對于癱瘓病人來說,，如果能用意念控制假肢并獲得觸感,，將極大改善生活質(zhì)量,，而這個設想正在逐漸接近現(xiàn)實,。一項最新研究已經(jīng)可以讓猴子用意念控制虛擬手臂,，而且還能獲得反饋給大腦的觸感,。
英國《自然》雜志網(wǎng)站日前刊登報告說，美國杜克大學等機構(gòu)研究人員設計出了這樣一套系統(tǒng),。他們給猴子大腦中關(guān)于運動和觸感的部位都接上電極,，猴子可以單用意念來控制電腦屏幕上一個虛擬手臂的行動，當手臂碰到屏幕上虛擬的物體時,，電極會傳給大腦相應的觸感信號,。實驗顯示，猴子能夠區(qū)分屏幕上看起來完全一樣但“觸感”不同的物體，通過控制虛擬手臂“觸摸”指定物體,。
過去的類似研究多停留在讓猴子用意念控制機械臂等物體的階段,，缺少對大腦的觸感反饋。而觸感十分重要,，比如要握住一個玻璃杯,，除了要能夠指揮機械臂有“握”的動作以外，還必須要有“握住”的感覺,，才能避免杯子掉下或用力過大將其握碎,。
因此，研究人員將此前研究中的“大腦－機器”接口模式改進為“大腦－機器－大腦”模式,。通過使用這套系統(tǒng),，可以直接把大腦和外部設備聯(lián)系到一起，用意念來指揮設備的行動并感知外界,。
研究人員說,，這項研究的最終目的就是能為癱瘓病人提供一套設備，讓他們不僅能用大腦意念來控制這些假肢的行動,，還能感受到“手”和“腳”上傳回的感覺,。研究人員還希望在2014年巴西世界杯上展示這套設備，讓癱瘓病人在設備的幫助下走進綠茵場,，自主地踢動足球,。（生物谷 Bioon.com）
doi:10.1038/nature10489
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Active tactile exploration using a brain-machine-brain interface
Joseph E. O’Doherty; Mikhail A. Lebedev; Peter J. Ifft; Katie Z. Zhuang; Solaiman Shokur; Hannes Bleuler; Miguel A. L. Nicolelis
Brain–machine interfaces1, 2 use neuronal activity recorded from the brain to establish direct communication with external actuators, such as prosthetic arms. It is hoped that brain–machine interfaces can be used to restore the normal sensorimotor functions of the limbs, but so far they have lacked tactile sensation. Here we report the operation of a brain–machine–brain interface (BMBI) that both controls the exploratory reaching movements of an actuator and allows signalling of artificial tactile feedback through intracortical microstimulation (ICMS) of the primary somatosensory cortex. Monkeys performed an active exploration task in which an actuator (a computer cursor or a virtual-reality arm) was moved using a BMBI that derived motor commands from neuronal ensemble activity recorded in the primary motor cortex. ICMS feedback occurred whenever the actuator touched virtual objects. Temporal patterns of ICMS encoded the artificial tactile properties of each object. Neuronal recordings and ICMS epochs were temporally multiplexed to avoid interference. Two monkeys operated this BMBI to search for and distinguish one of three visually identical objects, using the virtual-reality arm to identify the unique artificial texture associated with each. These results suggest that clinical motor neuroprostheses might benefit from the addition of ICMS feedback to generate artificial somatic perceptions associated with mechanical, robotic or even virtual prostheses.
