OBJECTIVE: In the last decade, multiple brain areas have been investigated with respect to their decoding capability of continuous arm or hand movements. So far, these studies have mainly focused on motor or premotor areas like M1 and F5. However, there is accumulating evidence that anterior intraparietal area (AIP) in the parietal cortex also contains information about continuous movement. APPROACH: In this study, we decoded 27 degrees of freedom representing complete hand and arm kinematics during a delayed grasping task from simultaneously recorded activity in areas M1, F5, and AIP of two macaque monkeys (Macaca mulatta). MAIN RESULTS: We found that all three areas provided decoding performances that lay significantly above chance. In particular, M1 yielded highest decoding accuracy followed by F5 and AIP. Furthermore, we provide support for the notion that AIP does not only code categorical visual features of objects to be grasped, but also contains a substantial amount of temporal kinematic information. SIGNIFICANCE: This fact could be utilized in future developments of neural interfaces restoring hand and arm movements.
OBJECTIVE: In the last decade, multiple brain areas have been investigated with respect to their decoding capability of continuous arm or hand movements. So far, these studies have mainly focused on motor or premotor areas like M1 and F5. However, there is accumulating evidence that anterior intraparietal area (AIP) in the parietal cortex also contains information about continuous movement. APPROACH: In this study, we decoded 27 degrees of freedom representing complete hand and arm kinematics during a delayed grasping task from simultaneously recorded activity in areas M1, F5, and AIP of two macaque monkeys (Macaca mulatta). MAIN RESULTS: We found that all three areas provided decoding performances that lay significantly above chance. In particular, M1 yielded highest decoding accuracy followed by F5 and AIP. Furthermore, we provide support for the notion that AIP does not only code categorical visual features of objects to be grasped, but also contains a substantial amount of temporal kinematic information. SIGNIFICANCE: This fact could be utilized in future developments of neural interfaces restoring hand and arm movements.
Authors: Z T Irwin; K E Schroeder; P P Vu; A J Bullard; D M Tat; C S Nu; A Vaskov; S R Nason; D E Thompson; J N Bentley; P G Patil; C A Chestek Journal: J Neural Eng Date: 2017-12 Impact factor: 5.379
Authors: Hwayoung Choi; Kyung-Jin You; Nitish V Thakor; Marc H Schieber; Hyun-Chool Shin Journal: IEEE Trans Neural Syst Rehabil Eng Date: 2018-10-12 Impact factor: 3.802
Authors: John E Downey; Lucas Brane; Robert A Gaunt; Elizabeth C Tyler-Kabara; Michael L Boninger; Jennifer L Collinger Journal: Sci Rep Date: 2017-12-05 Impact factor: 4.379
Authors: Alex K Vaskov; Zachary T Irwin; Samuel R Nason; Philip P Vu; Chrono S Nu; Autumn J Bullard; Mackenna Hill; Naia North; Parag G Patil; Cynthia A Chestek Journal: Front Neurosci Date: 2018-11-05 Impact factor: 4.677
Authors: Aneesha K Suresh; James M Goodman; Elizaveta V Okorokova; Matthew Kaufman; Nicholas G Hatsopoulos; Sliman J Bensmaia Journal: Elife Date: 2020-11-17 Impact factor: 8.140