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Titlebook: Dynamic Neuroscience; Statistics, Modeling Zhe Chen,Sridevi V. Sarma Book 2018 Springer International Publishing AG 2018 Neural signal proc

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From Physiological Signals to Pulsatile Dynamics: A Sparse System Identification Approachaid our understanding of the pathological states related to these signals and has the potential to be used in designing bio-inspired pulsatile controllers; immediate applications include understanding normal and pathological neuroendocrine and affective states.
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Inferring Neuronal Network Mechanisms Underlying Anesthesia-Induced Oscillations Using Mathematical only predict the networks underlying anesthesia-induced oscillations but also guide experiments to further understand the role of these oscillations in the behavioral states that accompany anesthesia.
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Retraction Note to: Artifact Rejection for Concurrent TMS-EEG Data,
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Sound,terizing neuronal population dynamics or analyzing various sorts of neural data. The inference of latent variable models can lead to novel solutions for signal detection, neural decoding, denoising, dimensionality reduction, and data visualization. We review general modeling and inference strategies
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