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Griggs, Norman et al. demonstrate a closed-loop ultrasound-based brain–machine interface (BMI) in rhesus macaques. The ultrasound BMI is capable of controlling eight independent movement directions and is stable across months without retraining.
Facemap is a data analysis framework for tracking keypoints on mouse faces and relating them to large-scale neural activity. Both of these steps use state-of-the-art convolutional neural networks to achieve high precision and fast processing speeds.
A multiplane confocal microscope provides high-contrast volumetric imaging at kilohertz rates. This system enables imaging of densely expressed genetically encoded voltage indicators with cellular resolution in the mouse brain in vivo and in vitro.
Sebenius et al. present Morphometric INverse Divergence (MIND), a robust MRI-based metric of similarity between brain areas that reflects biological factors that define cortical network architecture, such as gene expression and axonal connectivity.
Bonheur et al. developed a subcellular-distribution-based bidirectional neural activity reporter that operates on the timescale of minutes, and they demonstrate increases and decreases of neural activity associated with social behaviors in Drosophila.
The Neuro-stack is a wearable platform for recording from single neurons in freely moving humans. It also allows for personalized stimulation during real-time decoding of neural activity.
The authors developed flexible, unfolded mesh electronics for implantation in multiple brain regions of mice. The probes show minimal immune response and electrode drift, enabling stable recording of single-unit action potentials from the same neurons during the adult life of animals.