After participants completed these creative thinking tasks in the fMRI, we measured functional connectivity between all brain regions how much activity in one region correlated with activity in another region.
The most salient feature of rs-fMRI in AD is the ease of data acquisition in patients with dementia, specifically the ability to measure functional connectivity changes without requiring the performance of a task.
We will also measure functional connectivity between regions within the fronto-limbic system and construct graphical models that summarise the topological properties of fronto-limbic and whole brain networks [ 60, 61] in the resting state data.
However, measuring the functional connectivity of landscapes is challenging due to the lack of data on species landscape interactions and because connectivity is species-specific.
To date, the main methods of measuring brain functional connectivity include correlation coefficient (CF), partial correlation coefficient (PCF), mutual information (MI), wavelet correlation coefficient (WCF), and coherence (CH).
Particularly, the coherence function, which estimates the linear relationship between two simultaneous time series as a function of frequency, is widely used to measure brain functional connectivity.
Here, we develop methods to measure intrinsic functional connectivity in Drosophila, a powerful model for the study of neural computation.
Besides linear methods, nonlinear methods on the basis of deterministic chaos and information-based techniques can also be used to measure the functional connectivity in EEG/MEG.
In order to illustrate the generality of our approach, here we briefly describe how it can be extended to compute two other symmetric quantities commonly used to measure the functional connectivity, namely the mutual information and the magnitude-squared coherence [10, 37, 38].
A previous study indicated that regional volumes are positively correlated to their mutual information, which measures the functional connectivity between the region and the remaining brain regions [84].
