美國約翰斯 霍普金斯大學(xué)的神經(jīng)科學(xué)家近日通過研究，發(fā)現(xiàn)了可能與識(shí)別三維物體能力有關(guān)的大腦活動(dòng)模式,。相關(guān)論文10月5日在線發(fā)表于《自然—神經(jīng)學(xué)》（Nature Neuroscience）,。
人類的目標(biāo)視覺能力極為出色，計(jì)算機(jī)雖然在算術(shù)運(yùn)算、下棋方面能夠勝過人類,，但無法很好地識(shí)別三維物體,。雖然描述一個(gè)三維物體不難，但要從不斷變化的二維圖形中挑出三維信息卻是大腦執(zhí)行的最難的任務(wù)之一,。
約翰斯 霍普金斯大學(xué)的研究表明,，大腦負(fù)責(zé)高級(jí)視覺的區(qū)域?qū)⑷S物體當(dāng)作平面的立體組合，多個(gè)神經(jīng)細(xì)胞組合起來編碼整個(gè)物體表面,。約翰斯?霍普金斯大學(xué)Zanvyl Krieger意識(shí)-大腦研究所的Charles E. Connor說：“人類對物體結(jié)構(gòu)非常敏感,，這可能歸功于大腦清晰的結(jié)構(gòu)描繪方式。”
在這項(xiàng)研究中,，約翰斯 霍普金斯大學(xué)博士后Yukako Yamane訓(xùn)練2只恒河猴看電腦屏幕上不斷閃動(dòng)的三維圖像,，同時(shí)記錄猴腦中負(fù)責(zé)高級(jí)視覺區(qū)域中神經(jīng)細(xì)胞的電反應(yīng)，并應(yīng)用電腦程序指導(dǎo)實(shí)驗(yàn)逐漸形成誘發(fā)強(qiáng)烈反應(yīng)的物體形狀,。這一進(jìn)化刺激策略幫助研究人員確定了驅(qū)動(dòng)特定細(xì)胞反應(yīng)的精確3D信息,。
這種對大腦中物體編碼的研究可能對治療知覺障礙病人有幫助，此外,，它還可以幫助研發(fā)計(jì)算機(jī)視覺的新方法,。同時(shí)Connor也相信，對神經(jīng)編碼的理解可以幫助解釋人的視覺體驗(yàn),，甚至審美感覺,。（生物谷Bioon.com）
生物谷推薦原始出處：
Nature Neuroscience，doi:10.1038/nn.2202,，Yukako Yamane,，Charles E Connor
A neural code for three-dimensional object shape in macaque inferotemporal cortex
Yukako Yamane1, Eric T Carlson1,2, Katherine C Bowman1,3, Zhihong Wang1 & Charles E Connor1,3
Abstract
Previous investigations of the neural code for complex object shape have focused on two-dimensional pattern representation. This may be the primary mode for object vision given its simplicity and direct relation to the retinal image. In contrast, three-dimensional shape representation requires higher-dimensional coding derived from extensive computation. We found evidence for an explicit neural code for complex three-dimensional object shape. We used an evolutionary stimulus strategy and linear/nonlinear response models to characterize three-dimensional shape responses in macaque monkey inferotemporal cortex (IT). We found widespread tuning for three-dimensional spatial configurations of surface fragments characterized by their three-dimensional orientations and joint principal curvatures. Configural representation of three-dimensional shape could provide specific knowledge of object structure to support guidance of complex physical interactions and evaluation of object functionality and utility.
1 Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University, 3400 N. Charles Street, Baltimore, Maryland 21218, USA.
2 Department of Biomedical Engineering, Johns Hopkins University, School of Medicine, 720 Rutland Avenue, Baltimore, Maryland 21205, USA.
3 Department of Neuroscience, Johns Hopkins University, School of Medicine, 725 N. Wolfe Street, Baltimore, Maryland 21205, USA.
