Talk (Work in Progress): David Colaço (MCMP)

Title:

Transparency and the Remediation of Artifacts: Head motion in fMRI

Abstract:

Scientists aim to remediate artifacts in their datasets. These artifacts result from factors in an experimental arrangement that are distinct from the target of investigation. If they are not prevented, reduced, or corrected for, artifacts undercut researchers’ ability to use these data as evidence. While philosophers recently have taken interest in artifacts, parallel investigation has not been directed towards their remediation. However, remediation is a critical epistemic practice: if artifacts are not remediated, they affect researchers’ ability to use data as evidence for their targets. How are artifacts remediated? In this talk, I answer this question by exploring a case in neuroimaging where researchers aimed to remediate head motion artifacts. Due to their correction methods, their remediation of head motion resulted in the need to remediate a second artifact. In explaining why they ended up with a second artifact, I address what knowledge of one’s experimental arrangement and one’s remediation method is needed to remediate an artifact. In accounting for this knowledge, I explain that this case results from a threat to structural transparency: a second artifact can result when researchers do not know how the factors responsible for artifacts affect data or how a correction transforms data.