The differentiated effect of the task complexity on retention and transfer of stroke survivors

NeuroAIreh@b: an artificial intelligence-based methodology for personalized and adaptive neurorehabilitation

Cognitive impairments are a prevalent consequence of acquired brain injury, dementia, and age-related cognitive decline, hampering individuals' daily functioning and independence, with significant societal and economic implications. While neurorehabilitation represents a promising avenue for addressing these deficits, traditional rehabilitation approaches face notable limitations. First, they lack adaptability, offering one-size-fits-all solutions that may not effectively meet each patient's unique needs. Furthermore, the resource-intensive nature of these interventions, often confined to clinical settings, poses barriers to widespread, cost-effective, and sustained implementation, resulting in suboptimal outcomes in terms of intervention adaptability, intensity, and duration. In response to these challenges, this paper introduces NeuroAIreh@b, an innovative cognitive profiling and training methodology that uses an AI-driven framework to optimize neurorehabilitation prescription. NeuroAIreh@b effectively bridges the gap between neuropsychological assessment and computational modeling, thereby affording highly personalized and adaptive neurorehabilitation sessions. This approach also leverages virtual reality-based simulations of daily living activities to enhance ecological validity and efficacy. The feasibility of NeuroAIreh@b has already been demonstrated through a clinical study with stroke patients employing a tablet-based intervention. The NeuroAIreh@b methodology holds the potential for efficacy studies in large randomized controlled trials in the future.

Does Cognitive Impairment Impact Motor Learning? A Scoping Review of Elderly Individuals With Alzheimer's Disease and Mild Cognitive Impairment

Individuals with cognitive impairment may have motor learning deficits due to the high engagement of cognitive mechanisms during motor skill acquisition. We conducted a scoping review to address the quality of current research on the relationship between cognitive impairments (i.e., deficits in attention, memory, planning and executive functions) and motor learning among older adults with Alzheimer's Disease or Mild Cognitive Impairment. After screening thousands of articles, we selected 15 studies describing cognitive assessment tools, experimental designs, and the severity of cognitive impairment. Although seven studies reported that cognitive impairment impaired motor learning, most studies included a high risk of bias. We identified multiple assessment tools across these studies that make comparisons among findings difficult. Future research in this area should focus on the influence of increased practice days during motor learning acquisition and incorporate both retention and transfer tests. Cognitive assessments should target the specific cognitive skills or deficits most closely related to the motor learning process.