據(jù)物理學(xué)家組織網(wǎng)11月6日報(bào)道,，最近美國杜克大學(xué)領(lǐng)導(dǎo)了一項(xiàng)研究,，讓猴子學(xué)習(xí)只用腦活動(dòng)來控制兩條虛擬手臂的運(yùn)動(dòng),。這將對開發(fā)雙向腦控假體設(shè)備，幫助嚴(yán)重癱瘓病人恢復(fù)運(yùn)動(dòng)能力起到極大推動(dòng)作用,。相關(guān)論文發(fā)表在11月6日的《科學(xué)—轉(zhuǎn)化醫(yī)學(xué)》上,。
全球有數(shù)百萬人患有感覺和運(yùn)動(dòng)方面的疾病,，這是由脊髓受到傷害而導(dǎo)致的。研究人員正在研究各種工具,，希望把患者腦部和各種為殘疾人設(shè)計(jì)的設(shè)備連接起來,，幫他們恢復(fù)運(yùn)動(dòng)和觸覺。杜克大學(xué)神經(jīng)工程中心在2000年初發(fā)明了腦機(jī)接口,，這一技術(shù)在“伸手取物”任務(wù)中很有潛力,，但至今還只能控制一條假肢。
“在日?；顒?dòng)中,，從點(diǎn)擊鍵盤到開罐頭,，雙手配合運(yùn)動(dòng)非常關(guān)鍵,，”論文高級作者、杜克大學(xué)醫(yī)學(xué)院神經(jīng)生物學(xué)教授米格爾·尼科萊利斯說,，“未來腦機(jī)接口的目標(biāo)是要能結(jié)合多個(gè)肢體,，恢復(fù)嚴(yán)重癱瘓病人的運(yùn)動(dòng)能力，給他們帶來更大的利益,。”
研究人員在一個(gè)虛擬環(huán)境對猴子進(jìn)行了訓(xùn)練,。在此虛擬環(huán)境中，它們能看到屏幕上自己有兩條真實(shí)的“化身手臂”,。在雙手運(yùn)動(dòng)任務(wù)中,，研究人員鼓勵(lì)它們把“化身手臂”伸向某個(gè)特定目標(biāo)。猴子先是學(xué)會(huì)了用一雙操縱桿來控制化身手臂,，隨后逐漸學(xué)會(huì)僅通過腦活動(dòng)來控制“化身手臂”,，而自己的手臂不動(dòng)。在控制兩條“化身手臂”時(shí),，猴子表現(xiàn)越來越好,。研究人員發(fā)現(xiàn)，它們腦皮層的多區(qū)域表現(xiàn)出廣泛的可塑性,。這表明,，猴子的腦部可能把“化身手臂”與它們的身體內(nèi)影像結(jié)合在了一起。
為了讓猴子控制兩條虛擬手臂,，尼科萊利斯和同事研究了大范圍的腦皮層記錄,，努力為腦機(jī)接口提供足夠的信號，以精確控制雙手運(yùn)動(dòng),。他們發(fā)現(xiàn),，在雙手運(yùn)動(dòng)時(shí)，神經(jīng)元電活動(dòng)形成的特殊圖形,，與分別移動(dòng)每條手臂時(shí)所形成的神經(jīng)圖形不同,。這表明是大量的神經(jīng)元集合——而不是單個(gè)神經(jīng)元——決定了正常運(yùn)動(dòng)功能下面的基本生理單位,。皮層上小部分神經(jīng)元樣本，或許不足以通過腦機(jī)接口控制復(fù)雜的運(yùn)動(dòng)行為,。
“我們在觀察單個(gè)神經(jīng)元或整個(gè)皮層細(xì)胞群體的性質(zhì)時(shí)注意到,，當(dāng)兩條手臂在雙手任務(wù)中互相配合時(shí)，如果只把指揮右手和左手運(yùn)動(dòng)的神經(jīng)元活動(dòng)簡單地相加,，就無法預(yù)測某個(gè)神經(jīng)元或整個(gè)神經(jīng)元群體想要做什么,。”尼科萊利斯說，“這一發(fā)現(xiàn)表明當(dāng)兩手同時(shí)做事時(shí),，大腦還有一種自發(fā)的性質(zhì),，是一種非線性加總。”
尼科萊利斯正在將這些研究發(fā)現(xiàn)并入“重新行走計(jì)劃”,。這項(xiàng)計(jì)劃是一項(xiàng)國際合作項(xiàng)目,，致力于建造腦控神經(jīng)假體設(shè)備，并打算在2014年FIFA世界杯開幕式上展示他們的首個(gè)腦控外骨骼,。（生物谷Bioon.com）
生物谷推薦的英文摘要
Science Translational Medicine DOI: 10.1126/scitranslmed.3006159
A Brain-Machine Interface Enables Bimanual Arm Movements in Monkeys
Peter J. Ifft1,，2， Solaiman Shokur2,，3,， Zheng Li2，4,， Mikhail A. Lebedev2,，4 and Miguel A. L. Nicolelis
Brain-machine interfaces (BMIs) are artificial systems that aim to restore sensation and movement to paralyzed patients. So far， BMIs have enabled only one arm to be moved at a time. Control of bimanual arm movements remains a major challenge. We have developed and tested a bimanual BMI that enables rhesus monkeys to control two avatar arms simultaneously. The bimanual BMI was based on the extracellular activity of 374 to 497 neurons recorded from several frontal and parietal cortical areas of both cerebral hemispheres. Cortical activity was transformed into movements of the two arms with a decoding algorithm called a fifth-order unscented Kalman filter (UKF). The UKF was trained either during a manual task performed with two joysticks or by having the monkeys passively observe the movements of avatar arms. Most cortical neurons changed their modulation patterns when both arms were engaged simultaneously. Representing the two arms jointly in a single UKF decoder resulted in improved decoding performance compared with using separate decoders for each arm. As the animals’ performance in bimanual BMI control improved over time,， we observed widespread plasticity in frontal and parietal cortical areas. Neuronal representation of the avatar and reach targets was enhanced with learning,， whereas pairwise correlations between neurons initially increased and then decreased. These results suggest that cortical networks may assimilate the two avatar arms through BMI control. These findings should help in the design of more sophisticated BMIs capable of enabling bimanual motor control in human patients.
