Department of Neuroscience, Baylor College of Medicine , Houston, Texas.
J Neurophysiol. 2019 Jul 1;122(1):5-21. doi: 10.1152/jn.00168.2019. Epub 2019 Apr 10.
Our ability to perceive and discriminate textures is based on the processing of high-frequency vibrations generated on the fingertip as it scans across a surface. Although much is known about the processing of vibration amplitude and frequency information when cutaneous stimulation is experienced at a single location on the body, how these stimulus features are processed when touch occurs at multiple locations is poorly understood. We evaluated participants' ability to discriminate tactile cues (100-300 Hz) on one hand while they ignored distractor cues experienced on their other hand. We manipulated the relative positions of the hands to characterize how limb position influenced cutaneous touch interactions. In separate experiments, participants judged either the frequency or intensity of mechanical vibrations. We found that vibrations experienced on one hand always systematically modulated the perception of vibrations on the other hand. Notably, bimanual interaction patterns and their sensitivity to hand locations differed according to stimulus feature. Somatosensory interactions in intensity perception were only marked by attenuation that was invariant to hand position manipulations. In contrast, interactions in frequency perception consisted of both bias and sensitivity changes that were more pronounced when the hands were held in close proximity. We implemented models to infer the neural computations that mediate somatosensory interactions in the intensity and frequency dimensions. Our findings reveal obligatory and feature-dependent somatosensory interactions that may be supported by both feature-specific and feature-general operations. Little is known about the neural computations mediating feature-specific sensory interactions between the hands. We show that vibrations experienced on one hand systematically modulate the perception of vibrations felt on the other hand. Critically, interaction patterns and their dependence on the relative positions of the hands differed depending on whether participants judged vibration intensity or frequency. These results, which we recapitulate with models, imply that somatosensory interactions are mediated by feature-dependent neural computations.
我们感知和区分纹理的能力基于指尖在扫描表面时产生的高频振动的处理。尽管人们对身体单一部位接受皮肤刺激时振动幅度和频率信息的处理了解很多，但当触摸发生在多个部位时，这些刺激特征是如何被处理的还知之甚少。我们评估了参与者在一只手上辨别触觉提示（100-300 Hz）的能力，同时忽略了他们在另一只手上经历的干扰提示。我们操纵手的相对位置，以表征肢体位置如何影响皮肤接触的相互作用。在单独的实验中，参与者判断机械振动的频率或强度。我们发现一只手上经历的振动总是系统地调节另一只手上的振动感知。值得注意的是，双手相互作用的模式及其对手部位置的敏感性因刺激特征而异。强度感知中的体感相互作用仅表现为衰减，而与手部位置的操作无关。相比之下，在频率感知中的相互作用包括偏差和敏感性变化，当双手靠近时更为明显。我们实施了模型来推断介导强度和频率维度体感相互作用的神经计算。我们的研究结果揭示了强制性和特征依赖性的体感相互作用，这些相互作用可能由特征特异性和特征一般性操作支持。关于介导双手之间特征特异性感觉相互作用的神经计算知之甚少。我们表明，一只手上经历的振动会系统地调节另一只手上感觉到的振动的感知。至关重要的是，相互作用模式及其对手部相对位置的依赖性取决于参与者判断振动强度还是频率。这些结果与模型一起再现，意味着体感相互作用是由特征依赖性神经计算介导的。
