The dynamic mechanism of a novel stochastic neural firing pattern observed in a real biological system

In the experimental neural pacemaker of a rat, a novel firing pattern has been discovered. This pattern was generated between the period 2 firing pattern and the period 3 firing pattern during the periodic adding bifurcation and inverse periodic adding bifurcation. The pattern was observed and analyzed in the present investigation. The composition of this novel firing pattern could be regarded as a transition between a string of period 2 burst and a string of period 3 burst without single period 2 or period 3 burst, which was different from those chaotic and stochastic neural firing patterns in previous reports. It was identified to be stochastic by the inter-event intervals (IEIs) analysis, although it exhibited chaos-like characteristics with the results of the inter-spike intervals (ISIs) analysis. The numerical simulation suggested that the new pattern observed in the real biological system could be simulated in the stochastic Chay model but not in the deterministic model. With the signal to noise ratio (SNR) analysis and bifurcation analysis, this novel firing pattern was considered to be generated by stochastic resonance under the influence of noise near the periodic adding (inverse) bifurcation point. The probability analysis of transformed binary chain further confirmed that the origin of stochastic and chaos (deterministic)-like characteristics of this novel firing pattern.     

Brain MR kurtosis imaging study: Contrasting gray and white matter

This paper mainly focuses on characterization of different brain tissues such as White and Gray matter (WM and GM) using the relation between Diffusion Tensor Imaging and Diffusion Kurtosis Imaging parameters. Both Diffusion Tensor Imaging and Diffusion Kurtosis Imaging are the extension of Diffusion Weighted Imaging, which are widely applied for analysing micro fibre structure of human organs non-invasively. Diffusion Tensor Imaging assumes that the water diffusion is in Gaussian nature and Diffusion Kurtosis Imaging accounts the deviation of the Gaussian nature. This study, conducted a correlation and regression analysis between different parametric maps generated from Diffusion Kurtosis Images. For this we have chosen 200 regions of interest pixels drawn from brain MRIs. From the results, it is observed that there is a significant variation in the correlation results between Axial Diffusion and Kurtosis Fractional Anisotropy maps of Gray matter and White matter tissues. This can be employed for enhancing accuracy in MRI segmentation techniques and also as a potential tool for Neuro degenerative disease detection.