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哈佛大学医学院的研究人员展示了一个非常有趣的项目,项目中一个人类参与者成功的使用思维控制了一只老鼠。它的目的是用于磨合一种可以让人类思维激发老鼠运动皮质作用的系统,正是这部分大脑控制着动物的运动。
在这项研究中,测试者在头上佩戴着传感器观看一个同步显示脑电图扫描模式的屏幕。这种大脑模式被用于进行视觉刺激,而且当测试者的注意力转向控制老鼠时,系统就会激发一种超声波脉冲,然后之前经麻醉的老鼠的尾巴就会出现抽动。
上述实验的一个潜在问题或者说限制就是,这个系统目前还无法精致到使用特定的思维来控制特定的动作。然而,大门已经向远超出控制老鼠的未来应用敞开。事实上,我们甚至已经看到有研究项目致力于利用各种思维控制来机器人。
这项实验未来或许可以帮助肢体瘫痪者恢复运动,让截肢者更简单的操控假肢装置。
Non-Invasive Brain-to-Brain Interface (BBI): Establishing Functional Links between Two Brains
PLoS ONE, April 3, 2013 | doi:10.1371/journal.pone.0060410
Transcranial focused ultrasound (FUS) is capable of modulating the neural activity of specific brain regions, with a potential role as a non-invasive computer-to-brain interface (CBI). In conjunction with the use of brain-to-computer interface (BCI) techniques that translate brain function to generate computer commands, we investigated the feasibility of using the FUS-based CBI to non-invasively establish a functional link between the brains of different species (i.e. human and Sprague-Dawley rat), thus creating a brain-to-brain interface (BBI). The implementation was aimed to non-invasively translate the human volunteer’s intention to stimulate a rat’s brain motor area that is responsible for the tail movement. The volunteer initiated the intention by looking at a strobe light flicker on a computer display, and the degree of synchronization in the electroencephalographic steady-state-visual-evoked-potentials (SSVEP) with respect to the strobe frequency was analyzed using a computer. Increased signal amplitude in the SSVEP, indicating the volunteer’s intention, triggered the delivery of a burst-mode FUS (350 kHz ultrasound frequency, tone burst duration of 0.5 ms, pulse repetition frequency of 1 kHz, given for 300 msec duration) to excite the motor area of an anesthetized rat transcranially. The successful excitation subsequently elicited the tail movement, which was detected by a motion sensor. The interface was achieved at 94.0±3.0% accuracy, with a time delay of 1.59±1.07 sec from the thought-initiation to the creation of the tail movement. Our results demonstrate the feasibility of a computer-mediated BBI that links central neural functions between two biological entities, which may confer unexplored opportunities in the study of neuroscience with potential implications for therapeutic applications.
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