## 3 The Mechanisms Behind Broken MNs in ASD and Schizophrenia
### Methodological Limitations and Strengths of the Included Studies  
The selected studies that have investigated the MNS function in ASD and schizophrenia present a range of methodological strengths and limitations, particularly concerning the EEG protocols, sample sizes, and statistical rigor. [PERSON] et al. [59] employed high-density EEG with appropriate artifact correction to localize motor interference effects in high-functioning ASD, but their modest sample size (\(n\approx 20\) per group) limits generalisability of findings and statistical power. [PERSON] et al. 's [60] study lacked detailed reporting on EEG preprocessing parameters, raising concerns about the reproducibility of the findings and signal quality, however, the particular study has been notable for combining behavioural and EEG measures to argue against the MNS dysfunction in ASD. [PERSON] et al. 's [62] methodological design represents a methodological advance by integrating eye-tracking with EEG to control for visual attention, which has been a critical confound in MNS research, however, the relatively large dataset would benefit from more transparent reporting of effect sizes and corrections for multiple comparisons. Finally, [PERSON] et al. [63] demonstrated methodological rigor through the integration of EEG and TMS, offering multimodal evidence for intact MNS activity in ASD. Nevertheless, the small sample sizes and the complexity of dual-modality analyses introduce further potential noise and interpretation challenges. With respect to the studies that have investigated the MNS in schizophrenia, [PERSON] et al. [72] applied a well-established _mu_ rhythm suppression paradigm, and included a healthy control group enhancing interpretability. Crucially, their moderate sample size and lack of detailed artifact rejection procedures may limit replicability. [PERSON] et al. [73] contributed valuable cross-cultural data using EEG to examine _mu_ rhythm suppression activity in schizophrenia, but their relatively small and clinically heterogeneous sample, along with limited statistical correction for multiple comparisons, weakens the robustness of their findings. [PERSON] et al. [76] demonstrated methodological strength by comparing both early psychosis (EP) and ASD participants, yet the EEG analysis focused narrowly on sensor-level _mu_ rhythm suppression without source localization, potentially reducing neuroanatomical specificity. [PERSON] et al. [81] incorporated both fMRI and EEG measures, offering a multimodal perspective on empathy and the MNS function in schizophrenia; nevertheless, their modest sample and the limited temporal resolution of fMRI reduced the study's capacity to link neural activity directly to mirroring processes. Finally, [PERSON] et al. [82] employed a pharmacological intervention design using oxytocin, and incorporated neurophysiological measures to examine social processing, showcasing innovative methodology. Nonetheless, EEG outcomes were secondary to the pharmacological aims, and the study lacked _mu_ rhythm-specific analyses, making their study less directly informative about the MNS function. Collectively, while these studies provide valuable insights into _mu_ rhythm suppression activity and its link to socio-cognitive deficits in ASD and schizophrenia, future work would benefit from larger cohorts, standardized EEG processing pipelines, and robust statistical corrections to improve replicability and validity.