Background and Objectives: Meditation and mindfulness, rooted in ancient traditions, enhance mental well-being by cultivating awareness and emotional control. It has been shown to induce neuroplasticity, increase cortical thickness, reduce amygdala reactivity, and improve brain connectivity and neurotransmitter levels, leading to improved emotional regulation, cognitive function, and stress resilience. This systematic review will synthesize research on neurobiological changes associated with mindfulness and meditation practices. Materials and Methods: Studies were identified from an online search of PubMed, Web of Science, Cochrane Library, and Embase databases without any search time range. This review has been registered on Open OSF (n) GV2JY. Results: Mindfulness-Based Stress Reduction (MBSR) enhances brain regions related to emotional processing and sensory perception, improves psychological outcomes like anxiety and depression, and exhibits unique mechanisms of pain reduction compared to placebo. Conclusions: This review highlights that mindfulness, particularly through MBSR, improves emotional regulation and brain structure, reduces anxiety, and enhances stress resilience. Future research should focus on diverse populations and naturalistic settings to better understand and optimize these benefits.

Background and Objectives: Neurological disorders like stroke, spinal cord injury (SCI), and Parkinson’s disease (PD) significantly affect global health, requiring accurate diagnosis and long-term neurorehabilitation. Artificial intelligence (AI), such as machine learning (ML), may enhance early diagnosis, personalize treatment, and optimize rehabilitation through predictive analytics, robotic systems, and brain-computer interfaces, improving outcomes for patients. This systematic review examines how AI and ML systems influence diagnosis and treatment in neurorehabilitation among neurological disorders. Materials and Methods: Studies were identified from an online search of PubMed, Web of Science, and Scopus databases with a search time range from 2014 to 2024. This review has been registered on Open OSF (n) EH9PT. Results: Recent advancements in AI and ML are revolutionizing motor rehabilitation and diagnosis for conditions like stroke, SCI, and PD, offering new opportunities for personalized care and improved outcomes. These technologies enhance clinical assessments, therapy personalization, and remote monitoring, providing more precise interventions and better long-term management. Conclusions: AI is revolutionizing neurorehabilitation, offering personalized, data-driven treatments that enhance recovery in neurological disorders. Future efforts should focus on large-scale validation, ethical considerations, and expanding access to advanced, home-based care.

Neuroplasticity and neuroinflammation are variables seen during recovery from traumatic brain injury (TBI), while biomarkers are useful in monitoring injury and guiding rehabilitation efforts. This systematic review examines how neuroinflammation affects neuroplasticity and recovery following TBI in animal models and humans. Studies were identified from an online search of the PubMed, Web of Science, and Embase databases without any search time range. This review has been registered on Open OSF (n) UDWQM. Recent studies highlight the critical role of biomarkers like serum amyloid A1 (SAA1) and Toll-like receptor 4 (TLR4) in predicting TBI patients’ injury severity and recovery outcomes, offering the potential for personalized treatment and improved neurorehabilitation strategies. Additionally, insights from animal studies reveal how neuroinflammation affects recovery, emphasizing targets such as NOD-like receptor family pyrin domain-containing 3 (NLRP3) and microglia for enhancing therapeutic interventions. This review emphasizes the central role of neuroinflammation in TBI, and its adverse impact on neuroplasticity and recovery, and suggests that targeted anti-inflammatory treatments and biomarker-based personalized approaches hold the key to improvement. Such approaches will need further development in future research by integrating neuromodulation and pharmacological interventions, along with biomarker validation, to optimize management in TBI.

Chronic disorders of consciousness cause a total or partial and fluctuating unawareness of the surrounding environment. Virtual reality (VR) can be useful as a diagnostic and/or a neurorehabilitation tool, and its effects can be monitored by means of both clinical and electroencephalography (EEG) data recording of brain activity. We reported on the case of a 17-year-old patient with a disorder of consciousness (DoC) who was provided with VR training to improve her cognitive-behavioral outcomes, which were assessed using clinical scales (the Coma Recovery Scale-Revised, the Disability Rating Scale, and the Rancho Los Amigos Levels of Cognitive Functioning), as well as EEG recording, during VR training sessions. At the end of the training, significant improvements in both clinical and neurophysiological outcomes were achieved. Then, we carried out a systematic review of the literature to investigate the role of EEG and VR in the management of patients with DoC. A search on PubMed, Web of Science, Scopus, and Google Scholar databases was performed, using the keywords: “disorders of consciousness” and “virtual reality”, or “EEG”. The results of the literature review suggest that neurophysiological data in combination with VR could be useful in evaluating the reactions induced by different paradigms in DoC patients, helping in the differential diagnosis. In conclusion, the EEG plus VR approach used with our patient could be promising to define the most appropriate stimulation protocol, so as to promote a better personalization of the rehabilitation program. However, further clinical trials, as well as meta-analysis of the literature, are needed to be affirmative on the role of VR in patients with DoC.