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噪声会破坏反馈增强的图形-背景分割,但不会破坏前馈图形-背景分割。

Noise destroys feedback enhanced figure-ground segmentation but not feedforward figure-ground segmentation.

作者信息

Romeo August, Arall Marina, Supèr Hans

机构信息

Faculty of Psychology, Department of Basic Psychology, Universitat de Barcelona Barcelona, Spain.

出版信息

Front Physiol. 2012 Jul 17;3:274. doi: 10.3389/fphys.2012.00274. eCollection 2012.

Abstract

Figure-ground (FG) segmentation is the separation of visual information into background and foreground objects. In the visual cortex, FG responses are observed in the late stimulus response period, when neurons fire in tonic mode, and are accompanied by a switch in cortical state. When such a switch does not occur, FG segmentation fails. Currently, it is not known what happens in the brain on such occasions. A biologically plausible feedforward spiking neuron model was previously devised that performed FG segmentation successfully. After incorporating feedback the FG signal was enhanced, which was accompanied by a change in spiking regime. In a feedforward model neurons respond in a bursting mode whereas in the feedback model neurons fired in tonic mode. It is known that bursts can overcome noise, while tonic firing appears to be much more sensitive to noise. In the present study, we try to elucidate how the presence of noise can impair FG segmentation, and to what extent the feedforward and feedback pathways can overcome noise. We show that noise specifically destroys the feedback enhanced FG segmentation and leaves the feedforward FG segmentation largely intact. Our results predict that noise produces failure in FG perception.

摘要

图底(FG)分割是将视觉信息分离为背景和前景对象的过程。在视觉皮层中,FG反应在刺激反应后期被观察到,此时神经元以紧张性模式放电,并伴随着皮层状态的转换。当这种转换不发生时,FG分割就会失败。目前,尚不清楚在这种情况下大脑中会发生什么。先前设计了一种生物学上合理的前馈脉冲神经元模型,该模型成功地进行了FG分割。加入反馈后,FG信号得到增强,同时伴随着放电模式的改变。在前馈模型中,神经元以爆发模式反应,而在反馈模型中,神经元以紧张性模式放电。已知爆发可以克服噪声,而紧张性放电似乎对噪声更敏感。在本研究中,我们试图阐明噪声的存在如何损害FG分割,以及前馈和反馈通路能在多大程度上克服噪声。我们表明,噪声特别会破坏反馈增强的FG分割,而前馈FG分割在很大程度上保持完整。我们的结果预测,噪声会导致FG感知失败。

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