Classification of visuomotor tasks based on electroencephalographic data depends on age-related differences in brain activity patterns

2021 ◽  
Author(s):  
C. Goelz ◽  
K. Mora ◽  
J. Rudisch ◽  
R. Gaidai ◽  
E. Reuter ◽  
...  
2020 ◽  
pp. 003329411990034 ◽  
Author(s):  
Jacek Bielas ◽  
Łukasz Michalczyk

One of the well-documented behavioral changes that occur with advancing age is a decline in executive functioning, for example, attentional control. Age-related executive deficits are said to be associated with a deterioration of the frontal lobes. Neurofeedback is a training method which aims at acquiring self-control over certain brain activity patterns. It is considered as an effective approach to help improve attentional and self-management capabilities. However, studies evaluating the efficacy of neurofeedback training to boost executive functioning in an elderly population are still relatively rare and controversial. The aim of our study was to contribute to the assessment of the efficacy of neurofeedback as a method for enhancing executive functioning in the elderly. We provided a group of seniors with beta up-training (12–22 Hz), consisting of 20 sessions (30 minutes each), on the Cz site and tested its possible beneficiary influence on attentional control assessed by means of the Stroop and Simon tasks. The analysis of the subjects’ mean reaction times during consecutive tasks in the test and the retest, after implementation of neurofeedback training, showed a significant improvement. In contrast, the difference in reaction times between the test and the retest in the control group who had not been submitted to neurofeedback training was not significant.


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
E. Salari ◽  
Z. V. Freudenburg ◽  
M. P. Branco ◽  
E. J. Aarnoutse ◽  
M. J. Vansteensel ◽  
...  

Abstract For people suffering from severe paralysis, communication can be difficult or nearly impossible. Technology systems called brain-computer interfaces (BCIs) are being developed to assist these people with communication by using their brain activity to control a computer without any muscle activity. To benefit the development of BCIs that employ neural activity related to speech, we investigated if neural activity patterns related to different articulator movements can be distinguished from each other. We recorded with electrocorticography (ECoG), the neural activity related to different articulator movements in 4 epilepsy patients and classified which articulator participants moved based on the sensorimotor cortex activity patterns. The same was done for different movement directions of a single articulator, the tongue. In both experiments highly accurate classification was obtained, on average 92% for different articulators and 85% for different tongue directions. Furthermore, the data show that only a small part of the sensorimotor cortex is needed for classification (ca. 1 cm2). We show that recordings from small parts of the sensorimotor cortex contain information about different articulator movements which might be used for BCI control. Our results are of interest for BCI systems that aim to decode neural activity related to (actual or attempted) movements from a contained cortical area.


PLoS ONE ◽  
2014 ◽  
Vol 9 (5) ◽  
pp. e97296 ◽  
Author(s):  
Norberto Eiji Nawa ◽  
Hiroshi Ando

2019 ◽  
Author(s):  
Abdelhalim Elshiekh ◽  
Sivaniya Subramaniapillai ◽  
Sricharana Rajagopal ◽  
Stamatoula Pasvanis ◽  
Elizabeth Ankudowich ◽  
...  

AbstractRemembering associations between encoded items and their contextual setting is a feature of episodic memory. Although this ability deteriorates with age in general, there is substantial variability in how older individuals perform on episodic memory tasks. This variability may stem from genetic and/or environmental factors related to reserve, allowing some individuals to compensate for age-related decline through differential recruitment of brain regions. In this fMRI study, we tested predictions related to reserve and compensation in a large adult lifespan sample (N=154). We used multivariate Behaviour Partial Least Squares (B-PLS) analysis to examine how age, retrieval accuracy, and a proxy measure of reserve, impacted brain activity patterns during spatial and temporal context encoding and retrieval. Reserve modulated age-related compensatory brain responses in ventral visual, temporal, and fronto-parietal regions during memory encoding as a function of task demands. Activity in inferior parietal, medial temporal, and ventral visual regions were strongly impacted by age at encoding and retrieval, but were also related to individual differences in reserve. Our findings are consistent with the concepts of reserve and compensation and suggest that reserve may mitigate age-related decline by modulating compensatory brain responses in the aging brain.


2014 ◽  
Vol 28 (3) ◽  
pp. 148-161 ◽  
Author(s):  
David Friedman ◽  
Ray Johnson

A cardinal feature of aging is a decline in episodic memory (EM). Nevertheless, there is evidence that some older adults may be able to “compensate” for failures in recollection-based processing by recruiting brain regions and cognitive processes not normally recruited by the young. We review the evidence suggesting that age-related declines in EM performance and recollection-related brain activity (left-parietal EM effect; LPEM) are due to altered processing at encoding. We describe results from our laboratory on differences in encoding- and retrieval-related activity between young and older adults. We then show that, relative to the young, in older adults brain activity at encoding is reduced over a brain region believed to be crucial for successful semantic elaboration in a 400–1,400-ms interval (left inferior prefrontal cortex, LIPFC; Johnson, Nessler, & Friedman, 2013 ; Nessler, Friedman, Johnson, & Bersick, 2007 ; Nessler, Johnson, Bersick, & Friedman, 2006 ). This reduced brain activity is associated with diminished subsequent recognition-memory performance and the LPEM at retrieval. We provide evidence for this premise by demonstrating that disrupting encoding-related processes during this 400–1,400-ms interval in young adults affords causal support for the hypothesis that the reduction over LIPFC during encoding produces the hallmarks of an age-related EM deficit: normal semantic retrieval at encoding, reduced subsequent episodic recognition accuracy, free recall, and the LPEM. Finally, we show that the reduced LPEM in young adults is associated with “additional” brain activity over similar brain areas as those activated when older adults show deficient retrieval. Hence, rather than supporting the compensation hypothesis, these data are more consistent with the scaffolding hypothesis, in which the recruitment of additional cognitive processes is an adaptive response across the life span in the face of momentary increases in task demand due to poorly-encoded episodic memories.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Meir Meshulam ◽  
Liat Hasenfratz ◽  
Hanna Hillman ◽  
Yun-Fei Liu ◽  
Mai Nguyen ◽  
...  

AbstractDespite major advances in measuring human brain activity during and after educational experiences, it is unclear how learners internalize new content, especially in real-life and online settings. In this work, we introduce a neural approach to predicting and assessing learning outcomes in a real-life setting. Our approach hinges on the idea that successful learning involves forming the right set of neural representations, which are captured in canonical activity patterns shared across individuals. Specifically, we hypothesized that learning is mirrored in neural alignment: the degree to which an individual learner’s neural representations match those of experts, as well as those of other learners. We tested this hypothesis in a longitudinal functional MRI study that regularly scanned college students enrolled in an introduction to computer science course. We additionally scanned graduate student experts in computer science. We show that alignment among students successfully predicts overall performance in a final exam. Furthermore, within individual students, we find better learning outcomes for concepts that evoke better alignment with experts and with other students, revealing neural patterns associated with specific learned concepts in individuals.


2021 ◽  
Author(s):  
Adeline Jabès ◽  
Giuliana Klencklen ◽  
Paolo Ruggeri ◽  
Christoph M. Michel ◽  
Pamela Banta Lavenex ◽  
...  

AbstractAlterations of resting-state EEG microstates have been associated with various neurological disorders and behavioral states. Interestingly, age-related differences in EEG microstate organization have also been reported, and it has been suggested that resting-state EEG activity may predict cognitive capacities in healthy individuals across the lifespan. In this exploratory study, we performed a microstate analysis of resting-state brain activity and tested allocentric spatial working memory performance in healthy adult individuals: twenty 25–30-year-olds and twenty-five 64–75-year-olds. We found a lower spatial working memory performance in older adults, as well as age-related differences in the five EEG microstate maps A, B, C, C′ and D, but especially in microstate maps C and C′. These two maps have been linked to neuronal activity in the frontal and parietal brain regions which are associated with working memory and attention, cognitive functions that have been shown to be sensitive to aging. Older adults exhibited lower global explained variance and occurrence of maps C and C′. Moreover, although there was a higher probability to transition from any map towards maps C, C′ and D in young and older adults, this probability was lower in older adults. Finally, although age-related differences in resting-state EEG microstates paralleled differences in allocentric spatial working memory performance, we found no evidence that any individual or combination of resting-state EEG microstate parameter(s) could reliably predict individual spatial working memory performance. Whether the temporal dynamics of EEG microstates may be used to assess healthy cognitive aging from resting-state brain activity requires further investigation.


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