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Journal ArticleDOI

Modelling and analysis of local field potentials for studying the function of cortical circuits

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TLDR
Careful mathematical modelling and analysis are needed to take full advantage of the opportunities that this signal offers in understanding signal processing in cortical circuits and, ultimately, the neural basis of perception and cognition.
Abstract
Local field potentials (LFPs) provide a wealth of information about synaptic processing in cortical populations but are difficult to interpret. Einevoll and colleagues consider the neural origin of cortical LFPs and discuss LFP modelling and analysis methods that can improve the interpretation of LFP data.

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Citations
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Journal ArticleDOI

Theta coupling within the medial prefrontal cortex regulates fear extinction and renewal

TL;DR: In this article , the authors used electrophysiological recordings in awake behaving rats to identify increased theta activity in the prelimbic cortex during fear learning and in the infralimbic cortex following extinction.
Journal ArticleDOI

Cortical nicotinic enhancement of tone-evoked heightened activities and subcortical nicotinic enlargement of activated areas in mouse auditory cortex

TL;DR: In this article , the authors investigated the effect of 20 kHz and 5 kHz amplitude-modulated (AM) tones on tone-evoked local neuronal activity at an optimal frequency site and non-optimal frequency site.
Proceedings ArticleDOI

Estimation of Functional Dependence in High-Dimensional Spike-Field Activity

TL;DR: This work uses the Akaike information criterion (AIC) to enforce model sparsity by incorporating only a minimum number of non-zero dependency parameters into the point process model based on a trade-off between model complexity and its prediction power.
Journal ArticleDOI

Mutual information of local field potentials distinguishes area-V2 stripe compartments

TL;DR: The decomposition mutual information based on the power of different frequency bands of LFPs provides new insight into the impact of modular architecture on population coding in area V2 of macaque monkeys.
Journal ArticleDOI

Time-Frequency Representations of Brain Oscillations: Which One Is Better?

TL;DR: A methodology to evaluate the “quality” of TFRs of neural signals by quantifying how much information they retain about the experimental condition during visual stimulation and recognition tasks, in mice and humans, respectively is introduced.
References
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Journal ArticleDOI

A mathematical theory of communication

TL;DR: This final installment of the paper considers the case where the signals or the messages or both are continuously variable, in contrast with the discrete nature assumed until now.
MonographDOI

Causality: models, reasoning, and inference

TL;DR: The art and science of cause and effect have been studied in the social sciences for a long time as mentioned in this paper, see, e.g., the theory of inferred causation, causal diagrams and the identification of causal effects.
Book ChapterDOI

Investigating causal relations by econometric models and cross-spectral methods

TL;DR: In this article, it is shown that the cross spectrum between two variables can be decomposed into two parts, each relating to a single causal arm of a feedback situation, and measures of causal lag and causal strength can then be constructed.
Journal ArticleDOI

Learning the parts of objects by non-negative matrix factorization

TL;DR: An algorithm for non-negative matrix factorization is demonstrated that is able to learn parts of faces and semantic features of text and is in contrast to other methods that learn holistic, not parts-based, representations.

Learning parts of objects by non-negative matrix factorization

D. D. Lee
TL;DR: In this article, non-negative matrix factorization is used to learn parts of faces and semantic features of text, which is in contrast to principal components analysis and vector quantization that learn holistic, not parts-based, representations.
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