Aiming at local field potential, the present paper introduces a method of estimating lag of neuron activities between brain areas based on windowed Harmonic wavelet transform (WHWT). Firstly, the WHWT of signals of two brain areas are calculated. Secondly, the instantaneous amplitude of the signals is calculated and finally, these amplitudes are cross-correlated and the lag at which the cross-correlation peak occurs is determined as the lag of neurons activities. Comparing with amplitude cross-correlation based on Gabor wavelet transform (GWT) or Hilbert transform (HT), this method is more precise and efficient in estimating the directionality and lag.
Brain ; physiology ; Humans ; Neurons ; physiology ; Wavelet Analysis

Recording and extracting characteristic brain signals in freely moving animals is the basic and significant requirement in the study of brain-computer interface (BCI). To record animal's behaving and extract characteristic brain signals simultaneously could help understand the complex behavior of neural ensembles. Here, a system was established to record and analyse extracellular discharge in freely moving rats for the study of BCI. It comprised microelectrode and micro-driver assembly, analog front end (AFE), programmer system on chip (PSoC), wireless communication and the LabVIEW used as the platform for the graphic user interface.
Animals ; Behavior, Animal ; physiology ; Brain ; physiology ; Electroencephalography ; methods ; Microelectrodes ; Rats ; Signal Processing, Computer-Assisted ; instrumentation ; Telemetry ; instrumentation ; User-Computer Interface

We have brought forward a wavelet-based algorithm for electroencephalograph (EEG) signals--using scale dependent threshold based on median. In comparison with the universal threshold and Sure threshold, our proposed threshold, which is adaptive to the subband noise signals, preserves the noise free reconstruction property and takes lower risk than does the universal threshold; and our proposed threshold overcomes the drawback of Sure threshold. Evidently, the scale dependent threshold based on median is computationally simple and can obtain higher singal-to-noise ratio (SNR) it outperforms the universal threshold and Sure threshlold.
Algorithms ; Artifacts ; Electroencephalography ; Humans ; Signal Processing, Computer-Assisted