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Nonlinear principal component analysis using autoassociative neural networks
Nonlinear principal component analysis is a novel technique for multivariate data analysis, similar to the well-known method of principal component analysis. NLPCA, like PCA, is used to identify andExpand
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Dynamic cross-frequency couplings of local field potential oscillations in rat striatum and hippocampus during performance of a T-maze task
Oscillatory rhythms in different frequency ranges mark different behavioral states and are thought to provide distinct temporal windows that coherently bind cooperating neuronal assemblies. However,Expand
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Age-Related Changes in 1/f Neural Electrophysiological Noise
Aging is associated with performance decrements across multiple cognitive domains. The neural noise hypothesis, a dominant view of the basis of this decline, posits that aging is accompanied by anExpand
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Emergent network topology at seizure onset in humans
Epilepsy - the world's most common serious brain disorder - is defined by recurrent unprovoked seizures that result from complex interactions between distributed neural populations. We explore someExpand
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Sharp edge artifacts and spurious coupling in EEG frequency comodulation measures
Recent electroencephalogram (EEG), electrocorticogram (ECoG), and local field potential (LFP) observations suggest that distinct frequency bands interact. Numerous measures have been proposed toExpand
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Coalescence and Fragmentation of Cortical Networks during Focal Seizures
Epileptic seizures reflect a pathological brain state characterized by specific clinical and electrical manifestations. The proposed mechanisms are heterogeneous but united by the supposition thatExpand
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Emergence of Stable Functional Networks in Long-Term Human Electroencephalography
Functional connectivity networks have become a central focus in neuroscience because they reveal key higher-dimensional features of normal and abnormal nervous system physiology. Functional networksExpand
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Temporal Interactions between Cortical Rhythms
We propose a frequency transformation in which activity in two co-active local circuits may combine sequentially to generate a third frequency whose period is the concatenation sum of the original two, suggesting a robust mechanism for combining information processed on multiple concurrent spatiotemporal scales. Expand
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Neuronal assembly dynamics in the beta1 frequency range permits short-term memory
Cell assemblies have long been thought to be associated with brain rhythms, notably the gamma rhythm. Here, we use a computational model to show that the beta1 frequency band, as found in ratExpand
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Network inference with confidence from multivariate time series.
In this manuscript, we describe a principled and systematic procedure for the inference of functional connectivity networks from multivariate time series data. Expand
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