Neuroscience

Brain Machine Interface Technology and Its Challenges
Ting Zhao, Zhejiang University, Hangzhou

Being able to read and translate individual neuron activities from the brain, invasive brain machine interfaces (BMIs) is a new hope for paralyzed patients to restore their deficient motor functions. Invasive BMIs was first demonstrated on rats by Chapin lab at the State University of New York. In their experiment, a rat successfully controlled its brain activity to get water reward by triggering lever pressing. This inspired many neuroengineering researchers to build BMI systems towards clinical applications. Nicolelis lab at Duke University reported the first invasive BMI for monkeys. Schwartz lab at the University of Pittsburgh further showed that a monkey managed to control a robotic arm to feed itself with thoughts only. Besides animal research, clinical trials have also been conducted, initiating a revolutionary impact of the technology. However, there are still many challenges posed by the goal of smooth and safe usage of invasive BMIs, such as interpreting brain signals accurately in real time for movements with a high degree of freedom, keeping the long-term stability of a BMI system and facilitating a more natural close-loop interaction between the brain and the machine. To take on these challenges, our institute, named Qiushi Academy for Advanced Studies at Zhejiang University, has built BMI research platforms on both rats and monkeys since 2006. With these platforms, we have improved the accuracy, speed and stability of signal decoding algorithms, explored electrical stimulations as the way of sending environment information to the brain, and showed that various hand gestures of a monkey can be distinguished from its brain signal accurately.

References:

Carmena JM, Lebedev MA, Crist RE, O'Doherty JE, Santucci DM, Dimitrov DF, Patil PG, Henriquez CS, Nicolelis MAL. Learning to control a brain-machine interface for reaching and grasping by primates. Plos Biology, 2003; 1: 193-208

Velliste M, Perel S, Spalding MC, Whitford AS, Schwartz AB. Cortical control of a prosthetic arm for self-feeding. Nature, 2008; 453: 1098-101

Hochberg LR, Serruya MD, Friehs GM, Mukand JA, Saleh M, Caplan AH, Branner A, Chen D, Penn RD, Donoghue JP. Neuronal ensemble control of prosthetic devices by a human with tetraplegia. Nature, 2006b; 442: 164-71

Lebedev MA, Nicolelis MAL. Brain-machine interfaces: past, present and future. Trends in Neurosciences, 2006; 29: 536-546

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Neuroscience

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