Biology subjects

Eban-Rothschild, A.

Publications and source records attributed to Eban-Rothschild, A..

4 recordsLinked to original sources

bioRxiv2025

Sleep loss suppresses the motivation to prepare for sleep

In the period preceding sleep, humans and other animals display a stereotyped repertoire of behaviors-including hygiene-related activities and preparing a place to sleep. Evidence suggests that this pre-sleep phase actively contributes to sleep initiation and quality. Nonetheless, individuals can sometimes fall asleep without preparation, even under undesirable circumstances. These abrupt transitions into sleep can have severe consequences, particularly in high-risk environments. Although progress has been made in identifying neuronal populations controlling sleep/wake states and mechanisms regulating cortical oscillations during sleep, little is known about the natural processes that govern the pre-sleep phase, under baseline conditions and following sleep loss. Here, we examine factors regulating pre-sleep behaviors using environmental and behavioral manipulations, video recordings, machine-learning-based tracking, and EEG-EMG analysis in freely-behaving mice. We focus on nest-building-a key pre-sleep behavior-and assess its modulation by time of day and sleep deprivation. We find that mice are highly motivated to build nests during the light phase but show reduced motivation during most of the dark phase. Sleep deprivation significantly suppresses pre-sleep nest-building and promotes the direct initiation of sleep. Varying amounts of sleep deprivation, from 2-6 hours, uniformly suppress nest-building. This suppression is not due to stress, as mice exposed to acute restraint stress engage robustly in nest-building. Our findings provide insight into processes regulating the transition from wakefulness to sleep. Understanding pre-sleep regulation has important implications for treating sleep-onset difficulties-prevalent in insomnia and predictive of cognitive decline-and for mitigating risks associated with uncontrolled sleep onset in high-stakes situations. STATEMENT OF SIGNIFICANCEPrior to sleep, animals-including humans-engage in stereotyped behaviors such as preparing a sleep space, thought to facilitate sleep initiation and quality. However, sleep can occur abruptly without preparation, posing serious risks, especially in high-stakes environments. Despite progress in understanding sleep/wake circuitry, the regulation of pre-sleep behaviors remains poorly understood. Here, we used multiple techniques in mice to examine nest-building, a key pre-sleep behavior. We found that mice are more motivated to build nests during the light phase, but this behavior is strongly suppressed by sleep loss and is not affected by acute stress. These findings highlight pre-sleep behaviors as an active, regulated component of sleep onset, with implications for understanding and treating sleep initiation difficulties.

neuroscience↗

bioRxiv2024

Food intake enhances hippocampal sharp wave-ripples

Effective regulation of energy metabolism is critical for survival. Metabolic control involves various nuclei within the hypothalamus, which receive information about the bodys energy state and coordinate appropriate responses to maintain homeostasis, such as thermogenesis, pancreatic insulin secretion, and food-seeking behaviors. It has recently been found that the hippocampus, a brain region traditionally associated with memory and spatial navigation, is also involved in metabolic regulation. Specifically, hippocampal sharp wave ripples (SWRs), which are high-frequency neural oscillations supporting memory consolidation and foraging decisions, have been shown to reduce peripheral glucose levels. However, whether SWRs are enhanced by recent feeding- when the need for glucose metabolism increases, and if so, whether feeding-dependent modulation of SWRs is communicated to other brain regions involved in metabolic regulation, remains unknown. To address these gaps, we recorded SWRs from the dorsal CA1 region of the hippocampus of mice during sleep sessions before and after consumption of meals of varying caloric values. We found that SWRs occurring during sleep are significantly enhanced following food intake, with the magnitude of enhancement being dependent on the caloric content of the meal. This pattern occurred under both food-deprived and ad libitum feeding conditions. Moreover, we demonstrate that GABAergic neurons in the lateral hypothalamus, which are known to regulate food intake, exhibit a robust SWR-triggered increase in activity. These findings identify the satiety state as a factor modulating SWRs and suggest that hippocampal-lateral hypothalamic communication is a potential mechanism by which SWRs could modulate peripheral metabolism and food intake.

neuroscience↗

bioRxiv2024

DAMM for the detection and tracking of multiple animals within complex social and environmental settings

Accurate detection and tracking of animals across diverse environments are crucial for behavioral studies in various disciplines, including neuroscience. Recently, machine learning and computer vision techniques have become integral to the neuroscientists toolkit, enabling high-throughput behavioral studies. Despite advancements in localizing individual animals in simple environments, the task remains challenging in complex conditions due to intra-class visual variability and environmental diversity. These limitations hinder studies in ethologically- relevant conditions, such as when animals are concealed within nests or in obscured environments. Moreover, current tools are laborious and time-consuming to employ, requiring extensive, setup-specific annotation and model training/validation procedures. To address these challenges, we introduce the Detect Any Mouse Model (DAMM), a pretrained object detector for localizing mice in complex environments, capable of robust performance with zero to minimal additional training on new experimental setups. Our approach involves collecting and annotating a diverse dataset that encompasses single and multi-housed mice in various lighting conditions, experimental setups, and occlusion levels. We utilize the Mask R-CNN architecture for instance segmentation and validate DAMMs performance with no additional training data (zero-shot inference) and with few examples for fine-tuning (few-shot inference). DAMM excels in zero- shot inference, detecting mice, and even rats, in entirely unseen scenarios and further improves with minimal additional training. By integrating DAMM with the SORT algorithm, we demonstrate robust tracking, competitively performing with keypoint-estimation-based methods. Finally, to advance and simplify behavioral studies, we made DAMM accessible to the scientific community with a user-friendly Python API, shared model weights, and a Google Colab implementation. SignificancePresent deep learning tools for animal localization require extensive laborious annotation and time-consuming training for the creation of setup-specific models, slowing scientific progress. Additionally, the effectiveness of these tools in naturalistic settings is impeded by visual variability of objects and environmental diversity, hindering animal detection in complex environments. Our study presents the Detect Any Mouse Model (DAMM), a robustly validated object detector designed for localizing mice in complex environments. DAMM excels in generalization, robustly performing with zero to minimal additional training on previously unseen setups and multi-animal scenarios. Its integration with the SORT algorithm permits robust tracking, competitively performing with keypoint-estimation-based tools. These developments, along with our dissemination of DAMM, mark a significant step forward in streamlining ethologically-relevant animal behavioral studies.

animal behavior and cognition↗

bioRxiv2019

Arousal-State Dependent Alterations in VTA-GABAergic Neural Activity

Decades of research have implicated the ventral tegmental area (VTA) in motivation, reinforcement learning and reward processing. We and others recently demonstrated that it also serves as an important node in sleep/wake circuitry. Specifically, VTA-dopaminergic neuron activation is sufficient to drive wakefulness and necessary for the maintenance of wakefulness. However, the role of VTA gamma-aminobutyric acid (GABA)-expressing neurons in arousal regulation is not fully understood. It is still unclear whether VTA-GABAergic neurons predictably alter their firing properties across arousal states, what is the nature of interactions between VTA-GABAergic activity and cortical neural oscillations, and how activity in VTA-GABAergic neurons relates to VTA-dopaminergic neurons in the context of sleep/wake regulation. To address these questions, we simultaneously recorded population activity from VTA-GABAergic or VTA-dopaminergic neurons and EEG/EMG signals during spontaneous sleep/wake states and in the presence of salient stimuli in freely-behaving male mice. We observed that VTA-GABAergic neurons exhibit robust arousal-state-dependent alterations in population activity, with high activity and calcium transients during wakefulness and rapid-eye-movement (REM) sleep compared to non-REM (NREM) sleep. During wakefulness, population activity of VTA-GABAergic neurons, but not VTA-dopaminergic neurons, was positively correlated with EEG gamma power and negatively correlated with EEG theta power. During NREM sleep, population activity in both VTA-GABAergic and VTA-dopaminergic neurons negatively correlated with delta, theta, and sigma EEG power bands. Salient stimuli, with both positive and negative valence, activated VTA-GABAergic neurons. The strongest activation was observed for social stimuli irrespective of valence. Together, our data indicate that VTA-GABAergic neurons, like their dopaminergic counterparts, drastically alter their activity across sleep-wake states. Changes in their activity predicts cortical oscillatory patterns reflected in the EEG, which are distinct from EEG spectra associated with dopaminergic neural activity.\n\nStatement of SignificanceLittle is known about how ventral tegmental area (VTA) neural ensembles couple arousal to motivated behaviors. Using cell-type specific genetic tools, we investigated the population activity of GABAergic and dopaminergic neurons within the VTA across sleep/wake states and in the presence of salient stimuli. We demonstrate that coordinated neural activity within VTA-GABAergic neurons peaks during wakefulness and REM sleep. Furthermore, neuronal activity in VTA-GABAergic neurons is correlated with high frequency, low amplitude cortical oscillations during waking, but negatively correlated with high amplitude slower frequency oscillations during NREM sleep. Our results demonstrate that VTA-GABAergic neuronal activity is tightly linked to cortical arousal and highlight this population as a potential important node in sleep/wake regulation.

neuroscience↗