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(Neural Computation. 2000;12:2805-2821.)
© 2000 The MIT Press


Letter

Relating Macroscopic Measures of Brain Activity to Fast, Dynamic Neuronal Interactions

D. Chawla

Wellcome Department of Cognitive Neurology, Institute of Neurology, Queen Square, London WC1N 3BG, U.K.

E. D. Lumer

Wellcome Department of Cognitive Neurology, Institute of Neurology, Queen Square, London WC1N 3BG, U.K.

K. J. Friston

Wellcome Department of Cognitive Neurology, Institute of Neurology, Queen Square, London WC1N 3BG, U.K.

In this article we used biologically plausible simulations of coupled neuronal populations to address the relationship between phasic and fast coherent neuronal interactions and macroscopic measures of activity that are integrated over time, such as the BOLD response in functional magnetic resonance imaging. Event-related, dynamic correlations were assessed using joint peristimulus time histograms and, in particular, the mutual information between stimulus-induced transients in two populations. This mutual information can be considered as an index of functional connectivity. Our simulations showed that functional connectivity or dynamic integration between two populations increases with mean background activity and stimulus-related rate modulation. Furthermore, as the background activity increases, the populations become increasingly sensitive to the intensity of the stimulus in terms of a predisposition to transient phase locking. This reflects an interaction between background activity and stimulus intensity in producing dynamic correlations, in that background activity augments stimulus-induced coherence modulation. This is interesting from a computational perspective because background activity establishes a context that may have a profound effect on event-related interactions or functional connectivity between neuronal populations. Finally, total firing rates, which subsume both background activity and stimulus-related rate modulation, were almost linearly related to the expression of dynamic correlations over large ranges of activities. These observations show that under the assumptions implicit in our model, rate-specific metrics based on rate or coherence modulation may be different perspectives on the same underlying dynamics. This suggests that activity (averaged over all peristimulus times), as measured in neuroimaging, may be tightly coupled to the expression of dynamic correlations.




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