NOTE: End date changed to 2/29/2024 per TRISH (Ed., 9/12/23)

NOTE: End date changed to 7/31/2023 per TRISH (Ed., 8/4/22)

NOTE: End date changed to 7/31/2022 (originally 7/31/2021) per TRISH (Ed., 11/2/20)

Space exploration exposes humans to unique stressors that, if not addressed, compromise physical and psychological health and performance. Sleep is known to promote physiologic resilience making it paramount in challenging circumstances, but all sleep is not the same. Progressive, stereotyped sleep stages are common in mammals and form a basic structure known as “sleep architecture.” High homeostatic value has been placed on slow-wave sleep (SWS), which is the deepest state of sleep characterized synchronous 1–4 Hz brain oscillations. SWS co-occurs with important fluid rhythms and changes in neural microstructure that promote waste clearing, potentially underlying the important findings that SWS enhances memory and performance. This proposal aims to identify critical conditions for which enhancing SWS through non-invasive audio stimulation may mitigate the influence of stressors or augment performance. I propose a novel translational analog in the wild red squirrel as it is a freely behaving, tractable rodent model that exhibits human sleep patterns. The extreme northern latitude of the field site for this study provides an opportunity to investigate how a SWS countermeasure fares under varying, long-duration changes in circadian cueing. I will measure neural, cardiac, and accelerometry data to analytically describe how sleep architecture, autonomic markers of stress, and cognitive/physical performance interact. A major goal of this project is to concurrently refine the SWS countermeasure into a configurable, autonomous tool capable of being deployed towards long-duration human space missions. The perceived significance of the proposed work is to span evidence to products that bridge fundamental research towards understanding the foundations of performance and resilience while providing an operational toolset alongside empirically derived implementation strategy.

Our work specifically investigates these questions from both non-invasive and invasive methodologies. Firstly, we have gathered a massive amount of accelerometer data using non-invasive collaring (>7,000 total days) from red squirrels in the Yukon, where light and temperature drastically change across seasons. Although these data provide a wealth of information across many individuals (n > 200 squirrels), inertial data alone can not sufficiently identify sleep itself, let alone specific stages of sleep and its underlying architecture (e.g., REM-NREM). Therefore, a more invasive methodology was needed, albeit only possible to deploy on a smaller scale due to the relative complexity of the surgical implant procedure and required oversight. Such that, secondly, we have used the miniature neurophysiology platform we developed to record sleep in implanted, freely behaving red squirrels at the University of Michigan. The protocols we developed solve many outstanding issues related to the use of wild animals. Namely, humane anesthesia techniques that we developed through cross-institution conversations with domain experts, as well as technological advancements in performing real-time analysis of incoming neural data on our device. In sum, all of these directions build towards constructing better approaches to understanding sleep, its evolutionary importance and design, and compiling those ideas into testable countermeasure approaches to support astronaut – and more broadly, human – health.

RESULTS

My project aimed to characterize red squirrel sleep patterns in the wild; however, it was significantly impacted by border shutdowns at our primary field site in Canada due to COVID-19. I overcame those challenges by creating a local field site near the University of Michigan at Saginaw Forest, where I tagged, tracked, and trapped a local population of red squirrels. Although I did not collect a significant amount of field data, I was successful in a limited number of wild and lab-based neural recordings. The toolset I developed measured neural, cardiac, and accelerometry data. I demonstrated how such a device can be deployed in free-living conditions or used in a closed-loop paradigm to enhance SWS (see Gaidica & Dantzer, 2022). I also presented first-of-its-kind data that characterized red squirrel SWS periodicity, suggesting robust ~20-minute cycles. The significance of such work is threefold: (1) I refined a translational field model including new surgical methods for future use, (2) I developed a novel implantable with embedded technology that can apply to human conditions, and (3) I published convincing pilot data suggesting red squirrels are an ethologically relevant animal model who exhibits robust SWS cycles with behavioral patterns (e.g., sleep-wake) more like humans than rats or mice.

YEARS 1-2 IMPACT

In sum, my research worked toward a new approach and methods to reveal the foundations of performance and resilience.

YEAR 3 RESEARCH PLAN

The hindlimb unloading (HU) model has been used to simulate microgravity—and more broadly, disuse—for over 40 years. Since the National Aeronautics and Space Administration (NASA) confirmed similar tissue fluid shifts and musculoskeletal responses in rodents compared to subjects in the weightlessness of space, HU has become an important model to study other physiologic factors relating to metabolic, endocrine, and adrenal function. However, the current (and common) HU apparatus is statically calibrated, such that the hindlimbs are unloaded through tail suspension using a constant force. This weight is typically equal to a 30° incline (i.e., head-tilt down) which matches the cephalic fluid shift and pressures experienced in zero-G while providing normal weight-bearing on the forelimbs and unloading the lumbar vertebrae but not the cervical vertebrae. Since tilt-angle and weight-unloaded are co-linear, the notion that a standard unloading protocol could be implemented dynamically is possible if the unloaded weight could be monitored.

NOTE: End date changed to 2/29/2024 per TRISH (Ed., 9/12/23)

NOTE: End date changed to 7/31/2023 per TRISH (Ed., 8/4/22)

NOTE: End date changed to 7/31/2022 (originally 7/31/2021) per TRISH (Ed., 11/2/20)

Space exploration exposes humans to unique stressors that, if not addressed, compromise physical and psychological health and performance. Sleep is known to promote physiologic resilience making it paramount in challenging circumstances, but all sleep is not the same. Progressive, stereotyped sleep stages are common in mammals and form a basic structure known as “sleep architecture.” High homeostatic value has been placed on slow-wave sleep (SWS), which is the deepest state of sleep characterized synchronous 1–4 Hz brain oscillations. SWS co-occurs with important fluid rhythms and changes in neural microstructure that promote waste clearing, potentially underlying the important findings that SWS enhances memory and performance. This proposal aims to identify critical conditions for which enhancing SWS through non-invasive audio stimulation may mitigate the influence of stressors or augment performance. I propose a novel translational analog in the wild red squirrel as it is a freely behaving, tractable rodent model that exhibits human sleep patterns. The extreme northern latitude of the field site for this study provides an opportunity to investigate how a SWS countermeasure fares under varying, long-duration changes in circadian cueing. I will measure neural, cardiac, and accelerometry data to analytically describe how sleep architecture, autonomic markers of stress, and cognitive/physical performance interact. A major goal of this project is to concurrently refine the SWS countermeasure into a configurable, autonomous tool capable of being deployed towards long-duration human space missions. The perceived significance of the proposed work is to span evidence to products that bridge fundamental research towards understanding the foundations of performance and resilience while providing an operational toolset alongside empirically derived implementation strategy.

Our work specifically investigates these questions from both non-invasive and invasive methodologies. Firstly, we have gathered a massive amount of accelerometer data using non-invasive collaring (>7,000 total days) from red squirrels in the Yukon, where light and temperature drastically change across seasons. Although these data provide a wealth of information across many individuals (n > 200 squirrels), inertial data alone can not sufficiently identify sleep itself, let alone specific stages of sleep and its underlying architecture (e.g., REM-NREM). Therefore, a more invasive methodology was needed, albeit only possible to deploy on a smaller scale due to the relative complexity of the surgical implant procedure and required oversight. Such that, secondly, we have used the miniature neurophysiology platform we developed to record sleep in implanted, freely behaving red squirrels at the University of Michigan. The protocols we developed solve many outstanding issues related to the use of wild animals. Namely, humane anesthesia techniques that we developed through cross-institution conversations with domain experts, as well as technological advancements in performing real-time analysis of incoming neural data on our device. In sum, all of these directions build towards constructing better approaches to understanding sleep, its evolutionary importance and design, and compiling those ideas into testable countermeasure approaches to support astronaut – and more broadly, human – health.

In the first year, we also developed a miniaturized toolset to measure neural, cardiac, and accelerometry data to analytically describe how sleep architecture, autonomic markers of stress, and cognitive/physical performance interact. In the next year, we tested if closed-loop SWS enhancement is viable in a free-ranging species, while monitoring the physiological response to environmental and social interactions/conditions. This project concludes by connecting the SWS countermeasure as a configurable, autonomous tool capable of being deployed towards long-duration human space missions. The perceived significance of the proposed work is to span evidence to products that bridge fundamental research towards understanding the foundations of performance and resilience while providing an operational toolset alongside empirically derived implementation strategy.

NOTE: End date changed to 7/31/2022 (originally 7/31/2021) per TRISH (Ed., 11/2/20)

Space exploration exposes humans to unique stressors that, if not addressed, compromise physical and psychological health and performance. Sleep is known to promote physiologic resilience making it paramount in challenging circumstances, but all sleep is not the same. Progressive, stereotyped sleep stages are common in mammals and form a basic structure known as “sleep architecture.” High homeostatic value has been placed on slow-wave sleep (SWS), which is the deepest state of sleep characterized synchronous 1–4 Hz brain oscillations. SWS co-occurs with important fluid rhythms and changes in neural microstructure that promote waste clearing, potentially underlying the important findings that SWS enhances memory and performance. This proposal aims to identify critical conditions for which enhancing SWS through non-invasive audio stimulation may mitigate the influence of stressors or augment performance. I propose a novel translational analog in the wild red squirrel as it is a freely behaving, tractable rodent model that exhibits human sleep patterns. The extreme northern latitude of the field site for this study provides an opportunity to investigate how a SWS countermeasure fares under varying, long-duration changes in circadian cueing. I will measure neural, cardiac, and accelerometry data to analytically describe how sleep architecture, autonomic markers of stress, and cognitive/physical performance interact. A major goal of this project is to concurrently refine the SWS countermeasure into a configurable, autonomous tool capable of being deployed towards long-duration human space missions. The perceived significance of the proposed work is to span evidence to products that bridge fundamental research towards understanding the foundations of performance and resilience while providing an operational toolset alongside empirically derived implementation strategy.

Analytical tools for sleep data: We developed a novel method to classify sleep-wake behavior from accelerometer data alone. The data opens new possibilities for analyzing these data, which are typically only appreciated as being useful to identify active, daytime behaviors (e.g., running, grooming, chewing). Additionally, we discovered new sleeping patterns in the red squirrel, which may serve to identify sleep architecture ideal for extreme environment/high performers, or be useful to future hypotheses concerning how sleep has evolved and translates to the human condition.

In the first year, we also developed a miniaturized toolset to measure neural, cardiac, and accelerometry data to analytically describe how sleep architecture, autonomic markers of stress, and cognitive/physical performance interact. In the next year, we embark on a major goal to test whether closed-loop SWS enhancement is viable in a free-ranging species, while monitoring the physiological response to environmental and social interactions/conditions. This project concludes by connecting the SWS countermeasure as a configurable, autonomous tool capable of being deployed toward long-duration human space missions. The perceived significance of the proposed work is to span evidence to products that bridge fundamental research toward understanding the foundations of performance and resilience while providing an operational toolset alongside empirically derived implementation strategy.

Space exploration exposes humans to unique stressors that if not addressed compromise physical and psychological health and performance. Sleep is known to promote physiologic resilience making it paramount in challenging circumstances, but all sleep is not the same. Progressive, stereotyped sleep stages are common in mammals and form a basic structure known as “sleep architecture.” High homeostatic value has been placed on slow-wave sleep (SWS), which is the deepest state of sleep characterized synchronous 1–4 Hz brain oscillations. SWS co-occurs with important fluid rhythms and changes in neural microstructure that promote waste clearing, potentially underlying the important findings that SWS enhances memory and performance. This proposal aims to identify critical conditions for which enhancing SWS through non-invasive audio stimulation may mitigate the influence of stressors or augment performance. We propose a novel translational analog in the wild red squirrel as it is a freely behaving, tractable rodent model that exhibits human sleep patterns. The extreme northern latitude of the field site for this study provides an opportunity to investigate how a SWS countermeasure fares under varying, long-duration changes in circadian cueing. We will measure neural, cardiac, and accelerometry data to analytically describe how sleep architecture, autonomic markers of stress, and cognitive/physical performance interact. A major goal of this project is to concurrently refine the SWS countermeasure into a configurable, autonomous tool capable of being deployed towards long-duration human space missions. The perceived significance of the proposed work is to span evidence to products that bridge fundamental research towards understanding the foundations of performance and resilience while providing an operational toolset alongside empirically derived implementation strategy.