Age-related slowing down in the motor initiation in elderly adults

Bradykinesia in dystonic hand tremor: kinematic analysis and clinical rating

Introduction

Bradykinesia is an essential diagnostic criterion for Parkinson's disease (PD) but is frequently observed in many non-parkinsonian movement disorders, complicating differential diagnosis, particularly in disorders featuring tremors. The presence of bradykinetic features in the subset of dystonic tremors (DT), either "pure" dystonic tremors or tremors associated with dystonia, remains currently unexplored. The aim of the current study was to evaluate upper limb bradykinesia in DT patients, comparing them with healthy controls (HC) and patients with PD by observing repetitive finger tapping (FT).

Methods

The protocol consisted of two main parts. Initially, the kinematic recording of repetitive FT was performed using optical hand tracking system (Leap Motion Controller). The values of amplitude, amplitude decrement, frequency, frequency decrement, speed, acceleration and number of halts of FT were calculated. Subsequently, three independent movement disorder specialists from different movement disorders centres, blinded to the diagnosis, rated the presence of FT bradykinesia based on video recordings.

Results

Thirty-six subjects participated in the study (12 DT, 12 HC and 12 early-stage PD). Kinematic analysis revealed no significant difference in the selected parameters of FT bradykinesia between DT patients and HC. In comparisons between DT and PD patients, PD patients exhibited bigger amplitude decrement and slower FT performance. In the blinded clinical assessment, bradykinesia was rated, on average, as being present in 41.6% of DT patients, 27.7% of HC, and 91.7% of PD patients. While overall inter-rater agreement was moderate, weak agreement was noted within the DT group.

Discussion

Clinical ratings indicated signs of bradykinesia in almost half of DT patients. The objective kinematic analysis confirmed comparable parameters between DT and HC individuals, with more pronounced abnormalities in PD across various kinematic parameters. Interpretation of bradykinesia signs in tremor patients with DT should be approached cautiously and objective motion analysis might complement the diagnostic process and serve as a decision support system in the choice of clinical entities.

Aging alters functional connectivity of motor theta networks during sensorimotor reactions

OBJECTIVE

Both cognitive and primary motor networks alter with advancing age in humans. The networks activated in response to external environmental stimuli supported by theta oscillations remain less well explored. The present study aimed to characterize the effects of aging on the functional connectivity of response-related theta networks during sensorimotor tasks.

METHODS

Electroencephalographic signals were recorded in young and middle-to-older age adults during three tasks performed in two modalities, auditory and visual: a simple reaction task, a Go-NoGo task, and a choice-reaction task. Response-related theta oscillations were computed. The phase-locking value (PLV) was used to analyze the spatial synchronization of primary motor and motor control theta networks.

RESULTS

Performance was overall preserved in older adults. Independently of the task, aging was associated with reorganized connectivity of the contra-lateral primary motor cortex. In younger adults, it was synchronized with motor control regions (intra-hemispheric premotor/frontal and medial frontal). In older adults, it was only synchronized with intra-hemispheric sensorimotor regions.

CONCLUSIONS

Motor theta networks of older adults manifest a functional decoupling between the response-generating motor cortex and motor control regions, which was not modulated by task variables. The overall preserved performance in older adults suggests that the increased connectivity within the sensorimotor network is associated with an excessive reliance on sensorimotor feedback during movement execution compensating for a deficient cognitive regulation of motor regions during sensorimotor reactions.

SIGNIFICANCE

New evidence is provided for the reorganization of motor networks during sensorimotor reactions already at the transition from middle to old age.

Explainable cross-task adaptive transfer learning for motor imagery EEG classification

Objective. In the field of motor imagery (MI) electroencephalography (EEG)-based brain-computer interfaces, deep transfer learning (TL) has proven to be an effective tool for solving the problem of limited availability in subject-specific data for the training of robust deep learning (DL) models. Although considerable progress has been made in the cross-subject/session and cross-device scenarios, the more challenging problem of cross-task deep TL remains largely unexplored.Approach. We propose a novel explainable cross-task adaptive TL method for MI EEG decoding. Firstly, similarity analysis and data alignment are performed for EEG data of motor execution (ME) and MI tasks. Afterwards, the MI EEG decoding model is obtained via pre-training with extensive ME EEG data and fine-tuning with partial MI EEG data. Finally, expected gradient-based post-hoc explainability analysis is conducted for the visualization of important temporal-spatial features.Main results. Extensive experiments are conducted on one large ME EEG High-Gamma dataset and two large MI EEG datasets (openBMI and GIST). The best average classification accuracy of our method reaches 80.00% and 72.73% for OpenBMI and GIST respectively, which outperforms several state-of-the-art algorithms. In addition, the results of the explainability analysis further validate the correlation between ME and MI EEG data and the effectiveness of ME/MI cross-task adaptation.Significance. This paper confirms that the decoding of MI EEG can be well facilitated by pre-existing ME EEG data, which largely relaxes the constraint of training samples for MI EEG decoding and is important in a practical sense.

A hybrid linear discriminant analysis and genetic algorithm to create a linear model of aging when performing motor tasks through inertial sensors positioned on the hand and forearm

BACKGROUND

During the aging process, cognitive functions and performance of the muscular and neural system show signs of decline, thus making the elderly more susceptible to disease and death. These alterations, which occur with advanced age, affect functional performance in both the lower and upper members, and consequently human motor functions. Objective measurements are important tools to help understand and characterize the dysfunctions and limitations that occur due to neuromuscular changes related to advancing age. Therefore, the objective of this study is to attest to the difference between groups of young and old individuals through manual movements and whether the combination of features can produce a linear correlation concerning the different age groups.

METHODS

This study counted on 99 participants, these were divided into 8 groups, which were grouped by age. The data collection was performed using inertial sensors (positioned on the back of the hand and on the back of the forearm). Firstly, the participants were divided into groups of young and elderly to verify if the groups could be distinguished through the features alone. Following this, the features were combined using the linear discriminant analysis (LDA), which gave rise to a singular feature called the LDA-value that aided in verifying the correlation between the different age ranges and the LDA-value.

RESULTS

The results demonstrated that 125 features are able to distinguish the difference between the groups of young and elderly individuals. The use of the LDA-value allows for the obtaining of a linear model of the changes that occur with aging in the performance of tasks in line with advancing age, the correlation obtained, using Pearson's coefficient, was 0.86.

CONCLUSION

When we compare only the young and elderly groups, the results indicate that there is a difference in the way tasks are performed between young and elderly individuals. When the 8 groups were analyzed, the linear correlation obtained was strong, with the LDA-value being effective in obtaining a linear correlation of the eight groups, demonstrating that although the features alone do not demonstrate gradual changes as a function of age, their combination established these changes.

Directed functional connectivity of the sensorimotor system in young and older individuals

Introduction

Studies in the sensorimotor system of older versus young individuals have shown alterations in functional connectivity and organization. Our objective was to explore the implications of these differences in terms of local organizations, and to identify processes that correlate with neuropsychological parameters.

Methods

Using a novel multivariate analysis method on resting-state functional MRI data obtained from 50 young and 31 older healthy individuals, we identified directed 4-node functional pathways within the sensorimotor system and examined their correlations with neuropsychological assessments.

Results

In young individuals, the functional pathways were unidirectional, flowing from the primary motor and sensory cortices to higher motor and visual regions. In older individuals, the functional pathways were more complex. They originated either from the calcarine sulcus or the insula and passed through mutually coupled high-order motor areas before reaching the primary sensory and motor cortices. Additionally, the pathways in older individuals that resembled those found in young individuals exhibited a positive correlation with years of education.

Discussion

The flow pattern of young individuals suggests efficient and fast information transfer. In contrast, the mutual coupling of high-order motor regions in older individuals suggests an inefficient and slow transfer, a less segregated and a more integrated organization. The differences in the number of sensorimotor pathways and of their directionality suggests reduced efferent degenerated pathways and increased afferent compensated pathways. Furthermore, the positive effect of years of education may be associated with the Cognitive Reserve Hypothesis, implying that cognitive reserve could be maintained through specific information transfer pathways.

Postmenopausal women's cognitive function and performance of virtual reality tasks

OBJECTIVE

This study aimed to assess whether prior knowledge of computer use determines performance of virtual reality tasks by postmenopausal women and whether menopausal symptoms, sociodemographic factors, lifestyle and cognition modify or interfere with their performance.

METHOD

This cross-sectional study included 152 postmenopausal women divided into two groups: computer users and non-users. Age, ethnicity, time of menopause, menopausal symptoms, female health status, level of physical activity and cognitive function were considered. The participants played a virtual reality game and were assessed for hits, errors, omissions and game time. The Mann-Whitney, chi-square and Fisher exact tests and multivariate linear regression analysis were used.

RESULTS

Postmenopausal computer users play virtual reality games (p = 0.005) better than postmenopausal non-users of computers. Vasomotor symptoms were high in women who used computers compared to those who did not (p = 0.006). Multivariate linear regression analysis found that the best-fitting predictors for the number of hits - that is, age (p = 0.039), Mini-Mental State Examination score (p = 0.006) and the headache symptom (p = 0.021) - influence the performance of virtual reality tasks.

CONCLUSION

Computer users performed virtual reality tasks better than non-users. Headache and age but not vasomotor symptoms negatively affected the postmenopausal women's performance.

Aging exerts a limited influence on the perception of self-generated and externally generated touch

Touch generated by our voluntary movements is attenuated both at the perceptual and neural levels compared with touch of the same intensity delivered to our body by another person or machine. This somatosensory attenuation phenomenon relies on the integration of somatosensory input and predictions about the somatosensory consequences of our actions. Previous studies have reported increased somatosensory attenuation in elderly people, proposing an overreliance on sensorimotor predictions to compensate for age-related declines in somatosensory perception; however, recent results have challenged this direct relationship. In a preregistered study, we used a force-discrimination task to assess whether aging increases somatosensory attenuation and whether this increase is explained by decreased somatosensory precision in elderly individuals. Although 94% of our sample (n = 108, 21-77 yr old) perceived their self-generated touches as weaker than externally generated touches of identical intensity (somatosensory attenuation) regardless of age, we did not find a significant increase in somatosensory attenuation in our elderly participants (65-77 yr old), but a trend when considering only the oldest subset (69-77 yr old). Moreover, we did not observe a significant age-related decline in somatosensory precision or a significant relationship of age with somatosensory attenuation. Together, our results suggest that aging exerts a limited influence on the perception of self-generated and externally generated touch and indicate a less direct relationship between somatosensory precision and attenuation in the elderly individuals than previously proposed.NEW & NOTEWORTHY Self-generated touch is attenuated compared with externally generated touch of identical intensity. This somatosensory attenuation has been previously shown to be increased in elderly participants, but it remains unclear whether it is related to age-related somatosensory decline. In our preregistered study, we observed a trend for increased somatosensory attenuation in our oldest participants (≥69 yr), but we found no evidence of an age-related decline in somatosensory function or a relationship of age with somatosensory attenuation.

Investigating the effects of the aging brain on real tool use performance-an fMRI study

Introduction

Healthy aging affects several domains of cognitive and motor performance and is further associated with multiple structural and functional neural reorganization patterns. However, gap of knowledge exists, referring to the impact of these age-related alterations on the neural basis of tool use-an important, complex action involved in everyday life throughout the entire lifespan. The current fMRI study aims to investigate age-related changes of neural correlates involved in planning and executing a complex object manipulation task, further providing a better understanding of impaired tool use performance in apraxia patients.

Methods

A balanced number of sixteen older and younger healthy adults repeatedly manipulated everyday tools in an event-related Go-No-Go fMRI paradigm.

Results

Our data indicates that the left-lateralized network, including widely distributed frontal, temporal, parietal and occipital regions, involved in tool use performance is not subjected to age-related functional reorganization processes. However, age-related changes regarding the applied strategical procedure can be detected, indicating stronger investment into the planning, preparatory phase of such an action in older participants.

Perceptual Integration Compensates for Attention Deficit in Elderly during Repetitive Auditory-Based Sensorimotor Task

Sensorimotor integration (SI) brain functions that are vital for everyday life tend to decline in advanced age. At the same time, elderly people preserve a moderate level of neuroplasticity, which allows the brain's functionality to be maintained and slows down the process of neuronal degradation. Hence, it is important to understand which aspects of SI are modifiable in healthy old age. The current study focuses on an auditory-based SI task and explores: (i) if the repetition of such a task can modify neural activity associated with SI, and (ii) if this effect is different in young and healthy old age. A group of healthy older subjects and young controls underwent an assessment of the whole-brain electroencephalography (EEG) while repetitively executing a motor task cued by the auditory signal. Using EEG spectral power and functional connectivity analyses, we observed a differential age-related modulation of theta activity throughout the repetition of the SI task. Growth of the anterior stimulus-related theta oscillations accompanied by enhanced right-lateralized frontotemporal phase-locking was found in elderly adults. Their young counterparts demonstrated a progressive increase in prestimulus occipital theta power. Our results suggest that the short-term repetition of the auditory-based SI task modulates sensory processing in the elderly. Older participants most likely progressively improve perceptual integration rather than attention-driven processing compared to their younger counterparts.

Transcranial Magnetic Stimulation of the Dorsolateral Prefrontal Cortex Increases Posterior Theta Rhythm and Reduces Latency of Motor Imagery

Experiments show activation of the left dorsolateral prefrontal cortex (DLPFC) in motor imagery (MI) tasks, but its functional role requires further investigation. Here, we address this issue by applying repetitive transcranial magnetic stimulation (rTMS) to the left DLPFC and evaluating its effect on brain activity and the latency of MI response. This is a randomized, sham-controlled EEG study. Participants were randomly assigned to receive sham (15 subjects) or real high-frequency rTMS (15 subjects). We performed EEG sensor-level, source-level, and connectivity analyses to evaluate the rTMS effects. We revealed that excitatory stimulation of the left DLPFC increases theta-band power in the right precuneus (PrecuneusR) via the functional connectivity between them. The precuneus theta-band power negatively correlates with the latency of the MI response, so the rTMS speeds up the responses in 50% of participants. We suppose that posterior theta-band power reflects attention modulation of sensory processing; therefore, high power may indicate attentive processing and cause faster responses.

Age-related Deterioration of Alpha Power in Cortical Areas Slowing Motor Command Formation in Healthy Elderly Subjects

BACKGROUND/AIM

The same neural processes may govern older people's motor and cognitive abilities since an inability to switch between actions develops with aging. In this study, a dexterity test was used to measure motor and cognitive perseverance, which required participants to move their fingers fast and correctly on hole boards.

MATERIALS AND METHODS

An electroencephalography (EEG) recording was used to evaluate how healthy young and older adults process brain signals when performing the test.

RESULTS

A significant difference was found between the young and older groups in the average time taken to complete the test, with the older group taking 87.4 s and the young group taking 55.21 s. During motor movement, young participants showed alpha desynchronization over the cortex (Fz, Cz, Oz, Pz, T5, T6, P3, P4) in comparison to the resting state. However, compared to the younger group, no alpha desynchronization was found in the aging group during motor performance. It was noteworthy that alpha power (Pz, P3, and P4) in the parietal cortex was significantly lower in older compared to young adults.

CONCLUSION

Age-related slowdown in motor performance may be caused by deteriorating alpha activity in the parietal cortex, which functions as a sensorimotor interface. This study provides new insights into how perception and action are distributed between brain regions.

Aging in nucleus accumbens and its impact on alcohol use disorders

Ethanol is one of the most widely consumed drugs in the world and prolonged excessive ethanol intake might lead to alcohol use disorders (AUDs), which are characterized by neuroadaptations in different brain regions, such as in the reward circuitry. In addition, the global population is aging, and it appears that they are increasing their ethanol consumption. Although research involving the effects of alcohol in aging subjects is limited, differential effects have been described. For example, studies in human subjects show that older adults perform worse in tests assessing working memory, attention, and cognition as compared to younger adults. Interestingly, in the field of the neurobiological basis of ethanol actions, there is a significant dichotomy between what we know about the effects of ethanol on neurochemical targets in young animals and how it might affect them in the aging brain. To be able to understand the distinct effects of ethanol in the aging brain, the following questions need to be answered: (1) How does physiological aging impact the function of an ethanol-relevant region (e.g., the nucleus accumbens)? and (2) How does ethanol affect these neurobiological systems in the aged brain? This review discusses the available data to try to understand how aging affects the nucleus accumbens (nAc) and its neurochemical response to alcohol. The data show that there is little information on the effects of ethanol in aged mice and rats, and that many studies had considered 2-3-month-old mice as adults, which needs to be reconsidered since more recent literature defines 6 months as young adults and >18 months as an older mouse. Considering the actual relevance of an aged worldwide population and that this segment is drinking more frequently, it appears at least reasonable to explore how ethanol affects the brain in adult and aged models.

Statistical power in network neuroscience

Network neuroscience has emerged as a leading method to study brain connectivity. The success of these investigations is dependent not only on approaches to accurately map connectivity but also on the ability to detect real effects in the data - that is, statistical power. We review the state of statistical power in the field and discuss sample size, effect size, measurement error, and network topology as key factors that influence the power of brain connectivity investigations. We use the term 'differential power' to describe how power can vary between nodes, edges, and graph metrics, leaving traces in both positive and negative connectome findings. We conclude with strategies for working with, rather than around, power in connectivity studies.

Does aging amplify the rule-based efficiency effect in action selection?

When it comes to the selection of adequate movements, people may apply varying strategies. Explicit if-then rules, compared to implicit prospective action planning, can facilitate action selection in young healthy adults. But aging alters cognitive processes. It is unknown whether older adults may similarly, profit from a rule-based approach to action selection. To investigate the potential effects of aging, the Rule/Plan Motor Cognition (RPMC) paradigm was applied to three different age groups between 31 and 90 years of age. Participants selected grips either instructed by a rule or by prospective planning. As a function of age, we found a general increase in a strategy-specific advantage as quantified by the difference in reaction time between plan- and rule-based action selection. However, in older age groups, these differences went in both directions: some participants initiated rule-based action selection faster, while for others, plan-based action selection seemed more efficient. The decomposition of reaction times into speed of the decision process, action encoding, and response caution components suggests that rule-based action selection may reduce action encoding demands in all age groups. There appears a tendency for the younger and middle age groups to have a speed advantage in the rule task when it comes to information accumulation for action selection. Thus, one influential factor determining the robustness of the rule-based efficiency effect across the lifespan may be presented by the reduced speed of information uptake. Future studies need to further specify the role of these parameters for efficient action selection.

Motor Imagery: How to Assess, Improve Its Performance, and Apply It for Psychosis Diagnostics

With this review, we summarize the state-of-the-art of scientific studies in the field of motor imagery (MI) and motor execution (ME). We composed the brain map and description that correlate different brain areas with the type of movements it is responsible for. That gives a more complete and systematic picture of human brain functionality in the case of ME and MI. We systematized the most popular methods for assessing the quality of MI performance and discussed their advantages and disadvantages. We also reviewed the main directions for the use of transcranial magnetic stimulation (TMS) in MI research and considered the principal effects of TMS on MI performance. In addition, we discuss the main applications of MI, emphasizing its use in the diagnostics of various neurodegenerative disorders and psychoses. Finally, we discuss the research gap and possible improvements for further research in the field.

Age-Related Changes in Functional Connectivity during the Sensorimotor Integration Detected by Artificial Neural Network

Large-scale functional connectivity is an important indicator of the brain’s normal functioning. The abnormalities in the connectivity pattern can be used as a diagnostic tool to detect various neurological disorders. The present paper describes the functional connectivity assessment based on artificial intelligence to reveal age-related changes in neural response in a simple motor execution task. Twenty subjects of two age groups performed repetitive motor tasks on command, while the whole-scalp EEG was recorded. We applied the model based on the feed-forward multilayer perceptron to detect functional relationships between five groups of sensors located over the frontal, parietal, left, right, and middle motor cortex. Functional dependence was evaluated with the predicted and original time series coefficient of determination. Then, we applied statistical analysis to highlight the significant features of the functional connectivity network assessed by our model. Our findings revealed the connectivity pattern is consistent with modern ideas of the healthy aging effect on neural activation. Elderly adults demonstrate a pronounced activation of the whole-brain theta-band network and decreased activation of frontal–parietal and motor areas of the mu-band. Between-subject analysis revealed a strengthening of inter-areal task-relevant links in elderly adults. These findings can be interpreted as an increased cognitive demand in elderly adults to perform simple motor tasks with the dominant hand, induced by age-related working memory decline.

Effective Connectivity for Decoding Electroencephalographic Motor Imagery Using a Probabilistic Neural Network

Motor imagery (MI)-based brain-computer interfaces have gained much attention in the last few years. They provide the ability to control external devices, such as prosthetic arms and wheelchairs, by using brain activities. Several researchers have reported the inter-communication of multiple brain regions during motor tasks, thus making it difficult to isolate one or two brain regions in which motor activities take place. Therefore, a deeper understanding of the brain's neural patterns is important for BCI in order to provide more useful and insightful features. Thus, brain connectivity provides a promising approach to solving the stated shortcomings by considering inter-channel/region relationships during motor imagination. This study used effective connectivity in the brain in terms of the partial directed coherence (PDC) and directed transfer function (DTF) as intensively unconventional feature sets for motor imagery (MI) classification. MANOVA-based analysis was performed to identify statistically significant connectivity pairs. Furthermore, the study sought to predict MI patterns by using four classification algorithms-an SVM, KNN, decision tree, and probabilistic neural network. The study provides a comparative analysis of all of the classification methods using two-class MI data extracted from the PhysioNet EEG database. The proposed techniques based on a probabilistic neural network (PNN) as a classifier and PDC as a feature set outperformed the other classification and feature extraction techniques with a superior classification accuracy and a lower error rate. The research findings indicate that when the PDC was used as a feature set, the PNN attained the greatest overall average accuracy of 98.65%, whereas the same classifier was used to attain the greatest accuracy of 82.81% with the DTF. This study validates the activation of multiple brain regions during a motor task by achieving better classification outcomes through brain connectivity as compared to conventional features. Since the PDC outperformed the DTF as a feature set with its superior classification accuracy and low error rate, it has great potential for application in MI-based brain-computer interfaces.

A BCI-Based Vibrotactile Neurofeedback Training Improves Motor Cortical Excitability During Motor Imagery

In this study, we address the issue of whether vibrotactile feedback can enhance the motor cortex excitability translated into the plastic changes in local cortical areas during motor imagery (MI) BCI-based training. For this purpose, we focused on two of the most notable neurophysiological effects of MI - the event-related desynchronization (ERD) level and the increase in cortical excitability assessed with navigated transcranial magnetic stimulation (nTMS). For TMS navigation, we used individual high-resolution 3D brain MRIs. Ten BCI-naive and healthy adults participated in this study. The MI (rest or left/right hand imagery using Graz-BCI paradigm) tasks were performed separately in the presence and absence of feedback. To investigate how much the presence/absence of vibrotactile feedback in MI BCI-based training could contribute to the sensorimotor cortical activations, we compared the MEPs amplitude during MI after training with and without feedback. In addition, the ERD levels during MI BCI-based training were investigated. Our findings provide evidence that applying vibrotactile feedback during MI training leads to (i) an enhancement of the desynchronization level of mu-rhythm EEG patterns over the contralateral motor cortex area corresponding to the MI of the non-dominant hand; (ii) an increase in motor cortical excitability in hand muscle representation corresponding to a muscle engaged by the MI.

Revealing a multiplex brain network through the analysis of recurrences

A multilayer approach has recently received particular attention in network neuroscience as a suitable model to describe brain dynamics by adjusting its activity in different frequency bands, time scales, modalities, or ages to different layers of a multiplex graph. In this paper, we demonstrate an approach to a frequency-based multilayer functional network constructed from nonstationary multivariate data by analyzing recurrences in application to electroencephalography. Using the recurrence-based index of synchronization, we construct intralayer (within-frequency) and interlayer (cross-frequency) graph edges to model the evolution of a whole-head functional connectivity network during a prolonged stimuli classification task. We demonstrate that the graph edges' weights increase during the experiment and negatively correlate with the response time. We also show that while high-frequency activity evolves toward synchronization of remote local areas, low-frequency connectivity tends to establish large-scale coupling between them.

Age-Related Distinctions in EEG Signals during Execution of Motor Tasks Characterized in Terms of Long-Range Correlations

The problem of revealing age-related distinctions in multichannel electroencephalograms (EEGs) during the execution of motor tasks in young and elderly adults is addressed herein. Based on the detrended fluctuation analysis (DFA), differences in long-range correlations are considered, emphasizing changes in the scaling exponent α. Stronger responses in elderly subjects are confirmed, including the range and rate of increase in α. Unlike elderly subjects, young adults demonstrated about 2.5 times more pronounced differences between motor task responses with the dominant and non-dominant hand. Knowledge of age-related changes in brain electrical activity is important for understanding consequences of healthy aging and distinguishing them from pathological changes associated with brain diseases. Besides diagnosing age-related effects, the potential of DFA can also be used in the field of brain–computer interfaces.