Biology subjects

Lusk, N.

Publications and source records attributed to Lusk, N..

5 recordsLinked to original sources

bioRxiv2026

3D-MAESTRO: A scalable, modular, portable pipeline for automated processing of large-scale volumetric brain microscopy data

Light microscopy is routinely used to explore the cellular and molecular structure of tissues, but the scale and complexity of data remains a bottleneck for discovery. We introduce 3D-MAESTRO (3D-Microscopy Automation and Execution with Scalable Tools, Rendering, and Orchestration): an automated image processing workflow for large-scale microscopy data, built for scalable execution across cloud and local computing environments. 3D-MAESTRO orchestrates denoising, stitching of image tiles, atlas registration, and segmentation. Its modular architecture permits the integration and benchmarking of new packages, ensuring that performance evolves as more efficient or accurate algorithms emerge. We introduce a new 3D image template for automated registration of mouse brains cleared with aqueous reagents and an efficient method for detection of fluorescent cells. We apply 3D-MAESTRO to lightsheet images of whole mouse brains in the context of diverse anatomical and functional experiments, illustrating high-throughput and reproducible mapping of microscopic structures across the brain.

neuroscience↗

bioRxiv2026

Topographic structure and function of locus coeruleus norepinephrine neurons

Norepinephrine (NE) is released throughout most of the central nervous system by neurons in the locus coeruleus (LC). We found a relationship between the morphologies, gene expression, and activity of LC-NE neurons in mice. Axonal projections of individual neurons were extensive but largely confined to subsets of brain regions. Axonal projections and graded gene expression correlated with locations of cell bodies in LC. In a behavioral task requiring ongoing learning from actions, neurons in dorsal LC projecting to the cerebral cortex were excited when mice made a different choice from the previous one and by reward prediction errors, a signal driving learning. Background activity of neurons in ventral LC was higher when mice ignored stimuli indicating potential reward availability. These observations reveal a topographically organized structure and function of a neurotransmitter system and show that it contains learning signals for flexible behavior.

neuroscience↗

bioRxiv2024

Data-driven fine-grained region discovery in the mouse brain with transformers

Spatial transcriptomics offers unique opportunities to define the spatial organization of tissues and organs, such as the mouse brain. We address a key bottleneck in the analysis of organ-scale spatial transcriptomic data by establishing a workflow for self-supervised spatial domain detection that is scalable to multimillion cell datasets. This workflow uses a self-supervised framework for learning latent representations of tissue spatial domains or niches. We use a novel encoder-decoder architecture, which we named CellTransformer, to hierarchically learn higher-order tissue features from lower-level cellular and molecular statistical patterns. Coupling our representation learning workflow with minibatched GPU-accelerated clustering algorithms allows us to scale to multi-million cell MERFISH datasets where other methods cannot. CellTransformer is effective at integrating cells across tissue sections, identifying domains highly similar to ones in existing ontologies such as Allen Mouse Brain Common Coordinate Framework (CCF) while allowing discovery of hundreds of uncataloged areas with minimal loss of domain spatial coherence. CellTransformer domains recapitulate previous neuroanatomical studies of areas in the subiculum and superior colliculus, and characterize putatively uncataloged subregions in subcortical areas which currently lack subregion annotation. CellTransformer is also capable of domain discovery in whole-brain Slide-seqV2 datasets. Our workflows enable complex multi-animal analyses, achieving nearly perfect consistency of up to 100 spatial domains in a dataset of four individual mice with nine million cells across more than 200 tissue sections. CellTransformer advances the state of the art for spatial transcriptomics, by providing a performant solution for detection of fine-grained tissue domains from spatial transcriptomics data.

bioinformatics↗

bioRxiv2023

Enhancer-AAVs allow genetic access to oligodendrocytes and diverse populations of astrocytes across species

Proper brain function requires the assembly and function of diverse populations of neurons and glia. Single cell gene expression studies have mostly focused on characterization of neuronal cell diversity; however, recent studies have also revealed substantial diversity of glial cells, particularly astrocytes. To better understand glial cell types and their roles in neurobiology, we built a new suite of adeno-associated viral (AAV)-based genetic tools to enable genetic access to astrocytes and oligodendrocytes. These oligodendrocyte and astrocyte enhancer-AAVs are highly specific (usually > 95% cell type specificity) with variable expression levels, and the astrocyte enhancer-AAVs show multiple distinct expression patterns reflecting the spatial distribution of astrocyte cell types. To provide the best glial-specific functional tools, several enhancer-AAVs were: optimized for higher expression levels, shown to be functional and specific in rat and macaque, shown to maintain specific activity across transgenes and in epilepsy where traditional promoters changed activity, and used to drive functional transgenes in astrocytes including Cre recombinase and acetylcholine-responsive sensor iAChSnFR. The astrocyte-specific iAChSnFR revealed a clear reward-dependent acetylcholine response in astrocytes of the nucleus accumbens during reinforcement learning. Together, this collection of glial enhancer-AAVs will enable characterization of astrocyte and oligodendrocyte populations and their roles across species, disease states, and behavioral epochs.

neuroscience↗

bioRxiv2020

Mediodorsal thalamus contributes to the timing of instrumental actions

The perception of time is critical to adaptive behavior. While prefrontal cortex and basal ganglia have been implicated in interval timing in the seconds to minutes range, little is known about the role of the mediodorsal thalamus (MD), which is a key component of the limbic cortico-basal ganglia-thalamocortical loop. In this study we tested the role of the MD in timing, using an operant temporal production task in male mice. In this task, the expected timing of available rewards is indicated by lever pressing. Inactivation of the MD with muscimol produced rightward shifts in peak pressing on probe trials as well as increases in peak spread, thus significantly altering both temporal accuracy and precision. Optogenetic inhibition of glutamatergic projection neurons in the MD also resulted in similar changes in timing. The observed effects were found to be independent of significant changes in movement. Our findings suggest that the MD is a critical component of the neural circuit for interval timing, without playing a direct role in regulating ongoing performance. Significance StatementThe mediodorsal nucleus of the thalamus (MD) is strongly connected with the prefrontal cortex and basal ganglia, areas which have been implicated in interval timing. Previous work has shown that the MD contributes to working memory and learning of action-outcome contingencies, but its role in behavioral timing is poorly understood. Using an operant temporal production task, we showed that inactivation of the MD significantly impaired timing behavior.

neuroscience↗