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This work presents a spiking neural network for predicting kinematics from neural data towards accurate and energy-efficient brain machine interface. A brain machine interface is a technological system that interprets neural signals to allow motor impaired patients to control prosthetic devices. Spiking neural networks have the potential to improve brain machine interface technology due to their low power cost and close similarity to biological neural structures. The SNN in this study uses the leaky integrate-and-fire model to simulate the behavior of neurons, and learns using a local learning method that uses surrogate gradient to learn the parameters of the network. The network implements a novel continuous time output encoding scheme that allows for regression-based learning. The SNN is trained and tested offline on neural and kinematic data recorded from the premotor cortex of a primate and the hippocampus of a rat. The model is evaluated by finding the correlation between the predicted kinematic data and true kinematic data, and achieves peak Pearson Correlation Coefficients of 0.77 for the premotor cortex recordings and 0.80 for the hippocampus recordings. The accuracy of the model is benchmarked against a Kalman filter decoder and a LSTM network, as well as a spiking neural network trained with backpropagation to compare the effects of local learning.

Adeno-associated virus (AAV)-mediated genetic targeting of microglia remains challenging. Overcoming this hurdle is essential for gene editing in the central nervous system (CNS). Here, we characterized the minimal/native promoter of the HexB gene, which is known to be specifically and stably expressed in the microglia during homeostatic and pathological conditions. Dual reporter and serial deletion assays identified the critical role of the natural 5’ untranslated region (−97 bp related to the first ATG) in driving transcriptional activity of the mouse HexB gene. The native promoter region of mouse, human and monkey HexB located at -135, -134 and -170 bp to the first ATG, respectively. These promoters were highly active and specific in microglia with strong cross-species transcriptional activities, but had no activities in primary astrocytes. In addition, we identified a 135 bp promoter of CD68 gene was also highly active in microglia but not in astrocytes. Considering that HexB is specifically expressed in microglia, not in monocytes/macrophages or other neuronal cells, these data suggest that the newly characterized 134 bp microglia-specific HexB promoter can be an ideal candidate for microglia-targeting AAV gene therapy, which could be developed for HIV eradication in the brain wherein microglia harbor the main HIV reservoirs in the CNS.SummaryIt is hard to overstate the importance of gene therapy that can remove viral genes from human cells. A cure for HIV would mean a lifetime free of treatment for patients who now must maintain a strict regimen of ART indefinitely. In order to develop a cure using AAV delivery, payload DNA must meet the AAV vector size limitations, and the payload genes must be expressed appropriately. Previous studies have identified microglia-specific HexB gene that shows stable expression during neural homeostasis and pathogenesis. Our study identified the essential HexB gene promoter (134 bp) as a strong candidate for AAV gene therapy to specifically target the brain microglia, the main cellular reservoirs of HIV in the central nervous system. Our studies continue to move us closer to identifying target-specific gene therapy for NeuroAIDS.

Mitochondria coordinate diverse functions within neurites, including signaling events for axonal maintenance, and degeneration. However, less is known about the role of mitochondria in axon development and maturation. Here we find that in maturing retinal ganglion cells (RGCs) in vivo, axonal mitochondria increase in size, number, and total area throughout development. We demonstrate through multiple approaches in vivo that the mechanism underlying these mitochondrial changes are dependent on eye opening and associated neuronal activity, which can be mimicked by brain derived neurotrophic factor (BDNF). We report downstream gene and protein expression changes consistent with mitochondrial biogenesis and energetics pathways, and present evidence that the associated transcripts are localized and translated at mitochondria within axons in an activity-dependent manner. Together these data support a novel model for mitochondrial-localized translation in support of intra-axonal mitochondrial dynamics and axonal maturation.