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Complex behavior requires fast changes of functional connectivity in large-scale cortical networks. Here, we report on the dynamics of functional coupling across visual, auditory and parietal areas during a lateralized detection task in the ferret. We hypothesized that fluctuations in coupling, indicative of dynamic variations in the network state, should be predictive of the animals’ performance. Analysis of power for hit and miss trials revealed significant differences around stimulus- and response-onset. In contrast, phase coupling already differed between hits and misses before stimulus onset, indicating fluctuations in large-scale network connectivity. In particular, higher phase coupling of visual and auditory regions to parietal cortex was predictive of task performance. Furthermore, we observed that long-range coupling became more predominant during the task period compared to the pre-stimulus baseline. Taken together, these results suggest that fluctuations in the network state, particular with respect to long-range connectivity, are critical determinants of the animals’ behavior.

Intrinsic coupling modes (ICMs) provide a framework for describing the interactions of ongoing brain activity at multiple spatial and temporal scales. Two types of ICMs can be distinguished, namely phase ICMs arising from phase coupling of band-limited oscillatory signals, and envelope ICMs corresponding to coupled slow fluctuations of signal envelopes. These coupling modes represent a widely used concept in modern cognitive neuroscience for probing the connectional organization of intact or damaged brains. However, the principles that shape ICMs remain elusive, in particular their relation to the underlying brain structure. Here we explored ICMs from ongoing activity of multiple cortical areas recorded from awake ferrets using chronically implanted electrocorticographic (ECoG) arrays. Additionally, we obtained different structural connectivity (SC) estimates for the regions underlying the ECoG arrays. Large-scale computational models were used to explore the ability to predict both types of ICMs. We found that simple computational models based on the SC topology already reproduce the functional coupling patterns reasonably well. Thus, the results demonstrate that patterns of cortical functional coupling as reflected in both phase and envelope ICMs are strongly related to the underlying structural connectivity of the cerebral cortex.