Neural Bases of Age-Related Sensorimotor Slowing in the Upper and Lower Limbs

Cardiorespiratory fitness is associated with cognitive performance in 80 + -year-olds: Detangling processing levels

Cardiorespiratory fitness is known to protect against cognitive decline in older adults. Specifically, it has been shown that physical activity and fitness are beneficial for executive functions that are crucial for independent living up to old age. In this study, 115 individuals aged 80 years and older underwent a cardiorespiratory fitness assessment using the two-minute step test and had their electroencephalogram recorded during a colored flanker task in order to measure executive function performance. Cardiorespiratory fitness was related to quicker responses during the flanker task. A mediation analysis was carried out to determine whether these positive effects were mediated through event-related potentials (N1, N2, or P3) or motor-related cortical potentials (MRCP). Cardiorespiratory fitness was related to better visual discriminative processing as indicated by larger occipital N1 amplitudes. In addition, fitness was associated with larger MRCP amplitudes, which are a correlate of the response generation process. Fitness was not found to have a significant effect on fronto-central N2 or parietal P3, which are thought to capture cognitive control processes such as conflict detection and response inhibition. Moreover, all effects reported were present in all three flanker trial conditions (congruent, neutral, and incongruent). Thus, these results indicate that the quicker response times in fitter people were related to visual processing and motor response generation rather than cognitive control.

The Impact of Mental Fatigue on a Strength Endurance Task: Is There a Role for the Movement-Related Cortical Potential?

PURPOSE

Several mechanisms have been proposed to explain how mental fatigue degrades sport performance. In terms of endurance performance, a role for an increased perceived exertion has been demonstrated. Using electroencephalography and, more specifically, the movement-related cortical potential (MRCP), the present study explored the neural mechanisms that could underlie the mental fatigue-associated increase in perceived exertion.

METHODS

Fourteen participants (age, 23 ± 2 yr; 5 women, 9 men) performed one familiarization and two experimental trials in a randomized, blinded, crossover study design. Participants had to complete a submaximal leg extension task after a mentally fatiguing task (EXP; individualized 60-min Stroop task) or control task (CON; documentary). The leg extension task consisted of performing 100 extensions at 35% of 1 repetition maximum, during which multiple physiological (heart rate, electroencephalography) and subjective measures (self-reported feeling of mental fatigue, cognitive load, behand motivation, ratings of perceived exertion) were assessed.

RESULTS

Self-reported feeling of mental fatigue was higher in EXP (72 ± 18) compared with CON (37 ± 17; P < 0.001). A significant decrease in flanker accuracy was detected only in EXP (from 0.96 ± 0.03% to 0.03%; P < 0.05). No significant differences between conditions were found in MRCP characteristics and perceived exertion. Specifically in EXP, alpha wave power increased during the leg extension task ( P < 0.01).

CONCLUSIONS

Mental fatigue did not impact the perceived exertion or MRCP characteristics during the leg extension task. This could be related to low perceived exertion and/or the absence of a performance outcome during the leg extension task. The increase in alpha power during the leg extension task in EXP suggests that participants may engage a focused internal attention mechanism to maintain performance and mitigate feelings of fatigue.

Enhancing Motor Sequence Learning via Transcutaneous Auricular Vagus Nerve Stimulation (taVNS): An EEG Study

Motor learning plays a crucial role in human life, and various neuromodulation methods have been utilized to strengthen or improve it. Transcutaneous auricular vagus nerve stimulation (taVNS) has gained increasing attention due to its non-invasive nature, affordability and ease of implementation. Although the potential of taVNS on regulating motor learning has been suggested, its actual regulatory effect has yet been fully explored. Electroencephalogram (EEG) analysis provides an in-depth understanding of cognitive processes involved in motor learning so as to offer methodological support for regulation of motor learning. To investigate the effect of taVNS on motor learning, this study recruited 22 healthy subjects to participate a single-blind, sham-controlled, and within-subject serial reaction time task (SRTT) experiment. Every subject involved in two sessions at least one week apart and received a 20-minute active/sham taVNS in each session. Behavioral indicators as well as EEG characteristics during the task state, were extracted and analyzed. The results revealed that compared to the sham group, the active group showed higher learning performance. Additionally, the EEG results indicated that after taVNS, the motor-related cortical potential amplitudes and alpha-gamma modulation index decreased significantly and functional connectivity based on partial directed coherence towards frontal lobe was enhanced. These findings suggest that taVNS can improve motor learning, mainly through enhancing cognitive and memory functions rather than simple movement learning. This study confirms the positive regulatory effect of taVNS on motor learning, which is particularly promising as it offers a potential avenue for enhancing motor skills and facilitating rehabilitation.

Classification of cognitive impairment in older adults based on brain functional state measurement data via hierarchical clustering analysis

Introduction

Cognitive impairment (CI) is a common degenerative condition in the older population. However, the current methods for assessing CI are not based on brain functional state, which leads to delayed diagnosis, limiting the initiatives towards achieving early interventions.

Methods

A total of one hundred and forty-nine community-dwelling older adults were recruited. Montreal Cognitive Assessment (MoCA) and Mini-Mental State Exam (MMSE) were used to screen for CI, while brain functional was assessed by brain functional state measurement (BFSM) based on electroencephalogram. Bain functional state indicators associated with CI were selected by lasso and logistic regression models (LRM). We then classified the CI participants based on the selected variables using hierarchical clustering analysis.

Results

Eighty-one participants with CI detected by MoCA were divided into five groups. Cluster 1 had relatively lower brain functional states. Cluster 2 had highest mental task-switching index (MTSi, 13.7 ± 3.4), Cluster 3 had the highest sensory threshold index (STi, 29.9 ± 7.7), Cluster 4 had high mental fatigue index (MFi) and cluster 5 had the highest mental refractory period index (MRPi), and external apprehension index (EAi) (21.6 ± 4.4, 35.4 ± 17.7, respectively). Thirty-three participants with CI detected by MMSE were divided into 3 categories. Cluster 1 had the highest introspective intensity index (IIi, 63.4 ± 20.0), anxiety tendency index (ATi, 67.2 ± 13.6), emotional resistance index (ERi, 50.2 ± 11.9), and hypoxia index (Hi, 41.8 ± 8.3). Cluster 2 had the highest implicit cognitive threshold index (ICTi, 87.2 ± 12.7), and cognitive efficiency index (CEi, 213.8 ± 72.0). Cluster 3 had higher STi. The classifications both showed well intra-group consistency and inter-group variability.

Conclusion

In our study, BFSM-based classification can be used to identify clinically and brain-functionally relevant CI subtypes, by which clinicians can perform personalized early rehabilitation.

A data-driven machine learning approach for brain-computer interfaces targeting lower limb neuroprosthetics

Prosthetic devices that replace a lost limb have become increasingly performant in recent years. Recent advances in both software and hardware allow for the decoding of electroencephalogram (EEG) signals to improve the control of active prostheses with brain-computer interfaces (BCI). Most BCI research is focused on the upper body. Although BCI research for the lower extremities has increased in recent years, there are still gaps in our knowledge of the neural patterns associated with lower limb movement. Therefore, the main objective of this study is to show the feasibility of decoding lower limb movements from EEG data recordings. The second aim is to investigate whether well-known neuroplastic adaptations in individuals with an amputation have an influence on decoding performance. To address this, we collected data from multiple individuals with lower limb amputation and a matched able-bodied control group. Using these data, we trained and evaluated common BCI methods that have already been proven effective for upper limb BCI. With an average test decoding accuracy of 84% for both groups, our results show that it is possible to discriminate different lower extremity movements using EEG data with good accuracy. There are no significant differences (p = 0.99) in the decoding performance of these movements between healthy subjects and subjects with lower extremity amputation. These results show the feasibility of using BCI for lower limb prosthesis control and indicate that decoding performance is not influenced by neuroplasticity-induced differences between the two groups.

Does Cognitive Training Improve Mobility, Enhance Cognition, and Promote Neural Activation?

A close inter-relationship between mobility and cognition is reported in older adults, with improvements in gait performance noticeable after cognitive remediation in frail individuals. The aim of this study was to evaluate the efficacy of computerized cognitive training (CCT) on mobility in healthy, independently living older adults, and to determine whether CCT is associated with changes in neural activation for mobility-related brain processes. Using a randomized single-blind control design, sixty-three non-demented adults age 60 y and older (mean age = 67 y; 76% female, mean Montreal Cognitive Assessment [MoCA] score = 27) were recruited from a local Senior Activity Center. Participants were randomly assigned to either a 2-month CCT program (8 weeks, 3x/week, 40 min/session) or a wait-list control group. Primary outcome was self-selected gait speed during single- and dual-task walking. Secondary outcome was executive function on Trail Making Test (TMT), Part B. Neural activity was assessed via electroencephalography/event-related potentials (EEG/ERPs) targeting lower-limb performance. Results from a linear mixed effect model, adjusted for baseline MoCA score, age, gender, and study completion revealed that compared to controls, CCT improved gait speed during the dual-task (p = 0.008) but not during the single-task walking condition (p = 0.057). CCT also improved executive function (p = 0.024). Further, shorter foot reaction time responses (p = 0.019) were found with enhanced neural activation over sensorimotor areas, with shorter ERP latencies during the P2 component (p = 0.008) and enhanced motor responses (p = 0.009) also evident in the CCT group after the intervention. Overall, the electrophysiological findings suggest possible neural adaptations that could explain improvements in mobility and executive functions associated with CCT in healthy older adults.