Visual Adaptation and Neuronal Selectivity

现在可以设计出每秒计算数百万次的计算机，执行有用的任务，并识别物体。然而，尽管取得了这些进步，计算机在灵活性方面还不能模拟大脑的功能。大脑的一个显著特点是，它能以一种高度依赖情境和灵活的方式来解释刺激并组织其行动。对于视觉刺激，大脑能够学习大量刺激类别的结构和意义。对于某些类别，比如脸，它的表现是非常显著的：我们可以很容易地区分和识别成千上万个不同的人，基于面部成分和几何结构的非常细微的差异。考虑到我们每次看到一张给定的脸，它在视网膜上的图像与上次不同，这就更令人印象深刻了。在相同的距离和相同的光照条件下观察两个不同的个体，与在不同条件下两次观察同一个体相比，可能会产生非常相似的视网膜图像，至少是粗略的图像。尽管如此，我们能够流畅而毫不费力地识别人物、物体、地标和场景。这种能力是如何产生的？

It is now possible to design computers that compute millions of calculations per second, perform useful tasks, and recognize objects. However, despite these advances, computers fall short of emulating brain function in the domain of flexibility. One of the remarkable aspects of the brain is that it interprets stimuli and organizes its actions in a highly situation-dependent and flexible manner. With regard to visual stimuli, the brain is able to learn the structure and significance of a large number of stimulus categories. For some categories, such as faces, its performance is utterly remarkable: we readily can discriminate between and recognize thousands of different individuals based on very subtle differences in the face components and their geometrical configuration. This is all the more impressive given that each time we see a given face, its image on our retina is different from the last time. Two different individuals seen from the same distance and same lighting conditions may cast very similar retinal images, at least at a coarse level, than the same individual seen twice under different conditions. Nonetheless, we are able to fluidly and effortlessly recognize people, objects, landmarks, and scenes based on a single glance. How does this ability come about? One answer to this question relates to the manner in which complex visual stimuli are encoded in the brain. This topic has been a central focus of our research. In the past year, we have published papers related to the neural representation of stimuli in object-encoding regions V4 and TE of the visual cortex. We have previously shown that individual faces are systematically encoded based on their distinctiveness relative to an average face, so called norm-based encoding. In other words, the brain encodes to a given face according to how it differs in its structure from a mean, prototypical face. We first provided evidence for this means of encoding by conducting human behavioral experiments involving visual adaptation. In those experiments the presentation of one face for a few seconds altered the way a subsequently presented face was perceived. The misperceptions closely matched the expectations of norm-based encoding. This was strengthened by more recent neurophysiological recordings in nonhuman primates showing the neurons in the inferotemporal cortex adjust their firing rate based on the relative difference of a face from the average of many faces. Both lines of research point to the conclusion that the brain encodes face identity systematically, and relative to a prototypical average. A second important feature of face perception is the ability to learn and remember new faces, a process that undoubtedly involves changes in the brain. Unlike some skills (e.g. language acquisition), our capacity to learn new faces remains strong into adulthood. This implies that the neural machinery underlying our recognition remains, in a sense, plastic. How does experience modify neural responses? During the past year we have begun to approach this problem by monitoring the tuning functions of individual neurons over periods of days and weeks. While recording from single cells is a routine process, monitoring them for extended periods of time poses enormous challenges. We have overcome these challenges by developing, with the help of an outside collaborator, a novel inertialess microelectrode bundle array, which maintains close proximity to individual neurons by moving with the small movements of the brain. The advantage of this approach is that in recording the responses of isolated neurons over a period of many days the effects of visual learning on neural selectivity can be assessed. In the laboratory, nonhuman primates are presently being trained to learn new categories of stimuli, including novel human and simian faces, as neural responses are monitored. The results from this study will shed light on how we are able to learn stimuli because of changes in the selectivity of visual neurons.