Seminar Series

Connectomics and functional connectivity based on fMRI CCNI-Debate Preparation: Studies of large-scale brain networks – savior or hype?

Pascal Belin presents: Honey CJ, Sporns O, Cammoun L, Gigandet X, Thiran JP, Meuli R, Hagmann P. (2009) Predicting human resting-state functional connectivity from structural connectivity. Proc Natl Acad Sci U S A. 2009 Feb 10;106(6):2035-40. doi: 10.1073/pnas.0811168106. Epub 2009 Feb 2. In the cerebral cortex, the activity levels of neuronal populations are continuously fluctuating. When neuronal activity, as measured using functional MRI (fMRI), is temporally coherent across 2 populations, those populations are said to be functionally connected. Functional connectivity has previously been shown to correlate with structural (anatomical) connectivity patterns at an aggregate level. In the present study we investigate, with the aid of computational modeling, whether systems-level properties of functional networks--including their spatial statistics and their persistence across time--can be accounted for by properties of the underlying anatomical network. We measured resting state functional connectivity (using fMRI) and structural connectivity (using diffusion spectrum imaging tractography) in the same individuals at high resolution. Structural connectivity then provided the couplings for a model of macroscopic cortical dynamics. In both model and data, we observed (i) that strong functional connections commonly exist between regions with no direct structural connection, rendering the inference of structural connectivity from functional connectivity impractical; (ii) that indirect connections and interregional distance accounted for some of the variance in functional connectivity that was unexplained by direct structural connectivity; and (iii) that resting-state functional connectivity exhibits variability within and across both scanning sessions and model runs. These empirical and modeling results demonstrate that although resting state functional connectivity is variable and is frequently present between regions without direct structural linkage, its strength, persistence, and spatial statistics are nevertheless constrained by the large-scale anatomical structure of the human cerebral cortex. Alexander-Bloch A, Giedd JN, Bullmore E. (2013) Imaging structural co-variance between human brain regions. Nat Rev Neurosci. 2013 May;14(5):322-36. doi: 10.1038/nrn3465. Epub 2013 Mar 27. Review. Brain structure varies between people in a markedly organized fashion. Communities of brain regions co-vary in their morphological properties. For example, cortical thickness in one region influences the thickness of structurally and functionally connected regions. Such networks of structural co-variance partially recapitulate the functional networks of healthy individuals and the foci of grey matter loss in neurodegenerative disease. This architecture is genetically heritable, is associated with behavioural and cognitive abilities and is changed systematically across the lifespan. The biological meaning of this structural co-variance remains controversial, but it appears to reflect developmental coordination or synchronized maturation between areas of the brain. This Review discusses the state of current research into brain structural co-variance, its underlying mechanisms and its potential value in the understanding of various neurological and psychiatric conditions. Lars Muckli presents: Sporns O, Honey CJ. (2013) Topographic dynamics in the resting brain. Neuron. 2013 Jun 19;78(6):955-6. doi: 10.1016/j.neuron.2013.05.037. -> a preview on Wang et al. ... In this issue of Neuron, Wang et al. (2013) demonstrate that spontaneous neural activity measured using functional neuroimaging is strongly related to millisecond-scale neuronal interactions and topographically precise anatomical connections in the primate somatosensory cortex. Wang Z, Chen LM, Négyessy L, Friedman RM, Mishra A, Gore JC, Roe AW. (2013) The relationship of anatomical and functional connectivity to resting-state connectivity in primate somatosensory cortex. Neuron. 2013 Jun 19;78(6):1116-26. doi: 10.1016/j.neuron.2013.04.023. Studies of resting-state activity in the brain have provoked critical questions about the brain's functional organization, but the biological basis of this activity is not clear. Specifically, the relationships between interregional correlations in resting-state measures of activity, neuronal functional connectivity and anatomical connectivity are much debated. To investigate these relationships, we have examined both anatomical and steady-state functional connectivity within the hand representation of primary somatosensory cortex (areas 3b and 1) in anesthetized squirrel monkeys. The comparison of three data sets (fMRI, electrophysiological, and anatomical) indicate two primary axes of information flow within the SI: prominent interdigit interactions within area 3b and predominantly homotopic interactions between area 3b and area 1. These data support a strikingly close relationship between baseline functional connectivity and anatomical connections. This study extends findings derived from large-scale cortical networks to the realm of local millimeter-scale networks. Fornito A, Zalesky A, Pantelis C, Bullmore ET. (2012) Schizophrenia, neuroimaging and connectomics. Neuroimage. 2012 Oct 1;62(4):2296-314. doi: 10.1016/j.neuroimage.2011.12.090. Epub 2012 Feb 24. Review. Schizophrenia is frequently characterized as a disorder of brain connectivity. Neuroimaging has played a central role in supporting this view, with nearly two decades of research providing abundant evidence of structural and functional connectivity abnormalities in the disorder. In recent years, our understanding of how schizophrenia affects brain networks has been greatly advanced by attempts to map the complete set of inter-regional interactions comprising the brain's intricate web of connectivity; i.e., the human connectome. Imaging connectomics refers to the use of neuroimaging techniques to generate these maps which, combined with the application of graph theoretic methods, has enabled relatively comprehensive mapping of brain network connectivity and topology in unprecedented detail. Here, we review the application of these techniques to the study of schizophrenia, focusing principally on magnetic resonance imaging (MRI) research, while drawing attention to key methodological issues in the field. The published findings suggest that schizophrenia is associated with a widespread and possibly context-independent functional connectivity deficit, upon which are superimposed more circumscribed, context-dependent alterations associated with transient states of hyper- and/or hypo-connectivity. In some cases, these changes in inter-regional functional coupling dynamics can be related to measures of intra-regional dysfunction. Topological disturbances of functional brain networks in schizophrenia point to reduced local network connectivity and modular structure, as well as increased global integration and network robustness. Some, but not all, of these functional abnormalities appear to have an anatomical basis, though the relationship between the two is complex. By comprehensively mapping connectomic disturbances in patients with schizophrenia across the entire brain, this work has provided important insights into the highly distributed character of neural abnormalities in the disorder, and the potential functional consequences that these disturbances entail.