Gauging Functional Brain Activity: From Distinguishability to Accessibility

• Main Author: David Papo
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2019-05-01
• Series: Frontiers in Physiology
• Subjects: functional brain activity; functional networks; spatial networks; structure; dynamics; geometry
• Online Access: https://www.frontiersin.org/article/10.3389/fphys.2019.00509/full

Standard neuroimaging techniques provide non-invasive access not only to human brain anatomy but also to its physiology. The activity recorded with these techniques is generally called functional imaging, but what is observed per se is an instance of dynamics, from which functional brain activity should be extracted. Distinguishing between bare dynamics and genuine function is a highly non-trivial task, but a crucially important one when comparing experimental observations and interpreting their significance. Here we illustrate how neuroimaging’s ability to extract genuine functional brain activity is bounded by functional representations’ structure. To do so, we first provide a simple definition of functional brain activity from a system-level brain imaging perspective. We then review how the properties of the space on which brain activity is represented induce relations on observed imaging data which allow determining the extent to which two observations are functionally distinguishable and quantifying how far apart they are. It is also proposed that genuine functional distances would require defining accessibility, i.e., how a given observed condition can be accessed from another given one, under the dynamics of some neurophysiological process. We show how these properties result from the structure defined on dynamical data and dynamics-to-function projections, and consider some implications that the way and extent to which these are defined have for the interpretation of experimental data from standard system-level brain recording techniques.