It is disputed whether those neurons in the primary motor cortex（M1） that encode hand orientation constitute an independent channel for orientation control in reach-to-grasp behaviors. Here, we trained two monkeys t...It is disputed whether those neurons in the primary motor cortex（M1） that encode hand orientation constitute an independent channel for orientation control in reach-to-grasp behaviors. Here, we trained two monkeys to reach forward and grasp objects positioned in the frontal plane at different orientation angles, and simultaneously recorded the activity of M1 neurons. Among the 2235 neurons recorded in M1, we found that 18.7% had a high correlation exclusively with hand orientation, 15.9% with movement direction, and 29.5% with both movement direction and hand orientation. The distributions of neurons encoding hand orientation and those encoding movement direction were not uniform but coexisted in the same region. The trajectory of hand rotation was reproduced by the firing patterns of the orientation-related neurons independent of the hand reaching direction. These resultssuggest that hand orientation is an independent component for the control of reaching and grasping activity.展开更多
The cerebral cortex plays an important role in human and other animal adaptation to unpredictable terrain changes,but little was known about the functional network among the cortical areas during this process.To addre...The cerebral cortex plays an important role in human and other animal adaptation to unpredictable terrain changes,but little was known about the functional network among the cortical areas during this process.To address the question,we trained 6 rats with blocked vision to walk bipedally on a treadmill with a random uneven area.Whole-brain electroencephalography signals were recorded by 32-channel implanted electrodes.Afterward,we scan the signals from all rats using time windows and quantify the functional connectivity within each window using the phase-lag index.Finally,machine learning algorithms were used to verify the possibility of dynamic network analysis in detecting the locomotion state of rats.We found that the functional connectivity level was higher in the preparation phase compared to the walking phase.In addition,the cortex pays more attention to the control of hind limbs with higher requirements for muscle activity.The level of functional connectivity was lower where the terrain ahead can be predicted.Functional connectivity bursts after the rat accidentally made contact with uneven terrain,while in subsequent movement,it was significantly lower than normal walking.In addition,the classification results show that using the phase-lag index of multiple gait phases as a feature can effectively detect the locomotion states of rat during walking.These results highlight the role of the cortex in the adaptation of animals to unexpected terrain and may help advance motor control studies and the design of neuroprostheses.展开更多
Brain-computer interfaces have revolutionized the field of neuroscience by providing a solution for paralyzed patients to control external devices and improve the quality of daily life.To accurately and stably control...Brain-computer interfaces have revolutionized the field of neuroscience by providing a solution for paralyzed patients to control external devices and improve the quality of daily life.To accurately and stably control effectors,it is important for decoders to recognize an individual's motor intention from neural activity either by noninvasive or intracortical neural recording.Intracortical recording is an invasive way of measuring neural electrical activity with high temporal and spatial resolution.Herein,we review recent developments in neural signal decoding methods for intracortical brain-computer interfaces.These methods have achieved good performance in analyzing neural activity and controlling robots and prostheses in nonhuman primates and humans.For more complex paradigms in motor rehabilitation or other clinical applications,there remains more space for further improvements of decoders.展开更多
基金supported by the National Natural Science Foundation of China(61233015 and 31460263)the National Basic Research Development Program(973 Program)of China(2013CB329506)
文摘It is disputed whether those neurons in the primary motor cortex（M1） that encode hand orientation constitute an independent channel for orientation control in reach-to-grasp behaviors. Here, we trained two monkeys to reach forward and grasp objects positioned in the frontal plane at different orientation angles, and simultaneously recorded the activity of M1 neurons. Among the 2235 neurons recorded in M1, we found that 18.7% had a high correlation exclusively with hand orientation, 15.9% with movement direction, and 29.5% with both movement direction and hand orientation. The distributions of neurons encoding hand orientation and those encoding movement direction were not uniform but coexisted in the same region. The trajectory of hand rotation was reproduced by the firing patterns of the orientation-related neurons independent of the hand reaching direction. These resultssuggest that hand orientation is an independent component for the control of reaching and grasping activity.
基金supported by the National Key R&D Program of China(Grant Nos.2018YFB1307301 and 2017YFE0117000).
文摘The cerebral cortex plays an important role in human and other animal adaptation to unpredictable terrain changes,but little was known about the functional network among the cortical areas during this process.To address the question,we trained 6 rats with blocked vision to walk bipedally on a treadmill with a random uneven area.Whole-brain electroencephalography signals were recorded by 32-channel implanted electrodes.Afterward,we scan the signals from all rats using time windows and quantify the functional connectivity within each window using the phase-lag index.Finally,machine learning algorithms were used to verify the possibility of dynamic network analysis in detecting the locomotion state of rats.We found that the functional connectivity level was higher in the preparation phase compared to the walking phase.In addition,the cortex pays more attention to the control of hind limbs with higher requirements for muscle activity.The level of functional connectivity was lower where the terrain ahead can be predicted.Functional connectivity bursts after the rat accidentally made contact with uneven terrain,while in subsequent movement,it was significantly lower than normal walking.In addition,the classification results show that using the phase-lag index of multiple gait phases as a feature can effectively detect the locomotion states of rat during walking.These results highlight the role of the cortex in the adaptation of animals to unexpected terrain and may help advance motor control studies and the design of neuroprostheses.
基金supported by the National Key R&D Program of China(Grant Nos.2017YFA0701102)Beijing Nature Science Fund(Grant No.5192013)the Lundbeck Foundation(Grant No.R366-2021-233).
文摘Brain-computer interfaces have revolutionized the field of neuroscience by providing a solution for paralyzed patients to control external devices and improve the quality of daily life.To accurately and stably control effectors,it is important for decoders to recognize an individual's motor intention from neural activity either by noninvasive or intracortical neural recording.Intracortical recording is an invasive way of measuring neural electrical activity with high temporal and spatial resolution.Herein,we review recent developments in neural signal decoding methods for intracortical brain-computer interfaces.These methods have achieved good performance in analyzing neural activity and controlling robots and prostheses in nonhuman primates and humans.For more complex paradigms in motor rehabilitation or other clinical applications,there remains more space for further improvements of decoders.
