Spontaneous neuronal oscillations in the human insula are hierarchically organized traveling waves

  1. Anup Das
  2. John Myers
  3. Raissa Mathura
  4. Ben Shofty
  5. Brian A Metzger
  6. Kelly Bijanki
  7. Chengyuan Wu
  8. Joshua Jacobs
  9. Sameer A Sheth

  • Curated by eLife

    eLife logo

    Evaluation Summary:

    This manuscript is of interest to neuroscientists willing to deepen their knowledge related to the role of the insula and to any scientist interested in oscillatory activities. The substantial dataset and the novel methodological approach provide interesting insights on the functional organization of this brain region.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #2 agreed to share their name with the authors.)

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

The insula plays a fundamental role in a wide range of adaptive human behaviors, but its electrophysiological dynamics are poorly understood. Here, we used human intracranial electroencephalographic recordings to investigate the electrophysiological properties and hierarchical organization of spontaneous neuronal oscillations within the insula. We analyzed the neuronal oscillations of the insula directly and found that rhythms in the theta and beta frequency oscillations are widespread and spontaneously present. These oscillations are largely organized along the anterior–posterior (AP) axis of the insula. Both the left and right insula showed anterior-­to-posterior decreasing gradients for the power of oscillations in the beta frequency band. The left insula also showed a posterior-to-anterior decreasing frequency gradient and an anterior-to-posterior decreasing power gradient in the theta frequency band. In addition to measuring the power of these oscillations, we also examined the phase of these signals across simultaneous recording channels and found that the insula oscillations in the theta and beta bands are traveling waves. The strength of the traveling waves in each frequency was positively correlated with the amplitude of each oscillation. However, the theta and beta traveling waves were uncoupled to each other in terms of phase and amplitude, which suggested that insular traveling waves in the theta and beta bands operate independently. Our findings provide new insights into the spatiotemporal dynamics and hierarchical organization of neuronal oscillations within the insula, which, given its rich connectivity with widespread cortical regions, indicates that oscillations and traveling waves have an important role in intrainsular and interinsular communications.

Article activity feed

  1. Version published to 10.7554/elife.76702 on eLife
  2. eLife

    Author Response

    Reviewer #1 (Public Review):

    In this manuscript the authors investigate the spatiotemporal dynamics of oscillations in the human insula. The authors measure human intracranial EEG data in ten patients who had stereo EEG electrodes placed in the insula. They identify two dominant low frequency oscillations: a theta and a beta rhythm. The frequency and power gradients of these oscillations along the anterior-posterior and superior-inferior axes of the insula are then delineated. They find a beta power gradient that decreases anterior to posterior in both left and right insula. They also find that theta frequency increases and power decreases from anterior to posterior in the left insula. They show examples of traveling waves in some participants and using a cross-correlation analysis, they find that time-shifts between the amplitude and traveling wave strength indicate a functional role for these oscillations in the insula. The manuscript concludes that traveling waves have an important role in intra and inter insular communication.

    These data contribute in an interesting way to the ongoing understanding of oscillations in human brain regions by taking a detailed approach of identifying oscillations in one specific region, the insula. Such careful delineation contributes to our overall understanding of neural oscillations in different brain regions.

    The delineation of traveling waves in the human brain is a particularly challenging problem, where many lower-level analysis issues can affect the outcome statistics. The authors did a careful assessment of many of these analysis concerns, but several questions remain that may have a major impact on the outcomes and conclusions.

    We thank the reviewer for the encouraging comments. Below, please find point-by-point responses to the concerns.

    1. The authors should use additional metrics to ensure that results are not driven by individual subjects. For example, the theta frequency gradient shown in the left insula in figure 2A seems to be strongly driven by two sEEG probes with a lower frequency in the anterior insula. These seem to potentially correspond to subject 3 shown in figure 4C.

    We have revised the paper to more clearly explain that our main statistical analyses were all performed using a mixed-effects model that specifically ensured our findings were not driven by individual subjects. All group-level statistical tests for the spatial frequency and power gradients accounted for the identity of the subject that contributed each electrode, represented as a categorical variable in the linear mixed effects model, thus ensuring that subject-level results were not separately modeled. As a result of this procedure, therefore, all reported t-statistics reflect the overall strength (effect size) and spatial direction of spectral gradients across subjects, because the method separately accounted for the differences between them. Similarly, we also found that the number of electrodes contributed by each subject was also similar, with relatively low variance across subjects (mean = 23.9 contacts, standard error = +/- 2.43 contacts). Nevertheless, we do understand the concern and have now added a supplementary figure (Figure S11) in the revised version of our manuscript showing that single-subject gradients directionally align with the group level results. The text in manuscript has now been modified to reflect these changes (pages 6-7).

    1. To establish the fundamental spatiotemporal dynamics of oscillations in the human insula, the authors should include the full range of lower frequencies for their analysis. It is unclear why the 9-15 Hz range is excluded. Moreover, the peak frequency estimates in figure 1C seem to be found most often in the middle of the theta 6-9Hz and the beta 15-30Hz range. The possibility that including a certain frequency range introduces bias in the algorithm towards finding a peak in the middle of the range should be excluded.

    We fairly tested for oscillations and traveling waves at all frequencies and found no 9-15 Hz signals in the insula. The revised paper more clearly describes this interesting absence (see page 9).

    1. An assessment for the confidence of the power and frequency gradients should be presented. The authors carefully fit a 1/f function to the power spectrum to delineate the peak frequencies in the theta and beta range, but confidence intervals for the frequency and power estimates within each electrode should additionally be calculated to ensure that temporal outliers within an electrode do not drive the results. Moreover, while the peaks in figure 1 seem quite broad in the frequency range, varying in steps of about 0.25Hz, the frequencies of the oscillation clusters seem quite detailed, reported with 0.001Hz accuracy. These differ by several orders of magnitude. Information about the confidence for the frequency and power within individual electrodes compared to the variance across electrodes will provide better intuition about the relative variability of the estimates over time and space.

    We thank the reviewer for this concern. We added the following statement to the subsection ‘Analysis of frequency and power gradients’ in the Methods section to clarify the frequency resolution, “The resting-state recordings were five minutes duration and were analyzed from 1-50 Hz in 0.1 Hz intervals (491 frequencies).” The cluster frequency values reported in the Figures S1-S9 represent the average of the peak frequencies across all the electrodes and not the individual peak frequency values. While it is numerically correct, we agree that it is confusing to report these values with 3 significant figures, and we now report only one significant digit in the revised paper. The variability in peak frequencies across individual electrodes is shown via the red shading in Figure 1B, which indicates the standard error, and also in the histograms in Figure 1C. Peak frequencies of theta and beta oscillations appear to have relatively normal distributions across the insula. The caption of Figure 1 has been modified accordingly in the revised version of our manuscript to reflect these changes.

    1. The overall signal level can vary across electrodes, especially when they have different distances from the white matter. It should be assessed that the reported power gradients are not simply driven by the relative position of the electrodes.

    We appreciate the reviewer for pointing out the possibility that our results were impacted by white matter. We have analyzed this issue in detail and there is no meaningful impact of white matter to our results.

  3. eLife

    Evaluation Summary:

    This manuscript is of interest to neuroscientists willing to deepen their knowledge related to the role of the insula and to any scientist interested in oscillatory activities. The substantial dataset and the novel methodological approach provide interesting insights on the functional organization of this brain region.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #2 agreed to share their name with the authors.)

  4. eLife

    Reviewer #1 (Public Review):

    In this manuscript the authors investigate the spatiotemporal dynamics of oscillations in the human insula. The authors measure human intracranial EEG data in ten patients who had stereo EEG electrodes placed in the insula. They identify two dominant low frequency oscillations: a theta and a beta rhythm. The frequency and power gradients of these oscillations along the anterior-posterior and superior-inferior axes of the insula are then delineated. They find a beta power gradient that decreases anterior to posterior in both left and right insula. They also find that theta frequency increases and power decreases from anterior to posterior in the left insula. They show examples of traveling waves in some participants and using a cross-correlation analysis, they find that time-shifts between the amplitude and traveling wave strength indicate a functional role for these oscillations in the insula. The manuscript concludes that traveling waves have an important role in intra and inter insular communication.

    These data contribute in an interesting way to the ongoing understanding of oscillations in human brain regions by taking a detailed approach of identifying oscillations in one specific region, the insula. Such careful delineation contributes to our overall understanding of neural oscillations in different brain regions.

    The delineation of traveling waves in the human brain is a particularly challenging problem, where many lower-level analysis issues can affect the outcome statistics. The authors did a careful assessment of many of these analysis concerns, but several questions remain that may have a major impact on the outcomes and conclusions.

    1. The authors should use additional metrics to ensure that results are not driven by individual subjects. For example, the theta frequency gradient shown in the left insula in figure 2A seems to be strongly driven by two sEEG probes with a lower frequency in the anterior insula. These seem to potentially correspond to subject 3 shown in figure 4C.

    2. To establish the fundamental spatiotemporal dynamics of oscillations in the human insula, the authors should include the full range of lower frequencies for their analysis. It is unclear why the 9-15 Hz range is excluded. Moreover, the peak frequency estimates in figure 1C seem to be found most often in the middle of the theta 6-9Hz and the beta 15-30Hz range. The possibility that including a certain frequency range introduces bias in the algorithm towards finding a peak in the middle of the range should be excluded.

    3. An assessment for the confidence of the power and frequency gradients should be presented. The authors carefully fit a 1/f function to the power spectrum to delineate the peak frequencies in the theta and beta range, but confidence intervals for the frequency and power estimates within each electrode should additionally be calculated to ensure that temporal outliers within an electrode do not drive the results. Moreover, while the peaks in figure 1 seem quite broad in the frequency range, varying in steps of about 0.25Hz, the frequencies of the oscillation clusters seem quite detailed, reported with 0.001Hz accuracy. These differ by several orders of magnitude. Information about the confidence for the frequency and power within individual electrodes compared to the variance across electrodes will provide better intuition about the relative variability of the estimates over time and space.

    4. The overall signal level can vary across electrodes, especially when they have different distances from the white matter. It should be assessed that the reported power gradients are not simply driven by the relative position of the electrodes.

  5. eLife

    Reviewer #2 (Public Review):

    The authors investigate the spatial dynamics of neural oscillations of the insula during the resting-state. They first analyze the amplitude and the power of the theta and beta frequency oscillations from an impressive amount of data directly recorded from the insula of drug-resistant epileptic patients. They find the existence of spatial gradients, mostly in the anteroposterior axis, that differ across frequencies and hemispheres. Their second analysis examines the phase dynamics of these two frequency oscillation bands. They report some traveling waves of spontaneous neural oscillations in the theta and the beta bands, which are uncorrelated with each other.

    Overall, the conclusions of this paper are well supported by the data and the methodology.

    Strengths:

    Due to its location, the insula has always been hard to study. In this manuscript, the authors have access to a unique dataset of electrodes implanted directly in the insula of epileptic patients undergoing intraEEG procedure. The number of contacts included in the analysis is remarkable.

    The methodological approach is novel and well adapted for the analysis of spontaneous neural oscillations. The authors have a thorough approach where they look at the frequency signal from different angles: the spatial distribution of frequency and power, and the phase modulations.

    Weaknesses:

    Despite having such an extensive amount of data, some results regarding the traveling waves are too sparse and not consistent across participants to be generalizable. Some spatiotemporal information could be added to clarify the results about the clusters of neural oscillations as well as the traveling waves.

  6. Version published to 10.1101/2021.12.16.473034v1 on bioRxiv