Alpha oscillations (7–13 Hz) are the dominant rhythm in both the resting and active brain. Accordingly, translational research has provided evidence for the involvement of aberrant alpha activity in the onset of symptomatological features underlying syndromes such as autism, schizophrenia, major depression, and Attention Deficit and Hyperactivity Disorder (ADHD). However, findings on the matter are difficult to reconcile due to the variety of paradigms, analyses, and clinical phenotypes at play, not to mention recent technical and methodological advances in this domain. Herein, we seek to address this issue by reviewing the literature gathered on this topic over the last ten years. For each neuropsychiatric disorder, a dedicated section will be provided, containing a concise account of the current models proposing characteristic alterations of alpha rhythms as a core mechanism to trigger the associated symptomatology, as well as a summary of the most relevant studies and scientific contributions issued throughout the last decade. We conclude with some advice and recommendations that might improve future inquiries within this field.

Accurate outcome detection in neuro-rehabilitative settings is crucial for appropriate long-term rehabilitative decisions in patients with disorders of consciousness (DoC). EEG measures derived from high-density EEG can provide helpful information regarding diagnosis and recovery in DoC patients. However, the accuracy rate of EEG biomarkers to predict the clinical outcome in DoC patients is largely unknown. This study investigated the accuracy of psychophysiological biomarkers based on clinical EEG in predicting clinical outcomes in DoC patients. To this aim, we extracted a set of EEG biomarkers in 33 DoC patients with traumatic and nontraumatic etiologies and estimated their accuracy to discriminate patients’ etiologies and predict clinical outcomes 6 months after the injury. Machine learning reached an accuracy of 83.3% (sensitivity = 92.3%, specificity = 60%) with EEG-based functional connectivity predicting clinical outcome in nontraumatic patients. Furthermore, the combination of functional connectivity and dominant frequency in EEG activity best predicted clinical outcomes in traumatic patients with an accuracy of 80% (sensitivity = 85.7%, specificity = 71.4%). These results highlight the importance of functional connectivity in predicting recovery in DoC patients. Moreover, this study shows the high translational value of EEG biomarkers both in terms of feasibility and accuracy for the assessment of DoC.

Coordinated interactions between the central and autonomic nervous systems are crucial for survival due to the inherent propensity for human behavior to make errors. In our ever-changing environment, when individuals make mistakes, these errors can have life-threatening consequences. In response to errors, specific reactions occur in both brain activity and heart rate to detect and correct errors. Specifically, there are two brain-related indicators of error detection and awareness known as error-related negativity and error positivity. Conversely, error-related cardiac deceleration denotes a momentary slowing of heart rate following an error, signaling an autonomic response. However, what is the connection between the brain and the heart during error processing? In this review, we discuss the functional and neuroanatomical connections between the brain and heart markers of error processing, exploring the experimental conditions in which they covary. Given the current limitations of available data, future research will continue to investigate the neurobiological factors governing the brain-heart interaction, aiming to utilize them as combined markers for assessing cognitive control in healthy and pathological conditions.

A harmonic brain-body communication is fundamental to individual wellbeing and is the basis of human cognition and behavior. In the last 2 decades, the interaction between the brain and body functioning has become a central area of study for neurologists and neuroscientists in clinical and non-clinical contexts. Indeed, brain-body axis dysfunctions occur in many psychiatric, neurological and neurodegenerative diseases. This editorial will focus on recent advances and future therapeutic perspectives for studying brain-body interactions in health and diseases.