STXBP1 Syndrome Is Characterized by Inhibition-Dominated Dynamics of Resting-State EEG

Figures

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  Figure 1. Demographics, electrode positioning and mutation details. (A) Recordings of STXBP1 syndrome patients (n = 14) were collected from three recording sites. Recordings from Denmark were collected retrospectively, whereas recordings from Italy and the Netherlands were performed prospectively for this study. Typically developing children (TDC, n = 50), were collected from SPACE/BAMBI programs from UMC Utrecht (n = 29) and University of Amsterdam (n = 21). (B) Electrode map for selected 19 channels of 10–20 system. (C) Genetic mutations of STXBP1 syndrome patients indicated in the primary sequence (top) and crystal structure of the STXBP1/Munc18-1-syntaxin1 dimer (Misura et al., 2000; bottom). The three domains in the MUNC18-1 protein are indicated in three shades of blue. The white protein structure is the STXBP1/Munc18-1 binding partner Syntaxin1. In the primary sequence, the mutations are indicated as the nucleotide numbers (starting at 1 at the ATG start site) and the alterations in nucleotides. Inserted nucleotides (causing frame shift) are indicated with a plus symbol, intronic positions are indicated as the position relative to the exon, using a minus or plus sign, deletions are…

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  Figure 2. Higher low-frequency power in STXBP1 syndrome. (A) EEG records oscillations with power varying across frequency. (B) The power spectrum was computed using the Welch method with a Hamming window and a frequency resolution of 0.125 Hz. A typical example of a TDC with a clear 10-Hz alpha peak is shown. (C) Whole-brain average power spectrum of TDC and STXBP1 syndrome show higher power in the range 1.75–4.63 Hz in STXBP1 syndrome. ANCOVA was performed per frequency bin in the range 1–45 Hz and Bonferroni-corrected across the 353 frequency bins (p<.05353, black bars). Shaded areas show standard error of the mean (SEM). (D–F) Scalp topography of power averaged across 1.75–4.63 Hz for TDC (D), STXBP1 syndrome (E) and STXBP1 syndrome minus TDC (F). Low-frequency power is higher in STXBP1 syndrome at all electrodes. Solid white circles: p-values of factor group of the ANCOVA with age as a covariate, Bonferroni-corrected by the number of electrodes, p<.0519. (G) Whole-brain average power within the range 1.75–4.63 Hz was increased for STXBP1 syndrome.

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  Figure 3. Stronger long-range temporal correlations in STXBP1 syndrome. (A) The DFA exponent is the slope of the log–log linear fits shown, and was used to quantify long-range temporal correlations of brain oscillations. The fit is shown for a typical TDC and STXBP1 syndrome patient. The y-axis of the STXBP1 syndrome patient (blue axis) has been offset to highlight the difference in the DFA exponent compared with TDC. (B) DFA spectrum in the range 1–45 Hz shows higher DFA exponents for STXBP1 syndrome in the range 11–18 Hz, indicating stronger LRTC. Black bars: Bonferroni-corrected across frequencies, p<.0544. Confidence intervals show SEM. The spectrum shows the average DFA exponent across subjects and electrodes. (C) DFA difference spectrum, computed as STXBP1 syndrome minus TDC. (D–F) Scalp topographies of DFA exponents averaged in the range 11–18 Hz for TDC (D), STXBP1 syndrome (E), and for STXBP1 syndrome minus TDC (F). DFA was higher for STXBP1 syndrome across the cortex. White circles indicate significance based on p-values of factor group of the ANCOVA with age as a covariate; open white-circles: p < 0.05; solid white circles: Bonferroni-corrected,p<.0519. (G) Whole-brain average…

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  Figure 4. Inhibition-dominated network dynamics in STXBP1 syndrome. (A) Relationship between E/I ratio, DFA, and amplitude in the Critical Oscillations (CROS) model, adapted from Bruining et al. (2020) with permission. An inhibition-dominated regime is characterized by fE/I < 1, an excitation-dominated state fE/I > 1, and fE/I ≈ 1 corresponds to an E/I-balanced network state. Here, fE/I was computed in frequency bins of 1 Hz in the range 1–45 Hz, resulting in an fE/I spectrum to investigate potential frequency-specificity of E/I-imbalanced network activity. (B–D) From a technical perspective, fE/I quantifies the covariance between amplitude and a normalized fluctuation function that approximates the DFA exponent of brain oscillations (Bruining et al., 2020). Example signals of a TDC and patient with STXBP1 syndrome for electrode Pz, FIR-filtered for 14–15 Hz (B) and the corresponding Pearson correlation between amplitude and normalized fluctuations (C,D). fE/I is computed as 1 minus this correlation. (E) fE/I spectrum in the range 1–45 Hz averaged across subjects and electrodes shows lower fE/I in the range 12–24 Hz in STXBP1 syndrome. Black bars: Bonferroni-corrected across frequencies,…

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  Figure 5. Larger aperiodic exponents in STXBP1 syndrome. (A) The FOOOF algorithm was used to estimate the β exponent of the 1/fβ aperiodic component of the power spectrum in the range 1–30 Hz (blue dashed line). (B) Comparison of aperiodic components at channel Pz averaged across participants for TDC and STXBP1 syndrome. Aperiodic offset and exponent were used to reconstruct an ‘aperiodic-only’ spectrum where oscillatory peaks were removed. Shaded areas show standard error of the mean (SEM). (C–E) Scalp topographies of the aperiodic exponents in TDC (C), in STXBP1 syndrome (D), and STXBP1 syndrome minus TDC (E). The larger aperiodic exponent in STXBP1 syndrome compared to TDC was significant at all electrodes (solid white circles: p-values from factor group of the ANCOVA with age as a covariate, Bonferroni-corrected across electrodes, p<.0519). (F) Individual whole-brain average exponents show larger exponents in STXBP1 syndrome.

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  Figure 6. Correlations of EEG parameters with clinical scales. For the STXBP1 syndrome patients with clinical scores of motor-symptom severity, we computed a partial correlation (ρ) between clinical scales and (A) power (1.75–4.63 Hz), (B) DFA (11–18 Hz), (C) fE/I (12–24 Hz), and (D) aperiodic exponent (1–30 Hz), while controlling for the effect of age. Clinical scales were Gross-Motor Functional Classification System (GMFCS, n = 12), Manual Ability Classification System (MACS, n = 10) and Communication Functional Classification System (CFCS, n = 12). Open white-circles indicate p < 0.05, solid white circles indicate significance after Bonferroni correction for the number of channels, p<.0519).