A SMARTR workflow for multi-ensemble atlas mapping and brain-wide network analysis.

In the last decade, activity-dependent strategies for labelling multiple immediate early gene (IEG) ensembles in mice have generated unprecedented insight into the mechanisms of memory encoding, storage, and retrieval. However, few strategies exist for brain-wide mapping of multiple ensembles, including their overlapping population, and none incorporate capabilities for downstream network analysis. Here, we introduce a scalable workflow to analyze traditionally coronally-sectioned datasets produced by activity-dependent tagging systems. Intrinsic to this pipeline is simple multi-ensemble atlas registration and statistical testing in R (SMARTR), an R package which wraps mapping capabilities with functions for statistical analysis and network visualization. We demonstrate the versatility of SMARTR by mapping the ensembles underlying the acquisition and expression of learned helplessness (LH), a robust stress model. Applying network analysis, we find that exposure to inescapable shock (IS), compared to context training (CT), results in decreased centrality of regions engaged in spatial and contextual processing and higher influence of regions involved in somatosensory and affective processing. During LH expression, the substantia nigra emerges as a highly influential region which shows a functional reversal following IS, indicating a possible regulatory function of motor activity during helplessness. We also report that IS results in a robust decrease in reactivation activity across a number of cortical, hippocampal, and amygdalar regions, indicating suppression of ensemble reactivation may be a neurobiological signature of LH. These results highlight the emergent insights uniquely garnered by applying our analysis approach to multiple ensemble datasets and demonstrate the strength of our workflow as a hypothesis-generating toolkit.

Sex-Specific Effects of Anxiety on Cognition and Activity-Dependent Neural Networks: Insights from (Female) Mice and (Wo)Men.

INTRODUCTION: Neuropsychiatric symptoms (NPS), such as depression and anxiety, are observed in 90% of Alzheimer's disease (AD) patients, two-thirds of whom are women. NPS usually manifest long before AD onset creating a therapeutic opportunity. Here, we examined the impact of anxiety on AD progression and the underlying brain-wide neuronal mechanisms. METHODS: To gain mechanistic insight into how anxiety impacts AD progression, we performed a cross-sectional analysis on mood, cognition, and neural activity utilizing the ArcCreERT2 x enhanced yellow fluorescent protein (eYFP) x APP/PS1 (AD) mice. The ADNI dataset was used to determine the impact of anxiety on AD progression in human subjects. RESULTS: Female AD mice exhibited anxiety-like behavior and cognitive decline at an earlier age than control (Ctrl) mice and male mice. Brain-wide analysis of c-Fos+ revealed changes in regional correlations and overall network connectivity in AD mice. Sex-specific memory trace changes were observed; female AD mice exhibited impaired memory traces in dorsal CA3 (dCA3), while male AD mice exhibited impaired memory traces in the dorsal dentate gyrus (dDG). In the ADNI dataset, anxiety predicted transition to dementia. Female subjects positive for anxiety and amyloid transitioned more quickly to dementia than male subjects. CONCLUSIONS: While future studies are needed to understand whether anxiety is a predictor, a neuropsychiatric biomarker, or a comorbid symptom that occurs during disease onset, these results suggest that AD network dysfunction is sexually dimorphic, and that personalized medicine may benefit male and female AD patients rather than a one size fits all approach.