Discriminating brain activity from task-related artifacts in functional MRI: Fractal scaling analysis simulation and application JaeMin Lee, Jing Hu, Jianbo Gao, Bruce Crosson, Kyung Peck, Christina Wierenga, Keith McGregor, Qun Zhao, Keith White NeuroImage (2008).

When trying to use fMRI to study brain activity, the participant is asked to perform a specific task like tapping the right index finger. Identifying the task-related part of the fMRI signal is challenging and requires statistical analysis. The brain signals measured during fMRI are very complicated because the brain is not only involved in the assigned task but also in controlling breathing, thoughts, feelings and other unstoppable activities the person carries out. Further, during a functional brain scan, upper body movements can cause head motion leading to artifacts that can be mistaken for brain activity. The purpose of this study was to separate these false signals from the true brain activity. Because finger-tapping is a well-studied task and its true brain activity is well known, the study looked at new kinds of analysis using fractal statistics to separate out the false signals. One of these analyses was highly successful and better than any previous method for this purpose.