Large-Scale Communication in the Human Brain Is Rhythmically Modulated through Alpha Coherence

Abstract

Recent evidence has suggested that coherent neuronal oscillations may serve as a gating mechanism for flexibly modulating communication between brain regions. For this to occur, such oscillations should be robust and coherent between brain regions that also demonstrate time-locked correlations, with time delays that match the phase delays of the coherent oscillations. Here, by analyzing functional connectivity in both the time and frequency domains, we demonstrate that alpha oscillations satisfy these constraints and are well suited for modulating communication over large spatial scales in the human brain. We examine intracranial EEG in the human temporal lobe and find robust alpha oscillations that are coherent between brain regions with center frequencies that are consistent within each individual participant. Regions demonstrating coherent narrowband oscillations also exhibit time-locked broadband correlations with a consistent time delay, a requirement for an efficient communication channel. The phase delays of the coherent alpha oscillations match the time delays of the correlated components, and importantly, both broadband correlations and neuronal spiking activity are modulated by the phase of the oscillations. These results are specific to the alpha band and build upon emerging evidence suggesting that alpha oscillations may play an active role in cortical function. Our data therefore provide evidence that large-scale communication in the human brain may be rhythmically modulated by alpha oscillations.

Keywords: alpha; coherence; communication; connectivity; correlation; electrophysiology; functional; human; information; intracranial EEG.

Figure 1. Alpha oscillations rhythmically modulate spiking activity.

(A) Schematic demonstrating the principle of rhythmic communication. If neurons preferentially fire at a specific phase of an oscillation, and the oscillations at two regions are coherent with a phase delay matching the conduction delay between them, then spikes fired at the excitable phase in one region will arrive at the excitable phase in the downstream region. These rhythmic bouts of maximum gain can be used to set up an effective communication channel between two coherent regions. Conversely, when the phase does not match the delay then spikes will arrive away from the excitable phase and will be less likely to elicit firing. (B) Average spike field coherence spectrum (SFC) for the example participant. The average SFC spectrum across all units has a clear peak in the alpha band (f = [7,8] Hz). Inset: Individual spike waveforms (gray) and mean waveform (black) for a single example unit. Vertical scale bar = 10SD, Horizontal scale bar = 1.5ms. (C) Histogram of peak frequencies for individual units. For a large fraction of units (40%), the frequency of maximum SFC was also centered at f = [7,8] Hz. Inset: Distributions of correlations between LFP alpha power and instantaneous firing rate. On average, alpha power and spike rate are negatively correlated for alpha coherent units (orange) and uncorrelated for all other units (gray). (D) Spike triggered average for units with maximal SFC at f = [7,8] Hz. Alpha oscillations lasting several cycles are clearly visible. (E) Phase preference for the alpha coherent units. The preferred phase for spiking activity is near the trough of the alpha cycle. See also Figure S1.

Figure 2. Alpha activity and coherence.

(A) Subdural electrode grid for the example participant. (B) Time-frequency representation for the signals from two example electrodes (black circles in a) during a 30-second block. For both electrodes, there is consistently high power in a narrow band around 8 Hz. (C) Average power spectrum across all electrodes for the same participant (mean ± SEM over all blocks). There is clear peak at 8Hz, indicating that on average across all electrodes there is high narrowband alpha power above the f^−α background. (D) The frequency of maximum coherence for a large fraction of electrode pairs and blocks in this participant also occurred in the alpha band (f_c = [7,8] Hz; see inset for average coherence spectrum over all electrode pairs. See also Figure S2.

Figure 3. Relationship between alpha coherence and time-locked correlations.

(A) Time-locked coupling, a windowed and scaled measure of the time-lagged cross correlation (see STAR Methods), for the same electrode pair from Figure 2A. Across all blocks, the maximum coupling was large and occurred at a consistent time delay, τ_w. (B) Coherence spectra for the same example electrode pair in a. Across all blocks, there was a large and consistent peak in the coherence spectrum at f_c. The excess coherence, C_excess, captures the amount of coherence that is due only to narrowband activity (see STAR Methods). (C) The scatter plot shows all of the excess coherence and maximum coupling values for the example participant. By thresholding the distributions of these metrics (see STAR Methods) we can determine how many electrode pairs have both significant time-locked coupling and significant excess coherence (orange region). There are significantly more pairs than would be expected by chance (χ² test; see Table 1). (D) The Spearman correlations between excess coherence and average maximum coupling are positive and significant for all participants. (E) Correlations over time between alpha power and coupling for units with significant coupling and excess coherence are significant and positive. (F) Correlations between distance and coupling. (G) Correlations between distance and excess coherence. See also Figures S2, S3, S4A,B, and S5A,C.

Figure 4. Time delays for broadband and narrowband components.

(A) Time delays, τ_w, for individual electrode pairs in a single participant during different data blocks estimated from the cross-correlation analysis. Each point represents the time delay during a data block for a single coupled pair. Colored clouds of points (rows) represent all time delays for a single coupled electrode pair. (B) Time delays, τ_ϕ, for individual electrode pairs during different data blocks estimated from the cross-spectrum phase difference at f_c. inset: Distribution of phase differences for a single pair. The phase differences appear to be tightly concentrated at approximately 315°. (C) Distribution of root mean squared errors (RMSE) for a single participant between: τ_w and τ_α for coupled pairs (orange), τ_w and τ_α for uncoupled pairs (blue), and τ_w and τ_δ for coupled pairs (purple) The errors for the coupled pairs using τ_α are typically less than 10 milliseconds, and are significantly smaller than the errors for uncoupled pairs and the errors for coupled pairs using τ_δ. (D) Same as c but pooled across all participants. (E) Correlations between distance and absolute time delay for every participant. (F) Correlations between distance and absolute phase lag. See also Figures S4C and S5B,D.

Figure 5. Phase preference for large-scale correlations.

(A) Single participant. There are more electrode pairs with maximal correlations at the trough of the alpha cycle than at any other phase bin, and the fractions of pairs with maximal correlations at the peak and trough are larger than what would be expected if there was no phase dependence (gray bars). (B) Same as a but pooled across all participants. See also Figure S6.