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https://www.selleckchem.com/products/eed226.html Bi-directional brain-computer interfaces (BD-BCI) to restore movement and sensation must achieve concurrent operation of recording and decoding of motor commands from the brain and stimulating the brain with somatosensory feedback. Previously we developed and validated a benchtop prototype of a fully implantable BCI system for motor decoding. Here, a prototype artificial sensory stimulator was integrated into the benchtop system to develop a prototype of a fully-implantable BD-BCI. The artificial sensory stimulator incorporates an active charge balancing mechanism based on pulse-width modulation to ensure safe stimulation for chronically interfaced electrodes to prevent damage to brain tissue and electrodes. The feasibility of the BD-BCI system's active charge balancing was tested in phantom brain tissue. With the charge-balancing, the removal of the residual charges on an electrode was evident. This is a critical milestone toward fully-implantable BD-BCI systems.Brain-machine interfaces (BMIs) translate neural signals into digital commands to control external devices. During the use of BMI, neurons may change their activity corresponding to the same stimuli or movement. The changes are represented by the neural tuning parameters which may change gradually and abruptly. Adaptive algorithms were proposed to estimate the time-varying parameters in order to keep decoding performance stable. The existing methods only searched new parameters locally which failed to detect the abrupt changes. Global search helps but requires the known boundary of estimated parameter which is hard to be defined in many cases. We propose to estimate the neural modulation parameter by the global search using adaptive point process estimation. This neural modulation parameter represents the similarity between the kinematics and the neural preferred hyper tuning direction with finite range [0,1]. The preferred hyper tuning direction is then deco

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