Wikipedia

File:Diagram of Dynamic Causal Modelling - Causal Modelling and Brain Connectivity in Functional Magnetic Resonance Imaging by Karl Friston.png

Diagram_of_Dynamic_Causal_Modelling_-_Causal_Modelling_and_Brain_Connectivity_in_Functional_Magnetic_Resonance_Imaging_by_Karl_Friston.png ‎(548 × 600 pixels, file size: 103 KB, MIME type: image/png)

Description
English: This image is Figure 1 of Causal Modelling and Brain Connectivity in Functional Magnetic Resonance Imaging by Karl Friston.

Figure 1. Models of Effective Connectivity
This schematic shows the underlying equations on which dynamic (DCM) and Granger (GCM) causal models are based.
In DCM for fMRI, bilinear differential equations describe the changes in neuronal activity x(t)i in terms of linearly separable components that reflect the influence of other regional state variables. Known deterministic inputs u(t) elicit a change in neuronal states directly though ci or increase the coupling parameters aij in proportion to the bilinear coupling parameters bij. The neuronal states enter a region-specific haemodynamic model to produce the outputs y(t)i.
GCM tries to model the ensuing dependencies among the outputs with a time-lagged linear regression of the current response on previous responses (up to an order denoted by p).

In both models, the data contain observation noise ε(t) that is added to regional observations. The DCM is effectively a state-space model formulated in continuous time; whereas the GCM is a vector autoregression model in discrete time. See Figure 2 for a fuller explanation of the haemodynamic part of the model.
Source http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1000033
Author PLoS: Computational Biology
Permission
(Reusing this file)		 http://www.plos.org/about/open-access/license/
This diagram image could be re-created using vector graphics as an SVG file. This has several advantages; see Commons:Media for cleanup for more information. If an SVG form of this image is available, please upload it and afterwards replace this template with {{vector version available|new image name}}.


It is recommended to name the SVG file “Diagram of Dynamic Causal Modelling - Causal Modelling and Brain Connectivity in Functional Magnetic Resonance Imaging by Karl Friston.svg”—then the template Vector version available (or Vva) does not need the new image name parameter.


w:en:Creative Commons
attribution
This file is licensed under the Creative Commons Attribution 1.0 Generic license.
You are free:
  • to share – to copy, distribute and transmit the work
  • to remix – to adapt the work
Under the following conditions:
  • attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.

Captions

Add a one-line explanation of what this file represents

Items portrayed in this file

depicts

File history

Click on a date/time to view the file as it appeared at that time.

Date/TimeThumbnailDimensionsUserComment
current20:56, 27 November 2013Thumbnail for version as of 20:56, 27 November 2013548 × 600 (103 KB)Anishpotnis{{subst:Upload marker added by en.wp UW}} {{Information |Description = {{en|This image is Figure 1 of Causal Modelling and Brain Connectivity in Functional Magnetic Resonance Imaging by Karl Friston. Figure 1. Models of Effective Connectivity This sch...
The following pages on the English Wikipedia use this file (pages on other projects are not listed):

Global file usage

The following other wikis use this file:

Metadata

This file contains additional information, probably added from the digital camera or scanner used to create or digitize it.

If the file has been modified from its original state, some details may not fully reflect the modified file.

Retrieved from "https://en.wikipedia.org/wiki/File:Diagram_of_Dynamic_Causal_Modelling_-_Causal_Modelling_and_Brain_Connectivity_in_Functional_Magnetic_Resonance_Imaging_by_Karl_Friston.png"