Self-disorders are increasingly seen as the root cause of schizophrenia, not merely a symptom. This aligns with philosophical views of an enactive self, formed through action and interaction. The authors analyze definitions of the self and evaluate computational theories, particularly Bayesian and predictive processing approaches, for modeling the active self. They assess the implementation and challenges of these models in computational psychiatry and cognitive developmental robotics. Embodied robotic systems are described as valuable tools for assessing, validating, and simulating mechanisms of self-disorders, especially those involving sensorimotor learning, prediction, and self-other distinction. This link offers insights into self-formation and new avenues for treating psychiatric disorders.
Expert meditators show a lower decision threshold rather than higher accuracy in detecting near-threshold tactile stimuli, compared to non-meditators who read regularly. Electroencephalography revealed reduced prestimulus alpha power in meditators, suggesting enhanced alpha modulation. A trial-by-trial analysis found a negative correlation between prestimulus alpha activity and tactile perception. Meditators also reported greater interoceptive sensibility, less emotional suppression, and fewer difficulties describing feelings. These findings suggest that enhanced tactile perception in meditators may stem from reduced sensory filtering in the somatosensory cortex, increasing response rates without improving accuracy.