Editing Brain–computer interface (section)

====Nicolelis====
{{See also|Walk Again Project}}
[[Duke University]] professor [[Miguel Nicolelis]] advocates using multiple electrodes spread over a greater area of the brain to obtain neuronal signals.

After initial studies in rats during the 1990s, Nicolelis and colleagues developed BCIs that decoded brain activity in [[owl monkeys]] and used the devices to reproduce monkey movements in robotic arms. Monkeys' advanced reaching and grasping abilities and hand manipulation skills, made them good test subjects.

By 2000, the group succeeded in building a BCI that reproduced owl monkey movements while the monkey operated a [[joystick]] or reached for food.<ref>{{cite journal | vauthors = Wessberg J, Stambaugh CR, Kralik JD, Beck PD, Laubach M, Chapin JK, Kim J, Biggs SJ, Srinivasan MA, Nicolelis MA | display-authors = 6 | title = Real-time prediction of hand trajectory by ensembles of cortical neurons in primates | journal = Nature | volume = 408 | issue = 6810 | pages = 361–365 | date = November 2000 | pmid = 11099043 | doi = 10.1038/35042582 | s2cid = 795720 | bibcode = 2000Natur.408..361W }}</ref> The BCI operated in real time and could remotely control a separate robot. But the monkeys received no feedback ([[open-loop controller|open-loop]] BCI).

[[File:Brain-computer interface (schematic).jpg|thumb|Diagram of the BCI developed by Miguel Nicolelis and colleagues for use on [[rhesus monkeys]]]]

Later experiments on [[rhesus monkeys]] included [[feedback]] and reproduced monkey reaching and grasping movements in a robot arm. Their deeply cleft and furrowed brains made them better models for human [[neurophysiology]] than owl monkeys. The monkeys were trained to reach and grasp objects on a computer screen by manipulating a joystick while corresponding movements by a robot arm were hidden.<ref name=carmena2003>{{cite journal | vauthors = Carmena JM, Lebedev MA, Crist RE, O'Doherty JE, Santucci DM, Dimitrov DF, Patil PG, Henriquez CS, Nicolelis MA | display-authors = 6 | title = Learning to control a brain-machine interface for reaching and grasping by primates | journal = PLOS Biology | volume = 1 | issue = 2 | pages = E42 | date = November 2003 | pmid = 14624244 | pmc = 261882 | doi = 10.1371/journal.pbio.0000042 | doi-access = free }}</ref><ref name=lebedev2005>{{cite journal | vauthors = Lebedev MA, Carmena JM, O'Doherty JE, Zacksenhouse M, Henriquez CS, Principe JC, Nicolelis MA | title = Cortical ensemble adaptation to represent velocity of an artificial actuator controlled by a brain-machine interface | journal = The Journal of Neuroscience | volume = 25 | issue = 19 | pages = 4681–4693 | date = May 2005 | pmid = 15888644 | pmc = 6724781 | doi = 10.1523/JNEUROSCI.4088-04.2005 }}</ref> The monkeys were later shown the robot and learned to control it by viewing its movements. The BCI used velocity predictions to control reaching movements and simultaneously predicted [[Grip strength|gripping force]]. 

In 2011 O'Doherty and colleagues showed a BCI with sensory feedback with rhesus monkeys. The monkey controlled the position of an avatar arm while receiving sensory feedback through direct [[Cortical stimulation mapping|intracortical stimulation (ICMS)]] in the arm representation area of the [[sensory cortex]].<ref name="Odoherty2003">{{cite journal | vauthors = O'Doherty JE, Lebedev MA, Ifft PJ, Zhuang KZ, Shokur S, Bleuler H, Nicolelis MA | title = Active tactile exploration using a brain-machine-brain interface | journal = Nature | volume = 479 | issue = 7372 | pages = 228–231 | date = October 2011 | pmid = 21976021 | pmc = 3236080 | doi = 10.1038/nature10489 | bibcode = 2011Natur.479..228O }}</ref>