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Estimation of cortical connectivity in humans advanced signal processing techniques /

In the last ten years many different brain imaging devices have conveyed a lot of information about the brain functioning in different experimental conditions. In every case, the biomedical engineers, together with mathematicians, physicists and physicians are called to elaborate the signals related...

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Bibliographic Details
Main Author: Astolfi, Laura.
Other Authors: Babiloni, Fabio.
Format: Electronic
Language:English
Published: San Rafael, Calif. (1537 Fourth St, San Rafael, CA 94901 USA) : Morgan & Claypool Publishers, c2008.
Series:Synthesis lectures on biomedical engineering, #13.
Subjects:
Neurophysiology > Statistical methods.
Cerebral cortex > Physiology > Statistical methods.
Electroencephalography.
Online Access:View fulltext via EzAccess
Table of Contents:
  • Estimation of the effective connectivity from stationary data by structural equation modeling
  • Structural equation modeling
  • Simulation study
  • Signal generation
  • Parameter estimation
  • Evaluation of performances
  • Statistical analysis
  • Results of the simulations
  • Correct formulation of the connectivity model
  • Hypothesis of a model with an arc in excess or a missing arc
  • Arc in excess
  • Missing arc
  • Ambiguousness on an arc direction
  • Discussion
  • Estimation of the functional connectivity from stationary data by multivariate autoregressive methods
  • Multivariate autoregressive process
  • Directed transfer function
  • Partial directed coherence
  • Direct DTF
  • Simulation study
  • Signal generation
  • Evaluation of performance
  • Statistical analysis
  • Estimation of cortical activity by the use of realistic head modeling
  • The problems of conventional electroencephalogy recordings
  • The high-resolution electroencephalography
  • The search for the cortical sources
  • Head and cortical models
  • Regions of interest (ROI)
  • Distributed sources estimate
  • Cortical estimated waveforms
  • Application : estimation of connectivity from movement-related potentials
  • Subjects and experimental design
  • Eeg recordings
  • Selection of regions of interest (ROIs)
  • Definition of the a priori model for the effective connectivity
  • Statistical Evaluation of Connectivity Measurements by SEM and DTF
  • Connectivity pattern representation
  • Application to high-resolution EEG recordings in a cognitive task (Stroop test)
  • Subjects and experimental design
  • Eeg Recordings
  • Application to data related to the intention of limb movements in normal subjects and in a spinal cord injured patient
  • Subjects and experimental design
  • Estimated connectivity patterns
  • Cortical connectivity patterns in spinal cord injury
  • The instantaneous estimation of the time-varying cortical
  • Connectivity by adaptive multivariate estimators
  • Time-varying estimation of the cortical connectivity
  • The simulation study
  • Statistical analysis
  • Time-varying connectivity from event-related potentials
  • Experimental design and Eeg recordings
  • Head and cortical models
  • Regions of interest.

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