Workflows

Participant Workflow

_images/workflows-1.png

(Source code, png, svg, pdf)

The general workflow for a participant models the betaseries for each trial type for each bold file associated with the participant. Then betas within a region of interest are based off a parcellation are averaged together. This occurs as many times as there are trials for that particular trial type, resulting in a psuedo-timeseries (e.g. each point in “time” represents an occurrence of that trial). All the psuedo time-series within a trial type are correlated with each other, resulting in a final correlation (adjacency) matrix.

BetaSeries Workflow

_images/workflows-2.png

(Source code, png, svg, pdf)

The bold file is temporally filtered by nilearn (high pass and/or low pass) before being passed into nistats for modelling by least squares separate.

Correlation Workflow

_images/workflows-3.png

(Source code, png, svg, pdf)

The betaseries file has signal averaged across trials within a region defined by an atlas parcellation. After signal extraction has occurred for all regions, the signals are all correlated with each other to generate a correlation matrix.