The present paper focused on the extraction of event-related potentials on a single sweep under extremely low S/N ratio. Two methods that can efficiently remove spontaneous EEG, ocular artifacts and power line interference were presented based on ARX modeling and independent component analysis (ICA). The former method applied ARX model to the measured compound signal that extensively contained the three kinds of ordinary noises mentioned above, and used ARX algorithm for parametric identification. The latter decomposed the signal by means of independent component analysis. Besides, some of ICA's important decomposing characters and its intrinsic causality were pointed out definitely. According to the practical situation, some modification on FastICA algorithm was also given, so as to implement auto-adaptive mapping of decomposed results to ERP component. Through simulation, both the two ways are proved to be highly capable of signal extraction and S/N ratio improving.
Electroencephalography ; methods ; statistics & numerical data ; Event-Related Potentials, P300 ; physiology ; Evoked Potentials ; physiology ; Humans ; Signal Processing, Computer-Assisted

Quantitative analysis of biological image data generally involves the detection of many pixel spots. In live mitochondria video image, for which fluorescent microscopy is often used, the signal-to-noise ratio (SNR) can be extremely low, making the detection and tracking of mitochondria particle difficult. It is especially not easy to get the movement curve when the movement of the mitochondria involves its self-move and the motion caused by the neuron. An tracking algorithm for live mitochondria is proposed in this paper. First the whole image sequence is frame-to-frame registered, in which the edge corners are chosen to be the feature points. Then the mitochondria particles are tracked by frame-to-frame displacement vector. The algorithm proposed has been applied to the dynamic image sequence including neuron and mitochondria, saving time without manually picking up the feature points. It provides an new method and reference for medical image processing and biotechnological research.
Algorithms ; Animals ; Image Processing, Computer-Assisted ; methods ; Microscopy, Fluorescence ; Mitochondria ; metabolism ; ultrastructure ; Neurons ; ultrastructure ; Particle Size

Axonal transport of mitochondria is critical for neuronal survival and function. Automatically quantifying and analyzing mitochondrial movement in a large quantity remain challenging. Here, we report an efficient method for imaging and quantifying axonal mitochondrial transport using microfluidic-chamber-cultured neurons together with a newly developed analysis package named "MitoQuant". This tool-kit consists of an automated program for tracking mitochondrial movement inside live neuronal axons and a transient-velocity analysis program for analyzing dynamic movement patterns of mitochondria. Using this method, we examined axonal mitochondrial movement both in cultured mammalian neurons and in motor neuron axons of Drosophila in vivo. In 3 different paradigms (temperature changes, drug treatment and genetic manipulation) that affect mitochondria, we have shown that this new method is highly efficient and sensitive for detecting changes in mitochondrial movement. The method significantly enhanced our ability to quantitatively analyze axonal mitochondrial movement and allowed us to detect dynamic changes in axonal mitochondrial transport that were not detected by traditional kymographic analyses.
Animals ; Axonal Transport ; physiology ; Cerebral Cortex ; cytology ; metabolism ; Drosophila melanogaster ; cytology ; metabolism ; Embryo, Mammalian ; Gene Expression ; Lab-On-A-Chip Devices ; Microscopy, Confocal ; Mitochondria ; metabolism ; ultrastructure ; Motor Neurons ; metabolism ; ultrastructure ; Movement ; Mutation ; Primary Cell Culture ; RNA-Binding Protein FUS ; genetics ; metabolism ; Rats ; Rats, Sprague-Dawley ; Software