title: Distributed processing; distributed functions?
abstract: After more than twenty years busily mapping the human brain, what have we learned from neuroimaging? This review (coda) considers this question from the point of view of structure-function relationships and the two cornerstones of functional neuroimaging; functional segregation and integration. Despite remarkable advances and insights into the brain's functional architecture, the earliest and simplest challenge in human brain mapping remains unresolved: We do not have a principled way to map brain function onto its structure in a way that speaks directly to cognitive neuroscience. Having said this, there are distinct clues about how this might be done: First, there is a growing appreciation of the role of functional integration in the distributed nature of neuronal processing. Second, there is an emerging interest in data-driven cognitive ontologies, i.e., that are internally consistent with functional anatomy. We will focus this review on the growing momentum in the fields of functional connectivity and distributed brain responses and consider this in the light of meta-analyses that use very large data sets to disclose large-scale structure-function mappings in the human brain.
authors.affiliation: Research Imaging Institute and Department of Radiology, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX, USA. Fox@uthscsa.edu
authors.forename: Peter T
authors.initials: PT
authors.lastname: Fox
authors.forename: Karl J
authors.initials: KJ
authors.lastname: Friston
mesh_terms: D001499:Bayes Theorem; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D006801:Humans; D015201:Meta-Analysis as Topic; D008959:Models, Neurological; D009415:Nerve Net / Q000033:anatomy & histology / Q000502:physiology; D009434:Neural Pathways / Q000502:physiology; D059906:Neuroimaging / Q000379:methods*