9月9日，《神經(jīng)科學期刊》（Journal of Neuroscience）發(fā)表了中科院上海生命科學研究院神經(jīng)科學研究所姚海珊研究組的研究論文“外膝體感受野的時空頻率調(diào)諧特征可以提高神經(jīng)元分辨自然圖像的能力”。
理論研究表明,，初級視覺系統(tǒng)可以有效地編碼自然視覺圖像信息。尚未清楚的一個問題是,，初級視覺系統(tǒng)能否有選擇地放大特定的圖像信息成分,，從而利于神經(jīng)元分辨不同的圖像,。姚海珊研究組研究了外膝體的時空頻率調(diào)諧特征在處理自然圖像中的作用,。他們測量外膝體的時空感受野,，觀察到神經(jīng)元的時空頻率調(diào)諧具有不可分特性，該不可分特性與信息論方法計算出來的可以最優(yōu)化傳遞自然圖像信息的神經(jīng)元模型相一致,。他們分析了自然圖像的時空頻譜特征,，觀察到不同圖像在時間頻率為10 Hz附近的頻譜能量變異最大,。有趣的是,，外膝體神經(jīng)元的最佳時間頻率與該頻譜能量變異最大的頻率段重合。他們進一步測量了外膝體神經(jīng)元對自然圖像和與自然圖像具有相同平均頻譜能量的合成圖像的反應,，觀察到外膝體神經(jīng)元對不同自然圖像的分辨能力高于對不同合成圖像的分辨能力,。這些結果表明，外膝體感受野不僅去除自然圖像中的冗余信息,，還通過其時空頻率調(diào)諧特征使得神經(jīng)元能更好地分辨不同的自然圖像,。（生物谷Bioon.com）
生物谷推薦原始出處：
The Journal of Neuroscience, September 9, 2009, 29(36):11409-11416; doi:10.1523/JNEUROSCI.1268-09.2009
The Spatiotemporal Frequency Tuning of LGN Receptive Field Facilitates Neural Discrimination of Natural Stimuli
Zhongchao Tan and Haishan Yao
Institute of Neuroscience, State Key Laboratory of Neuroscience, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
Correspondence should be addressed to Haishan Yao at the above address.
The efficient coding hypothesis suggests that the early visual system is optimized to represent stimuli in the natural environment. While it is believed that LGN processing removes the redundant information of natural scenes, it is not clear whether the early visual processing can selectively amplify important signals in natural stimuli to facilitate discrimination. In this study, we examined the functional role of LGN spatiotemporal frequency tuning in the processing of natural scenes. First, we characterized the relationship between spatial and temporal frequency tuning for LGN receptive fields. We found that LGN neurons exhibit inseparable spatiotemporal frequency tuning in a manner consistent with the feature of optimal filters that can maximize information transmission of natural scenes. Second, we analyzed the spatiotemporal power spectrum of natural scenes and found that some frequencies exhibit larger variation in power across different scenes. Interestingly, the preferred frequency of ensemble LGN neurons matches the range of frequencies in which natural power spectrum varies most. Comparison of neural discrimination for natural stimuli and for artificial stimuli with similar mean power spectra but different variation structure showed that the match between LGN tuning and natural spectra variation enhances neural discrimination for natural stimuli. Our results indicate that, in addition to removing redundancy, the spatiotemporal frequency characteristics of LGN neurons can facilitate neural discrimination of natural stimuli.
