Search

The d2 Test of Attention (d2) is widely used for assessing sustained attention and we aimed at verifying whether working memory may be a secondary construct measured by d2. 70 university students were assessed using d2 conventional paper-and-pencil and computational version. The experimental group and control group performed the task with or without target key, respectively. Continuous Performance Test (CPT) and N-back (1 and 2-back) tasks were used to measure sustained attention and working memory, respectively. Computational d2 performance was predicted by CPT (p <.05; R2 =.15) in the experimental group, and it was predicted by 2-back (p <.05; R2 =.28) in the control group. Conventional d2 performance was predicted by 2-back for both control group (p =.01; R2 =.20) and experimental group (p =.02, R2 =.17). Results suggest the involvement of working memory in d2, possibly a secondary construct assessed by this instrument. [ABSTRACT FROM AUTHOR]

Background: Caring for people with dementia (PwD) usually triggers stress and leads to mental and somatic health complaints (SHCs). Physical activity (PA) can provide burden relief in PwD caregivers, but it is not clear whether PA habits would contribute to reducing SHCs. This study aims to analyze the effect of PA on the relationship between burden and SHCs in a sample of family caregivers of PwD. Methods: One hundred and fifty‐seven caregivers of PwD reported their PA habits, and completed the Giessen's Subjective Health Complaints Questionnaire (GBB‐8) and the Zarit Burden Interview (ZBI). The relationship between PA habits, burden of care (ZBI), and SHCs (B‐GBB‐8 scale) was examined. Subsequently, the moderating effect of PA habits on the relationship between burden and SHCs was tested. Results: PA habit was inversely associated with ZBI (rbp = −0.242) and GBB‐8 scores (rbp (Gastrointestinal) = −0.174; rbp (Musculoskeletal) = −0.195; rbp (Exhaustion) = −0.247; rbp (Cardiovascular) = −0.250; and rbp (Overall) = −0.257, respectively), whereas moderate positive correlations were found between ZBI and GBB‐8 scores (r (Gastrointestinal) = 0.483; r (Musculoskeletal) = 0.536; r (Exhaustion) = 0.542; r (Cardiovascular) = 0.438; and r (Overall) = 0.598, respectively). The interaction effect of PA habit and burden was significant for the overall SHCs (b = −0.11; P < 0.05) and cardiovascular complaints (b = −0.06; P < 0.05). However, the association between burden and SHCs was significant (P < 0.001) only for sedentary caregivers. Conclusion: These findings indicate that maintaining an active lifestyle through regular PA could potentially help alleviate the adverse effects of caregiver burden on somatic health among caregivers of PwD. Encouraging and endorsing PA interventions for informal caregivers might yield substantial advantages for their health and general well‐being. [ABSTRACT FROM AUTHOR]

Background: Transcranial direct current stimulation (tDCS) is a promising treatment for Alzheimer's Disease (AD). However, identifying objective biomarkers that can predict brain stimulation efficacy, remains a challenge. The primary aim of this investigation is to delineate the cerebral regions implicated in AD, taking into account the existing lacuna in comprehension of these regions. In pursuit of this objective, we have employed a supervised machine learning algorithm to prognosticate the neurophysiological outcomes resultant from the confluence of tDCS therapy plus cognitive intervention within both the cohort of responders and non-responders to antecedent tDCS treatment, stratified on the basis of antecedent cognitive outcomes. Methods: The data were obtained through an interventional trial. The study recorded high-resolution electroencephalography (EEG) in 70 AD patients and analyzed spectral power density during a 6 min resting period with eyes open focusing on a fixed point. The cognitive response was assessed using the AD Assessment Scale-Cognitive Subscale. The training process was carried out through a Random Forest classifier, and the dataset was partitioned into K equallypartitioned subsamples. The model was iterated k times using K-1 subsamples as the training bench and the remaining subsample as validation data for testing the model. Results: A clinical discriminating EEG biomarkers (features) was found. The ML model identified four brain regions that best predict the response to tDCS associated with cognitive intervention in AD patients. These regions included the channels: FC1, F8, CP5, Oz, and F7. Conclusion: These findings suggest that resting-state EEG features can provide valuable information on the likelihood of cognitive response to tDCS plus cognitive intervention in AD patients. The identified brain regions may serve as potential biomarkers for predicting treatment response and maybe guide a patient-centered strategy. [ABSTRACT FROM AUTHOR]

Copyright of Revista Neuropsicologia Latinoamericana is the property of Yves Joannette and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objectives 1) To study the relationship between resilience resources (both social and individual) and emotional symptomatology (depression and anxiety symptoms), taking into account the potential indirect effects through perceived stress; 2) to investigate whether this network of relationships varies in different age groups. Method: A sample of 718 Brazilians completed self-reports on perceived stress, depressive and anxious symptomatology, social support and individual resilience. The sample comprised two age groups: a sample of adults aged 60 or older (n = 361; 38.78% men; Mage = 67.32 years, SDage = 5.76, range = 60-86), and a sample of younger adults (n = 357; 29.41% men; Mage = 41.37 years, SDage = 7.23, range = 18-59). Multigroup multiple indicator, multiple cause (MIMIC) modelling was used to test for the direct and indirect effects of resilience resources on emotional symptom development, considering the age groups. Results: The relationship between individual resilience resources and depressive or anxiety symptomatology was found to take place exclusively through stressfulness appraisal. On the other hand, social resilience resources showed a direct and indirect effect on emotional symptoms. This pattern of relationships was found to be invariant across age groups. Conclusion: Our findings suggest that both individual and social resilience resources are negatively related to both depressive and anxiety symptoms in adults regardless of age, thus opening the way to future research analysing how interventions may build resilience resources to minimise the influence of stressful and traumatic events across the lifespan. [ABSTRACT FROM AUTHOR]

This study aims to analyze the psychometric properties of the new Brazilian-Portuguese version of the Brief Resilience Scale (B-BRS) in older adults. A sample of 1251 participants (54.20% women; M = 68.02 years, SD = 6.52) completed the B-BRS and seven scales on successful aging and mental health. Confirmatory factor analysis was used to study the B-BRS dimensionality. Convergent and divergent validity was analyzed by means of examining the relationships of B-BRS with scales on successful aging and mental health. The results supported the unidimensionality of the B-BRS after controlling for wording method, as well as satisfactory reliability (ω =.79). B-BRS structure remained invariant across education level and income groups. B-BRS scores positively correlated with successful aging factors and negatively with psychopathology symptoms. To conclude, our findings provide some evidence on the reliability and validity of the B-BRS, as well as its validation for use in the senior population. [ABSTRACT FROM AUTHOR]

Introduction: Persons affected by certain motor disabilities such as amyotrophic lateral sclerosis can evolve with important motor and speech difficulties in communication. A BCI (Brain Computer Interface) is a system that allows interaction between the human brain and a computer, permitting the user to control a communication channel through his or her brain activity. It is based on the analysis and processing of electroencephalographic (EEG) signals to generate control commands. The present study focuses on the subjects' capability to improve the way they learn to control a BCI system. Methods: Two training procedures were compared: standard and progressive shaping response. Six volunteers participated in a reversal singlesubject ABAC design. Results: The study showed that both procedures are equally effective in producing a differential responding in the EEG signals, with no significant differences between them. Nevertheless, there were significant differences when distinguishing two neuronal responses (relax state and hand-movement imagination). Also, in the analysis of individual signals, an adaptive process for the shaping process and a lower error rate in the idle response appeared. Conclusion: Both proposed training procedures, standard and progressive shaping, are equally effective to achieve training of differential responses (imagination of hand/relax) in the interaction with a BCI. [ABSTRACT FROM AUTHOR]

There is a growing consensus regarding the multidimensional nature of successful aging (SA), including both the biomedical and psychosocial domains of the aging process. The Successful Aging Scale (SAS) is a self-rated instrument addressing both of these components. The aim of this study was to analyze the psychometric properties of the Brazilian Portuguese version of the SAS (SAS-B) with regard to reliability and validity in 949 Brazilian community-dwelling older adults (53.60% women; M = 69.49 years; standard deviation = 7.67). Confirmatory factorial analysis (CFA) was performed to provide evidence on its structural validity. Convergent and divergent validity was studied by means of examining the relationships of SAS-B with scales concerning resilience, life satisfaction, self-esteem, social support, perceived stress, and health, as well as mental health. The CFA showed that the SAS-B is multidimensional with three correlated factors (χ 2 /df = 2.74; standardized root mean square residual = 0.03; root mean square error approximation = 0.04; comparative fit index = 0.91), and its factors showed adequate reliability (ω = 0.70 for Healthy living habits, ω = 0.69 for Adaptive coping, and ω = 0.70 for Engagement with Life). Convergent and divergent validity was endorsed by correlations with related factors. The SAS-B is a reliable and valid self-rated instrument to measure the SA from a multidimensional perspective., (© 2020 Wiley Periodicals LLC.)

BCI (Brain-Computer Interface) is a system that allows interaction between the human brain and a computer. It is based on analyzing electroencephalographic signals (EEG) and processing them to generate control commands. The study analyzed the possible influence of psychological variables, such as the imaginative kinesthetic capacity and anxiety, in relation to performance in a BCI. All participants (4 male and 19 female students) completed the questionnaires and carried out a session of BCI to control their EEG signals in a virtual setting of a car along a straight road. The group was divided into two subgroups according to their EEG signals or differential responses obtained in the left-right discrimination. Study results showed no significant differences in cognitive variables of imagination or in anxiety. By comparing the degree of participants' BCI control, a new quantitative parameter for comparing performances and making decisions in signal processing was found. The findings, the ongoing research process to refine the control of a BCI, and the interaction of psychological and computer procedures are discussed.

In this work, an electroencephalographic analysis-based, self-paced (asynchronous) brain-computer interface (BCI) is proposed to control a mobile robot using four different navigation commands: turn right, turn left, move forward and move back. In order to reduce the probability of misclassification, the BCI is to be controlled with only two mental tasks (relaxed state versus imagination of right hand movements), using an audio-cued interface. Four healthy subjects participated in the experiment. After two sessions controlling a simulated robot in a virtual environment (which allowed the user to become familiar with the interface), three subjects successfully moved the robot in a real environment. The obtained results show that the proposed interface enables control over the robot, even for subjects with low BCI performance., (© 2011 IEEE)