Tools of the trade: psychophysiological interactions and functional connectivity.

By J. O’Reilly, Mark William Woolrich, Timothy Edward John Behrens, Stephen M. Smith, Heidi Johansen-Berg. Social Cognitive and Affective Neuroscience, 2012

783 citations recorded by the source corpus.

Psychophysiological interactions (PPIs) analysis is a method for investigating task-specific changes in the relationship between activity in different brain areas, using functional magnetic resonance imaging (fMRI) data. Specifically, PPI analyses identify voxels in which activity is more related to activity in a seed region of interest (seed ROI) in a given psychological context, such as during attention or in the presence of emotive stimuli. In this tutorial, we aim to give a simple conceptual explanation of how PPI analysis works, in order to assist readers in planning and interpreting their own PPI experiments.

Subfields: Cognitive Neuroscience, Experimental and Cognitive Psychology

View Paper: https://www.semanticscholar.org/paper/9680acfe494e898ad3666150d9b8cc132a02af29

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Citations in the corpus

Exploring the role of the posterior middle temporal gyrus in semantic cognition: Integration of anterior temporal lobe with executive processes (2016, positive): “We used this pMTG region as a mask and extracted the time-course (for each participant and each run) within this area to examine psychophysiological interactions (PPI; O'Reilly et al., 2012) between the pMTG and other brain regions involved in event semantics.”
Structural foundations of resting-state and task-based functional connectivity in the human brain (2013, methodology): “Alternatively, a generalized linear model (GLM) can be used in combination with techniques such as partial least squares (PLS) or psychophysiological interactions (PPI) [45, 46] to identify task-related activations across cortical and subcortical structures.”
Questions and controversies in the study of time-varying functional connectivity in resting fMRI (2020, neutral): “State-based approaches can differ in whether they assume smooth transitions between states (Allen et al., 2014; Ou et al., 2015) or instantaneous reconﬁgurations (Liu, Zhang, et al., 2018; Yaesoubi et al., 2018), their focus on a particular signal domain (e.g., frequency, Yaesoubi et al., 2015;…”
Precuneus Is a Functional Core of the Default-Mode Network (2014, background): “Specifically, we included two nuisance regressors that summarized individual differences in motion (average volume-to-volume motion and the proportion of outlier volumes identified), as well as a regressor indicating SFNR, as differences in SFNR may be associated with spurious differences in connect”
Estimating trial-wise modulation of functional connectivity using event-related fMRI (2026, unknown): “Second, task-evoked responses capture changes in local activity magnitudes that are evoked by task inputs (e.g., computational variable or stimulus conditions) and thus do not reflect changes in functional connectivity (O’Reilly et al., 2012) .”