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A practical brain-machine interface (BMI) requires real-time decoding algorithms to be realised in a portable device rather than a personal computer. In this article, a field-programmable gate array (FPGA) implementation of a probabilistic neural network (PNN) is proposed and developed to decode motor cortical ensemble recordings in rats performing a(More)
OBJECTIVE The high-dimensional neural recordings bring computational challenges to movement decoding in motor brain machine interfaces (mBMI), especially for portable applications. However, not all recorded neural activities relate to the execution of a certain movement task. This paper proposes to use a local-learning-based method to perform neuron(More)
BACKGROUND Ghrelin was associated with several of cancers. The conflict results of SNPs with GHRL and GHSR gene were demonstrated in different studies. Thus, this meta-analysis is to evaluate the associations. METHODS Systematic literature search was done on PubMed database up to October 2013. We used odds ratios (ORs) with 95% confidence intervals (CIs)(More)
The loss of hand function, due to amputation or neurological injuries, severely debilitates physically and psychosocially. The most evident and critical impairment after upper limb amputation or neurological injury like brachial plexus or spinal cord injury is the loss of prehension, i.e., the ability to perform those movements in which an object is seized(More)
OBJECTIVE Recent studies have shown that dorsal premotor cortex (PMd), a cortical area in the dorsomedial grasp pathway, is involved in grasp movements. However, the neural ensemble firing property of PMd during grasp movements and the extent to which it can be used for grasp decoding are still unclear. APPROACH To address these issues, we used(More)
In this paper, rats were trained to press a lever over a threshold to get water as rewards, and neural ensemble activities in primary motor cortex (MI) and pressure signal of the lever were recorded synchronously. Meanwhile, two algorithms, Kalman filter (KF) and Optimal Linear Estimation (OLE), were used to decode neural ensemble activities around the(More)
Recently, local field potentials (LFPs) have been successfully used to extract information of arm and hand movement in some brain-machine interfaces (BMIs) studies, which suggested that LFPs would improve the performance of BMI applications because of its long-term stability. However, the performance of LFPs in different frequency bands has not been(More)
Real-time computation, portability and flexibility are crucial for practical brain-machine interface (BMI) applications. In this work, we proposed Hardware Processing Modules (HPMs) as a method for accelerating BMI computation. Two HPMs have been developed. One is the field-programmable gate array (FPGA) implementation of spike sorting based on(More)
Novel gold-shell nanoparticles (pH-GSNPs) are designed for the first time, which exhibit drug leakage-free behavior in a physiological environment, while achieving rapid drug release and remarkable aggregation for the nanogold interlayer of pH-GSNPs to shift their absorption to far-red and NIR as a photothermal agent in the intracellular microenvironment.
Previous studies have shown that the dorsal premotor cortex (PMd) neurons are relevant to reaching as well as grasping. In order to investigate their specific contribution to reaching and grasping, respectively, we design two experimental paradigms to separate these two factors. Two monkeys are instructed to reach in four directions but grasp the same(More)