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The development of increasingly sophisticated methods for recording and manipulating neural activity is revolutionizing neuroscience. By probing how activity patterns in different types of neurons and circuits contribute to behavior, these tools can help inform mechanistic models of brain function and explain the roles of distinct circuit elements. However, in systems where functions are distributed over large networks, interpreting causality experiments can be challenging. Here we reviewdoi:10.1016/j.conb.2018.01.004 pmid:29414070 pmcid:PMC5957484 fatcat:uxdbpg4hwzbyxhpdctg7z5jgme