Lecture08_FunctionalConnectivity - Functional neuroimaging and brain connectivity Why bother The brain adheres to certain principles of functional

Functional neuroimaging and brain connectivity • Why bother? – The brain adheres to certain principles of functional segregation but these are insufficient to describe its operations satisfactorily – A description of regional patterns of activity in terms of causal relationships with other brain regions obviates some of the theoretical constraints in the simple brain mapping approach – A better model for some brain disorders? Functional Connectivity vs. Effective Connectivity • Functional Connectivity – the temporal correlation of spatially remote neurophysiological events • Effective Connectivity – The influential relationship between one brain region and another An observed inter-regional correlation… These two regions are functionally connected. The observation of correlation is an observation of functional connectivity. They may be Effectively connected. The observation of correlation is compatible with this but also with other possibilities. r Why might we observe functional connectivity? Because of effective connectivity i.e. a uni-or bi-directional influential (‘effective’) relationship Why might we observe functional connectivity? No effective connectivity between the two regions. Correlation arises due to the common influence of a third factor (region or task) How do we represent connectivity? •Descriptive •Correlative •Psychophysiological interaction/physiophysiological interaction •Path analysis/structural equation modelling/DCM Functional Effective Data-led Model-based

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Observation of task-related coactivation is a rather unsatisfying index of inter-regional connectivity Produced by a standard analysis of task-related activation, representing simply a different theoretical treatment of the results Regions thus implicated may not be directly correlated (correlation is not transitive) Non-transitivity of separate regional task-associated activations Task Baseline Region 1 Region 2 Correlative analysis Requires some a priori model (albeit a simple one) Y (1-n) = c + ß .X (1-n) + Є X = voxel/region of interest Y = every other region ß = functional connectivity between X and Y Ultimately, this approach - though it ensures that two regions do indeed correlate - adds little to a simple description of regional co-activation. Psychophysiological interaction/ Physiophysiological interaction (PPI) • The observation of task- or context-dependent inter- regional covariance • Measures the ways in which a given region ‘predicts’ activity in other brain regions. • This has been referred to as the (context-dependent) ‘contribution’ of activity in one area to that in another (here contribution is used used in a statistical sense – contributes to an explanation of the variance) The convolved signal • A burst of neuronal firing is succeeded by a haemodynamic response (the form of which we think that we know in advance).