The ability to allow subjects, including paralyzed patients, to perform a task using brain-computer interfaces has seen a rapid and growing success. Surprisingly, however, it is still not known how far such performance can be improved - especially in cases of long term amputation where both efferent and afferent functions are abolished and may lead to deterioration of the relevant brain representations. Here we used real-time fMRI to demonstrate a remarkably high performance of long term amputees in controlling a computer generated avatar using their missing hand. The missing limb BCI performance showed similar levels both when compared to the intact hand and to control participants.
|Title of host publication||8th International IEEE EMBS Conference on Neural Engineering, NER 2017|
|Publisher||IEEE Computer Society|
|Number of pages||4|
|State||Published - 10 Aug 2017|
|Event||8th International IEEE EMBS Conference on Neural Engineering, NER 2017 - Shanghai, China|
Duration: 25 May 2017 → 28 May 2017
|Name||International IEEE/EMBS Conference on Neural Engineering, NER|
|Conference||8th International IEEE EMBS Conference on Neural Engineering, NER 2017|
|Period||25/05/17 → 28/05/17|
Bibliographical noteFunding Information:
VII. ACKNOWLEDGMENTS This research was supported by the European Union FP7 Integrated Project VERE (No 657295), www. vereproject.eu. We would like to thank the subjects for their participation, and the Weizmann Institute fMRI scanner staff Edna Furman-Haran, Nachum Stern and Fanny Attar for their help in this experiment.
© 2017 IEEE.