Biology subjects

Golden, S. A.

Publications and source records attributed to Golden, S. A..

12 recordsLinked to original sources

bioRxiv2026

A community benchmark enables high-resolution, cross-lab quantification of mouse social behavior

Social behavior is a sensitive readout of brain state, but quantifying rodent social behavior at scale has relied on siloed, lab-specific tools. We assembled Days of our Mice (DooM), a benchmark of manually annotated video and pose tracking spanning 15 laboratories and 33 social and solitary behaviors, and hosted a community behavior classification challenge. We built on challenge solutions to develop the High-Dimensional Rodent Annotator (HiDRA), a behavior classification tool that generalizes to labs unseen during training and learns cross-lab movement features. Applied without retraining to experimental data, HiDRA resolves line-specific and state-dependent behavioral fingerprints with strong generalizability and reproducibility, establishing high-resolution, shareable social phenotyping as a scalable readout of brain and internal state. We release the DooM dataset and HiDRA classifiers as open resources.

neuroscience↗

bioRxiv2026

An oral fentanyl self-administration model reveals dissociable escalation and relapse phenotypes in outbred vs inbred mice

Fentanyl-related overdose deaths now commonly involve non-injection routes, yet preclinical opioid self-administration is modeled predominantly intravenously. Here we establish an oral fentanyl self-administration procedure in male and female inbred C57BL/6 and outbred CD1 mice that measures volitional intake, cue-driven seeking, extinction, and relapse. Mice self-administered oral fentanyl (70 {micro}g/mL) on a fixed-ratio 1 schedule across fifteen 3-hour sessions, followed by ten extinction sessions and a cued reinstatement test. A separate cohort underwent between-session dose thresholding across a quarter-log series from 222 to 22 {micro}g/mL. Seventy-five percent of mice acquired self-administration, with similar rates across genetic background and sex. Responding increased as fentanyl concentration fell, indicating dose-sensitivity toward a preferred drug level. C57BL/6 mice escalated intake and lever pressing across sessions, responded persistently early in extinction before declining, and reinstated pressing to a conditioned cue. CD1 mice consumed high levels from the outset with limited escalation and showed neither extinction nor cued reinstatement of pressing, but shortened their reward-port approach latency when cues returned. This shows that lever presses alone would have misclassified them as weakly conditioned. A composite severity score summing seven components of fentanyl-use risk varied continuously rather than splitting into high and low groups, even among inbred mice. Sex differences were largely confined to C57BL/6 mice, in which females showed stronger cue association and higher severity scores than males. These results reveal separable escalation-prone and relapse-prone phenotypes that track genetic background. Protocols, hardware specifications, and analysis code are openly available, lowering the barrier to adopting oral fentanyl self-administration.

neuroscience↗

bioRxiv2025

Synthetic modulation of brain-wide anesthesia-activated neural ensembles using a transgenic mouse system

BackgroundGeneral anesthesia is commonly used to produce unconsciousness across species, though the underlying neural substrates remain poorly understood. Here we test the hypothesis that isoflurane anesthesia produces unconsciousness by targeting discrete cell types and neural circuits distributed brain-wide, rather than by brain-wide non-specific binding or binding exclusively within single brain regions. MethodsWe take advantage of a transgenic mouse system that expresses chemogenetic designer receptors exclusively activated by a designer drug (DREADDs) in an inducible Cre-dependent manner driven by Fos immediate early gene expression. Since Fos peaks with metabolic activity, we use this system to insert DREADDs brain-wide into neurons that are active under isoflurane anesthesia. We then test the effects of chemogenetic manipulation of brain-wide anesthesia-activated neural ensembles on behavior, in the absence of isoflurane. ResultsUsing iDisco+ intact brain clearing and light sheet microscopy, we describe brain-wide expression of the captured neurons revealing sparse, heterogeneous and spatially distributed cells. We quantify dense labeling across mesolimbic pathways that include the amygdala, hypothalamus, thalamus, and hindbrain nuclei, implicating these regions as candidate mediators of the anesthetic state. Chemogenetic manipulation of the brain-wide activated neural ensembles reproduces key components of anesthesia, including immobility and thermal anti-nociception. We observe significantly increased isoflurane sensitivity, though not a complete loss of consciousness as measured by the righting reflex, suggesting alternative mechanisms contribute to unconsciousness that are not captured by specific neural signatures. ConclusionsWe provide causal evidence that isoflurane anesthesia engages discrete, distributed brain-wide circuitry, recapitulating dissociable components of general anesthesia. Significance StatementOver 300 million people worldwide undergo general anesthesia each year, yet the neural circuit mechanisms that produce unconsciousness remain unresolved. This fundamental gap limits the development of safer anesthetic strategies and hinders efforts to understand long-term cognitive consequences. Here we define the intact brain-wide neural signatures of isoflurane anesthesia-induced unconsciousness using a transgenic mouse system. We capture brain-wide neurons that are activated by isoflurane, manipulate those ensembles using chemogenetic tools and characterize their spatial representations at the cellular resolution using light sheet microscopy. Together, our data provides causal evidence that anesthesia engages discrete, distributed brain-wide circuitry, offering a systems-level framework for understanding how unconsciousness is generated.

neuroscience↗

bioRxiv2025

Hierarchical and Spatial Mapping of Whole-Brain c-Fos Activity Reveals Distinct Opioid and Withdrawal Neuronal Ensembles

How opioid exposure and withdrawal states shape brain activity at the systems and circuit level remains poorly understood. Here, we use whole-brain, cellular-resolution c-Fos mapping to define brain-wide activity patterns and neuronal ensembles associated with morphine administration and withdrawal. To account for the brains anatomically nested structure, we developed and applied a hierarchical statistical framework that detects region-specific changes in activity and outperforms conventional methods that treat brain regions as individual, unrelated units. These distributed signals formed ensembles with consistent and anatomically structured patterns of activity, both within subregions and across multiple connected brain areas. By combining TRAP2-based activity tagging with acute whole-brain c-Fos staining, we identified morphine- and withdrawal-activated ensembles and found that they are largely non-overlapping at the single-cell level, even within the same brain region. Integration with existing spatial transcriptomics datasets identified molecular markers for these state-specific ensembles in key brain areas such as the nucleus of accumbens, amygdala and ventral tegmental areas. Lastly, by integrating Allen mouse whole-brain transcriptional datasets, we identified the molecular identity of the morphine- administration and withdrawal ensembles. These findings define dissociable neuronal ensembles that encode opposing drug states and introduce a scalable framework for linking whole-brain activity to molecular and circuit-level mechanisms. HighlightsO_LIWhole-brain neural activity mapping identifies the regional and spatial difference of morphine-administration and withdrawal neuronal ensembles. C_LIO_LIBRANCH, a hierarchical statistical testing framework, offers increased sensitivity and anatomical interpretability for whole-brain datasets. C_LIO_LITRAP2-based activity tagging reveals brain-wide separation of acute morphine and withdrawal ensembles at the cellular level. C_LIO_LIA systematic analysis of the whole brain neural activity data combined with spatial transcriptomic data revealed molecular features of opioid-related neural ensembles. C_LI

neuroscience↗

bioRxiv2025

Brainwide genetic capture for conscious state transitions

Neural circuits underlying unconsciousness remain poorly defined. We test the hypothesis that unconsciousness arises from specific, distributed circuits using general anesthesia in mice as a reproducible model. We identify a cortical-to-subcortical shift in neural activity during isoflurane anesthesia that is organized into nine discrete functional communities mapped at single-cell resolution. The lateral parabrachial nucleus (LPB) emerges as a central hub, exhibiting high interconnectivity, spontaneous firing under anesthesia, and preferential recruitment during reactivation of the brain-wide ensemble confirmed by single unit recordings. Chemogenetic reactivation of the captured brain-wide ensemble induces sedation, slow wave oscillations, hypothermia, and analgesia, which are components of anesthesia-induced unconsciousness. Reactivation of the LPB ensemble alone recapitulates a subset of these effects. Together, we define a global neural substrate for unconsciousness and recapitulate its dissociable autonomic, neurophysiologic, and behavioral effects using brain-wide ensemble manipulations. These results establish a neural circuit framework for anesthesia-induced unconsciousness in the mammalian brain.

neuroscience↗

bioRxiv2024

Distinct dynamics and intrinsic properties in ventral tegmental area populations mediate reward association and motivation

Ventral tegmental area (VTA) dopamine neurons regulate reward-related associative learning and reward-driven motivated behaviors, but how these processes are coordinated by distinct VTA neuronal subpopulations remains unresolved. Here we examine the neural correlates of reward-related prediction-error, action, cue, and outcome encoding as well as effort exertion and reward anticipation during reward-seeking behaviors. We compare the contribution of two primarily dopaminergic and largely non-overlapping VTA subpopulations, all VTA dopamine neurons, and VTA GABAergic neurons of the mouse midbrain to these processes. The dopamine subpopulation that projects to the nucleus accumbens (NAc) core preferentially encodes prediction-error and reward-predictive cues. In contrast, the dopamine subpopulation that projects to the NAc shell preferentially encodes goal-directed actions and reflects relative reward anticipation. VTA GABA neuron activity strongly contrasts VTA dopamine population activity and preferentially encodes reward outcome and retrieval. Electrophysiology, targeted optogenetics, and whole-brain input mapping reveal heterogeneity among VTA dopamine subpopulations. Our results demonstrate that VTA subpopulations carry distinct reward-related learning and motivation signals and reveal a striking pattern of functional heterogeneity among projection-defined VTA dopamine neuron populations.

neuroscience↗

bioRxiv2022

Individual differences in volitional social motivation in male and female mice following social stress.

BackgroundA key challenge in developing new treatments for neuropsychiatric illness is the disconnect between preclinical models and the complexity of human social behavior. We aimed to integrate voluntary social self-administration into a preclinical rodent stress model, as a platform for the identification of basic brain and behavior mechanisms underlying stress-induced individual differences in social motivation. Here, we introduce an operant social stress (OSS) procedure with male and female mice, where lever presses are reinforced by freely moving social interaction with a familiar social partner across social stress exposure. MethodsOSS is composed of three phases: (i) social self-administration training, (ii) social stress concurrent with daily reinforced social self-administration testing, and (iii) post-stress operant social reward testing under both non-reinforced and reinforced conditions. We resolve social stress-induced changes to social motivation behaviors using hierarchical clustering and aggregated z-scores, capturing the spectrum of individual differences that we describe with a social index score. ResultsOSS captures a range of stress-related dynamic social motivation behaviors inclusive of sex as a biological variable. Both male and female mice lever press for access to a social partner, independent of social partner coat color or familiarity. Social stress attenuates social self-administration in males and promotes social reward seeking behavior in females. Hierarchical clustering does not adequately describe the relative distributions of social motivation following stress, which we find is better described as a non-binary behavioral distribution that we define by introducing the social index score. This index is stable across individual mice. ConclusionWe demonstrate that OSS can be used to detect stable individual differences in stress-induced changes to social motivation in male and female mice. These differences may reflect unique neurobiological, cellular and circuit mechanisms not captured by preclinical models that omit voluntary social behaviors. The inclusion of volitional social procedures may enhance the understanding of behavioral adaptations promoting stress resiliency and their mechanisms under more naturalistic conditions.

neuroscience↗

bioRxiv2022

A diverse network of pericoerulear neurons control arousal states

As the primary source of norepinephrine (NE) in the brain, the locus coeruleus (LC) regulates arousal, avoidance and stress responses1,2. However, how local neuromodulatory inputs control LC function remains unresolved. Here we identify a population of transcriptionally, spatially and functionally diverse GABAergic neurons in the LC dendritic field that receive distant inputs and modulate modes of LC firing to control global arousal levels and arousal-related processing and behaviors. We define peri-LC anatomy using viral tracing and combine single-cell RNA sequencing with spatial transcriptomics to molecularly define both LC-NE and peri-LC cell types. We identify several neuronal cell types which underlie peri-LC functional diversity using a series of complementary neural circuit approaches in behaving mice. Our findings indicate that LC and peri-LC neurons are transcriptionally, functionally, and anatomically heterogenous neuronal populations which modulate arousal and avoidance states. Defining the molecular, cellular, and functional diversity of the LC and peri-LC provides a road map for understanding the neurobiological basis of arousal, motivation and neuropsychiatric disorders.

neuroscience↗

bioRxiv2022

Incubation of palatable food craving is associated with brain-wide neuronal activation in mice

Studies using rodent models have shown that relapse to drug or food seeking increases progressively during abstinence, a phenomenon termed incubation of craving. Mechanistic studies of incubation of craving have focused on specific neurobiological targets within pre- selected brain areas. Recent methodological advances in whole-brain immunohistochemistry, clearing, and imaging now enable unbiased brain-wide cellular resolution mapping of regions and circuits engaged during learned behaviors. However, these whole brain imaging approaches were developed for mouse brains while incubation of drug craving has primarily been studied in rats and incubation of food craving has not been demonstrated in mice. Here, we established a mouse model of incubation of palatable food craving and examined food reward seeking after 1, 15, and 60 abstinence days. We then used the neuronal activity marker Fos with intact brain mapping procedures to identify corresponding patterns of brain-wide activation. Relapse to food seeking was significantly higher after 60 abstinence days than after 1 or 15 days. Using unbiased ClearMap analysis, we identified increased activation of multiple brain regions, particularly corticostriatal structures, following 60, but not 15 abstinence days. We used orthogonal SMART2 analysis to confirm these findings within corticostriatal and thalamocortical subvolumes and applied expert-guided registration to investigate subdivision and layer-specific activation patterns. Overall, we (1) identified novel brain-wide activity patterns during incubation of food seeking using complementary analytical approaches, and (2) provide a single-cell resolution whole-brain atlas that can be used to identify functional networks and global architecture underlying incubation of food craving. Significance StatementRelapse to reward seeking progressively increases during abstinence, a phenomenon termed incubation of craving. Mechanistic studies of incubation can lead to novel relapse treatments. However, previous studies have primarily used rat models and targeted region-by-region analyses and a brain-wide functional atlas of incubation of reward seeking is lacking. We established a behavioral procedure for incubation of palatable food seeking in mice and applied whole-brain activity mapping with Fos as a neuronal activity marker to identify the functional connectome of this incubation. Like rats, mice showed incubation of food seeking during abstinence. Using two complementary activity mapping approaches, we identified a brain-wide pattern of increased neural activation that mirrored incubation of food seeking after 60, but not 15, days of abstinence.

neuroscience↗

bioRxiv2021

Lateral Line Ablation by Toxins Results in Distinct Rheotaxis Profiles in Fish

The zebrafish lateral line is an established model for hair cell organ damage, yet few studies link mechanistic disruptions to changes in biologically relevant behavior. We used larval zebrafish to determine how damage via ototoxic compounds impact rheotaxis. Larvae were treated with CuSO4 or neomycin to disrupt lateral line function then exposed to water flow stimuli. Their swimming behavior was recorded on video then DeepLabCut and SimBA software were used to track movements and classify rheotaxis behavior, respectively. Lateral line-disrupted fish performed rheotaxis, but they swam greater distances, for shorter durations, and with greater angular variance than controls. Furthermore, spectral decomposition analyses confirmed that lesioned fish exhibited ototoxic compound-specific behavioral profiles with distinct changes in the magnitude, frequency, and cross-correlation between fluctuations in linear and angular movements. Our observations demonstrate that lateral line input is needed for fish to hold their station in flow efficiently and reveals that commonly used lesion methods have unique effects on rheotaxis behavior.

animal behavior and cognition↗

bioRxiv2020

Simple Behavioral Analysis (SimBA): an open source toolkit for computer classification of complex social behaviors in experimental animals

Aberrant social behavior is a core feature of many neuropsychiatric disorders, yet the study of complex social behavior in freely moving rodents is relatively infrequently incorporated into preclinical models. This likely contributes to limited translational impact. A major bottleneck for the adoption of socially complex, ethology-rich, preclinical procedures are the technical limitations for consistently annotating detailed behavioral repertoires of rodent social behavior. Manual annotation is subjective, prone to observer drift, and extremely time-intensive. Commercial approaches are expensive and inferior to manual annotation. Open-source alternatives often require significant investments in specialized hardware and significant computational and programming knowledge. By combining recent computational advances in convolutional neural networks and pose-estimation with further machine learning analysis, complex rodent social behavior is primed for inclusion under the umbrella of computational neuroethology. Here we present an open-source package with graphical interface and workflow (Simple Behavioral Analysis, SimBA) that uses pose-estimation to create supervised machine learning predictive classifiers of rodent social behavior, with millisecond resolution and accuracies that can out-perform human observers. SimBA does not require specialized video acquisition hardware nor extensive computational background. Standard descriptive statistical analysis, along with graphical region of interest annotation, are provided in addition to predictive classifier generation. To increase ease-of-use for behavioural neuroscientists, we designed SimBA with accessible menus for pre-processing videos, annotating behavioural training datasets, selecting advanced machine learning options, robust classifier validation functions and flexible visualizations tools. This allows for predictive classifier transparency, explainability and tunability prior to, and during, experimental use. We demonstrate that this approach is flexible and robust in both mice and rats by classifying social behaviors that are commonly central to the study of brain function and social motivation. Finally, we provide a library of poseestimation weights and behavioral predictive classifiers for resident-intruder behaviors in mice and rats. All code and data, together with detailed tutorials and documentation, are available on the SimBA GitHub repository. Graphical abstractSimBA graphical interface (GUI) for creating supervised machine learning classifiers of rodent social behavior. (a) Pre-process videos. SimBA supports common video pre-processing functions (e.g., cropping, clipping, sampling, format conversion, etc.) that can be performed either on single videos, or as a batch. (b) Managing poseestimation data and creating classification projects. Pose-estimation tracking projects in DeepLabCut and DeepPoseKit can be either imported or created and managed within the SimBA graphical user interface, and the tracking results are imported into SimBA classification projects. SimBA also supports userdrawn region-of-interests (ROIs) for descriptive statistics of animal movements, or as features in machine learning classification projects. (c) Create classifiers, perform classifications, and analyze classification data. SimBA has graphical tools for correcting poseestimation tracking inaccuracies when multiple subjects are within a single frame, annotating behavioral events from videos, and optimizing machine learning hyperparameters and discrimination thresholds. A number of validation checkpoints and logs are included for increased classifier explainability and tunability prior to, and during, experimental use. Both detailed and summary data are provided at the end of classifier analysis. SimBA accepts behavioral annotations generated elsewhere (such as through JWatcher) that can be imported into SimBA classification projects. (d) Visualize classification results. SimBA has several options for visualizing machine learning classifications, animal movements and ROI data, and analyzing the durations and frequencies of classified behaviors. See the SimBA GitHub repository for a comprehensive documentation and user tutorials. O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

animal behavior and cognition↗

bioRxiv2019

SMART: An open source extension of WholeBrain for iDISCO+ LSFM intact mouse brain registration and segmentation

Mapping immediate early gene (IEG) expression across intact brains is becoming a popular approach for identifying the brain-wide activity patterns underlying behavior. Registering whole brains to an anatomical atlas presents a technical challenge that has predominantly been tackled using automated voxel-based registration methods; however, these methods may fail when brains are damaged or only partially imaged, can be challenging to correct, and require substantial computational power. Here we present an open source package in R called SMART (semi-manual alignment to reference templates) as an extension to the WholeBrain framework for automated segmentation and semi-automated registration of experimental images to vectorized atlas plates from the Allen Brain Institute Mouse Common Coordinate Framework (CCF).\n\nThe SMART package was created with the novice programmer in mind and introduces a streamlined pipeline for aligning, registering, and segmenting large LSFM volumetric datasets with the CCF across the anterior-posterior axis, using a simple choice game and interactive user-friendly menus. SMART further provides the flexibility to register partial brains or discrete user-chosen experimental images across the CCF, making it compatible with analysis of traditionally sectioned coronal brain slices. In addition to SMART, we introduce a modified tissue clearing protocol based on the iDISCO+ procedure that is optimized for uniform Fos antibody labeling and tissue clearing across whole intact mouse brains. Here we demonstrate the utility of the SMART-WholeBrain pipeline, in conjunction with the modified iDISCO+ Fos procedure, by providing example datasets alongside a full user tutorial. Finally, we present a subset of these data online in an interactive web applet. The complete SMART package is available for download on GitHub.

neuroscience↗