Biology subjects

Horstick, E. J.

Publications and source records attributed to Horstick, E. J..

8 recordsLinked to original sources

bioRxiv2025

MCA: A Multicellular analysis Calcium Imaging toolbox for ImageJ

Functional imaging using genetically encoded indicators, such as GCaMP, has become a foundational tool for in vivo experiments and allows for the analysis of cellular dynamics, sensory processing, and cellular communication. However, large scale or complex functional imaging experiments pose analytical challenges. Many programs have worked to create pipelines to address these challenges, however, most platforms require proprietary software, impose operational restrictions, offer limited outputs, or require significant knowledge of various programming languages, which collectively can limit utility. To address this, we designed MCA (a Multicellular Analysis toolkit) to work with ImageJ, a widely used open-source software which has been the standard image analysis platform for the last 30 years. We developed MCA to be visually intuitive, utilizing ImageJs platform to generate new images based on completed tasks so users can visually see each step in the analysis pipeline. In addition, MCA implements a user-friendly GUI providing a simple interface which resembles other native ImageJ plugins. We incorporated functionality for rigid registration to correct motion artifacts, algorithms for cell body prediction, and methods for annotating cells and exporting data. For cell prediction, we trained a custom model in Cellpose 2.0 for segmentation of nuclei expressing pan-neuronal nuclear localized GCaMP in zebrafish. We validated the accuracy of MCA output to previously published zebrafish calcium imaging data which elicited visually evoked neuronal responses. To show the versatility of MCA, we also show that our software can be utilized for multiple sensory modalities, brain regions, and multiple model organisms including Drosophila and mouse. Together these data show that MCA is viable for extracting calcium dynamics in a user-friendly environment for multiple forms of functional imaging. MotivationCalcium imaging has become one of the most common methods for investigating neural activity, however analytical methods are limited to a few software platforms or are custom made. This limits replicability and imposes restrictions on incorporating additional tools to support analysis. To address these challenges, we developed a modular, graphical based, open-source toolbox, based in the ImageJ application, for performing functional imaging analysis in diverse models and datasets. HighlightsO_LIDeveloped MCA, an ImageJ based plugin for analyzing functional imaging datasets. C_LIO_LIValidated accuracy of MCA functions C_LIO_LIUtilized MCA across multiple sensory modalities and model organisms C_LI

neuroscience↗

bioRxiv2025

High throughput machine learning pipeline to characterize larval zebrafish motor behavior

Using machine learning, we developed models that rigorously detect and classify larval zebrafish spontaneous and stimulus-evoked behaviors in various well plate formats. Zebrafish are an ideal model system for investigating the neural substrates underlying behavior due to their simple nervous system and well-documented responses to environmental stimuli. To track movement, we utilized an 8 key point pose estimation model, allowing precise capture of zebrafish kinematics. Using this kinematic data, we trained two random forest classifiers in a semi-supervised learning framework to classify various discreet behavioral outputs including stationary, scoot, turn, acoustic-startle like behavior, and visual-startle like behavior. The classifiers were trained on a manually labeled dataset, and their accuracy was validated showing high precision. To validate our machine learning models, we analyzed behavioral outputs during various stimulus evoked responses and during spontaneous behavior. For additional validation, and to show the utility of our recording and analysis pipeline, we investigated the locomotor effects of several established drugs with well-defined impacts on neurophysiology. Here we show that machine learning model development, enabled by semi-supervised learning developed classification models, provide detailed insights into the behavioral phenotypes of zebrafish, offering a powerful, high throughput method for studying neural control of behavior.

neuroscience↗

bioRxiv2023

Thalamic neurons drive distinct forms of motor asymmetry that are conserved in teleost and dependent on visual evolution

Brain laterality is a prominent feature in Bilateria, where neural functions are favored in a single brain hemisphere. These hemispheric specializations are thought to improve behavioral performance and are commonly observed as sensory or motor asymmetries, such as handedness in humans. Despite its prevalence, our understanding of the neural and molecular substrates instructing functional lateralization is limited. Moreover, how functional lateralization is selected for or modulated throughout evolution is poorly understood. While comparative approaches offer a powerful tool for addressing this question, a major obstacle has been the lack of a conserved asymmetric behavior in genetically tractable organisms. Previously, we described a robust motor asymmetry in larval zebrafish. Following the loss of illumination, individuals show a persistent turning bias that is associated with search pattern behavior with underlying functional lateralization in the thalamus. This behavior permits a simple yet robust assay that can be used to address fundamental principles underlying lateralization in the brain across taxa. Here, we take a comparative approach and show that motor asymmetry is conserved across diverse larval teleost species, which have diverged over the past 200 million years. Using a combination of transgenic tools, ablation, and enucleation, we show that teleosts exhibit two distinct forms of motor asymmetry, vision-dependent and - independent. These asymmetries are directionally uncorrelated, yet dependent on the same subset of thalamic neurons. Lastly, we leverage Astyanax sighted and blind morphs, which show that fish with evolutionarily derived blindness lack both retinal-dependent and -independent motor asymmetries, while their sighted surface conspecifics retained both forms. Our data implicate that overlapping sensory systems and neuronal substrates drive functional lateralization in a vertebrate brain that are likely targets for selective modulation during evolution.

neuroscience↗

bioRxiv2022

Thalamic regulation of a visual critical period and motor behavior

During the visual critical period, sensory experience refines the structure and function of visual circuits. The basis of this plasticity was long thought to be limited to cortical circuits, yet recently described thalamic ocular dominance plasticity challenges this dogma and demonstrates greater complexity underlying visual plasticity. Yet how visual experience modulates responses of thalamic neurons or how the thalamus modulates CP timing is incompletely understood. Using a novel larval zebrafish, thalamus-centric ocular dominance model, we show functional changes in the thalamus and a role of inhibitory signaling to establish critical period timing using a combination of functional imaging, optogenetics, and pharmacology. Moreover, hemisphere-specific functional changes in genetically defined thalamic neurons correlate with changes in visuomotor behavior, establishing a role of thalamic plasticity in modulating motor performance. Together, our work demonstrates that visual plasticity is more broadly conserved and shows that visual experience leads to neuron-level functional changes in the thalamus that require inhibitory signaling to establish critical period timing.

neuroscience↗

bioRxiv2022

Stac1 Regulates Sensory Stimulus Induced Escape Locomotion

The stac family of genes are expressed by several cell types including neurons and muscles in a wide variety of animals. In vertebrates, stac3 encodes an adaptor protein specifically expressed by skeletal muscle that regulates L-type calcium channels (CaChs) and excitation-contraction coupling. The function of Stac proteins expressed by neurons in the vertebrate CNS, however, is unclear. To better understand neuronal Stac proteins, we identified the stac1 gene in zebrafish. stac1 is expressed selectively in the embryonic CNS including in Kolmer-Agduhr (KA) neurons, the cerebral fluid-contacting neurons (CSF-cNs) in the spinal cord. Previously CSF-cNs in the spinal cord were implicated in locomotion by zebrafish larvae. Thus, expression of stac1 by CSF-cNs and the regulation of CaChs by Stac3 suggest the hypothesis that Stac1 may be important for normal locomotion by zebrafish embryos. We tested to see if optogenetic activation of CSF-cNs was sufficient to induced swimming in embryos as it is in larvae. Indeed, optogenetic activation of CSF-cNs in embryos induced swimming in embryos. Next, we generated stac1-/- null embryos and found that both mechanosensory and noxious stimulus-induced swimming were decreased. We further found that zebrafish embryos respond more vigorously to tactile stimulation in the light compared to the dark. Interestingly, light enhancement of touch-induced swimming was eliminated in stac1 mutants. Thus, Stac1 regulates escape locomotion in zebrafish embryos perhaps by regulating the activity of CSF-cNs. SIGNIFICANCE STATEMENTThe stac genes are a small family of genes found in neurons and muscle in both vertebrates and invertebrates. Stac3 is a muscle protein that controls excitation-contraction coupling via regulation of L-type calcium channels and in humans a STAC3 mutation is responsible for a congenital myopathy. The function of neural Stac proteins, however, is unknown in vertebrates. The findings of this report show that neural stac1 is expressed by cerebral fluid-contacting neurons (CSF-cNs) in the spinal cord of zebrafish embryos and that it is necessary for normal sensory stimulus induced escape swimming. To our knowledge this is the first demonstration of a function for stac genes in neurons in the vertebrate nervous system.

neuroscience↗

bioRxiv2021

Environmental and molecular modulation of motor individuality in larval zebrafish

Innate behavioral biases such as human handedness are a ubiquitous form of inter-individual variation that are not strictly hardwired into the genome and are influenced by diverse internal and external cues. Yet, genetic and environmental factors modulating behavioral variation remain poorly understood, especially in vertebrates. To identify genetic and environmental factors that influence behavioral variation, we take advantage of larval zebrafish light-search behavior. During light-search, individuals preferentially turn in leftward or rightward loops, in which directional bias is sustained and non-heritable, and maintained by a habenula-rostral PT circuit. Here we use a medium-throughput recording strategy and unbiased analysis to show that significant individual to individual variation exists in wildtype larval zebrafish turning preference. We classify stable left, right, and unbiased turning types, with most individuals exhibiting a directional preference. Raising larvae at elevated temperature selectively reduces the leftward turning type and impacts rostral PT neurons, specifically. Exposure to conspecifics, variable salinity, environmental enrichment, and physical disturbance does not significantly impact inter-individual turning bias. Pharmacological manipulation of Notch signaling and carrying a mutant allele of a known Notch pathway affecter gene, gsx2, disrupted turn bias individuality in a dose-dependent manner. These results establish that larval zebrafish is a powerful vertebrate model for inter-individual variation with sensitivity to specific environmental perturbations and gene dosage.

neuroscience↗

bioRxiv2019

Molecular and cellular determinants of motor asymmetry in zebrafish

Asymmetries in motor behavior, such as human hand preference, are observed throughout bilateria. However, neural substrates and developmental signaling pathways that impose underlying functional lateralization on a broadly symmetric nervous system are unknown. Here we report that in the absence of over-riding visual information, zebrafish larvae show intrinsic lateralized motor behavior that is mediated by a cluster of 60 posterior tuberculum (PT) neurons in the forebrain. PT neurons impose motor bias via a projection through the epithalamic commissure to the habenula. Acquisition of left/right identity is disrupted by heterozygous mutations in mosaic eyes and mindbomb, genes that regulate Notch signaling. These results define the neuronal substrate for motor asymmetry in a vertebrate and support the idea that developmental pathways that establish visceral asymmetries also govern acquisition of left/right identity.

neuroscience↗

bioRxiv2016

High precision registration between zebrafish brain atlases using symmetric diffeomorphic normalization

Atlases provide a framework for information from diverse sources to be spatially mapped and integrated into a common reference space. In particular, brain atlases allow regional annotation of gene expression, cell morphology, connectivity and activity. In larval zebrafish, advances in genetics, imaging and computational methods have enabled the collection of large datasets providing such information on a whole-brain scale. However, datasets from different sources may not be aligned to the same spatial coordinate system, because technical considerations may necessitate use of different reference templates. Two recent brain atlases for larval zebrafish exemplify this problem. The Z-Brain atlas contains information on gene expression, neural activity and neuroanatomical segmentation acquired using immunohistochemical staining of fixed tissue. In contrast, the Zebrafish Brain Browser (ZBB) atlas was constructed from live scans of fluorescent reporter genes in transgenic larvae. Although different reference brains were used, the two atlases included several transgene patterns in common that provided potential 'bridges' for transforming each into the others coordinate space. We therefore tested multiple bridging channels and registration algorithms. The symmetric diffeomorphic normalization (SyN) algorithm in ANTs improved the precision of live brain registration while better preserving cell morphology than the previously used B-spline elastic registration algorithm. SyN could also be calibrated to correct for tissue distortion introduced during fixation and permeabilization. Finally, multi-reference channel optimization provided a transformation matrix that enabled Z-Brain and ZBB to be co-aligned with acceptable precision and minimal perturbation of cell and tissue morphology. This study demonstrates the feasibility of integrating whole brain datasets, despite disparate acquisition protocols and reference templates, when sufficient information is present for bridging.\n\nAnatomical abbreviations

neuroscience↗