Fast-scale network dynamics in human cortex have specific spectral covariance patterns

Abstract

Whether measured by MRI or direct cortical physiology, infraslow rhythms have defined state invariant cortical networks. The time scales of this functional architecture, however, are unlikely to be able to accommodate the more rapid cortical dynamics necessary for an active cognitive task. Using invasively monitored epileptic patients as a research model, we tested the hypothesis that faster frequencies would spectrally bind regions of cortex as a transient mechanism to enable fast network interactions during the performance of a simple hear-and-repeat speech task. We term these short-lived spectrally covariant networks functional spectral networks (FSNs). We evaluated whether spectrally covariant regions of cortex, which were unique in their spectral signatures, provided a higher degree of task-related information than any single site showing more classic physiologic responses (i.e., single-site amplitude modulation). Taken together, our results showing that FSNs are a more sensitive measure of task-related brain activation and are better able to discern phonemic content strongly support the concept of spectrally encoded interactions in cortex. Moreover, these findings that specific linguistic information is represented in FSNs that have broad anatomic topographies support a more distributed model of cortical processing.

Keywords: covariant amplitude response; electrocorticography; oscillating electrical potential.

Fig. 1.

Amplitude response vs. covariant amplitude response for any spoken word vs. rest for subjects 1–5 (rows 1–5, respectively) at the time period containing the voice onset time. (A) Thresholded (P < 0.05) electrode vs. frequency signed r² values (with red indicating a positive and blue a negative r² value). (B) Locations of the electrodes with at least one frequency bin with a significant r² value in amplitude response (yellow circles), the electrodes included in the FSN (blue circles), or both (green circles). (C) The right column shows FSN patterns in electrode vs. frequency, with small to large increases and decreases indicated with light to dark red and blue.

Fig. 2.

Anatomic and spectral distribution of physiologic response over all subjects and significant time periods. (A) Distribution of the percentages of electrodes with a significant amplitude response (AR) for speaking vs. rest (I.), AR for any phoneme comparison (II.), within a FSN for speaking vs. rest (III.), and FSN for any phoneme comparison (IV.). *P < 0.0001. Boxes represent upper and lower quartile of data; whiskers represent maxima and minima of data. +, outlier data points. (B) Summated pseudospectra for ARs (gray shaded areas; Left) and FSNs (red shaded areas; Right) with significant increases (above zero line) or decreases (below zero line) over all task comparisons. Significant ARs had P < 0.05, and significant FSNs frequency bins had a SE above or below zero for all of the electrodes in a single spectral grouping.

Fig. 3.

Temporal characteristics. (A) Significant speaking vs. rest time periods for subjects 1–5 (top to bottom rows). Time points with a significant AR and/or FSN are indicated by black and red rectangles, respectively. The vertical black lines indicate the time periods that include the –1-, –0.5-, 0-, 0.5-, 1-, 1.5-, and 2-s time samples relative to voice onset time. The mean onset and end times of significance across ARs and FSNs and all subjects are indicated by the gray-shaded vertical columns. (B) The speech vs. rest FSNs for time periods that include the 0-, 0.5-, 1-, and 1.5-s time samples (columns from left to right) for subject 1. Each plot shows the locations on the brain and spectral distributions of the electrodes in the FSNs. The patterns represent amplitude modulations (increases or decreases) that are shared across the electrode group (as shown by the star plots) that are consistent during task when compared against rest. The shaded gray regions indicate spectral ranges with a SE within the spectral group electrode above or below zero.

Fig. 4.

FSN spectral diversity. A–C show FSNs for subject 5 and the time period from 250 to 417 ms after voice onset time. (A) Speech vs. rest. The top brain plot shows the locations of the electrodes included in the FSN projected onto a standardize MNI brain surface. The bottom plot shows the mean (dark blue line) and SE range (shaded blue region) of amplitude change across the spectral bins for all electrodes in the FSN. The shaded gray regions indicate spectral ranges with a SE within the spectral group electrode above or below zero. (B) [i] vs. [æ], with blue, red, yellow, and green indicating the four spectral groups within the FSN. (C) [ε] vs. [æ]. (D) Distributions of number of spectral groups in all speech vs. rest (black) and all phoneme-discriminant (red) FSNs. Boxes represent upper and lower quartile of data; whiskers represent maxima and minima of data. +, outlier data points.

Fig. 5.

Phoneme discrimination for AR vs. FSN. (A) Graph of time periods (horizontal axis) with significant AR (black) and FSN (red) phoneme discrimination. Rows 1–5 and 6–10 correspond to the AR and FSN results, respectively. The grids in rows 1–10 depict the six possible phoneme comparisons as described in the figure key. Rows 11 and 12 correspond to the AR and FSN results summed over subjects and phoneme pairs for each time period. (B) Histograms of AR (top row) and FSN (bottom row) phoneme pair discrimination for subjects 1–5. Each plot indicates the number of significant time periods between each for the six phoneme comparisons, with no significant time periods marked with a gray line. (C) Distributions of the number of significant time periods for ARs and FSNs summed over subjects. VOT, voice onset time.