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Resting-state gamma-band power alterations in schizophrenia reveal E/I-balance abnormalities across illness-stages

  1. Tineke Grent-'t-Jong
  2. Joachim Gross
  3. Jozien Goense
  4. Michael Wibral
  5. Ruchika Gajwani
  6. Andrew I Gumley
  7. Stephen M Lawrie
  8. Matthias Schwannauer
  9. Frauke Schultze-Lutter
  10. Tobias Navarro Schröder
  11. Dagmar Koethe
  12. F Markus Leweke
  13. Wolf Singer
  14. Peter J Uhlhaas  Is a corresponding author
  1. University of Glasgow, United Kingdom
  2. Institute for Biomagnetism and Biosignalanalysis, University of Muenster, Germany
  3. Goethe University, Germany
  4. Institute of Health and Wellbeing, University of Glasgow, United Kingdom
  5. University of Edinburgh, United Kingdom
  6. University Edinburgh, United Kingdom
  7. University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Switzerland
  8. Medical Faculty, Heinrich-Heine-University, Germany
  9. Norwegian University of Science and Technology, Norway
  10. Central Institute of Mental health, Medical Faculty Mannheim, Heidelberg University, Germany
  11. University of Sydney, Australia
  12. Medical Faculty Mannheim, Heidelberg University, Germany
  13. Max Planck Institute for Brain Research, Germany
  14. Ernst Strüngmann Institute for Neuroscience and the Max Planck Society, Germany
  15. Frankfurt Institute for Advanced Studies, Germany
Research Article
Cite this article as: eLife 2018;7:e37799 doi: 10.7554/eLife.37799
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6 figures, 2 tables and 1 additional file

Figures

Whole-Brain Gamma-Band Power Group Differences Across Illness-Stages.

(A) Low gamma (30–46 Hz) source-power differences for the three main group contrasts: CHR vs.CON1 (left panel), FEP vs.CON2 (middle panel), ScZ vs.CON2 (right panel). Sources were estimated using a DICS beamformer method. Slice- and surface plot representations are shown with t-values corresponding to significant voxels (non-parametric, Monte-Carlo permutation based independent t-tests, FDR corrected at p<0.05, two-sided). Red colors (positive t-values) indicate an increase in gamma-band power compared to controls, whereas blue colors (negative t-values) reflect decreased gamma-band power in the clinical groups. (B) As panel A, but for high gamma (64 – 90 Hz) band activity.

https://doi.org/10.7554/eLife.37799.003
Figure 2 with 1 supplement
Whole-Brain Gamma-Band Power for CHR-Groups.

(A) Low gamma-band (30–46 Hz) source-power differences for the three CHR-group contrasts: SPI-A vs.CON1 (left panel), CAARMS vs.CON1 (middle panel), CAARMS + SPI-A vs.CON1 (right panel). Sources were estimated using a DICS beamformer method. Slice- and surface plot representations are shown with t-values corresponding to significant voxels (non-parametric, Monte-Carlo permutation based independent t-tests, FDR corrected at p<0.05, two-sided). Red colors (positive t-values) indicate an increase in gamma-band power compared to controls, whereas blue colors (negative t-values) reflect decreased gamma-band power in the clinical groups. (B) As panel A, but for high gamma (64 – 90 Hz) band activity.

https://doi.org/10.7554/eLife.37799.005
Figure 2—figure supplement 1
Broadband nature of gamma band effects.

For each group, virtual channel data was reconstructed from central AAL-atlas nodes within the brain regions of significant group effect (Table 2, Manuscript). These data were then submitted to FFT analyses, focusing on 5 Hz bins between 30–90 Hz. Non-parametric, Monte-Carlo based permutation statistics, FDR corrected, were then used to find significant group differences within each 5 Hz bin, averaged across all significant regions. The results showed that spectral changes were broadband in nature, with increased gamma activity in CHR (CAARMS + SPI A group) participants between 35–90 Hz (0.006 < p < 0.031) and FEP group between 30–90 Hz (0.004 < p < 0.015), and decreased gamma-band activity in FEP patients and chronic SCZ patients between 30–90 Hz (FEP: 0.0001 < p < 0.006; SCZ: 0.0001 < p < 0.002). Significant bins are indicated with an asterisk in the Figure.

https://doi.org/10.7554/eLife.37799.006
Illness Severity and Aberrant Gamma Activity.

Surface-projected statistical group differences in low gamma (30–46 Hz; left column) and high gamma-band (64–90 Hz; right column) for all main and the three CHR-subgroups contrasts. Values represent t-values corresponding to significant voxels (p<0.05; uncorrected, masked at critical t-values of non-parametric, Monte-Carlo permutation independent t-tests).

https://doi.org/10.7554/eLife.37799.007
Figure 4 with 1 supplement
Clinical and Demographical Variables and Gamma-band Effects.

Overview of the influence of AGE, SEX, total CAARMS, total PANSS, and composite BACS scores on low g and high gamma-band power GROUP differences. As with the main effects of GROUP, non-parametric, Monte-Carlo permutation-based independent t-test were used to test for GROUP differences, but data was permutated over the control variable data rather than the actual gamma-band source power data. The resulting remaining significant activity then represents the interaction between the main group effect and the variation in the control variable. Surface-projected interaction-effects are shown between control groups and CHR group: (top panel), FEP group (mid panel) and chronic SciZ group (lower panel).

https://doi.org/10.7554/eLife.37799.008
Figure 4—figure supplement 1
Influence of Control Variable AGE on main GROUP effect and interaction effect.

Overview of results of control analyses including a subset of 25 chronic SCZ patients and 25 age-matched controls (from CON2 group) to investigate whether AGE is a confounding or a contributing factor to the main group effects on low-Gamma (30–46 Hz; left panels) and high gamma-band (64–90 Hz; right panels) RS power changes.

Compared to the reported results in the main manuscript (including non-age-matched samples of 34 SCZ and 37 CON2 participants), the main effects are very similar, and the interaction effect with AGE is still significant.

https://doi.org/10.7554/eLife.37799.009
Aberrant Gamma band activity is linked to changes in E/I balance.

Upper Left Panel: Data from a 2 × 2 × 2 cm voxel placed in the right Middle Occiptal Gyrus (RMOG) during 1H-MRS of GABA and Glx (Glutamate/Glutamine) concentrations (MEGAPRESS GABA editing sequence). Right Column: dot-violin distribution plots showing concentration of each metabolite (or ratio between them) for each individual participant (black dots), separately forControls (n = 35) and CHR (n = 69) participants. Red lines indicate median concentration (middle line) and 1st and 3rd quartiles of the distribution. Data was tested for statistical group differences, using one-way repeated-measures ANOVAs, followed up by post-hoc Welch t-tests (bootstrapping: n = 1000, LSD corrected for multiple comparisons). Significant increases were found for CHRs, compared to CONs, in both Glx concentration and Glx/GABA ratio scores. Middle Column: Surface-projected t-values representing linear-regression based correlations between MRS variables and high gamma-band (64– 90 Hz) power from all 104 participants (35 CON plus 69 UHR). Both Glx and ratio scores correlate positively with increased occipital gamma-band power (uncorrected), whereas GABA concentrations correlate negatively with increased gamma-band power in calcarine areas (FDR corrected), resulting in a significantly increased ratio score in the same regions. Lower Left Panel: Correlation plots for the two strongest effects in calcarine regions.

https://doi.org/10.7554/eLife.37799.010
Author response image 1
Overview of effects of the scaling procedure on shifts in the FFT spectrum: shown are two example trials from the same virtual channel data (LMOG), but from different participants, with either high (four top panel figures) or low variance across trials (four bottom panel figures).

Left column shows the unscaled data prior to (top) and after (bottom) Fast-Fourier transformation. Right column shows the same data, but rescaled, using the minimum and maximum values within that trial across time (formula: X(t) – min/ (max-min), with X(t) representing the amplitude at time t). These comparisons show that the rescaling procedure does not change the shape of the powerspectrum.

https://doi.org/10.7554/eLife.37799.013

Tables

Table 1
Demographical and clinical data.
https://doi.org/10.7554/eLife.37799.002
CHR
(n = 88)
CON1
(n = 48)
FEP
(n = 21)
SCZ
(n = 34)
CON2
(n = 37)
GROUP effect*Pairwise comparisons*H/p -values
Age (mean/SEM)
22.0/0.522.7/0.527.0/1.537.1/2.028.6/1.2H(4)=80.8
p<0.0001
CHR vs. FEP
CHR vs. SCZ
−54.6/0.006
−104.5/0.000
Sex (mean/SEM)
female/male67/2133/155/1612/2213/24H(4)=38.9
p<0.0001
FEP vs. CHR
CON2 vs.CON1
59.6/0.000
38.2/0.020
Education (mean/SEM)
Years15.5/0.516.6/0.414.1/0.714.2/0.616.6/0.6H(4)=16.7
p=0.002
CON1 vs. SCZ41.8/0.027
BACS(mean/SEM)CHR
(n = 88)
CON1
(n = 48)
FEP
(n = 18)
SCZ
(n = 28)
CON2
(n = 37)
GROUP effectPairwise comparisonsH/p -values
Verbal Memory−0.36/0.170.23/0.17−0.41/0.38−0.93/0.240.79/0.14H(4)=26.5
p<0.0001
SCZ vs. CON2−76.1/0.000
Digit Sequencing−0.39/0.12−0.07/0.110.26/0.36−1.07/0.200.62/0.17H(4)=35.5
p<0.0001
SCZ vs. FEP
SCZ vs. CHR
SCZ vs. CON2
66.9/0.003
38.6/0.036
−90.1/0.000
Token Motor Task−0.64/0.150.28/0.160.60/0.270.47/0.211.39/0.15H(4)=56.9
p<0.0001
SCZ vs. CHR
CHR vs. CON1
CHR vs. FEP
SCZ vs. CON2
46.9/0.004
−37.8/0.005
−54.5/0.006
−45.3/0.050
Verbal Fluency0.15/0.120.38/0.19−0.85/0.49−0.90/0.200.64/0.21H(4)=27.1
p<0.0001
SCZ vs. CHR
FEP vs. CON2
SCZ vs. CON2
52.0/0.001
−51.7/0.000
−73.3/0.000
Symbol Coding−0.04/0.140.62/0.16−0.96/0.27−1.19/0.23−0.26/0.15H(4)=46.6
p<0.0001
SCZ vs. CHR
FEP vs. CHR
SCZ vs. CON2
CHR vs. CON1
57.0/0.000
44.5/0.049
−48.0/0.030
−32.4/0.031
Tower of London0.18/0.120.28/0.100.51/0.24−0.19/0.210.85/0.13H(4)=15.0
p<0.0001
SCZ vs. CON2−76.1/0.000
COMPOSITE score−0.31/0.140.46/0.10−0.22/0.35−1.03/0.211.11/0.11H(4)=61.0
p<0.0001
SCZ vs. CON2
FEP vs. CON2
CHR vs. CON1
−111.3/0.000
−72.1/0.001
−38.5/0.004
PANSS (mean/SEM)FEP
(n = 16)
SCZ
(n = 30)
GROUP effect
Negative18.0/1.316.6/1.1not sign diff
Excitation9.4/0.87.2/0.7H(1)=6.1, p=0.013
Cognitive12.3/1.110.5/0.7not sign diff
Positive12.5/0.79.8/0.7H(1)=5.1, p=0.024
Depression14.8/1.112.2/0.6H(1)=3.9, p=0.047
TOTAL66.9/3.256.3/3.0H(1)=5.4, p=0.020
CAARMS (mean/SEM) *frequencyCHR (n = 88)SPI-A (n = 25)CAARMS (n = 29)BOTH(n = 34)GROUP effectPairwise comparisonsH/p -values
Unusual Thought Content5.2/0.83.6/1.43.9/1.17.6/1.3H(2)=6.8
p=0.033
not sign diff
Non-Bizarre Ideas9.9/0.85.6/1.19.7/1.413.3/1.3H(2)=14.3
p=0.001
SPI-A vs. SPI-A+CAARMS−25.2/0.000
Perceptual Abnormalities8.1/0.73.9/0.79.4/1.310.2/1.1H(2)=15.7
p<0.0001
SPI-A vs. SPI-A+CAARMS
SPI-A vs. SPI-A+CAARMS
−21.5/0.006
−25.2/0.000
Disorganized Speech4.3/0.63.8/0.92.1/0.86.5/0.9H(2)=11.9
p=0.003
CAARMS vs. SPI-A+CAARMS−20.8/0.002
TOTAL27.6/1.816.8/2.925.0/2.437.6/2.8H(2)=22.2
p<0.0001
SPI-A vs. SPI-A+CAARMS
CAARMS vs. SPI-A+CAARMS
−31.4/0.000
−17.4/0.021
Global Functioning (GAF: mean/SEM)CHR
(n = 88)
CON1
(n = 48)
GROUP effect
59.8/1.287.4/1.0H(1)=81.0, p<0.0001
MEDICATIONCHR
(n = 88)
CON1
(n = 48)
None3946
Anti-psychotic10
Mood-stabilizer10
Anti-depressant200
Anti-convulsant00
Other110
Multiple162
  1. *Kruskal-Wallis independent-sample test. Alpha-level 0.05, two-sided with p-values adjusted for ties.

    †Kruskal-Wallis independent-sample test performed on z-standardized data (Keefe et al., 2008). Alpha-level 0.05, two-sided, p-values adjusted for ties.

Table 2
Overview of AAL regions of significantly modulated resting-state low and high gamma-band power.
https://doi.org/10.7554/eLife.37799.004
Group contrastLabels of significant AAL regions*t-values (range)p-values (range)
Low GAMMA (30–46 Hz)
FEP vs CON2left Calcarine Fissure,
left Inferior Occipital Gyrus
2.82 to 3.800.002–0.006
right and left Superior Medial Frontal Gyrus,
right Middle Frontal Gyrus
−2.15 to −3.790.002–0.006
SCZ vs CON2right and left Superior Medial Frontal Gyrus,
right Middle Frontal Gyrus,
left Inferior Parietal Lobule,
left Superior Orbital Frontal Gyrus,
left Superior Temporal Gyrus,
left PostCentral Gyrus,
right PreCentral Gyrus
−2.35 to −4.240.002–0.006
High GAMMA (64–90 Hz)
CHR vs CON1left Middle Occipital Gyrus,
right and left Middle Frontal Gyrus,
left Angular Gyrus,
left Inferior Parietal Lobule
2.40 to 2.740.002–0.006
SPI-A only vs CON1No significant voxels
CAARMS only vs CON1left Middle Frontal Gyrus,
left Middle Occipital Gyrus
2.670.006
CAARMS + SPI A vs CON1right and left Middle Occipital Gyrus,
right and left Middle Frontal Gyrus.
left Angular Gyrus,
right Inferior Parietal Lobule, left Superior Medial Frontal Gyrus
2.16 to 3.430.002–0.006
FEP vs CON2right and left Calcarine Fissure, right and left Inferior Occipital Gyrus,
right and left Middle Occipital Gyrus,right and left PreCuneus,
left Inferior Frontal Gyrus,left Angular Gyrus
2.48 to 4.080.002–0.006
right Middle Frontal Gyrus−2.42 to −3.260.002–0.006
SCZ vs CON2right and left Superior Medial Frontal Gyrus,
left Superior Orbital Frontal Gyrus, left Middle Orbital Frontal Gyrus, left PostCentral Gyrus
−2.40 to −3.560.002–0.006
  1. *Non-parametric Monte-Carlo permutation based independent-sample tests, alpha-level 0.05, two-sided, FDR corrected voxels.

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