Titlebook: Signal Processing in Neuroscience; Xiaoli Li Book 2016 Springer Science+Business Media Singapore 2016 Spike trains.Local filed potential.E

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Cross-Frequency Coupling in Neural Oscillations,ythmic activities interact has been a hot research topic in electrophysiological studies. A series of studies have found that interaction between different rhythms is associated with cognitive processes. This chapter will present the related information to introduce the cross-frequency methods..An a

Ceramic

Nonnegative Matrix and Tensor Decomposition of EEG,in. The nonnegative data in the two domains can be modeled using bilinear and multi-linear transform. In this chapter, the nonnegative matrix factorization (NMF) and tensor decomposition of the canonical polyadic and Tucker models are introduced for decomposing the two-way data and the multi-way dat

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Book 2016ssuch as spike trains, local filed potentials and EEG. The analysis of neural activity can yield vital insights into the function of the brain. This book highlights the contribution of signal processing in the area of computational neuroscience by providing a forum for researchers in this field to share their experiences to date..

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Estimating Coupling Direction Between Neuronal Populations,tetanus toxin model of focal epilepsy; the propagation direction of the seizure events could be elucidated through this coupling direction estimation method. An important next goal is to investigate whether the method proposed herein is suited to analyze interactions in real EEG data.

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Causality of Spike Trains Based on Entropy,l entropy (CE) methods at identifying the coupling direction between the spike trains. The advantages of PCMI are twofold: it is able to estimate the directionality index under the weak coupling and against the missing and extra spikes.

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Cross-Frequency Coupling in Neural Oscillations,ies of speech perception allowing for top-down feedback connections and also provided insight into children’s speech perception development. It indicated that the interaction of different oscillatory activities could be exploited to investigate the bottom-up and top-down mechanisms in speech perception.