## 4 Conclusions  
Research in the field of MNs has advanced in the past years. However, the findings with respect to ASD and schizophrenia do not reach a consensus with respect to the functionality of this set of neurons and/or the validity of the theories around it. Mirror neurons are a class of neurons that fire both during the performance of an action or action observation, and have considerable impact on the individuals' social cognition skills, including imitation, empathy, intention, emotion recognition and Theory of Mind. In both ASD and schizophrenia, research has shown that the MNS may be dysfunctional, indicating abnormal activation and impaired perception of motion activity, which has in turn detrimental effects on the social cognitive skills of the individuals. On the other hand, the two disorders differ markedly in terms of the neural abnormalities they demonstrate, despite the shared social cognitive deficits that are often linked to MN dysfunction. In individuals with ASD, MN dysfunction is frequently associated with reduced \(mu\) rhythm suppression during both action observation and execution tasks, suggesting impaired resonance mechanisms that may hinder the development of imitation and Theory of Mind [63]. By contrast, schizophrenia patients may exhibit more variable MN responses; while some studies show preserved \(mu\) suppression, others report reduced MN activity specifically in relation to negative symptoms and disrupted intention attribution [72,76]. This dissociation may reflect differences in the timing and nature of the neurodevelopmental disruptions that occur in the two conditions: in ASD, MNS anomalies often emerge early and are relatively stable, whereas in schizophrenia, they may develop later and interact with broader network dysfunctions, such as impaired salience attribution and executive functioning. Moreover, compensatory mechanisms such as attentional engagement, may differentially influence MN responses in each disorder [62]. The MN hypothesis, which posits that dysfunctions in the MNS underlie the social and communicative deficits observed in ASD and schizophrenia, has garnered significant attention but remains highly controversial. Initial support for the hypothesis stemmed from findings of reduced \(mu\) suppression in individuals with ASD, which was interpreted as a manifestation of impaired MNS activity [77]. However, subsequent research has challenged this interpretation, suggesting that such findings may be confounded by atypical attentional engagement rather than specific MNS dysfunctions [84]. Moreover, alternative models posit that deficits in ASD and schizophrenia may instead reflect broader disruptions in large-scale neural networks, such as the default mode or salience networks, which are crucial for social cognition [85,86]. In schizophrenia, for instance, impaired social cognition has been linked to dysfunctional connectivity in frontotemporal and limbic circuits, rather than isolated MN abnormalities [87]. Research also suggests that observed MNS abnormalities may instead be secondary to deficits in visual attention. With respect to ASD, studies have indicated that reduced \(mu\) suppression during biological motion perception correlates with decreased visual attention, as measured by eye-tracking metrics. This suggests that attentional factors, rather than intrinsic MNS dysfunction, may underlie observed neural differences in ASD [62]. Similarly, in schizophrenia, impairments in social attention and deficits in processing salient stimuli have been found to influence neural responses during action observation tasks [88], raising questions about the specificity of the MNS dysfunction. This counter-evidence underscores the necessity of cautiously interpreting MNS -related findings, and further advocates for a more integrative, network-based approach to understanding social deficits in neurodevelopmental and psychiatric disorders. Table 3 illustrates the supporting and opposing evidence of the \"broken\" MN hypothesis as explored by the studies reviewed in this paper: