It is shown that the circadian system is affected in patients with Alzheimer's disease (AD) even at an early stage of the disease and that such dysfunction may be detrimental to sleep, mood, and cognitive functioning. Light is a strong central modulator of the circadian rhythms and is potentially beneficial to mood and cognitive functioning via a direct effect or indirectly via its modulating effects on circadian rhythms. This study focuses on tracking the effect of light therapy on sleep quality, mood, and cognition in AD of mild/moderate severity. We performed a single-blind randomized controlled trial to investigate the effects of a light therapy treatment tailored to the individual circadian phase as measured by dim light melatonin onset (DLMO). Such a treatment induced an objective circadian phase shift consistent with the melatonin phase response curve to light exposure, led to a shortening of the phase angle DLMO-falling asleep time, and was associated with an improvement in subjective sleep quality and cognitive performance.

Background: Given the limited effectiveness of pharmacological treatments for cognitive decline, non-pharmacological interventions have gained increasing attention. Evidence exists on the effectiveness of cognitive rehabilitation in preventing elderly subjects at risk of cognitive decline and in reducing the progression of functional disability in cognitively impaired individuals. In recent years, telerehabilitation has enabled a broader application of cognitive rehabilitation programs. The purpose of this study is to test a computer-based intervention administered according to two different modalities (at the hospital and at home) using the tools CoRe and HomeCoRe, respectively, in participants with Mild or Major Neurocognitive Disorders.Methods: Non-inferiority, single-blind randomized controlled trial where 40 participants with Mild or Major Neurocognitive Disorders will be assigned to the intervention group who will receive cognitive telerehabilitation through HomeCoRe or to the control group who will receive in-person cognitive intervention through CoRe, with the therapist administering the same computer-based exercises. The rehabilitative program will last 6 weeks, with 3 sessions/week, each lasting ~45 min. All the participants will be evaluated on an exhaustive neuropsychological battery before (T0) and after (T1) the intervention; follow-up visits will be scheduled after 6 (T2) and 12 months (T3).Discussion: The results of this study will inform about the comparability (non-inferiority trial) of HomeCoRe with CoRe. Their equivalence would support the use of HomeCoRe for at distance treatment, favoring the continuity of care.Ethics and Dissemination: This study has been approved by the Local Ethics Committee and registered in https://clinicaltrials.gov (NCT04889560). The dissemination plan includes the scientific community through publication in open-access peer-reviewed scientific journals and presentations at national and international conferences.Trial Registration:Clinicaltrials.govhttps://clinicaltrials.gov/ct2/show/NCT04889560 (registration date: May 17, 2021).

In Parkinson’s disease (PD), physical activity may represent a possible non-pharmacological intervention not only for improving motor symptoms but also for modulating cognitive impairment. To evaluate the efficacy of an intensive physical program on cognitive functions in mid-stage PD patients with mild cognitive impairment (PD-MCI) over a 6-month follow-up. This is a 6-month randomized controlled follow-up study. 40 PD-MCI patients were randomized to receive physical therapy (PT) or no specific intervention beside drug treatment (CT). Cognitive and motor assessments were performed at baseline (T0), 4 weeks after baseline (T1) and 6 months after T0. In a previous study, we reported a significant improvement in global cognitive functioning and attention/working-memory at T1. Here, we evaluated the residual effect of the training intervention at 6 months on both cognitive and motor performances. Intra-group analysis showed that at T2 most of cognitive and motor performances remained stable in the PT when compared to T0, while a significant worsening was observed in the CT. Between-group comparison at T2 showed significantly better results in PT than CT as regards MoCA and motor scales. The percentage change of cognitive and motor performances between T1 and T2 confirmed the benefit of physical therapy on global cognitive functioning scores (MMSE and MoCA). In this follow-up extension of a longitudinal randomized controlled study, we demonstrated that physical therapy has a positive effect on cognitive functions, which extends beyond the duration of the treatment itself to, at least temporarily, reducing cognitive decline. Trial registration number (ClinicalTrials.gov): NCT04012086 (9th July 2019).

Background: Smart Aging is a serious game (SG) platform that generates a 3D virtual reality environment in which users perform a set of screening tasks designed to allow evaluation of global cognition. Each task replicates activities of daily living performed in a familiar environment. The main goal of the present study was to ascertain whether Smart Aging could differentiate between different types and levels of cognitive impairment in patients with neurodegenerative disease. Methods: Ninety-one subjects (mean age = 70.29 ± 7.70 years)—healthy older adults (HCs, n = 23), patients with single-domain amnesic mild cognitive impairment (aMCI, n = 23), patients with single-domain executive Parkinson's disease MCI (PD-MCI, n = 20), and patients with mild Alzheimer's disease (mild AD, n = 25)—were enrolled in the study. All participants underwent cognitive evaluations performed using both traditional neuropsychological assessment tools, including the Mini-Mental State Examination (MMSE), Montreal Overall Cognitive Assessment (MoCA), and the Smart Aging platform. We analyzed global scores on Smart Aging indices (i.e., accuracy, time, distance) as well as the Smart Aging total score, looking for differences between the four groups. Results: The findings revealed significant between-group differences in all the Smart Aging indices: accuracy (p < 0.001), time (p < 0.001), distance (p < 0.001), and total Smart Aging score (p < 0.001). The HCs outperformed the mild AD, aMCI, and PD-MCI patients in terms of accuracy, time, distance, and Smart Aging total score. In addition, the mild AD group was outperformed both by the HCs and by the aMCI and PD-MCI patients on accuracy and distance. No significant differences were found between aMCI and PD-MCI patients. Finally, the Smart Aging scores significantly correlated with the results of the neuropsychological assessments used. Conclusion: These findings, although preliminary due to the small sample size, suggest the validity of Smart Aging as a screening tool for the detection of cognitive impairment in patients with neurodegenerative diseases.

The COVID-19 pandemic is a global health problem that is radically transforming public and private healthcare organizations around the world, negatively affecting the rehabilitative treatments of non-COVID pathologies as well. In this situation, it becomes crucial to be able to guarantee the continuity of care also to all those patients with neurodegenerative diseases unable to reach healthcare services. Remote communication technologies are gaining momentum as potentially effective options to support health care interventions-including cognitive rehabilitation-while patients can stay safely at home. In this context, we are implementing HomeCoRe (i.e., Home Cognitive Rehabilitation software) in order to offer an innovative approach and a valid support for home-based cognitive rehabilitation in neurodegenerative diseases, such as mild cognitive impairment and early dementia. HomeCoRe has been developed within a research project between engineers and clinicians in order to obtain a usable and safe cognitive rehabilitation tool. This software has multiple advantages for patients and therapists over traditional approaches, as shown in its use in hospital settings. HomeCoRe could then represent an opportunity for accessing cognitive rehabilitation in all those situations where patients and therapists are not in the same location due to particular restrictions, such as COVID-19 pandemic.

This is the processed data for the manuscript " Rodella C, Bernini S, Panzarasa S, Sinforiani E, Picascia M, Quaglini S, Cavallini E, Vecchi T, Tassorelli C, Bottiroli S. A double-blind randomized controlled trial combining cognitive training (CoRe) and neurostimulation (tDCS) in the early stages of cognitive impairment. Aging Clin Exp Res. 2021 Jun 22. Epub ahead of print". Dataset refers to a Randomized Controlled Trial aimed to evaluate the effectiveness of a combined treatment protocol associating a computerized cognitive training (CoRe) with anodal transcranial direct current stimulation (tDCS) in early phases of cognitive impairment. The dataset contains cognitive performances in neuropsychological tests (raw scores) at baseline (T0), post-intervention (T1) and 6-months later (T2). Data highlights the efficacy of combining cognitive training and neurostimulation.

BackgroundFrontotemporal Spectrum Disorder (FTSD) and Amyotrophic Lateral Sclerosis (ALS) are neurodegenerative diseases often considered as a continuum from clinical, epidemiologic, and genetic perspectives. We used localized brain volume alterations to evaluate common and specific features of FTSD, FTSD-ALS, and ALS patients to further understand this clinical continuum.MethodsWe used voxel-based morphometry on structural magnetic resonance images to localize volume alterations in group comparisons: patients (20 FTSD, seven FTSD-ALS, and 18 ALS) versus healthy controls (39 CTR), and patient groups between themselves. We used mean whole-brain cortical thickness (CT¯) to assess whether its correlations with local brain volume could propose mechanistic explanations of the heterogeneous clinical presentations. We also assessed whether volume reduction can explain cognitive impairment, measured with frontal assessment battery, verbal fluency, and semantic fluency.ResultsCommon (mainly frontal) and specific areas with reduced volume were detected between FTSD, FTSD-ALS, and ALS patients, confirming suggestions of a clinical continuum, while at the same time defining morphological specificities for each clinical group (e.g., a difference of cerebral and cerebellar involvement between FTSD and ALS). CT¯ values suggested extensive network disruption in the pathological process, with indications of a correlation between cerebral and cerebellar volumes and CT¯ in ALS. The analysis of the neuropsychological scores indeed pointed toward an important role for the cerebellum, along with fronto-temporal areas, in explaining impairment of executive, and linguistic functions.ConclusionWe identified common elements that explain the FTSD-ALS clinical continuum, while also identifying specificities of each group, partially explained by different cerebral and cerebellar involvement.

BACKGROUND:The effectiveness of computer-based cognitive training (CCT) remains controversial, especially in older adults with neurodegenerative diseases.AIMS:To evaluate the efficacy of CCT in patients with Parkinson's disease and mild cognitive impairment (PD-MCI).METHODS:In this randomized controlled trial, 53 patients were randomized to receive CCT delivered by means of CoRe software, traditional paper-and-pencil cognitive training (PCT), or an unstructured activity intervention (CG). In each group, the intervention lasted 3 consecutive weeks (4 individual face-to-face sessions/week). Neuropsychological assessment was administered at baseline (T0) and post-intervention (T1). Outcome measures at T0 and T1 were compared within and between groups. The Montreal Overall Cognitive Assessment (MoCA) was taken as the primary outcome measure.RESULTS:Unlike the PCT group and the CG, the patients receiving CCT showed significant medium/large effect size improvements in MoCA performance, global cognition, executive functions, and attention/processing speed. No baseline individual/demographic variables were associated with greater gains from the intervention, although a negative correlation with baseline MoCA performance was found.CONCLUSION:CCT proved effective in PD-MCI patients when compared with traditional PCT. Further follow-up assessments are being conducted to verify the retention of the gains and the potential ability of the tool to delay conversion to PD-dementia. Trial registration number (ClinicalTrials.gov): NCT04111640 (30th September 2019).

Objective Brain atrophy is an established biomarker for dementia, yet spinal cord involvement has not been investigated to date. As the spinal cord is relaying sensorimotor control signals from the cortex to the peripheral nervous system and viceversa, it is indeed a very interesting question to assess whether it is affected by atrophy in a disease that is known for its involvement of cognitive domains first and foremost, with motor symptoms being clinically assessed too. We therefore hypothesize that Alzheimer Disease severe atrophy can affect the spinal cord too and that spinal cord atrophy is indeed an important in vivo imaging biomarker contributing to understanding neurodegeneration associated with dementia. Methods 3DT1 images of 31 Alzheimer’s disease (AD) and 35 healthy control (HC) subjects were processed to calculate volumes of brain structures and cross-sectional area (CSA) and volume (CSV) of the cervical cord (per vertebra as well as the C2-C3 pair (CSA23 and CSV23)). Correlated features (ρ>0.7) were removed, and best subset identified for patients’ classification with the Random Forest algorithm. General linear model regression was used to find significant differences between groups (p<=0.05). Linear regression was implemented to assess the explained variance of the Mini Mental State Examination (MMSE) score as dependent variable with best features as predictors. Results Spinal cord features were significantly reduced in AD, independently of brain volumes. Patients classification reached 76% accuracy when including CSA23 together with volumes of hippocampi, left amygdala, white and grey matter, with 74% sensitivity and 78% specificity. CSA23 alone explained 13% of MMSE variance. Discussion Our findings reveal that C2-C3 spinal cord atrophy contributes to discriminate AD from HC, together with more established features. Results show that CSA23, calculated form the same 3DT1 scan as all other brain volumes (including right and left hippocampi), has a considerable weight in classification tasks warranting further investigations. Together with recent studies revealing that AD atrophy is spread beyond the temporal lobes, our result adds the spinal cord to a number of unsuspected regions involved in the disease. Interestingly, spinal cord atrophy explains also cognitive scores, which could significantly impact how we model sensorimotor control in degenerative diseases with a primary cognitive domain involvement. Prospective studies should be purposely designed to understand the mechanisms of atrophy and the role of the spinal cord in AD.

Among dementia-like diseases, Alzheimer disease (AD) and vascular dementia (VD) are two of the most frequent. AD and VD may share multiple neurological symptoms that may lead to controversial diagnoses when using conventional clinical and MRI criteria. Therefore, other approaches are needed to overcome this issue. Machine learning (ML) combined with magnetic resonance imaging (MRI) has been shown to improve the diagnostic accuracy of several neurodegenerative diseases, including dementia. To this end, in this study, we investigated, first, whether different kinds of ML algorithms, combined with advanced MRI features, could be supportive in classifying VD from AD and, second, whether the developed approach might help in predicting the prevalent disease in subjects with an unclear profile of AD or VD. Three ML categories of algorithms were tested: artificial neural network (ANN), support vector machine (SVM), and adaptive neuro-fuzzy inference system (ANFIS). Multiple regional metrics from resting-state fMRI (rs-fMRI) and diffusion tensor imaging (DTI) of 60 subjects (33 AD, 27 VD) were used as input features to train the algorithms and find the best feature pattern to classify VD from AD. We then used the identified VD-AD discriminant feature pattern as input for the most performant ML algorithm to predict the disease prevalence in 15 dementia patients with a "mixed VD-AD dementia" (MXD) clinical profile using their baseline MRI data. ML predictions were compared with the diagnosis evidence from a 3-year clinical follow-up. ANFIS emerged as the most efficient algorithm in discriminating AD from VD, reaching a classification accuracy greater than 84% using a small feature pattern. Moreover, ANFIS showed improved classification accuracy when trained with a multimodal input feature data set (e.g., DTI + rs-fMRI metrics) rather than a unimodal feature data set. When applying the best discriminant pattern to the MXD group, ANFIS achieved a correct prediction rate of 77.33%. Overall, results showed that our approach has a high discriminant power to classify AD and VD profiles. Moreover, the same approach also showed potential in predicting earlier the prevalent underlying disease in dementia patients whose clinical profile is uncertain between AD and VD, therefore suggesting its usefulness in supporting physicians' diagnostic evaluations.

Background: Sleep disorders and cognitive impairment are frequently reported in Parkinson's disease (PD) as non-motor disabling symptoms. While it is known that REM sleep Behaviour Disorder (RBD) in PD is associated with motor and cognitive decline, little is known about the neurobiological significance of NREM sleep arousal-related disorders. Objectives: to evaluate the cognitive and clinical correlates of arousal-related disorders in PD. Methods: Clinical data and video-polysomnography were analysed from one hundred-seventy consec-utive subjects with PD. Based on the neuropsychological assessment, the subjects were divided into three groups: no cognitive impairment (PD; n = 58), mild cognitive impairment (PD-MCI; n = 58) and overt dementia (PDD; n = 54). Results: Arousal-related disorders by history were reported in 32.9% of the subjects: 10.3% PD, 31.6% PD MCI and 59.3% PDD (p = 0.001). Video-PSG captured arousal-related disorders in 1.7% PD, 21.2% MCI-PD and 35.6% PDD (p = 0.001). Arousal-related disorders and RBD were recorded in the same night in 7.7% PD, 9.8% MCI-PD and 15.6% PDD (p = 0.04). Patients with arousal-related disorders captured at V-PSG have a longer disease duration (p = 0.003), higher UPDRS score (p = 0.039), longer duration of treatment with levodopa (p = 0.017) and dopamine agonists (p = 0.018), worse H&Y staging (p = 0.001), lower MMSE score (p = 0.019) and more frequently hallucinations (p = 0.004). In multivariate analysis, cognitive impairment significantly increases the risk of arousal-related disorders (OR 3.387-95% CI 1.395-8.220, p = 0.007). Conclusion: Arousal-related disorders appear to be a marker of cognitive decline in PD. Recognizing arousal-related disorders should make clinicians aware of a possible cognitive decline in PD and eventually modify the therapeutic approach. (C) 2020 Elsevier B.V. All rights reserved.

Background: Circadian and sleep disturbances are associated with increased risk of mild cognitive impairment (MCI) and Alzheimer's disease (AD). Wearable activity trackers could provide a new approach in diagnosis and prevention. Objective: To evaluate sleep and circadian rhythm parameters, through wearable activity trackers, in MCI and AD patients as compared to controls, focusing on sex dissimilarities. Methods: Based on minute level data from consumer wearable devices, we analyzed actigraphic sleep parameters by applying an electromedical type I registered algorithm, and the corresponding circadian variables in 158 subjects: 86 females and 72 males (42 AD, 28 MCI, and 88 controls). Moreover, we used a confusion-matrix chart method to assess accuracy, precision, sensitivity, and specificity of two decision-tree models based on actigraphic data in predicting disease or health status. Results: Wake after sleep onset (WASO) was higher (p < 0.001) and sleep efficiency (SE) lower (p = 0.003) in MCI, and Sleep Regularity Index (SRI) was lower in AD patients compared to controls (p = 0.004). SE was lower in male AD compared to female AD (p = 0.038) and SRI lower in male AD compared to male controls (p = 0.008), male MCI (p = 0.047), but also female AD subjects (p = 0.046). Mesor was significantly lower in males in the overall population. Age reduced the dissimilarities for WASO and SE but demonstrated sex differences for amplitude (p = 0.009) in the overall population, controls (p = 0.005), and AD subjects (p = 0.034). The confusion-matrices showed good predictive power of actigraphic data. Conclusion: Actigraphic data could help identify disease or health status. Sex (possibly gender) differences could impact on neurodegeneration and disease trajectory with potential clinical applications.

BACKGROUND:There is no successful pharmacological treatment for cognitive impairment in Parkinson's Disease, therefore treatments capable of slowing down the progression of cognitive dysfunction are needed. OBJECTIVE:To evaluate the effectiveness of a cognitive training, supported by the CoRe computerized tool, in patients with Parkinson's Disease Mild Cognitive Impairment. METHODS:This is a prospective, open-unblinded, randomized, controlled study. After baseline cognitive assessment (T0), enrolled patients were randomized to receive motor rehabilitation plus cognitive intervention (G1) or motor rehabilitation only (G2). Follow-up assessments were scheduled 4 weeks (T1) and 6 months after (T2). Global cognitive functioning scores (MOCA and MMSE) were considered as primary outcome. Outcome measures at T0, T1 and T2 were compared within- and between-groups. A percentage change score between T0 and next assessments was calculated to identify patients who improved, remain stable or worsened. RESULTS:Differently from G2, G1 showed a medium/large effect size improvement in primary (MoCA) and secondary outcome, both between T0 and T1 and T0 and T2. Moreover, within G1, most patients improved their cognitive state compared to the baseline. CONCLUSIONS:Patients trained with CoRe showed a better evolution of cognitive decline, while untreated patients tended to get worse over time.

Study Objectives: To search for a specific neuropsychological profile in idiopathic REM sleep behavior disorder (iRBD), able to predict the onset of neurodegenerative disorders. Methods: In a longitudinal follow-up study of 63 consecutive iRBD patients (follow-up duration 6.7 +/- 3.8 years), the baseline cognitive profile of converters to neurodegenerative disease was compared with that of the nonconverters. Five cognitive domains were assessed: memory, attention-working memory, executive functions, visuospatial abilities, language. Mild cognitive impairment (MCI) was diagnosed according to the Movement Disorder Society's diagnostic criteria for Parkinson's disease. Results: 30 subjects (47.6%) developed a neurodegenerative disease (latency to conversion 60.33 +/- 44.81 months). MCI was found in 50% of the converters and 12% of the nonconverters (p = .001), and its presence conferred a neurodegenerative disease risk of 10% at 3 years, 36% at 5 years, and 73% at 10 years (p = .002). Pathological equivalent scores on at least one neuropsychological test were detected in 46.7% of the converters versus 21.2% of the nonconverters in the memory domain (p = .032), in 40.0% versus 6.1% in that of executive functions (p = .002), and in 20.0% versus 3% in the visuospatial abilities domain (p = .047). On multivariate analysis, impaired executive functions significantly correlated with phenoconversion (p = .018). Lower Mini Mental State Examination (MMSE) scores (p = .004) and memory deficits (p = .031) were found in patients who developed dementia first. Conclusions: Cognitive profile is useful for stratifying risk of phenoconversion in patients with iRBD. The presence of MCI and impaired executive functions, memory, and visuospatial abilities discriminated the converters. Lower MMSE scores and memory deficits may characterize those subjects who first develop dementia.

OBJECTIVE:This study aimed to evaluate the association between polypharmacy and delirium, the association of specific drug categories with delirium, and the differences in drug-delirium association between medical and surgical units and according to dementia diagnosis.METHODS:Data were collected during 2 waves of Delirium Day, a multicenter delirium prevalence study including patients (aged 65 years or older) admitted to acute and long-term care wards in Italy (2015-2016); in this study, only patients enrolled in acute hospital wards were selected (n = 4,133). Delirium was assessed according to score on the 4 "A's" Test. Prescriptions were classified by main drug categories; polypharmacy was defined as a prescription of drugs from 5 or more classes.RESULTS:Of 4,133 participants, 969 (23.4%) had delirium. The general prevalence of polypharmacy was higher in patients with delirium (67.6% vs 63.0%, P = .009) but varied according to clinical settings. After adjustment for confounders, polypharmacy was associated with delirium only in patients admitted to surgical units (OR = 2.9; 95% CI, 1.4-6.1). Insulin, antibiotics, antiepileptics, antipsychotics, and atypical antidepressants were associated with delirium, whereas statins and angiotensin receptor blockers exhibited an inverse association. A stronger association was seen between typical and atypical antipsychotics and delirium in subjects free from dementia compared to individuals with dementia (typical: OR = 4.31; 95% CI, 2.94-6.31 without dementia vs OR = 1.64; 95% CI, 1.19-2.26 with dementia; atypical: OR = 5.32; 95% CI, 3.44-8.22 without dementia vs OR = 1.74; 95% CI, 1.26-2.40 with dementia). The absence of antipsychotics among the prescribed drugs was inversely associated with delirium in the whole sample and in both of the hospital settings, but only in patients without dementia.CONCLUSIONS:Polypharmacy is significantly associated with delirium only in surgical units, raising the issue of the relevance of medication review in different clinical settings. Specific drug classes are associated with delirium depending on the clinical setting and dementia diagnosis, suggesting the need to further explore this relationship.

Background: Circadian dysfunction is thought to take part in the pathogenesis of sleep disorders in Alzheimer's disease (AD) and in AD pathophysiology itself. Objective: Our study aims to calculate dim light melatonin onset (DLMO) secretion in order to define the circadian phase in patients with AD at an early stage of the disease. Methods: Twenty-one patients (M/F: 11/10; mean age 74.1 +/- 5.4 years; mean disease duration 3.4 +/- 1.6 years) with a diagnosis of AD and 17 healthy controls (HC; M/F: 10/ 7; mean age 67.47 +/- 3.8 years) were investigated for subjective nocturnal sleep quality and chronotype, for DLMO and quantitative aspects of the evening melatonin secretion by means of a 5-point in-home evening melatonin saliva test. Results: Subjective sleep quality score on the Pittsburgh Sleep Quality Index questionnaire (PSQI) above 5 (p = 0.24), insomnia frequency as measured by Sleep Condition Indicator Questionnaire (p = 0.823) and the subjective chronotype according to Morning Evening Questionnaire (MEQ) scores distribution (p = 0.464) did not differ between AD and HC. However, DLMO occurred significantly later (55 min; p = 0.028), and melatonin secretion following DLMO was significantly decreased in AD patients compared to HC. Conclusion: Initial evening secretion of melatonin proves to be delayed and mildly impaired in patients with a mild/moderate form of Alzheimer disease while patients' subjective sleep parameters and chronotype are reported to be similar to those of HC. These results indicate that subclinical altered patterns of melatonin secretion occur in subjects with AD at an early stage of the disease. (C) 2019 Elsevier B.V. All rights reserved.