Could EEG be a translational biomarker in neurodevelopmental conditions? - Studies in mouse models of idiopathic and syndromic autism
Bibliographic record
Abstract
Background: Autism is predominantly idiopathic, while many syndromic forms have also been identified. Fragile X Syndrome (FXS) is the most common syndromic form of autism and intellectual disability. No effective approaches currently exist for reducing the negative impact of autism or FXS symptoms, and drug development has suffered many failures in clinical trials, which were based on promising preclinical findings. Thus, effective translational biomarkers that bridge animal and human studies are urgently needed. Both autism and FXS are developmentally dynamic and sexually dimorphic regarding prevalence, clinical presentations and neural mechanisms. Recently, electroencephalography (EEG) has been proposed as a low-cost translational biomarker in neurodevelopmental conditions. However, there is still a dearth of EEG research in autism, especially in research using animal models. Hypothesis: EEG profiles in mouse models of idiopathic and syndromic autism vary depending on sex, age, and genetic background. Methods: We compared the BTBR model of idiopathic autism with the control B6 mice, as well as the fmr1 knockout model of FXS and syndromic autism with the control wildtype mice. A custom-made stand-alone Open-Source Electrophysiology Recording system for Rodents (OSERR) was used for EEG recording. Results: We found absolute EEG power in the beta and gamma frequency bands was increased in juvenile male BTBR mice, while relative theta power was increased and relative alpha power decreased. In the FXS model on a FVB genetic background, we confirmed previous findings of an increase in the absolute gamma power in the male mice. Detailed analysis in the females indicated that in both juvenile and adult animals, increases in the alpha and beta power were present besides an increase in the gamma power, compared with age-matched wildtype controls. Additionally, both wildtype and FXS model had increased absolute and relative gamma power in adult females compared with juvenile females. Furthermore, we analyzed phase-amplitude cross frequency coupling between gamma frequency (30–100 Hz) and theta-alpha frequency (4–12 Hz), to quantify the modulation of gamma oscillation amplitude by the phase of the theta-alpha frequency. Our results indicated that this phase-amplitude coupling was increased in the female FXS model, similar to the findings in the FXS patients. Additionally, both wildtype and FXS model had increased coupling in adult females compared with juvenile females. We also recorded EEG in the female FXS model on a B6 genetic background and observed that relative EEG power was deceased in alpha frequency but increased in gamma frequency, while phase-amplitude coupling was similar, compared with wildtype controls. Lastly, we observed that these EEG phenotypes were stable when recorded in different arenas, including home cage, open field arena, and light-dark arena, for all female groups tested. Discussion and Conclusion: Together, our findings revealed a consistent and robust increase in the gamma power in mouse models of both idiopathic and syndromic autism, and this includes female FXS models. In addition, we identified changes in the EEG signal that depended on sex, developmental stage, and genetic background. Collectively, our findings support further investigation of EEG signal as translational biomarkers in neurodevelopmental conditions, while factors including sex, developmental stage, and genetic background should be incorporated into the design and interpretation of such studies. University of Calgary Veterinary Medicine, Alberta Children's Hospital Research Foundation, FRAXA Research Foundation, NSERC of Canada, CIHR of Canada, Alberta Student Aid This abstract was presented at the American Physiology Summit 2025 and is only available in HTML format. There is no downloadable file or PDF version. The Physiology editorial board was not involved in the peer review process.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".