Mental Imagery (MI), the ability to see with the mind's eyes, is related to autobiographical memory deficits in Alzheimer's disease (AD). Furthermore, preliminary data show a deficit in MI ability also in the prodromal dementia stage (i.e. Mild Cognitive Impairment-MCI). The hippocampus, affected by AD neuropathology since early stages, plays a pivotal contribution to the recollection of previous memories in service of MI; this could explain the MI deficit in MCI. Based on the current model of MI and findings that the various processes and contents of MI decline differently in physiological and pathological ageing, SeeD objectives are three-folded: clinically, SeeD aimed to (1) investigate the presence of MI deficit to confirm preliminary data in a larger sample of MCI and (2) to evaluate the reliability of MI assessment as an early neuropsychological marker of dementia, employing a computerized assessment that could be a feasible instrument to be implemented into a telemedicine platform; theoretically SeeD results (3) could provide new insight into the cognitive model of MI through the investigation of such ability in a pathological population that could be considered a clinical model to test cognitive one.
SeeD's results will provide both theoretical and clinical insights. From a theoretical point of view, SeeD's results could be helpful in disentangling the role of perceptive abilities in MI, challenged by recent neuroimaging findings in healthy subjects. On the other hand, they could have important clinical applications. The number of patients with dementia is going to nearly triple every 20 years, reaching 152 million by 2050 (World Alzheimer Report 2018). MI deficits are described in AD patients. SeeD, investigating MI skills in a longitudinal perspective and taking into account different MI contents and processes (in terms of both accuracy and time response), could disclose new insight into the neuropsychological markers of dementia. As mentioned above, investigating the predictive accuracy of cognitive assessment has important clinical applications because neuropsychological assessments are easily available in the clinical setting and relatively low-cost as compared with biomarkers. Furthermore, investigating the predictive accuracy of MI will inform future studies aimed at integrating multiple markers (i.e cognitive, neurological etc) in a predictive model that could take into account the complexity of the neurodegenerative disease.
Finally, the recent pandemic situation highlighted the importance of telemedicine, in other words of the possibility to reach and provide health services to everyone, limiting costs both for patients and for the health service. The use of a computerized MI assessment software could be useful to be administered also to people that can't reach healthy service specialized in the early diagnosis of dementia, and/or could be useful to identify, with reducing cost, people at risk to develop dementia who require further diagnostic investigation.