An interoceptive circuit regulating energy balance
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Higher cortical areas carry a wide range of sensory, cognitive and motor signals mixed in heterogeneous responses of single neurons tuned to multiple task variables. Dimensionality reduction methods that rely on correlations between neural activity and task variables leave unknown how heterogeneous responses arise from connectivity to drive behavior. We develop the latent circuit model, a dimensionality reduction approach in which task variables interact via low-dimensional recurrent connectivity to produce behavioral output. We apply the latent circuit inference to recurrent neural networks trained to perform a context-dependent decision-making task and find a suppression mechanism in which contextual representations inhibit irrelevant sensory responses. We validate this mechanism by confirming the behavioral effects of patterned connectivity perturbations predicted by the latent circuit model. We find similar suppression of irrelevant sensory responses in the prefrontal cortex of monkeys performing the same task. We show that incorporating causal interactions among task variables is critical for identifying behaviorally relevant computations from neural response data.
Skeletal interoception and prospective application in biomaterials for bone regeneration
Accumulating research has shed light on the significance of skeletal interoception, in maintaining physiological and metabolic homeostasis related to bone health. This review provides a comprehensive analysis of how skeletal interoception influences bone homeostasis, delving into the complex interplay between the nervous system and skeletal system. One key focus of the review is the role of various factors such as prostaglandin E2 (PGE2) in skeletal health via skeletal interoception. It explores how nerves innervating the bone tissue communicate with the central nervous system to regulate bone remodeling, a process critical for maintaining bone strength and integrity. Additionally, the review highlights the advancements in biomaterials designed to utilize skeletal interoception for enhancing bone regeneration and treatment of bone disorders. These biomaterials, tailored to interact with the body’s interoceptive pathways, are positioned at the forefront of innovative treatments for conditions like osteoporosis and fractures. They represent a convergence of bioengineering, neuroscience, and orthopedics, aiming to create more efficient and targeted therapies for bone-related disorders. In conclusion, the review underscores the importance of skeletal interoception in physiological regulation and its potential in developing more effective therapies for bone regeneration. It emphasizes the need for further research to fully understand the mechanisms of skeletal interoception and to harness its therapeutic potential fully.
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Community green hydrogen systems, typically consisting of rooftop photovoltaic panels paired with hybrid hydrogen-battery storage, offer urban environments with improved access to clean, on-site energy. However, economically viable pathways for deploying hydrogen storage within urban communities remain unclear. Here we develop a bottom-up energy model linking climate, human behavior and community characteristics to assess the impacts of pathways for deploying community green hydrogen systems in North America from 2030 to 2050. We show that for the same community conditions, the cost difference between the best and worst pathways can be as high as 60%. In particular, the household centralized option emerges as the preferred pathway for most communities. Furthermore, enhancing energy storage demands within these deployment pathways can reduce system design costs up to fourfold. To achieve cost-effective urban decarbonization, the study underscores the critical role of selecting the right deployment pathway and prioritizing the integration of increased energy storage in pathway designs.
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Dynamic thermalization on noisy quantum hardware
Emulating thermal observables on a digital quantum computer is essential for quantum simulation of many-body physics. However, thermalization typically requires a large system size due to incorporating a thermal bath, whilst limited resources of near-term digital quantum processors allow for simulating relatively small systems. We show that thermal observables and fluctuations may be obtained for a small closed system without a thermal bath. Thermal observables occur upon classically averaging quantum mechanical observables over randomized variants of their time evolution that run independently on a digital quantum processor. Using an IBM quantum computer, we experimentally find thermal occupation probabilities with finite positive and negative temperatures defined by the initial state’s energy. Averaging over random evolutions facilitates error mitigation, with the noise contributing to the temperature in the simulated observables. This result fosters probing the dynamical emergence of equilibrium properties of matter at finite temperatures on noisy intermediate-scale quantum hardware.
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