Current theories propose that coherence of oscillatory brain activity in the gamma band (30-80 Hz) constitutes an avenue for communication among remote neural populations. However, reports documenting stimulus dependency and time variability of gamma frequency suggest that distant neuronal populations may, at any one time, operate at different frequencies precluding synchronization. To test this idea, we recorded from macaque V1 and V2 simultaneously while presenting gratings of varying contrast. Although gamma frequency increased with stimulus contrast in V1 and V2 (by ∼25 Hz), V1-V2 gamma coherence was maintained for all contrasts. Moreover, while gamma frequency fluctuated by ∼15 Hz during constant contrast stimulation, this fluctuation was highly correlated between V1 and V2. The strongest coherence connections showed a layer-specific pattern, matching feedforward anatomical connectivity. Hence, gamma coherence among remote populations can occur despite large stimulus-induced and time-dependent changes in gamma frequency, allowing communication through coherence to operate without a stimulus independent, fixed-frequency gamma channel.

Synchronization or phase-locking between oscillating neuronal groups is considered to be important for coordination of information among cortical networks. Spectral coherence is a commonly used approach to quantify phase locking between neural signals. We systematically explored the validity of spectral coherence measures for quantifying synchronization among neural oscillators. To that aim, we simulated coupled oscillatory signals that exhibited synchronization dynamics using an abstract phase-oscillator model as well as interacting gamma-generating spiking neural networks. We found that, within a large parameter range, the spectral coherence measure deviated substantially from the expected phase-locking. Moreover, spectral coherence did not converge to the expected value with increasing signal-to-noise ratio. We found that spectral coherence particularly failed when oscillators were in the partially (intermittent) synchronized state, which we expect to be the most likely state for neural synchronization. The failure was due to the fast frequency and amplitude changes induced by synchronization forces. We then investigated whether spectral coherence reflected the information flow among networks measured by transfer entropy (TE) of spike trains. We found that spectral coherence failed to robustly reflect changes in synchrony-mediated information flow between neural networks in many instances. As an alternative approach we explored a phase-locking value (PLV) method based on the reconstruction of the instantaneous phase. As one approach for reconstructing instantaneous phase, we used the Hilbert Transform (HT) preceded by Singular Spectrum Decomposition (SSD) of the signal. PLV estimates have broad applicability as they do not rely on stationarity, and, unlike spectral coherence, they enable more accurate estimations of oscillatory synchronization across a wide range of different synchronization regimes, and better tracking of synchronization-mediated information flow among networks.

Attention can be "covertly" directed without eye movements; yet, even during fixation, there are continuous microsaccades (MSs). In areas V4 and IT of macaques, we found that firing rates and stimulus representations were enhanced by attention but only following a MS toward the attended stimulus. The onset of neural attentional modulations was tightly coupled to the MS onset. The results reveal a major link between the effects of covert attention on cortical visual processing and the overt movement of the eyes.