The lure of misleading causal statements in functional connectivity research

Understand

As neuroscientists we want to understand how causal interactions or mechanisms within the brain give rise to perception, cognition, and behavior.

• It is typical to estimate interaction effects from measured activity using statistical techniques such as functional connectivity, Granger Causality, or information flow, whose outcomes are often falsely treated as revealing mechanistic insight.
• Since these statistical techniques fit models to low-dimensional measurements from brains, they ignore the fact that brain activity is high-dimensional.
• Here we focus on the obvious confound of common inputs: the countless unobserved variables likely have more influence than the few observed ones.