The Vibrissotactile Natural Scene

人类的触觉与手的动作密切相关。神经科学中的一个悬而未决的问题是，大脑如何将触觉信号（感觉）与手部运动（运动）结合起来，形成对物体的统一触觉感知。由于研究人类大脑如何结合这些线索很困难，研究人员研究了老鼠，老鼠使用大约60根胡须来实际探索环境。须系统是研究神经元如何表现和统一触摸和运动的绝佳模型，但神经科学家目前正在努力以一种模仿自然探索行为中获得的信号的方式刺激须。在这个提议中，研究者将描述大鼠大脑进化处理的触觉输入的自然模式，并将开发新的数学工具来描述大鼠所经历的环境特征。这项工作在科学上很重要，原因有二。首先，由于啮齿动物是神经科学中最常用的动物，这些实验将有助于研究人员研究大脑中与触觉和运动有关的许多部分。其次，这些新的数学工具将有助于量化包括人类在内的不同物种的触觉。拟议的工作将对科学和数学教育以及公众宣传产生重大而广泛的影响。本科生将参与这项工作，研究人员将领导西北大学的机器人俱乐部探索基于触须的触觉传感的工程应用。调查人员还将通过西班牙裔专业工程师协会、女性工程师协会和芝加哥科学与工业博物馆继续开展外联工作。在视觉和听觉领域，中枢神经元的接收区被调整为“自然场景”的统计数据，即动物在自然环境中可能遇到的刺激的那些特性。在体感领域，量化自然触觉场景是一项挑战，部分原因是体感信号与动物的运动密切相关。这项工作旨在通过结合仔细的行为监测和对老鼠头部和胡须运动的模拟，开始量化老鼠振动系统的自然触觉场景。该项目有两个主要目标。首先是描述老鼠自然生存环境的统计特征。在贝叶斯术语中，这种统计分布被称为“先验”，因为它描述了环境的几何特征，不受动物触觉抽样选择的影响。第二步是量化老鼠所取样环境的统计数据，给定它的头部运动和拍打周期的选择。在贝叶斯术语中，这种统计分布被称为“后验”，因为它包含了老鼠在优先取样触觉场景时的偏见。这项工作是首次尝试量化主动触摸的统计数据之一，旨在对能够实现时空整合的感受野特性做出具体预测。同样重要的是，这项工作将开发一个适当的数学框架来描述自然场景的几何形状，这是使用信息理论方法描述活跃体感的重要一步。

In humans, the sense of touch is closely linked with hand movements. An open question in neuroscience is how the brain combines touch signals (sensory) with hand movements (motor) to create a unified tactile perception of an object. Because of difficulties in studying how the human brain combines these cues, researchers study rats, which use ~60 whiskers to tactually explore the environment. The whisker system is an excellent model to investigate how neurons represent and unify touch and movement, but neuroscientists currently struggle to stimulate the whiskers in a way that imitates the signals obtained during natural exploratory behavior. In this proposal, the investigators will characterize naturalistic patterns of tactile input that the rat's brain evolved to process, and will develop new mathematical tools to describe the environmental features that the rat experiences. The proposed work is scientifically important for two reasons. First, because rodents are the most commonly used animals in neuroscience, these experiments will aid researchers studying many parts of the brain involved with touch and movement. Second, these new mathematical tools will help quantify the sense of touch across species, including humans. The proposed work will have significant broader impacts on science and mathematics education and public outreach. Undergraduate students will contribute to the work, and the investigators will lead Northwestern's Robotics Club to explore engineering applications of whisker-based tactile sensing. The investigators will also continue outreach efforts through the Society of Hispanic Professional Engineers, the Society of Women Engineers, and Chicago's Museum of Science and Industry. In the fields of vision and audition, the receptive fields of central neurons are tuned to the statistics of the "natural scenes,- to those properties of the stimuli that the animal is likely to encounter in its natural environment. In the field of somatosensation it is challenging to quantify the natural tactile scene, in part because somatosensory signals are tightly linked to the animal's movements. The proposed work aims to begin to quantify the natural tactile scene for the rat vibrissal system by combining careful behavioral monitoring and simulations of rat head and whisker movements. The project has two major goals. The first is to characterize the statistics of the environments that the rat naturally inhabits. In Bayesian terms, this statistical distribution is called the "prior," because it describes the environment's geometrical features, unbiased by the tactile sampling choices of the animal. The second is to quantify the statistics of the environment sampled by the rat, given its choices of head motions and whisk cycle. In Bayesian terms, this statistical distribution is called the "posterior," because it incorporates the bias of the rat when preferentially sampling the tactile scene. This work is one of the first attempts to quantify the statistics of active touch, and it aims to make specific predictions for the receptive field properties that enable spatiotemporal integration. Equally important, this work will develop an appropriate mathematical framework for characterizing the geometry of natural scenes, an essential step towards describing active somatosensation using information theoretic measures.