Elderly people affected by Mild Cognitive Impairment (MCI) usually report a perceived decline in cognitive functions that deeply impacts their quality of life. This subtle waning, although it cannot be diagnosable as dementia, is noted by caregivers on the basis of their relative’s behaviors. Crucially, if this condition is also not detected in time by clinicians, it can easily turn into dementia. Thus, early detection of MCI is strongly needed. Classical neuropsychological measures – underlying a categorical model of diagnosis - could be integrated with a dimensional assessment approach involving Virtual Reality (VR) and Artificial Intelligence (AI). VR can be used to create highly ecologically controlled simulations resembling the daily life contexts in which patients’ daily instrumental activities (IADL) usually take place. Clinicians can record patients’ kinematics, particularly gait, while performing IADL (Digital Biomarkers). Then, Artificial Intelligence employs Machine Learning (ML) to analyze them in combination with clinical and neuropsychological data. This integrated computational approach would enable the creation of a predictive model to identify specific patterns of cognitive and motor impairment in MCI. Therefore, this new dimensional cognitive-behavioral assessment would reveal elderly people’s neural alterations and impaired cognitive functions, typical of MCI and dementia, even in early stages for more time-sensitive interventions.

Unilateral spatial neglect (USN) is a frequent repercussion of a cerebrovascular accident, typically a stroke. USN patients fail to orient their attention to the contralesional side to detect auditory, visual, and somatosensory stimuli, as well as to collect and purposely use this information. Traditional methods for USN assessment and rehabilitation include paper-and-pencil procedures, which address cognitive functions as isolated from other aspects of patients’ functioning within a real-life context. This might compromise the ecological validity of these procedures and limit their generalizability; moreover, USN evaluation and treatment currently lacks a gold standard. The field of technology has provided several promising tools that have been integrated within the clinical practice; over the years, a “first wave” has promoted computerized methods, which cannot provide an ecological and realistic environment and tasks. Thus, a “second wave” has fostered the implementation of virtual reality (VR) devices that, with different degrees of immersiveness, induce a sense of presence and allow patients to actively interact within the life-like setting. The present paper provides an updated, comprehensive picture of VR devices in the assessment and rehabilitation of USN, building on the review of Pedroli et al. (2015). The present paper analyzes the methodological and technological aspects of the studies selected, considering the issue of usability and ecological validity of virtual environments and tasks. Despite the technological advancement, the studies in this field lack methodological rigor as well as a proper evaluation of VR usability and should improve the ecological validity of VR-based assessment and rehabilitation of USN.

Background: Cognitive-motor dual-task (CMDT) is defined as the parallel processing of motor (eg, gait) and cognitive (eg, executive functions) activities and is an essential ability in daily life. Older adults living with frailty, chronic conditions (eg, neurodegenerative diseases), or multimorbidity pay high costs during CMDT. This can have serious consequences on the health and safety of older adults with chronic age-related conditions. However, CMDT rehabilitation can provide useful and effective therapies for these patients, particularly if delivered through technological devices. Objective: This review aims to describe the current technological applications, CMDT rehabilitative procedures, target populations, condition assessment, and efficacy and effectiveness of technology-assisted CMDT rehabilitation in chronic age-related conditions. Methods: We performed this systematic review, following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, on 3 databases (Web of Science, Embase, and PubMed). Original articles that were published in English; involved older adults (>65 years) with ≥1 chronic condition and/or frailty; and tested, with a clinical trial, a technology-assisted CMDT rehabilitation against a control condition were included. Risk of bias (Cochrane tool) and the RITES (Rating of Included Trials on the Efficacy-Effectiveness Spectrum) tool were used to evaluate the included studies. Results: A total of 1097 papers were screened, and 8 (0.73%) studies met the predefined inclusion criteria for this review. The target conditions for technology-assisted CMDT rehabilitation included Parkinson disease and dementia. However, little information regarding multimorbidity, chronicity, or frailty status is available. The primary outcomes included falls, balance, gait parameters, dual-task performance, and executive functions and attention. CMDT technology mainly consists of a motion-tracking system combined with virtual reality. CMDT rehabilitation involves different types of tasks (eg, obstacle negotiation and CMDT exercises). Compared with control conditions, CMDT training was found to be pleasant, safe, and effective particularly for dual-task performances, falls, gait, and cognition, and the effects were maintained at midterm follow-up. Conclusions: Despite further research being mandatory, technology-assisted CMDT rehabilitation is a promising method to enhance motor-cognitive functions in older adults with chronic conditions.

Background: Several studies suggested that anxiety can significantly affect the outcome of schizophrenia. Despite this evidence, non-pharmacological interventions targeting anxiety are still heterogenous. This study aims to test the efficacy of a novel training specifically designed to target anxiety in patients with schizophrenia. Innovatively, this training, beyond psychoeducation and problem solving, also targets Theory of Mind, as it provides coping strategies.Method: Twenty-seven outpatients with schizophrenia received a novel rehabilitative training targeting anxiety (Anxiety Management Group [AMG]) combined with a Computer-Assisted Cognitive Remediation (CACR), and twenty received CACR plus a control intervention (Control Newspaper discussion Group [CNG]). All patients were assessed at baseline and after treatment for quality of life, neurocognition and anxiety.Results: After training, patients treated with AMG + CACR showed significantly greater improvements on anxiety. A significant increase in quality of life was observed only for AMG + CACR group. Moreover, the participants’ appraisal showed a significant difference between treatment groups with higher ratings among patients who received the AMG + CACR.Conclusions: This study thus suggests feasibility and efficacy of the proposed intervention, that could be implemented in rehabilitative programs for patients with schizophrenia with potential benefits also on disease course and outcome.

The aim of this perspective is to propose and discuss the integration of transcranial magnetic stimulation (TMS) over the dorsolateral prefrontal cortex with virtual reality (VR) food exposure for therapeutic interventions for food addiction. “Food addiction” is a dysfunctional eating pattern which is typically observed in eating disorders (ED) such as bulimia nervosa and binge eating disorder. Food addiction has been compared to substance use disorder due to the necessity of consuming a substance (food) and the presence of a dependence behavior. In recent years, VR has been applied in the treatment of ED because it triggers psychological and physiological responses through food exposure in place of real stimuli. Virtual reality-Cue exposure therapy has been proven as a valid technique for regulating anxiety and food craving in ED. More, TMS has been proven to modulate circuits and networks implicated in neuropsychiatric disorders and is effective in treating addiction such as nicotine craving and consumption and cocaine use disorder. The combination of a simulative technology and a neurostimulation would presumably provide better improvement compared to a single intervention because it implies the presence of both cognitive and neuropsychological techniques. The possible advantage of this approach will be discussed in the perspective.