A Neural Computation for Visual Acuity in the Presence of Eye Movements
A Neural Computation for Visual Acuity in the Presence of Eye Movements
复制标题
眼球运动时视力的神经计算
作者：
Xaq Pitkow;H. Sompolinsky;M. Meister
人类可以区分不同的视觉刺激，这些刺激的特征只有几个光感受器的大小。这是可能的，尽管由于固定的眼睛运动，这可能比要区分的特征大很多倍，不断的图像运动。为了表现良好，大脑必须识别刺激诱导的视网膜放电模式，同时忽视自发视网膜活动引起的类似模式。这是一个挑战，因为眼睛运动的轨迹以及因此刺激位置是未知的。我们推导出一个决策规则，使用视网膜尖峰列车区分两个刺激，鉴于他们的视网膜图像移动与一个未知的随机游走轨迹。该算法动态地估计在不同视网膜位置处的刺激的概率，并且使用该概率来调制稍后获得的视网膜尖峰的影响。应用于一个简单的方向辨别任务，算法的性能与人类的敏锐度是一致的，而天真的策略，忽视眼球运动的表现要差得多。然后，我们展示了一个简单的，生物学上合理的神经网络如何使用与眼球运动统计数据近似匹配的局部，活动依赖性增益和横向相互作用来实现该算法。最后，我们讨论了这样一个网络可能在初级视觉皮层中运作的证据。
Humans can distinguish visual stimuli that differ by features the size of only a few photoreceptors. This is possible despite the incessant image motion due to fixational eye movements, which can be many times larger than the features to be distinguished. To perform well, the brain must identify the retinal firing patterns induced by the stimulus while discounting similar patterns caused by spontaneous retinal activity. This is a challenge since the trajectory of the eye movements, and consequently, the stimulus position, are unknown. We derive a decision rule for using retinal spike trains to discriminate between two stimuli, given that their retinal image moves with an unknown random walk trajectory. This algorithm dynamically estimates the probability of the stimulus at different retinal locations, and uses this to modulate the influence of retinal spikes acquired later. Applied to a simple orientation-discrimination task, the algorithm performance is consistent with human acuity, whereas naive strategies that neglect eye movements perform much worse. We then show how a simple, biologically plausible neural network could implement this algorithm using a local, activity-dependent gain and lateral interactions approximately matched to the statistics of eye movements. Finally, we discuss evidence that such a network could be operating in the primary visual cortex.
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影响因子：
2.5
作者：
Cavanaugh, JR;Bair, W;Movshon, JA
通讯作者：
Movshon, JA
DOI：
10.1364/josaa.2.001508
发表时间：
1985-01-01
影响因子：
1.9
作者：
PELLI, DG
通讯作者：
PELLI, DG
影响因子：
2.5
作者：
Shadlen, MN;Newsome, WT
通讯作者：
Newsome, WT
影响因子：
56.9
作者：
GUTHRIE, BL;PORTER, JD;SPARKS, DL
通讯作者：
SPARKS, DL
DOI：
10.1073/pnas.98.4.1935
发表时间：
2001-02
影响因子：
11.1
作者：
Mariano Sigman;Guillermo A. Cecchi;Charles D. Gilbert;M. Magnasco
通讯作者：
Mariano Sigman;Guillermo A. Cecchi;Charles D. Gilbert;M. Magnasco