Neurophotonic strategies for cell-resolved, non-invasive brain machine interfaces: multicolor bioluminescence delivered by gene therapy

脑机接口（bmi）有可能通过恢复因神经系统疾病而丧失的功能来提高生活质量。然而，目前的微创bmi（如皮质表面电极）不能提供足够的信息来进行复杂的控制。产生高信息量的bmi（例如植入的电极阵列）会损害脑组织，限制其使用寿命。该项目将开发下一代BMI，它使用光代替电，比植入电极阵列侵入性更小，使用寿命更长，并且能够记录高信息量。该提案将加强教材和暑期项目，重点是招收UMR学生（以及那些没有真正实验室研究经验的学生）。这可能会对更多的学生产生积极影响，并吸引他们学习多学科科学或STEM项目。该项目将在神经元中病毒式表达钙敏感的生物发光蛋白，因此光会随着神经活动而发出。为了区分不同的神经元，这种传感器的多种颜色是随机表达的，因此每个神经元包含不同数量的生物发光传感器的每种颜色，产生独特的光谱特征。为了监测神经活动，发射光的波长和强度被检测为时间的函数。这些数据经过处理后，可以得到大量单个神经元活动的信息。这种方法可以为实现长期、稳健和高保真的BMI提供途径。

Brain-machine interfaces (BMIs) have the potential to enhance quality of life by restoring functions lost to neurological disease. However, current minimally-invasive BMIs (e.g. cortical surface electrodes) do not provide enough information for complex control. BMIs that yield high information content (e.g. implanted electrode arrays) damage brain tissue, limiting their lifespan. This project will develop a next-generation BMI that uses light instead of electricity, is less invasive and longer-lasting than implanted electrode arrays, and is capable of high information-content recording. This proposal will enhance teaching materials and summer programs with strong emphasis on recruitment of UMR students (and those who did not have real lab research experience). This could positively influence more students and attract them to multidisciplinary sciences or STEM programs in general.The project will virally express calcium-sensitive bioluminescent proteins in neurons, so light is emitted with neural activity. To distinguish different neurons, multiple colors of such sensors are stochastically expressed, so each neuron contains different amounts of each color of the bioluminescent sensor, yielding a unique spectral signature. To monitor neural activity, the wavelength and intensity of emitted light is detected as a function of time. These data are processed to yield information on the activity of a large ensemble of individual neurons. This approach could provide a path to a long-term, robust, and high-fidelity BMI.