Back and front peripersonal space: behavioural and EMG evidence of top-down and bottom-up mechanisms.

Previous studies have identified a 'defensive graded field' in the peripersonal front space where potential threatening stimuli induce stronger blink responses, mainly modulated by top-down mechanisms, which include various factors, such as proximity to the body, stimulus valence, and social cues. However, very little is known about the mechanisms responsible for representation of the back space and the possible role of bottom-up information. By means of acoustic stimuli, we evaluated individuals' representation for front and back space in an ambiguous environment that offered some degree of uncertainty in terms of both distance (close vs. far) and front-back egocentric location of sound sources. We aimed to consider verbal responses about localization of sound sources and EMG data on blink reflex. Results suggested that stimulus distance evaluations were better explained by subjective front-back discrimination, rather than real position. Moreover, blink response data were also better explained by subjective front-back discrimination. Taken together, these findings suggest that the mechanisms that dictate blink response magnitude might also affect sound localization (possible bottom-up mechanism), probably interacting with top-down mechanisms that modulate stimuli location and distance. These findings are interpreted within the defensive peripersonal framework, suggesting a close relationship between bottom-up and top-down mechanisms on spatial representation.

PainRE-Life: A FHIR Based Telemonitoring Ecosystem for the Management of Patients with Chronic Pain.

Chronic pain is a condition in which the use of digital health technologies, ecological momentary assessments, and digital communication tools may boost patient's engagement and coping. Here we present the results of the PainRE-Life a project, financed by the Lombardy Region (Italy), aimed to develop a dynamic and integrated technology ecosystem based on big data management and analysis to allow care continuity in patients with pain, and able to act as a decision aid for patients and caregivers.

Personalized Integrated Care Promoting Quality of Life for Older People: Protocol for a Multicenter Randomized Controlled Trial.

BACKGROUND: Alzheimer disease (AD) and Parkinson disease (PD) are the 2 most common neurodegenerative diseases affecting millions of people worldwide. The Personalized Integrated Care Promoting Quality of Life for Older People (PC4L) project proposes an integrated, scalable, and interactive care ecosystem that can be easily adapted to the needs of several neurodegenerative and chronic diseases, care institutions, and end user requirements. OBJECTIVE: The study protocol developed within the framework of the PC4L project aims to iteratively test the integrated platform and its modules, and focuses primarily on assessing the impact of the proposed solution (ie, the PC4L platform) on patients' quality of life, as well as its usability and feasibility on a large-scale sample size in 3 different scenarios (home, neurorehabilitation, and day care centers). METHODS: A prospective multicenter clinical study is conducted in 5 European countries (Germany, Italy, Portugal, Romania, and Spain) at 6 different pilot centers, for 3 months, in patients with PD, Parkinsonism, AD, and other dementias (ODs). Patients were randomized in a ratio of 1:1 to the intervention group (use of the PC4L system) or the control group (no intervention). The PC4L system consists mainly of a wristband for monitoring parameters such as steps and levels of physical activity, and the PC4L app, which includes different engaging functionalities. Both groups are assessed through baseline and end-of-study clinical evaluations, including assessment of quality of life through the EQ-5D-3L scale. RESULTS: The study protocol is part of a project approved and funded by the European Commission Horizon 2020 (grant agreement number 875221). The ethics committees of all involved centers reviewed and approved the study protocol. The study began with the recruitment phase in September 2022, and enrollment ended in February 2023. Recruitment is now closed (April 2023). The results of this study are expected to be published in summer 2023. A total of 558 patients, 279 per study group, were recruited. The results will allow to clarify the impact of PC4L on quality of life, will assess the empowerment of patients and the medical resources use, as well as the usability of the final version of the PC4L system. It will also provide information on the support of the system as a tool to facilitate the decision-making process. CONCLUSIONS: The PC4L project intends to test a technology-based, integrated, scalable, and interactive care platform on patients with neurodegenerative diseases and proposes a good coordinated care model between all involved actors. Future developments of the PC4L solution may involve caregivers and socio-health professionals in the decision-making process in order to facilitate efficient communication between all stakeholders and ensure reliable and protected access to data within Europe. TRIAL REGISTRATION: ClinicalTrials.gov NCT05538455; https://clinicaltrials.gov/study/NCT05538455. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/47916.

Complexity analysis from EEG data in congestive heart failure: A study via approximate entropy.

AIM: Congestive heart failure (CHF) is a very complex clinical syndrome that may lead to ischemic cerebral hypoxia condition. The aim of the present study is to analyze the effects of CHF on brain activity through electroencephalographic (EEG) complexity measures, like approximate entropy (ApEn). METHODS: Twenty patients with CHF and 18 healthy elderly people were recruited. ApEn values were evaluated in the total spectrum (0.2-47 Hz) and main EEG frequency bands: delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-11 Hz), alpha 2 (11-13 Hz), beta 1 (13-20 Hz), beta 2 (20-30 Hz), and gamma (30-45 Hz) to identify differences between CHF group and control. Moreover, a correlation analysis was performed between ApEn parameters and clinical data (i.e., B-type natriuretic peptides (BNP), New York Heart Association (NYHA), and systolic blood pressure (SBP)) within the CHF group. RESULTS: Statistical topographic maps showed statistically significant differences between the two groups in the total spectrum and theta frequency band. Within the CHF group, significant negative correlations were found between total ApEn and BNP in O2 channel and between theta ApEn and NYHA scores in Fp1, Fp2, and Fz channels; instead, a significant positive correlation was found between theta ApEn and SBP in C3 channel and a nearly significant positive correlation was obtained between theta ApEn and SBP in F4 channel. CONCLUSION: EEG abnormalities in CHF are very similar to those observed in cognitive-impaired patients, suggesting analogies between the effects of neurodegeneration and brain chronic hypovolaemia due to heart disorder and underlying high brain sensitivity to CHF.

The Effects of Directional and Non-Directional Stimuli during a Visuomotor Task and Their Correlation with Reaction Time: An ERP Study.

Different visual stimuli can capture and shift attention into different directions. Few studies have explored differences in brain response due to directional (DS) and non-directional visual stimuli (nDS). To explore the latter, event-related potentials (ERP) and contingent negative variation (CNV) during a visuomotor task were evaluated in 19 adults. To examine the relation between task performance and ERPs, the participants were divided into faster (F) and slower (S) groups based on their reaction times (RTs). Moreover, to reveal ERP modulation within the same subject, each recording from the single participants was subdivided into F and S trials based on the specific RT. ERP latencies were analysed between conditions ((DS, nDS); (F, S subjects); (F, S trials)). Correlation was analysed between CNV and RTs. Our results reveal that the ERPs' late components are modulated differently by DS and nDS conditions in terms of amplitude and location. Differences in ERP amplitude, location and latency, were also found according to subjects' performance, i.e., between F and S subjects and trials. In addition, results show that the CNV slope is modulated by the directionality of the stimulus and contributes to motor performance. A better understanding of brain dynamics through ERPs could be useful to explain brain states in healthy subjects and to support diagnoses and personalized rehabilitation in patients with neurological diseases.

The combination of hyperventilation test and graph theory parameters to characterize EEG changes in mild cognitive impairment (MCI) condition.

Hyperventilation (HV) is a voluntary activity that causes changes in the neuronal firing characteristics noticeable in the electroencephalogram (EEG) signals. HV-related changes have been scribed to modulation of pO2/pCO2 blood contents. Therefore, an HV test is routinely used for highlighting brain abnormalities including those depending to neurobiological mechanisms at the basis of neurodegenerative disorders. The main aim of the present paper is to study the effectiveness of HV test in modifying the functional connectivity from the EEG signals that can be typical of a prodromal state of Alzheimer's disease (AD), the Mild Cognitive Impairment prodromal to Alzheimer condition. MCI subjects and a group of age-matched healthy elderly (Ctrl) were enrolled and subjected to EEG recording during HV, eyes-closed (EC), and eyes-open (EO) conditions. Since the cognitive decline in MCI seems to be a progressive disconnection syndrome, the approach we used in the present study is the graph theory, which allows to describe brain networks with a series of different parameters. Small world (SW), modularity (M), and global efficiency (GE) indexes were computed among the EC, EO, and HV conditions comparing the MCI group to the Ctrl one. All the three graph parameters, computed in the typical EEG frequency bands, showed significant changes among the three conditions, and more interestingly, a significant difference in the GE values between the MCI group and the Ctrl one was obtained, suggesting that the combination of HV test and graph theory parameters should be a powerful tool for the detection of possible cerebral dysfunction and alteration.

Prognostic Role of Hemispherical Functional Connectivity in Stroke: A Study via Graph Theory Versus Coherence of Electroencephalography Rhythms.

BACKGROUND: The objective of the present study is to explore whether acute stroke may result in changes in brain network architecture by electroencephalography functional coupling analysis and graph theory. METHODS: Ninety acute stroke patients and 110 healthy subjects were enrolled in different clinical centers in Rome, Italy, starting from 2013, and for each one electroencephalographies were recorded within <15 days from stroke onset. All patients were clinically evaluated through National Institutes of Health Stroke Scale, Barthel Index, and Action Research Arm Test in the acute stage and during the follow-up. Functional connectivity was assessed using Total Coherence and Small World (SW) by comparing the affected and the unaffected hemisphere between groups (Stroke versus Healthy). Correlations between connectivity and poststroke recovery scores have been carried out. RESULTS: In stroke patients, network hemispheric asymmetry, in terms of Total Coherence, was mainly detected in the affected hemisphere with lower values in Delta, Theta, Alpha1, and Alpha2 (P=0.000001), whereas the unaffected hemisphere showed lower Total Coherence only in Delta and Theta (P=0.000001). SW revealed a significant difference only in the affected hemisphere in all electroencephalography bands (lower SW in Delta (P=0.000003), Theta (P=0.000003), Alpha1 (P=0.000203), and Alpha2 (P=0.028) and higher SW in Beta2 (P=0.000002) and Gamma (P=0.000002)). We also found significant correlations between SW and improvement in National Institutes of Health Stroke Scale (Theta SW: r=-0.2808), Barthel Index (Delta SW: r=0.3692; Theta SW: r=0.3844, Beta2 SW: r=-0.3589; Gamma SW: r=-04948), and Action Research Arm Test (Beta2 SW: r=-0.4274; Gamma SW: r=-0.4370). CONCLUSIONS: These findings demonstrated changes in global functional connectivity and in the balance of network segregation and integration induced by acute stroke. The findings on the correlations between clinical outcome(s) and poststroke network architecture indicate the possibility to identify a predictive index of recovery useful to address and personalize the rehabilitation program.

PROCare4Life lessons learned.

PeRsOnalised Integrated CARE Solution for Elderly (PROCare4Life) was an EU-funded project that ran from January 2020 until June 2023, whose focus was to further develop and integrate previous ICT solutions developed by several previous EU-funded projects into a unique modular system able to support the autonomy and empowerment and to increase the Quality of Life (QoL) of elderly people living with Parkinson's, Alzheimer's, or similar dementia, having also tested the system for elderly people living with comorbidities. This article focuses on the methodology and results used to identify the internal lessons learned. PROCare4Life was developed using a codesign approach involving more than 2,000 participants whose input has been listened to and transformed into valuable changes of the system and also into lessons learned included in this case study report. Since the beginning of the implementation of PROCare4Life, there has been a commitment to make invisible knowledge visible through open discussion and including our lessons learned in each of our deliverables. In the last six months of implementation, qualitative research has been implemented by the PROCare4Life consortium to identify and select our most relevant challenges and recommendations for future projects and initiatives. PROCare4Life was highly impacted by the COVID-19 pandemic, and it is acknowledged in the lessons learned. However, the consortium has focused on the recommendations that could be more valuable for ordinary implementation of future projects and initiatives developing eHealth tools for elderly citizens living with conditions that might affect their cognitive or mobility capacities.

PeRsOnalised Integrated CARE Solution for Elderly (PROCare4Life) was an EU-funded project that ran from January 2020 until June 2023, aiming at improving the quality of life of older people living with Parkinson's, Alzheimer's or other dementia using ICT technologies. The term implementation refers to the process of putting a plan or idea into action. It is a complex process that involves multiple stages, including planning, execution, and evaluation. Implementation research is a growing field of health research that aims to study the factors that affect the implementation of health policies, programs, and practices. It can help identify the best strategies for introducing potential solutions into a health system or promoting their large-scale use and sustainability. For PROCare4Life, when using the term implementation it covers all the stages, including ideation and design phases, although focusing on the pilot 3 iterative codesign and testing of the system. Using daily life devices such as smartphones and smart watches, more than 2,000 people have contributed to co-creating PROCare4Life. The three profiles focused on were older people living with Parkinson's, Alzheimer's or other dementia, their main carers and their healthcare professionals, with an ICT system providing direct communication and allowing them to share their health status. Along the journey to develop PROCare4Life, our European consortium has learned many things that we have internally investigated and reported in this article. We have identified 20 challenges and 41 recommendations. We hope that our lessons learned might be inspiring and valuable for others, particularly future projects and initiatives developing eHealth tools for elderly EU citizens living with different conditions that might affect their cognitive or mobility capabilities.

End Users' and Other Stakeholders' Needs and Requirements in the Development of a Personalized Integrated Care Platform (PROCare4Life) for Older People With Dementia or Parkinson Disease: Mixed Methods Study.

BACKGROUND: With what has been known as the "triple-win effect", introducing information and communication technologies (ICTs) in the health care of neurodegenerative diseases is beneficial in delaying the need for institutional care, reducing the associated health care costs, reducing the caregiving burden, and improving individuals' quality of life. Nevertheless, the mismatch between the users' expectations and their actual needs remains one of the main challenges that can reduce the usability of technology solutions. Therefore, the European project Personalized Integrated Care Promoting Quality of Life for Older People (PROCare4Life), which aimed to develop an ICT-based platform for all parties involved in the health care of neurodegenerative diseases, adopted a user-centered design approach, where all users are involved from the inception and throughout the platform development and implementation to integrate their needs and requirements in the proposed platform. OBJECTIVE: This paper presents the results of a study on the needs and requirements of the potential end users (older people with neurodegenerative diseases, caregivers, and health care professionals) and other key stakeholders in the development of the PROCare4Life platform. METHODS: A mixed qualitative and quantitative study design was used, including 2 web-based surveys, 40 interviews, and 4 workshops. The study was conducted between April and September 2020 in 5 European countries: Germany, Italy, Portugal, Romania, and Spain. Both data types were analyzed separately and then merged and interpreted, with greater priority placed on qualitative research. RESULTS: A total of 217 participants were recruited; 157 (72.4%) of them completed the web-based surveys (n=85, 54.1% patients and n=72, 45.9% caregivers), and 60 (27.6%) individuals participated in the qualitative research (20/60, 33% health care professionals; 5/60, 8% patients; 5/60, 8% caregivers; and 30/60, 50% key stakeholders). We identified 3 main themes (T): (T1) experiences associated with illness, (T2) thoughts about the platform technology, and (T3) desired properties. Alerts for adverse events, communication tools, reminders, and monitoring are constantly needed functionalities, whereas ease of use, personalization, and user-friendliness are foreseen as necessary features. CONCLUSIONS: This paper identified the key personal, social, and health factors that influence the daily lives of the potential end users and reflected on their needs and expectations regarding the design of the proposed PROCare4Life platform. The collected data were useful for the development of the PROCare4Life platform. Although the combination and collection of features for diverse user groups are typical for integrated care platforms, it results in exponential complexity for designers, developers, and users. Contradicting opinions and several concerns in this study demonstrate that an ICT-integrated care platform should not promise too much for too many. Instead, selection, focus, and, sometimes, restriction to essentials are necessary. Users and other stakeholders should be involved in these decisions. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/22463.

Electroencephalographic hallmarks of Alzheimer's disease.

In the human brain, physiological aging is characterized by progressive neuronal loss, leading to disruption of synapses and to a degree of failure in neurotransmission and information flow. However, there is increasing evidence to support the notion that the aged brain has a remarkable level of resilience (i.s. ability to reorganize itself), with the aim of preserving its physiological activity. It is therefore of paramount interest to develop objective markers able to characterize the biological processes underlying brain aging in the intact human, and to distinguish them from brain degeneration associated to age-related neurological progressive diseases like Alzheimer's disease. EEG, alone and combined with transcranial magnetic stimulation (TMS-EEG), is particularly suited to this aim, due to the functional nature of the information provided, and thanks to the ease with which it can be integrated in ecological scenarios including behavioral tasks. In this review, we aimed to provide the reader with updated information about the role of modern methods of EEG and TMS-EEG analysis in the investigation of physiological brain aging and Alzheimer's disease. In particular, we focused on data about cortical connectivity obtained by using readouts such graph theory network brain organization and architecture, and transcranial evoked potentials (TEPs) during TMS-EEG. Overall, findings in the literature support an important potential contribution of such neurophysiological techniques to the understanding of the mechanisms underlying normal brain aging and the early (prodromal/pre-symptomatic) stages of dementia.

Performance prediction in a visuo-motor task: the contribution of EEG analysis.

Brain state in the time preceding the task affects motor performance at single trial level. Aim of the study was to investigate, through a single trial analysis of the Power Spectral Density (PSD) of the cortical sources of EEG rhythms, whether there are EEG markers, which can predict trial-by-trial the subject's performance as measured by the reaction time (RT). 20 healthy adult volunteers performed a specific visuomotor task while continuously recorded with a 64 electrodes EEG. For each single trial, the PSD of the cortical sources of EEG rhythms was obtained from EEG data to cortical current density time series in 12 regions of interest at Brodmann areas level. Results showed a statistically significant increase of posterior and limbic alpha 1 and of frontal beta 2 power, and a reduction of frontal and limbic delta and of temporal alpha 1 power, during triggering stimulus presentation for better performance, namely faster responses. At single trial level, correlation analyses between RTs and significant PSD, revealed positive correlations in frontal delta, temporal alpha 1, and limbic delta bands, and negative ones in frontal beta 2, parietal alpha 1, and occipital alpha 1 bands. Furthermore, the subject's faster responses have been found as correlated with the similarity between the PSD values in parietal and occipital alpha 1. Predicting individual's performance at single trial level, might be extremely useful in the clinical context, since it could allow to launch rehabilitative therapies in the most efficient brain state, avoiding useless interventions.

Brain Connectivity and Graph Theory Analysis in Alzheimer's and Parkinson's Disease: The Contribution of Electrophysiological Techniques.

In recent years, applications of the network science to electrophysiological data have increased as electrophysiological techniques are not only relatively low cost, largely available on the territory and non-invasive, but also potential tools for large population screening. One of the emergent methods for the study of functional connectivity in electrophysiological recordings is graph theory: it allows to describe the brain through a mathematic model, the graph, and provides a simple representation of a complex system. As Alzheimer's and Parkinson's disease are associated with synaptic disruptions and changes in the strength of functional connectivity, they can be well described by functional connectivity analysis computed via graph theory. The aim of the present review is to provide an overview of the most recent applications of the graph theory to electrophysiological data in the two by far most frequent neurodegenerative disorders, Alzheimer's and Parkinson's diseases.

Human Brain Networks in Physiological and Pathological Aging: Reproducibility of Electroencephalogram Graph Theoretical Analysis in Cortical Connectivity.

Background: Physiological and pathological brain aging plays a central role in brain network modulation. The aim of the present article was to assess the stability of a proposed method for evaluation of small-world (SW) characteristics for the study of the human connectome. Subjects and Methods: Eighty subjects were recruited: 36 young healthy controls, 32 elderly healthy controls, and 12 patients affected by Alzheimer's disease (AD). Electroencephalograms (EEGs) were recorded during six separate sessions (480 recordings) at an average intersession interval of 3.8 ± 0.2 days. We applied graph theory functions to the weighted and undirected networks obtained by the lagged linear coherence estimated by exact low-resolution electromagnetic tomography (eLORETA). We explored the following frequency bands: delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), beta 2 (20-30 Hz), and gamma (30-40 Hz). Results: The proposed method for evaluation of SW characteristics exhibited good reproducibility and stability. Furthermore, results showed the pattern, Young>Elderly>AD, in low-frequency delta and theta bands and vice versa in the higher alpha band. Finally, a correlation with age was confirmed in healthy subjects, showing that the older the age, the higher the SW values for alpha 2. Discussion: Evidences from the present study confirm the stability of the SW index and suggest that the analysis of connectivity patterns evaluated from EEGs can be supported by the graph theory. The proposed method for evaluation of SW characteristics has shown good reproducibility and stability. This technique, applied to patient data, could provide more information on the pathophysiological processes underlying age-related brain disconnection, as well as on administration of rehabilitation treatments at the right time, which could allow patients to avoid unnecessary interventions. Impact statement The graph analysis tools described in this study represent an interesting approach to study the distinctive characteristics of physiological aging by focusing on functional connectivity networks. The proposed method for evaluation of small-world characteristics has shown good reproducibility and stability. This technique, applied to patient data, could provide more information on the pathophysiological processes underlying age-related brain disconnection, as well as on delivery of rehabilitation treatments at the right time, which could allow patients to avoid unnecessary interventions.

Graph Theory on Brain Cortical Sources in Parkinson's Disease: The Analysis of 'Small World' Organization from EEG.

Parkinson's disease (PD) is the second most common neurodegenerative disease in the elderly population. Similarly to other neurodegenerative diseases, the early diagnosis of PD is quite difficult. The current pilot study aimed to explore the differences in brain connectivity between PD and NOrmal eLDerly (Nold) subjects to evaluate whether connectivity analysis may speed up and support early diagnosis. A total of 26 resting state EEGs were analyzed from 13 PD patients and 13 age-matched Nold subjects, applying to cortical reconstructions the graph theory analyses, a mathematical representation of brain architecture. Results showed that PD patients presented a more ordered structure at slow-frequency EEG rhythms (lower value of SW) than Nold subjects, particularly in the theta band, whereas in the high-frequency alpha, PD patients presented more random organization (higher SW) than Nold subjects. The current results suggest that PD could globally modulate the cortical connectivity of the brain, modifying the functional network organization and resulting in motor and non-motor signs. Future studies could validate whether such an approach, based on a low-cost and non-invasive technique, could be useful for early diagnosis, for the follow-up of PD progression, as well as for evaluating pharmacological and neurorehabilitation treatments.

Contribution of Graph Theory Applied to EEG Data Analysis for Alzheimer's Disease Versus Vascular Dementia Diagnosis.

BACKGROUND: Most common progressive brain diseases in the elderly are Alzheimer's disease (AD) and vascular dementia (VaD). They present with relatively similar clinical symptoms of cognitive decline, but the underlying pathophysiological mechanisms are different. OBJECTIVE: The aim is to explore the brain connectivity differences between AD and VaD patients compared to mild cognitive impairment (MCI) and normal elderly (Nold) subjects applying graph theory, in particular the Small World (SW) analysis. METHODS: 274 resting state EEGs were analyzed in 100 AD, 80 MCI, 40 VaD, and 54 Nold subjects. Graph theory analyses were applied to undirected and weighted networks obtained by lagged linear coherence evaluated by eLORETA tool. RESULTS: VaD and AD patients presented more ordered low frequency structure (lower value of SW) than Nold and MCI subjects, and more random organization (higher value of SW) in low and high frequency alpha rhythms. Differences between patients have been found in high frequency alpha rhythms in VaD (higher value of SW) with respect to AD, and in theta band with a trend which is more similar to MCI and Nold than to AD. MCI subjects presented a network organization which is intermediate, in low frequency bands, between Nold and patients. CONCLUSION: Graph theory applied to EEG data has proved very useful in identifying differences in brain network patterns in subjects with dementia, proving to be a valid tool for differential diagnosis. Future studies will aim to validate this method to diagnose especially in the early stages of the disease and at single subject level.

Entropy modulation of electroencephalographic signals in physiological aging.

Aging is a multifactorial physiological process characterized by the accumulation of degenerative processes impacting on different brain functions, including the cognitive one. A tool largely employed in the investigation of brain networks is the electroencephalogram (EEG). Given the cerebral complexity and dynamism, many non-linear approaches have been applied to explore age-related brain electrical activity modulation detected by the EEG: one of them is the entropy, which measures the disorder of a system. The present study had the aim to investigate aging influence on brain dynamics applying Approximate Entropy (ApEn) parameter to resting state EEG data of 68 healthy adult participants, divided with respect to their age in two groups, focusing on several specialized brain regions. Results showed that elderly participants present higher ApEn values than younger participants in the central, parietal and occipital areas, confirming the hypothesis that aging is characterized by an evolution of brain dynamics. Such findings may reflect a reduced synchronization of the neural networks cyclic activity, due to the reduction of cerebral connections typically found in aging process. Understanding the dynamics of brain networks by applying the entropy parameter could be useful for developing appropriate and personalized rehabilitation programs and for future studies on neurodegenerative diseases.

Brain sources' activity in resting state before a visuo-motor task.

Objective.In modern neuroscience, the underlying mechanisms of the elaboration and reaction to different kinds of stimuli of the brain hemispheres remain still very challenging to understand, together with the possibility to anticipate certain behaviors to improve the performance.Approach.The purpose of the present study was to investigate the brain rhythms characteristics of electroencephalographic (EEG) recordings and in particular, their interhemispheric differences in resting state condition before a visuo-motor task in a population of healthy adults. During the task, subjects were asked to react to a sequence of visual cues as quick as possible. The reaction times (RTs) to the task were measured, collected and correlated with the EEG signals recorded in a resting state condition immediately preceding the task. The EEG data were analyzed in the space of cortical sources of EEG rhythms by the computation of the global spectra power density (GSPD) in the left and in the right hemisphere, and of an index of brain laterality (L).Main results.The results showed a negative correlation between the RTs and the GSPD in the central areas in the left and in the right hemisphere in both eyes open (EO) and eyes closed (EC) conditions. A close to significant and negative correlation was found in the parietal areas. Furthermore, RTs negatively correlated withLin the central areas in EC condition. The results showed a negative correlation between the RTs and the GSPD in the central areas in the left and in the right hemisphere in both EO and EC conditions.Significance.The correlations between the brain activity before a task and the RTs to the task can represent an interesting tool for exploring the brain state characterization for the upcoming tasks performance.

Investigating Users' and Other Stakeholders' Needs in the Development of a Personalized Integrated Care Platform (PROCare4Life) for Older People with Dementia or Parkinson Disease: Protocol for a Mixed Methods Study.

BACKGROUND: Dementias-including Alzheimer disease-and Parkinson disease profoundly impact the quality of life of older population members and their families. PROCare4Life (Personalized Integrated Care Promoting Quality of Life for Older Adults) is a European project that recognizes the benefit of technology-based integrated care models in improving the care coordination and the quality of life of these target groups. This project proposes an integrated, scalable, and interactive care platform targeting older people suffering from neurodegenerative diseases, their caregivers, and socio-health professionals. PROCare4Life adopts a user-centered design approach from the early stage and throughout platform development and implementation, during which the platform is designed and adapted to the needs and requirements of all the involved users. OBJECTIVE: This paper presents the study protocol for investigating users' needs and requirements regarding the design of the proposed PROCare4Life platform. METHODS: A mixed qualitative and quantitative study design is utilized, including online surveys, interviews, and workshops. The study aimed to recruit approximately 200 participants, including patients diagnosed with dementia or Parkinson disease, caregivers, socio-health professionals, and other stakeholders, from five different European countries: Germany, Italy, Portugal, Romania, and Spain. RESULTS: The study took place between April and September 2020. Recruitment is now closed, and all the data have been collected and analyzed in order to be used in shaping the large-scale pilot phase of the PROCare4Life project. Results of the study are expected to be published in spring 2021. CONCLUSIONS: This paper charts the protocol for a user-centered design approach at the early stage of the PROCare4Life project in order to shape and influence an integrated health platform suitable for its intended target group and purpose. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/22463.

Assessing the dependence of the number of EEG channels in the brain networks' modulations.

Aim of the study was to evaluate the influence of the EEG channels number on the brain networks' analysis, to establish whether and how much higher density EEG actually contributes to add supplementary information to brain networks analyses. 59 electrodes EEGs were recorded in 20 healthy subjects in eyes open and closed condition. For each condition, we analyzed the recording dataset of 59 channels, and three sub-datasets obtained by the selection of 44, 30, 19 channels from the 59 ones. Then we computed the EEG sources of current density and evaluated the SW index in the four EEGs data montages. Results showed that in the eyes open condition the number of recording channels influences more the SW index modulation respect that in the eyes closed condition. Conversely, in the eyes closed condition the brain activity is less affected by specific brain regions' activations and the signal's generators produced not significant variations on EEG data and consequently the small world network measure is not affected by the recording channels number. We can conclude that in the eyes closed condition, the 19 EEG channels is an acceptable montage to study brain networks' modulations, to both detect the higher and the lower brain waves' frequencies.

Approximate Entropy of Brain Network in the Study of Hemispheric Differences.

Human brain, a dynamic complex system, can be studied with different approaches, including linear and nonlinear ones. One of the nonlinear approaches widely used in electroencephalographic (EEG) analyses is the entropy, the measurement of disorder in a system. The present study investigates brain networks applying approximate entropy (ApEn) measure for assessing the hemispheric EEG differences; reproducibility and stability of ApEn data across separate recording sessions were evaluated. Twenty healthy adult volunteers were submitted to eyes-closed resting EEG recordings, for 80 recordings. Significant differences in the occipital region, with higher values of entropy in the left hemisphere than in the right one, show that the hemispheres become active with different intensities according to the performed function. Besides, the present methodology proved to be reproducible and stable, when carried out on relatively brief EEG epochs but also at a 1-week distance in a group of 36 subjects. Nonlinear approaches represent an interesting probe to study the dynamics of brain networks. ApEn technique might provide more insight into the pathophysiological processes underlying age-related brain disconnection as well as for monitoring the impact of pharmacological and rehabilitation treatments.