A Dynamic Directional Model for Effective Brain Connectivity Using Electrocorticographic (ECoG) Time Series

Tingting Zhang, Jingwei Wu, Fan Li, Brian S Caffo, Dana Boatman-Reich

Research output: Contribution to journalArticle

Abstract

We introduce a dynamic directional model (DDM) for studying brain effective connectivity based on intracranial electrocorticographic (ECoG) time series. The DDM consists of two parts: a set of differential equations describing neuronal activity of brain components (state equations), and observation equations linking the underlying neuronal states to observed data. When applied to functional MRI or EEG data, DDMs usually have complex formulations and thus can accommodate only a few regions, due to limitations in spatial resolution and/or temporal resolution of these imaging modalities. In contrast, we formulate our model in the context of ECoG data. The combined high temporal and spatial resolution of ECoG data result in a much simpler DDM, allowing investigation of complex connections between many regions. To identify functionally segregated subnetworks, a form of biologically economical brain networks, we propose the Potts model for the DDM parameters. The neuronal states of brain components are represented by cubic spline bases and the parameters are estimated by minimizing a log-likelihood criterion that combines the state and observation equations. The Potts model is converted to the Potts penalty in the penalized regression approach to achieve sparsity in parameter estimation, for which a fast iterative algorithm is developed. The methods are applied to an auditory ECoG dataset.

Original languageEnglish (US)
Pages (from-to)93-106
Number of pages14
JournalJournal of the American Statistical Association
Volume110
Issue number509
DOIs
StatePublished - Jan 2 2015

Fingerprint

Connectivity
Time series
Potts Model
Spatial Resolution
Penalized Regression
Model
Cubic Spline
State Equation
Sparsity
Modality
Iterative Algorithm
Fast Algorithm
Linking
Penalty
Parameter Estimation
Likelihood
Imaging
Brain
Differential equation
Formulation

Keywords

  • Brain mapping
  • Dynamic system
  • Effective connectivity
  • Ordinary differential equation (ODE)
  • Potts model

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Cite this

A Dynamic Directional Model for Effective Brain Connectivity Using Electrocorticographic (ECoG) Time Series. / Zhang, Tingting; Wu, Jingwei; Li, Fan; Caffo, Brian S; Boatman-Reich, Dana.

In: Journal of the American Statistical Association, Vol. 110, No. 509, 02.01.2015, p. 93-106.

Research output: Contribution to journalArticle

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