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Abstract Experimental neuroscience techniques are advancing rapidly, with major recent developments in high-density electrophysiology and targeted electrical stimulation. In combination with these techniques, cortical organoids derived from pluripotent stem cells show great promise asin vitromodels of brain development and function. Although sensory input is vital to neurodevelopmentin vivo, few studies have explored the effect of meaningful input toin vitroneural cultures over time. In this work, we demonstrate the first example of goal-directed learning in brain organoids. We developed a closed-loop electrophysiology framework to embody mouse cortical organoids into a simulated dynamical task (the inverted pendulum problem known as ‘Cartpole’) and evaluate learning through high-frequency training signals. Longitudinal experiments enabled by this framework illuminate how different methods of selecting training signals enable improvement on the tasks. We found that for most organoids, training signals chosen by artificial reinforcement learning yield better performance on the task than randomly chosen training signals or the absence of a training signal. This systematic approach to studying learning mechanismsin vitroopens new possibilities for therapeutic interventions and biological computation. 

Abstract How seizures begin at the level of microscopic neural circuits remains unknown. High-density CMOS microelectrode arrays provide a new avenue for investigating neuronal network activity, with unprecedented spatial and temporal resolution. We use high-density CMOS-based microelectrode arrays to probe the network activity of human hippocampal brain slices from six patients with mesial temporal lobe epilepsy in the presence of hyperactivity promoting media. Two slices from the dentate gyrus exhibited epileptiform activity in the presence of low magnesium media with kainic acid. Both slices displayed an electrophysiological phenotype consistent with a reciprocally connected circuit, suggesting a recurrent feedback loop is a key driver of epileptiform onset. Larger prospective studies are needed, but these findings have the potential to elucidate the network signals underlying the initiation of seizure behavior. 

SUMMARY Electrophysiology offers a high-resolution method for real-time measurement of neural activity. Longitudinal recordings from high-density microelectrode arrays (HD-MEAs) can be of considerable size for local storage and of substantial complexity for extracting neural features and network dynamics. Analysis is often demanding due to the need for multiple software tools with different runtime dependencies. To address these challenges, we developed an open-source cloud-based pipeline to store, analyze, and visualize neuronal electrophysiology recordings from HD-MEAs. This pipeline is dependency agnostic by utilizing cloud storage, cloud computing resources, and an Internet of Things messaging protocol. We containerized the services and algorithms to serve as scalable and flexible building blocks within the pipeline. In this paper, we applied this pipeline on two types of cultures, cortical organoids andex vivobrain slice recordings to show that this pipeline simplifies the data analysis process and facilitates understanding neuronal activity. 

Abstract The analysis of tissue cultures, particularly brain organoids, requires a sophisticated integration and coordination of multiple technologies for monitoring and measuring. We have developed an automated research platform enabling independent devices to achieve collaborative objectives for feedback-driven cell culture studies. Our approach enables continuous, communicative, non-invasive interactions within an Internet of Things (IoT) architecture among various sensing and actuation devices, achieving precisely timed control ofin vitrobiological experiments. The framework integrates microfluidics, electrophysiology, and imaging devices to maintain cerebral cortex organoids while measuring their neuronal activity. The organoids are cultured in custom, 3D-printed chambers affixed to commercial microelectrode arrays. Periodic feeding is achieved using programmable microfluidic pumps. We developed a computer vision fluid volume estimator used as feedback to rectify deviations in microfluidic perfusion during media feeding/aspiration cycles. We validated the system with a set of 7-day studies of mouse cerebral cortex organoids, comparing manual and automated protocols. The automated protocols were validated in maintaining robust neural activity throughout the experiment. The automated system enabled hourly electrophysiology recordings for the 7-day studies. Median neural unit firing rates increased for every sample and dynamic patterns of organoid firing rates were revealed by high-frequency recordings. Surprisingly, feeding did not affect firing rate. Furthermore, performing media exchange during a recording showed no acute effects on firing rate, enabling the use of this automated platform for reagent screening studies. 

Most physical therapists would agree that physical rehabilitation is difficult to perform remotely. Consequently, the global COVID-19 pandemic has forced many physical therapists and their clients to adapt to telehealth, especially with video conferencing. In this article, we ask: How has telehealth for physical rehabilitation evolved with the global pandemic and what are the largest technological needs, treatment methodologies, and patient barriers? With the increased widespread use of telehealth for physical therapy, we present a qualitative study towards examining the shortcomings of current physical therapy mediums and how to steer future virtual reality technologies to promote remote patient evaluation and rehabilitation. We interviewed 130 physical rehabilitation professionals across the United States through video conferencing during the COVID19 pandemic from July—August 2020. Interviews lasted 30–45 min using a semi-structured template developed from an initial pilot of 20 interviews to examine potential barriers, facilitators, and technological needs. Our findings suggest that physical therapists utilizing existing telehealth solutions have lost their ability to feel their patients’ injuries, easily assess range of motion and strength, and freely move about to examine their movements when using telehealth. This makes it difficult to fully evaluate a patient and many feel that they are more of a “life coach” giving advice to a patient rather than a traditional in-person rehabilitation session. The most common solutions that emerged during the interviews include: immersive technologies which allow physical therapists and clients 1) to remotely walk around each other in 3D, 2) enable evidence-based measures, 3) automate documentation, and 4) provider clinical practice operation through the cloud. We conclude with a discussion on opportunities for immersive virtual reality towards telehealth for physical rehabilitation.