise placement of a recording electrode, pipette or other tool into a specific brain area that can be quite small and/or located deep beneath the surface. This process is typically aided with stereotaxic methods but remains challenging due to a lack of advanced technology to aid the experimenter. Currently, procedures require a significant amount of skill, have a high failure rate, and take up a significant amount of time. We developed a next generation robotic stereotaxic platform for small rodents by combining a three-dimensional (3D) skull profiler sub-system and a full six degree-of-freedom (6DOF) robotic platform. The 3D skull profiler is based on structured illumination in which a series of horizontal and vertical line patterns are projected onto an animal skull. These patterns are captured by two two-dimensional (2D) CCD cameras which reconstruct an accurate 3D skull surface based on structured illumination and geometrical triangulation. Using the reconstructed 3D profile, the skull can repositioned using a 6DOF robotic platform to accurately align a surgical tool. The system was evaluated using mechanical measurement techniques, and the accuracy of the platform was demonstrated using brain phantoms. Additionally, small and deep brain nuclei were targeted in rodents for additional testing. The results indicate that this new stereotaxic system can improve the accuracy and speed of small-animal brain surgeries and reduce the failure rate of experiments.

bioengineering↗

bioRxiv2017

Scaling single cell transcriptomics through split pool barcoding

Constructing an atlas of cell types in complex organisms will require a collective effort to characterize billions of individual cells. Single cell RNA sequencing (scRNA-seq) has emerged as the main tool for characterizing cellular diversity, but current methods use custom microfluidics or microwells to compartmentalize single cells, limiting scalability and widespread adoption. Here we present Split Pool Ligation-based Transcriptome sequencing (SPLiT-seq), a scRNA-seq method that labels the cellular origin of RNA through combinatorial indexing. SPLiT-seq is compatible with fixed cells, scales exponentially, uses only basic laboratory equipment, and costs one cent per cell. We used this approach to analyze 109,069 single cell transcriptomes from an entire postnatal day 5 mouse brain, providing the first global snapshot at this stage of development. We identified 13 main populations comprising different types of neurons, glia, immune cells, endothelia, as well as types in the blood-brain-barrier. Moreover, we resolve substructure within these clusters corresponding to cells at different stages of development. As sequencing capacity increases, SPLiT-seq will enable profiling of billions of cells in a single experiment.

genomics↗