Robust Gamma Coherence between Macaque V1 and V2 by Dynamic Frequency Matching

Abstract

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.

Alpha and gamma oscillations characterize feedback and feedforward processing in monkey visual cortex

“…The feedforward signature of γ is in line with recent studies showing stronger Granger causality for γ from V1 to V2 and from V1 to V4 than in the opposite direction (18,49,65). It is also reminiscent of a study in cats, showing that γ-oscillations propagate from the LGN to V1 with an average delay of ∼2 ms (47).…”

“…At first sight, this result appears to contradict a recent finding that Granger causality between V1 and V2 in the α-range is strongest in the feedforward direction (18). We suspect that methodological differences (the previous study only selected electrode combinations with high γ-coherence) and perhaps differences between tasks are responsible for this discrepancy.…”

“…One influential hypothesis has been that γ-oscillations play a role in feature binding (14), but later studies cast doubt on this proposal (15,16). A more recent hypothesis holds that γ-oscillations facilitate the communication between cortical areas (17), but both evidence in favor of this proposal (18) and against it (19)(20)(21)(22) have been presented. Although the causal role of oscillatory rhythms in cognition is therefore not undisputed, it would also be of great value if oscillations could be used as markers for feedforward and feedback effects (23).…”

Visual stimulus eccentricity affects human gamma peak frequency

“…While this mixture potentially limits comparability to invasive recordings, there are indications that visual areas synchronize their peak frequencies. In a recent study, Roberts et al (2013) showed, using simultaneous shaft electrode recordings in monkey regions V1 and V2, that gamma peak frequencies cofluctuate in these visual areas during visual stimulation with stimuli of different contrasts. V2 activity shows the same gamma peak frequencies as V1, and also V1-V2 coherence exhibits the same peak frequency as the individual areas.…”

Significant reductions in human visual gamma frequency by the gaba reuptake inhibitor tiagabine revealed by robust peak frequency estimation

“…The peak frequency of visual gamma responses is modulated by properties of the visual stimulus such as size [Gieselmann and Thiele, 2008; Jia et al, 2013; Ray and Maunsell, 2011; van Pelt and Fries, 2013], contrast [Hadjipapas et al, 2015; Jia et al, 2013; Lowet et al, 2015; Perry et al, 2015; Ray and Maunsell, 2010; Roberts et al, 2013], motion [Friedman‐Hill, 2000; Muthukumaraswamy and Singh, 2013; Swettenham et al, 2009], motion velocity [Gray et al, 1990; Gray and Viana Di Prisco, 1997; Orekhova et al, 2015], eccentricity [van Pelt and Fries, 2013], noise masking [Jia et al, 2013], and cross‐orientation masking [Lima et al, 2010; Perry, 2015]. Across individuals, peak gamma frequency correlates with psychophysical performance in visual discrimination tasks [Dickinson et al, 2015; Edden et al, 2009].…”