Biology subjects

Owen, S. F.

Publications and source records attributed to Owen, S. F..

5 recordsLinked to original sources

bioRxiv2026

Adolescent development accelerates responses to input in human neocortical neurons

Through childhood and adolescence, profound changes to the physiology of individual neurons accompany large-scale network changes in the mammalian neocortex. These physiological changes are well understood in rodent models but far less is known in the human neocortex. Here we combine patch-clamp electrophysiology and single-cell sequencing (Patch-Seq) in neurosurgically-resected pediatric human brain slices and age-matched mouse brain slices to elucidate the unique developmental trajectory of human neurons. We find that human Layer 2/3 pyramidal neurons show distinctive postnatal changes in neuronal physiology that align with the more directed, feedforward network architecture of human neocortex relative to the mouse. Human-specific changes to spike train dynamics include faster spike latencies and selective acceleration of early spiking. By applying linear modeling to our Patch-Seq data, we identify genes that predict physiological variation across single cells. This unbiased approach unexpectedly identifies BK-type calcium-activated potassium channels as key drivers of human postnatal changes in spike train dynamics between childhood and adolescence. We further test this pathway through pharmacology and computational modeling. Together, our results reveal novel mechanisms of postnatal maturation in human neocortical neurons and demonstrate a new application of Patch-Seq to uncover gene-physiology relationships at single-cell resolution.

neuroscience↗

bioRxiv2024

Data-driven synapse classification reveals a logic of glutamate receptor composition

The rich diversity of synapses facilitates the capacity of neural circuits to transmit, process and store information. We used multiplex super-resolution proteometric imaging through array tomography to define features of single synapses in mouse neocortex. We find that glutamatergic synapses cluster into subclasses that parallel the distinct biochemical and functional categories of receptor subunits: GluA1/4, GluA2/3 and GluN1/GluN2B. Two of these subclasses align with physiological expectations based on synaptic plasticity: large AMPAR-rich synapses may represent potentiated synapses, whereas small NMDAR-rich synapses suggest "silent" synapses. The NMDA receptor content of large synapses correlates with spine neck diameter, and thus the potential for coupling to the parent dendrite. Overall, ultrastructural features predict receptor content of synapses better than parent neuron identity does, suggesting synapse subclasses act as fundamental elements of neuronal circuits. No barriers prevent future generalization of this approach to other species, or to study of human disorders and therapeutics.

neuroscience↗

bioRxiv2024

Transcriptomically-measured gene expression predicts physiological variation across single neurons in humans and mice

Single-cell transcriptomics measures the molecular landscape of individual neurons with unprecedented efficiency and scale. This insight has the potential to advance our understanding of the molecular basis of neuronal function, and to identify druggable targets for disease treatments. However, transcriptomics also suffers from greater measurement noise than traditional techniques (e.g., RT-PCR), which raises questions about its ability to offer insight into function at true single-cell resolution. We tested if transcriptomic data could yield insight into function of individual neurons in human and mouse neocortex by analyzing two datasets collected via Patch-Seq, a powerful technique for obtaining transcriptomic and physiology data from the same neuron. We found that computational models trained on single-cell transcriptomic data robustly predicted physiology of individual neurons. Critically, models trained on single cells outperformed those trained on cell type averages when predicting single-cell physiology. Thus, the standard approach of denoising single-cell transcriptomic data by averaging on cell types sacrifices functionally-relevant information. Our analysis also revealed novel relationships between gene expression and physiology, including a potential molecular substrate of human- mouse cross-species differences in the speed of single-neuron computation. Broadly, our findings highlight the promise of Patch-Seq for generating new insight into the molecular basis of neuronal function.

neuroscience↗

bioRxiv2018

An open-source control system for in vivo fluorescence measurements from deep-brain structures

BackgroundIntracranial photometry through chronically implanted optical fibers is a widely adopted technique for measuring signals from fluorescent probes in deep-brain structures. The recent proliferation of bright, photo-stable, and specific genetically-encoded fluorescent reporters for calcium and for other neuromodulators has greatly increased the utility and popularity of this technique.\n\nNew MethodHere we describe an open-source, cost-effective, microcontroller-based solution for controlling optical components in an intracranial photometry system and processing the resulting signal.\n\nResultsWe show proof-of-principle that this system supports high quality intracranial photometry recordings from dorsal striatum in freely moving mice. A single system supports simultaneous fluorescence measurements in two independent color channels, but multiple systems can be integrated together if additional fluorescence channels are required. This system is designed to work in combination with either commercially available or custom-built optical components. Parts can be purchased for less than one tenth the cost of commercially available alternatives and complete assembly takes less than one day for an inexperienced user.\n\nComparison with Existing Method(s)Currently available hardware draws on a variety of commercial, custom-built, or hybrid elements for both optical and electronic components. Many of these hardware systems are either specialized and inflexible, or over-engineered and expensive.\n\nConclusionsThis open-source system increases experimental flexibility while reducing cost relative to current commercially available components. All software and firmware are open-source and customizable, affording a degree of experimental flexibility that is not available in current commercial systems.

neuroscience↗

bioRxiv2018

A genetically-encoded fluorescent sensor enables rapid and specific detection of dopamine in flies, fish, and mice

Dopamine (DA) is a central monoamine neurotransmitter involved in many physiological and pathological processes. A longstanding yet largely unmet goal is to measure DA changes reliably and specifically with high spatiotemporal precision, particularly in animals executing complex behaviors. Here we report the development of novel genetically-encoded GPCR-Activation-Based-DA (GRABDA) sensors that enable these measurements. In response to extracellular DA rises, GRABDA sensors exhibit large fluorescence increases ({Delta}F/F0[~]90%) with sub-second kinetics, nanomolar to sub-micromolar affinities, and excellent molecular specificity. Importantly, GRABDA sensors can resolve a single-electrical-stimulus evoked DA release in mouse brain slices, and detect endogenous DA release in the intact brains of flies, fish, and mice. In freely-behaving mice, GRABDA sensors readily report optogenetically-elicited nigrostriatal DA release and depict dynamic mesoaccumbens DA changes during Pavlovian conditioning or during sexual behaviors. Thus, GRABDA sensors enable spatiotemporal precise measurements of DA dynamics in a variety of model organisms while exhibiting complex behaviors.

neuroscience↗