Computational and Hardware Models of Active Sensing Behaviors

老鼠大约有60根巨大的面部胡须，它们是非常敏感的触觉传感器。来自胡须的触觉信息被传递到称为三叉神经节的大脑结构，然后传递到称为三叉神经核的结构。这条通路大致类似于将信息从人类皮肤传递到大脑的通路。Hartmann、Memik和Oberci-Memik教授正在使用大鼠胡须系统作为模型，研究动物获取和完善传入感官信息以构建周围世界表征的过程。该研究在三叉神经核的神经生理学记录和所观察到的神经反应的计算建模之间进行迭代。由于神经系统是大规模并行的，模型很快就超过了传统计算机的限制。因此，这些模型是用现场可编程门阵列（FPGA）实现的，它可以有效地复制脑干电路的巨大并行性。值得注意的是，这些模型被构建为处理来自真实的和机器人胡须的数据，并且可以用于生成关于真实的动物的生理反应的预测。这项工作有可能在工业界和学术界产生影响。从工业的角度来看，它可能会激发使用非光学传感器进行无监督3D物体识别的研究。这种感测能力在各种专用环境中可能是有用的。例如，搜索和救援机器人在有限或没有视觉的情况下操作，可能会使用类似于这里开发的硬件和算法。在神经生理学方面，这项工作揭示了各种形式（视觉，听觉，躯体感觉和本体感觉）的处理算法。这项工作还有助于在博士后，研究生和本科生水平的强跨学科培训，以及少数民族学生的招聘。这项工作还补充了PI和Co-PI开发的研究生课程。

Rats have approximately sixty large facial whiskers that serve as exquisitely sensitive tactile sensors. Tactile information from the whiskers is carried to a brain structure called the trigeminal ganglion, and then to structures called the trigeminal nuclei. This pathway is roughly analogous to the pathway that carries information from the human skin to the brain. Professors Hartmann, Memik, and Ogrenci -Memik are using the rat whisker system as a model to study the process by which animals acquire and refine incoming sensory information to construct representations of the world around them. The research iterates between neurophysiological recordings in the trigeminal nuclei and computational modeling of the observed neural responses. Because the nervous system is massively parallel, the models quickly exceed the limits imposed by conventional computers. The models are therefore being implemented with Field Programmable Gate Arrays (FPGAs), which can effectively replicate the immense parallelism of brainstem circuitry. Notably, the models are built to process data from both real and robotic whiskers, and can be used to generate predictions about physiological responses in the real animal. This work has the potential to have an impact in industry as well as academia. From an industrial perspective, it is likely to inspire studies on unsupervised 3D object recognition using non-optical sensors. Such sensing ability may be useful in a variety of specialized environments. For example, search and rescue robots operating with limited or no vision could potentially use hardware and algorithms similar to those developed here. In neurophysiology, the work is shedding light on processing algorithms common across modalities (vision, audition, somatosensation and proprioception). The work also contributes to strongly-interdisciplinary training at the post-doc, graduate and undergraduate levels, as well as to minority student recruiting. The work also complements graduate-level courses developed by the PI and Co-PIs.