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首页> 外文期刊>The Journal of Neuroscience: The Official Journal of the Society for Neuroscience >Visual saliency computations: mechanisms, constraints, and the effect of feedback.
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Visual saliency computations: mechanisms, constraints, and the effect of feedback.

机译：视觉显着计算：机制，约束和反馈的效果。

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摘要

The primate visual system continuously selects spatial proscribed regions, features or objects for further processing. These selection mechanisms--collectively termed selective visual attention--are guided by intrinsic, bottom-up and by task-dependent, top-down signals. While much psychophysical research has shown that overt and covert attention is partially allocated based on saliency-driven exogenous signals, it is unclear how this is accomplished at the neuronal level. Recent electrophysiological experiments in monkeys point to the gradual emergence of saliency signals when ascending the dorsal visual stream and to the influence of top-down attention on these signals. To elucidate the neural mechanisms underlying these observations, we construct a biologically plausible network of spiking neurons to simulate the formation of saliency signals in different cortical areas. We find that saliency signals are rapidly generated through lateral excitation and inhibition in successive layers of neural populations selective to a single feature. These signals can be improved by feedback from a higher cortical area that represents a saliency map. In addition, we show how top-down attention can affect the saliency signals by disrupting this feedback through its action on the saliency map. While we find that saliency computations require dominant slow NMDA currents, the signal rapidly emerges from successive regions of the network. In conclusion, using a detailed spiking network model we find biophysical mechanisms and limitations of saliency computations which can be tested experimentally.
机译：灵长类动物视觉系统连续选择空间禁用区域，特征或物体以进行进一步处理。这些选择机制 - 集体称为选择性视觉注意力 - 由固有，自下而上和通过任务依赖性的自上而下信号引导。虽然很多心理物理研究表明，基于显着驱动的外源信号部分分配了公开和隐蔽的注意，但目前尚不清楚在神经元水平上实现这一点。最近猴子的电生理学实验指向升起背面视觉流时逐渐出现的显着性信号，并对这些信号的全面关注的影响。为了阐明这些观察结果的神经机制，我们构建了一种生物合理的尖刺神经元网络，以模拟不同皮质区域的显着信号的形成。我们发现，通过选择性地，通过在连续的神经群体中选择性的横向激发和抑制来快速产生显着性信号。通过从代表显着图的较高皮质区域的反馈来提高这些信号。此外，我们展示了通过对显着图的动作中断这一反馈来对视力上下的注意力如何影响显着性信号。虽然我们发现显着计算需要主导的慢速NMDA电流，但信号从网络的连续区域迅速出现。总之，使用详细的尖峰网络模型，我们发现了可以通过实验测试的显着计算的生物物理机制和局限性。

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