NeuralCipher Research overview
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Background: Healthy cognitive functioning is a primary component of well-being, independence, and successful aging. Cognitive deficits can arise from various conditions, such as brain injury, mental illness, and neurological disorders. Rehabilitation is a highly specialized service limited to patients who have access to institutional settings. In response to this unmet need, telehealth solutions are ideal for triggering the migration of care from clinics to patients' homes. Objectives: The aim of EARLY-COGN^3 will be threefold: (1) to test the efficacy of a digital health at-home intervention (tele@cognitive protocol) as compared to an unstructured cognitive at-home rehabilitation in a cohort of patients with Chronic Neurological Diseases (CNDs); (2) to investigate its effects on the biomolecular and neurophysiological marker hypothesizing that people with CNDs enrolled in this telerehabilitation program will develop changes in biological markers and cortical and subcortical patterns of connectivity; (3) to analyze potential cognitive, neurobiological, and neurophysiological predictors of response to the tele@cognitive treatment. Method: In this single-blind, randomized, and controlled pilot study, we will assess the short- and long-term efficacy of cognitive telerehabilitation protocol (tele@cognitive) as compared to an unstructured cognitive at-home rehabilitation (Active Control Group-ACG) in a cohort of 60 people with Mild Cognitive Impairment (MCI), Subjective Cognitive Complaints (SCCs), or Parkinson's Disease (PD). All participants will undergo a clinical, functional, neurocognitive, and quality of life assessment at the baseline (T0), post-treatment (5 weeks, T1), and at the 3-month (T2) follow-up. Neurophysiological markers and biomolecular data will be collected at T0 and T1. Conclusions: EARLY-COGN^3 project could lead to a complete paradigm shift from the traditional therapeutic approach, forcing a reassessment on how CNDs could take advantage of a digital solution. (clinicaltrials.gov database, ID: NCT06657274).
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