Toward a cumulative science of functional integration: A meta-analysis of psychophysiological interactions

David V. Smith, Mouad Gseir, Megan E. Speer, Mauricio R. Delgado

Research output: Contribution to journalArticlepeer-review

30 Scopus citations

Abstract

Much of the work in cognitive neuroscience is shifting from a focus on single brain regions to a focus on the connectivity between multiple brain regions. These inter-regional connectivity patterns contribute to a wide range of behaviors and are studied with models of functional integration. The rapid expansion of the literature on functional integration offers an opportunity to scrutinize the consistency and specificity of one of the most popular approaches for quantifying connectivity: psychophysiological interaction (PPI) analysis. We performed coordinate-based meta-analyses on 284 PPI studies, which allowed us to test (a) whether those studies consistently converge on similar target regions and (b) whether the identified target regions are specific to the chosen seed region and psychological context. Our analyses revealed two key results. First, we found that different types of PPI studies—e.g., those using seeds such as amygdala and dorsolateral prefrontal cortex (DLPFC) and contexts such as emotion and cognitive control, respectively—each consistently converge on similar target regions, thus supporting the reliability of PPI as a tool for studying functional integration. Second, we also found target regions that were specific to the chosen seed region and psychological context, indicating distinct patterns of brain connectivity. For example, the DLPFC seed reliably contributed to a posterior cingulate cortex target during cognitive control but contributed to an amygdala target in other contexts. Our results point to the robustness of PPI while highlighting common and distinct patterns of functional integration, potentially advancing models of brain connectivity. Hum Brain Mapp 37:2904–2917, 2016.

Original languageEnglish (US)
Pages (from-to)2904-2917
Number of pages14
JournalHuman Brain Mapping
Volume37
Issue number8
DOIs
StatePublished - Aug 1 2016

All Science Journal Classification (ASJC) codes

  • Anatomy
  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Neurology
  • Clinical Neurology

Keywords

  • CBMA
  • brain connectivity
  • coordinate-based meta-analysis
  • coupling
  • effective connectivity
  • fMRI

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