Lowet, E., Roberts, M. J., Gips, B. C. I., De Weerd, P., & Peter, A. (2017)
eLife, 2017, 6:e26642.
Abstract
Gamma-band synchronization coordinates brief periods of excitability in oscillating neuronal populations to optimize information transmission during sensation and cognition. Commonly, a stable, shared frequency over time is considered a condition for functional neural synchronization. Here, we demonstrate the opposite: instantaneous frequency modulations are critical to regulate phase relations and synchronization. In monkey visual area V1, nearby local populations driven by different visual stimulation showed different gamma frequencies. When similar enough, these frequencies continually attracted and repulsed each other, which enabled preferred phase relations to be maintained in periods of minimized frequency difference. Crucially, the precise dynamics of frequencies and phases across a wide range of stimulus conditions was predicted from a physics theory that describes how weakly coupled oscillators influence each other’s phase relations. Hence, the fundamental mathematical principle of synchronization through instantaneous frequency modulations applies to gamma in V1 and is likely generalizable to other brain regions and rhythms.
Contribution to the field
This paper delves deeper into the earlier idea from Roberts et al. (Neuron, 2013) that a mechanism that could regulate frequency differences would be in a good position to also regulate synchronization. Simultaneous recordings from V1 sites driven by different contrasts showed – on top of an average frequency difference – a dynamic modulation of instantaneous frequency, during which brief periods of low detuning enabled temporary fixed phase relations permitting neural communication. We found that the amplitude of the instantaneous frequency modulation related to estimates of anatomical connectivity strength among recorded locations. The average difference in frequency between stimulated (and recorded) sites was related to the contrast difference of stimuli giving input to these sites. Thus, the amount of synchronization (phase locking) is controlled by the average difference in gamma frequency (or in excitatory drive) in different recording sites, and by connectivity strength. Thus, an analysis of a change in the dynamics of instantaneous phase differences and frequency differences over time can give information about whether the same increase in synchronization was due to a decrease of average detuning (e.g., more similar stimulation conditions) or due to a change in connectivity (interaction) strength (e.g., due to learning). Hence, the proposed theoretical framework, to which we started referring as the ‘Dynamic Frequency Matching (DFM)’ theory, permits a deeper analysis of the mechanisms underlying changes in synchronization between different cognitive conditions. In coming years, the goal is to test the general applicability of DFM in different cognitive contexts and frequency ranges.