Coherence fails to reliably capture inter-areal interactions in bidirectional neural systems with transmission delays.

Accurately measuring and quantifying the underlying interactions between brain areas is crucial for understanding the flow of information in the brain. Of particular interest in the field of electrophysiology is the analysis and characterization of the spectral properties of these interactions. Coherence and Granger-Geweke causality are well-established, commonly used methods for quantifying inter-areal interactions, and are thought to reflect the strength of inter-areal interactions. Here we show that the application of both methods to bidirectional systems with transmission delays is problematic, especially for coherence. Under certain circumstances, coherence can be completely abolished despite there being a true underlying interaction. This problem occurs due to interference caused in the computation of coherence, and is an artifact of the method. We motivate an understanding of the problem through computational modelling and numerical simulations. In addition, we have developed two methods that can recover the true bidirectional interactions in the presence of transmission delays.

Attentional modulation of inter-areal coherence explained by frequency shifts.

Inter-areal coherence has been hypothesized as a mechanism for inter-areal communication. Indeed, empirical studies have observed an increase in inter-areal coherence with attention. Yet, the mechanisms underlying changes in coherence remain largely unknown. Both attention and stimulus salience are associated with shifts in the peak frequency of gamma oscillations in V1, which suggests that the frequency of oscillations may play a role in facilitating changes in inter-areal communication and coherence. In this study, we used computational modeling to investigate how the peak frequency of a sender influences inter-areal coherence. We show that changes in the magnitude of coherence are largely determined by the peak frequency of the sender. However, the pattern of coherence depends on the intrinsic properties of the receiver, specifically whether the receiver integrates or resonates with its synaptic inputs. Because resonant receivers are frequency-selective, resonance has been proposed as a mechanism for selective communication. However, the pattern of coherence changes produced by a resonant receiver is inconsistent with empirical studies. By contrast, an integrator receiver does produce the pattern of coherence with frequency shifts in the sender observed in empirical studies. These results indicate that coherence can be a misleading measure of inter-areal interactions. This led us to develop a new measure of inter-areal interactions, which we refer to as Explained Power. We show that Explained Power maps directly to the signal transmitted by the sender filtered by the receiver, and thus provides a method to quantify the true signals transmitted between the sender and receiver. Together, these findings provide a model of changes in inter-areal coherence and Granger-causality as a result of frequency shifts.