• Corpus ID: 14392479

Detecting causality in Plant electrical signal by a hybrid causal analysis approach

  title={Detecting causality in Plant electrical signal by a hybrid causal analysis approach},
  author={Yang Chen and Dongjie Zhao and Chao Song and Wei-He Liu and Zi-Yang Wang and Zhongyi Wang and Guiliang Tang and Lan Huang},
  journal={arXiv: Neurons and Cognition},
At present, multi-electrode array (MEA) approach and optical recording allow us to acquire plant electrical activity with higher spatio-temporal resolution. To understand the dynamic information flow of the electrical signaling system and estimate the effective connectivity, we proposed a solution to combine the two casualty analysis approaches, i.e. Granger causality and transfer entropy, which they complement each other to measure dynamics effective connectivity of the complex system. Our… 


Analyzing information flow in brain networks with nonparametric Granger causality
Nonlinear connectivity by Granger causality
Spatiotemporal dynamics of the electrical network activity in the root apex
The dynamic electrochemical activity of root apex cells is proposed to continuously integrate internal and external signaling for developmental adaptations in a changing environment.
Spatio-temporal mapping of variation potentials in leaves of Helianthus annuus L. seedlings in situ using multi-electrode array
The results suggest that MEA can enable recordings with high spatio-temporal resolution that facilitate the determination of the bioelectrical response mode of higher plants under stress.
A Multivariate Granger Causality Concept towards Full Brain Functional Connectivity
This paper proposes a new fully multivariate Granger Causality approach with embedded dimension reduction that makes it possible to obtain a representation of functional connectivity for spatially high-dimensional data and demonstrates that a number of different community detection algorithms reveal meaningful information on the underlying network module structure.
A MATLAB toolbox for Granger causal connectivity analysis
  • A. Seth
  • Computer Science
    Journal of Neuroscience Methods
  • 2010
High-resolution non-contact measurement of the electrical activity of plants in situ using optical recording
This work combines a cooled charge-coupled device camera with a voltage-sensitive dye to record action potentials in the stem of Helianthus annuus and variation potentials at multiple sites simultaneously with high spatial resolution, providing direct visualization of the phloem, which is the distribution region of the electrical activities in the stems of higher plants.
Visualization of synchronous propagation of plant electrical signals using an optical recording method
Research progress on electrical signals in higher plants
Analyzing brain networks with PCA and conditional Granger causality
This work proposes a new algorithm called PCA based conditional GCM, which achieves greater accuracy in detecting network connectivity than the commonly used pairwise Granger causality method and greatly reduces the computational cost relative to the use of individual voxel time series.