Biology subjects

Eddison, M.

Publications and source records attributed to Eddison, M..

12 recordsLinked to original sources

bioRxiv2026

A Scalable Cross-Modal Workflow for Linking In Vivo Neural Activity to Neuronal Cell Types via Spatial Gene Profiling

A central challenge in systems neuroscience research is to elucidate how distinct neuronal cell types coordinate to produce complex behaviors: an endeavor that requires linking their molecular identity, connectivity and activity patterns in behaving animals. Recent advances in single-cell RNA sequencing and spatial transcriptomics have revealed remarkable molecular diversity among neurons. However, most functional recording techniques, including in vivo two-photon calcium imaging, do not reveal the molecular cell identities of recorded cells. Although manual one-to-one matching between functional imaging and post hoc molecular profiling has been achieved for dozens to a few hundred neurons, these approaches are typically labor-intensive, difficult to scale, and capture only a limited fraction of cell types. Integrating these two modalities at large scale remains challenging, limiting our ability to fully understand the general logic of neural computation. Here we present a cross-modal workflow that integrates in vivo two-photon calcium imaging in behaving mice with Expansion-Assisted Iterative Fluorescence In Situ Hybridization (EASI-FISH), a thick-tissue spatial transcriptomic approach. As a proof of concept, we apply this workflow to the mouse dorsal hippocampus, a brain region with high neuronal density and small cell size where manual cell matching is impractical, making it a stringent test for the accuracy and scalability of this method. Using our approach, we achieved highly accurate alignment between in vivo neural activity and ex vivo molecular cell-type identity across hundreds to thousands of neurons, enabling direct mapping of neural dynamics to molecularly defined neuronal populations. We showed that longitudinal neural recordings followed by molecular mapping reveal distinct neural activity patterns that emerge as animals learn a spatial navigation task. By linking activity patterns to molecularly defined cell types, this method provides a framework for testing whether neural representations are organized through cell-type-specific coding or distributed population activity, offering insight into the computational logic by which neural circuits generate complex behaviors.

neuroscience↗

bioRxiv2026

Whole-Brain Co-Mapping of Gene Expression and NeuronalActivity at Cellular Resolution in Behaving Zebrafish

The brains capabilities rely on both the molecular properties of individual cells and their interactions across brain-wide networks. However, relating gene expression to activity in individual neurons across the entire brain remains elusive. Here we developed an experimental-computational platform, WARP, for whole-brain imaging of neuronal activity during behavior, expansion-assisted spatial transcriptomics, and cellular-level registration of these two modalities. Through joint analysis of whole-brain neuronal activity during multiple behaviors, cellular gene expression, and anatomy, we identified functions of molecularly defined populations--including luminance coding in a cckb-pou4f2 midbrain population and task-structured activity in pvalb7-eomesa hippocampal-like neurons--and defined over 2,000 other function-gene-anatomy subpopulations. Analysis of this unprecedented multimodal dataset also revealed that most gene-matched neurons showed stronger activity correlations, highlighting a brain-wide role for gene expression in functional organization. WARP establishes a foundational platform and open-access dataset for cross-experiment discovery, high-throughput function-to-gene mapping, unification of cell biology and systems neuroscience, and scalable circuit modeling at the whole-brain scale.

neuroscience↗

bioRxiv2025

SpotDMix: informed mRNA transcript assignment using mixture models

Unveiling the genetic profiles of spatially distinguished cells is an important aspect in many areas of brain research, as the genetic identity contains information about a cells physiological properties and internal state. On top of this, knowledge of the genetic details of each cell can reveal structural organization within tissue. As image-based spatial transcriptomics moves toward applications in tissues with dense cellular packing, accurate assignment of detected mRNA transcripts ("spots") to correct segmented cells becomes increasingly difficult, rendering simple methods insufficient with many incorrect assignments to neighboring cells. Here we introduce SpotDMix, a statistical model for assigning spots to cells by modeling spots as coming from a mixture model of distributions matching segmented cell shapes, with assignment probabilities and shape parameters optimized using the Expectation Maximization algorithm. Performance is assessed and compared against several simple methods in various scenarios on both surrogate data and larval zebrafish data. In all tested scenarios SpotDMix outperforms the simple methods on all evaluated metrics, including individual transcript assignment accuracy, total assigned number of spots per cell error and cell type classification. Further, SpotDMix produces a higher degree of exclusivity between genes which are known to not or rarely co-express.

neuroscience↗

bioRxiv2025

Octopamine instructs head direction plasticity

Many plasticity rules rely on adjusting the strength of synapses between pairs of cells based on their coincident activity. We uncovered a new mechanism for coincidence detection in the Drosophila head direction network. To maintain an accurate sense of direction, head direction neurons that signal orientation during navigation must learn to anchor to relevant external sensory cues in novel environments. Yet the synaptic mechanism for this form of unsupervised learning is unknown in any organism. In Drosophila, GABAergic visual inputs converge onto head direction neurons, and these inhibitory synapses change strength with experience to learn the relationship between visual landmarks and head direction. However, how coincident pre- and postsynaptic activity is detected across this inhibitory synapse is not understood. We discovered that neurons which release the monoamine octopamine close a feedback loop that conveys postsynaptic head direction activity onto presynaptic terminals of visual inputs. This octopamine pathway is required for anchoring the head direction network to visual cues. Furthermore, pairing structured activation of octopamine neurons with a visual cue is sufficient to drive rapid plasticity, even without postsynaptic head direction cell activity. Previous work has extensively characterized coincidence detection mechanisms at excitatory synapses; our work defines a novel mechanism for coincidence detection at an inhibitory synapse, in which postsynaptic activity is relayed via a neuromodulatory neuron onto presynaptic terminals.

neuroscience↗

bioRxiv2025

Imaging cellular activity simultaneously across all organs of a vertebrate reveals body-wide circuits

All cells in an animal collectively ensure, moment-to-moment, the survival of the whole organism in the face of environmental stressors1,2. Physiology seeks to elucidate the intricate network of interactions that sustain life, which often span multiple organs, cell types, and timescales, but a major challenge lies in the inability to simultaneously record time-varying cellular activity throughout the entire body. We developed WHOLISTIC (WHole Organism Live Imaging System for recording Tissue and IntraCellular activity), a method to image second-timescale, time-varying intracellular dynamics across cell-types of the vertebrate body. By advancing and integrating volumetric fluorescence microscopy, machine learning, and pancellular transgenic expression of calcium sensors in transparent young Danio rerio (zebrafish) and with proof of concept in adult Danionella, the method enables real-time recording of cellular dynamics across the organism. Calcium is a universal intracellular messenger, with a large array of cellular processes depending on changes in calcium concentration across varying time-scales, making it an ideal proxy of cellular activity3. Using this platform to screen the dynamics of most cells in the body, we discovered unexpected responses of specific cell types to stimuli, such as chondrocyte reactions to cold, meningeal responses to ketamine, and state-dependent activity, such as oscillatory ependymal-cell activity during periods of extended motor quiescence. At the organ scale, the method uncovered pulsating traveling waves along the kidney nephron. At the multi-organ scale, we uncovered muscle synergies and independencies, as well as muscle-organ interactions. Integration with optogenetics allowed us to all-optically determine the causal direction of brain-body interactions. At the whole-organism scale, the method captured the rapid brainstem-controlled redistribution of blood flow across the body. Finally, we advanced Whole-Body Expansion Microscopy4 to provide ground-truth molecular and ultrastructural anatomical context, explaining the spatiotemporal structure of activity captured by WHOLISTIC. Together, these innovations establish a new paradigm for systems biology, bridging cellular and organismal physiology, with broad implications for both fundamental research and drug discovery.

neuroscience↗

bioRxiv2024

Discovery of neuronal cell types by pairing whole cell reconstructions with RNA expression profiles

Effective classification of neuronal cell types requires both molecular and morphological descriptors to be collected in situ at single-cell resolution. However, current spatial transcriptomics techniques are not compatible with imaging workflows that successfully reconstruct the morphology of complete axonal projections. Here, we introduce a new method, which we call morphoFISH, that combines tissue clearing, submicron whole-brain two photon imaging, and Expansion-Assisted Iterative Fluorescence In Situ Hybridization (EASI-FISH) to assign molecular identities to fully reconstructed neurons in the mouse brain. We used morphoFISH to molecularly identify a previously unknown population of cingulate neurons projecting ipsilaterally to the dorsal striatum and contralaterally to higher-order thalamus. By pairing whole-brain morphometry, improved techniques for nucleic acid preservation and spatial gene expression, morphoFISH offers a quantitative solution for discovery of multimodal cell types and complements existing techniques for characterization of increasingly fine-grained cellular heterogeneity in brain circuits.

neuroscience↗

bioRxiv2024

Cell type-specific driver lines targeting the Drosophila central complex and their use to investigate neuropeptide expression and sleep regulation

The central complex (CX) plays a key role in many higher-order functions of the insect brain including navigation and activity regulation. Genetic tools for manipulating individual cell types, and knowledge of what neurotransmitters and neuromodulators they express, will be required to gain mechanistic understanding of how these functions are implemented. We generated and characterized split-GAL4 driver lines that express in individual or small subsets of about half of CX cell types. We surveyed neuropeptide and neuropeptide receptor expression in the central brain using fluorescent in situ hybridization. About half of the neuropeptides we examined were expressed in only a few cells, while the rest were expressed in dozens to hundreds of cells. Neuropeptide receptors were expressed more broadly and at lower levels. Using our GAL4 drivers to mark individual cell types, we found that 51 of the 85 CX cell types we examined expressed at least one neuropeptide and 21 expressed multiple neuropeptides. Surprisingly, all co-expressed a small neurotransmitter. Finally, we used our driver lines to identify CX cell types whose activation a)ects sleep, and identified other central brain cell types that link the circadian clock to the CX. The well-characterized genetic tools and information on neuropeptide and neurotransmitter expression we provide should enhance studies of the CX.

neuroscience↗

bioRxiv2024

Synaptic Specializations at Dopamine Release Sites Orchestrate Efficient and Precise Neuromodulatory Signaling

Neuromodulators are generally understood to act through expansive projections that broadcast signals relatively indiscriminately, in stark contrast to the precise, synapse-bound organization of fast neurotransmitters like glutamate and GABA. This dichotomy has left the local architecture of neuromodulatory release and receptor engagement largely obscure. Here, using dopamine as a model system, we reveal that neuromodulatory signaling can be guided by precise molecular specificity. We show that dopamine axons exhibit a fundamental tropism for neurons expressing D1 or D2 receptors in the striatum and amygdala, a targeting principle that is conserved in dissociated co-cultures. Importantly, single-bouton-resolved optical imaging of release shows that dopamine is not broadcast broadly but is highly localized to varicosities that form direct, synapse-like appositions with receptor-expressing somata and dendrites. In contrast, varicosities lacking such appositions, or contacting receptor-negative neurons, are largely quiescent, indicating that local interactions with receptor-expressing targets help specify dopamine release competence. To directly visualize receptor organization relative to release sites at endogenous expression levels, we generated ALFA-tag knock-in mice (ALFADoR mice) in which the N-termini of D1 and D2 dopamine receptors are epitope-tagged. Combining these mice with immunolabeling and expansion microscopy in dissociated culture and intact tissue, we show that both D1 and D2 receptors are organized into discrete puncta rather than diffuse membrane distributions. Across major terminal fields of midbrain dopamine neurons, including striatum, amygdala, and prefrontal cortex, these receptor nanoclusters are preferentially positioned near dopamine varicosities at distances far smaller than expected from spatial shuffling controls. Moreover, receptor clusters apposed to dopamine varicosities were observed to be larger than non-apposed clusters, consistent with specialized receptor microdomains that may enhance signaling efficacy. Together, our data demonstrate that dopaminergic signaling is spatially organized by receptor-specific targeting and subcellular microdomain specialization. This structured framework challenges the canonical dichotomy between precise fast transmission and diffuse neuromodulation. It reveals that principles of synaptic organization extend to and define a previously hidden layer of specificity in neuromodulatory systems, opening new frontiers in understanding cell-type specific neuromodulation, axon guidance, and subcellular GPCR organization.

neuroscience↗

bioRxiv2022

Multimodal mapping of cell types and projections in the central nucleus of the amygdala

The central nucleus of the amygdala (CEA) is a brain region that integrates external and internal sensory information and executes innate and adaptive behaviors through distinct output pathways. Despite its complex functions, the diversity of molecularly defined neuronal types in the CEA and their contributions to major axonal projection targets have not been examined systematically. Here, we performed single-cell RNA-sequencing (scRNA-Seq) to classify molecularly defined cell types in the CEA and identified marker-genes to map the location of these neuronal types using expansion assisted iterative fluorescence in situ hybridization (EASI-FISH). We developed new methods to integrate EASI-FISH with 5-plex retrograde axonal labeling to determine the spatial, morphological, and connectivity properties of [~]30,000 molecularly defined CEA neurons. Our study revealed spatio-molecular organization of the CEA, with medial and lateral CEA associated with distinct cell families. We also found a long-range axon projection network from the CEA, where target regions receive inputs from multiple molecularly defined cell types. Axon collateralization was found primarily among projections to hindbrain targets, which are distinct from forebrain projections. This resource reports marker-gene combinations for molecularly defined cell types and axon-projection types, which will be useful for selective interrogation of these neuronal populations to study their contributions to the diverse functions of the CEA.

neuroscience↗

bioRxiv2021

Expansion-Assisted Iterative-FISH defines lateral hypothalamus spatio-molecular organization

Determining the spatial organization and morphological characteristics of molecularly defined cell types is a major bottleneck for characterizing the architecture underpinning brain function. We developed Expansion-Assisted Iterative Fluorescence In Situ Hybridization (EASI-FISH) to survey gene expression in brain tissue, as well as a turnkey computational pipeline to rapidly process large EASI-FISH image datasets. EASI-FISH was optimized for thick brain sections (300 {micro}m) to facilitate reconstruction of spatio-molecular domains that generalize across brains. Using the EASI-FISH pipeline, we investigated the spatial distribution of dozens of molecularly defined cell types in the lateral hypothalamic area (LHA), a brain region with poorly defined anatomical organization. Mapping cell types in the LHA revealed nine novel spatially and molecularly defined subregions. EASI-FISH also facilitates iterative re-analysis of scRNA-Seq datasets to determine marker-genes that further dissociated spatial and morphological heterogeneity. The EASI-FISH pipeline democratizes mapping molecularly defined cell types, enabling discoveries about brain organization. Highlights- EASI-FISH enables robust gene expression profiling in thick brain slices - A turnkey analysis pipeline for facile analysis of large EASI-FISH image datasets - EASI-FISH reveals novel subregions of the lateral hypothalamus - Identification of rare cell types based on morphological and spatial heterogeneity

neuroscience↗

bioRxiv2021

Visualizing cellular and tissue ultrastructure using Ten-fold Robust Expansion Microscopy (TREx)

Expansion microscopy (ExM) is a powerful technique to overcome the diffraction limit of light microscopy that can be applied in both tissues and cells. In ExM, samples are embedded in a swellable polymer gel to physically expand the sample and isotropically increase resolution in x, y and z. The maximum resolution increase is limited by the expansion factor of the gel, which is four-fold for the original ExM protocol. Variations on the original ExM method have been reported that allow for greater expansion factors but at the cost of ease of adoption or versatility. Here, we systematically explore the ExM recipe space and present a novel method termed Ten-fold Robust Expansion Microscopy (TREx) that, like the original ExM method, requires no specialized equipment or procedures. We demonstrate that TREx gels expand ten-fold, can be handled easily, and can be applied to both thick mouse brain tissue sections and cultured human cells enabling high-resolution subcellular imaging with a single expansion step. Furthermore, we show that TREx can provide ultrastructural context to subcellular protein localization by combining antibody-stained samples with off-the-shelf small molecule stains for both total protein and membranes.

cell biology↗

bioRxiv2020

SNT: A Unifying Toolbox for Quantification of Neuronal Anatomy

Quantification of neuronal morphology is essential for understanding neuronal connectivity and many software tools have been developed for neuronal reconstruction and morphometry. However, such tools remain domain-specific, tethered to specific imaging modalities, and were not designed to accommodate the rich metadata generated by recent whole-brain cellular connectomics. To address these limitations, we created SNT: a unifying framework for neuronal morphometry and analysis of single-cell connectomics for the widely used Fiji and ImageJ platforms. We demonstrate that SNT can be used to tackle important problems in contemporary neuroscience, validate its utility, and illustrate how it establishes an end-to-end platform for tracing, proof-editing, visualization, quantification, and modeling of neuroanatomy. With an open and scriptable architecture, a large user base, and thorough community-based documentation, SNT is an accessible and scalable resource for the broad neuroscience community that synergizes well with existing software.

neuroscience↗