Classification-Based Prediction of Effective Connectivity Between Timeseries With a Realistic Cortical Network Model

Classification-Based Prediction of Effective Connectivity Between Timeseries With a Realistic Cortical Network Model

Effective connectivity measures the pattern of causal interactions between brain regions. Traditionally, these patterns of causality are inferred from brain recordings using either non-parametric, i.e., model-free, or parametric, i.e., model-based, approaches. The latter approaches, when based on bi...

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Bibliographic Details
Main Authors: Emanuele Olivetti, Danilo Benozzo, Jan Bím, Stefano Panzeri, Paolo Avesani
Format: Article
Language:English
Published: Frontiers Media S.A. 2018-06-01
Series:Frontiers in Computational Neuroscience
Subjects:
causality
classification and prediction
cortical network model
neural networks
connectivity
effective connectivity
Online Access:https://www.frontiersin.org/article/10.3389/fncom.2018.00038/full

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https://www.frontiersin.org/article/10.3389/fncom.2018.00038/full

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