A real-time spike sorting method based on the embedded GPU.

Microelectrode arrays with hundreds of channels have been widely used to acquire neuron population signals in neuroscience studies. Online spike sorting is becoming one of the most important challenges for high-throughput neural signal acquisition systems. Graphic processing unit (GPU) with high parallel computing capability might provide an alternative solution for increasing real-time computational demands on spike sorting. This study reported a method of real-time spike sorting through computing unified device architecture (CUDA) which was implemented on an embedded GPU (NVIDIA JETSON Tegra K1, TK1). The sorting approach is based on the principal component analysis (PCA) and K-means. By analyzing the parallelism of each process, the method was further optimized in the thread memory model of GPU. Our results showed that the GPU-based classifier on TK1 is 37.92 times faster than the MATLAB-based classifier on PC while their accuracies were the same with each other. The high-performance computing features of embedded GPU demonstrated in our studies suggested that the embedded GPU provide a promising platform for the real-time neural signal processing.

Localizing seizure onset zone by convolutional transfer entropy from iEEG.

Automatic localization of the seizure onset zone (SOZ) is able to output an objective result and help clinical doctors greatly in epilepsy therapy. Transfer entropy is one of the most frequently used measures based on information theory to localize the SOZ. However, if only using transfer entropy to localize the SOZ, different results can be obtained during different periods, thus humans still need to identify which one is most reasonable. This paper proposes a new method to output only a few (e.g. 1 or 2) results along a long time slot. Based on the results of traditional transfer entropy, we use a 3D convolution method to enhance the connection between the spatial channels and also between different temporal positions. After that, a connected component method is used to extract the stable blocks that indicate the SOZ. To evaluate the effectiveness of our method, preliminary experiments on a short iEEG signals are conducted. The experimental results show that our method can achieve a sensitivity of 100% and a false positive rate of 1.79% for SOZ localization.

Free cholesterol overloading induced smooth muscle cells death and activated both ER- and mitochondrial-dependent death pathway.

OBJECTIVE: Smooth muscle cells (SMCs) death promotes atherosclerotic lesion necrosis and plaque destabilization. We investigated the potential mechanisms of rat SMCs death in response to excess free cholesterol (FC). METHODS AND RESULTS: Rat aortic SMCs were incubated with "water soluble cholesterol" and acyl-CoA:cholesterol acyltransferase (ACAT) inhibitor Sandoz58035 to establish FC-overloading cell model. Disruption of mitochondrial network and endoplasmic reticulum (ER) was observed after 12h incubation by transient transfection. After treated for 24h, enhanced cell death was noted as detected by propidium iodide (PI) staining/flow cytometry (P<0.001 vs. control). SMCs death was associated with markedly decreased mitochondrial transmembrane potential (Deltaphim), as well as upregulation of cellular reactive oxygen species (ROS) and ER stress. We also investigated possible signaling pathways involved in excess FC-initiated cell death and found that unfolded protein response (UPR) was activated, with increased cellular Bax expression and release of mitochondrial cytochrome c. CONCLUSION: Our findings suggested that FC-overloading might trigger SMCs death. Both ER- and mitochondria-based signals might be implicated in these lethal events.