EEG beta 2 power as surrogate marker for memory impairment: a pilot study

Kaiser, Andreas; Doppelmayr, Michael; Iglseder, Bernhard

doi:10.1017/s1041610217000758

Cited by 11 publications

(6 citation statements)

References 28 publications

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“…Low cost spontaneous speech data had been used by researchers to detect MCI or AD [14]- [17]. Relatively low-cost electroencephalography (EEG) is also being investigated to detect [2], [7], [18]- [23] and classify [21] MCI from other diseases that affect the cognitive state. Multi-channel EEG data have been used to characterize MCI or AD using EEG signals in various literature such as: (i) mismatch negativity (MMN) and auditory P300 component from 256-channel EEG [2], (ii) features extracted by recurrence quantification analysis (RQA) and cross recurrence quantification analysis (CRQA) from 14-channel EEG [21], (iii) spectral features extracted from 19-channel EEG [7], (iv) auditory P2 component computed from 64-channel EEG [22], (v) the auditory mismatch negativity (MMN) from 19-channel EEG [23], (vi) event-related potential (ERP) amplitude and latency from 256-channel EEG [24], (vii) accuracy and response time during low and high working memory conditions of memory task using 32channel EEG [19] etc.…”

Section: Introductionmentioning

confidence: 99%

A Single-Channel EEG-Based Approach to Detect Mild Cognitive Impairment via Speech-Evoked Brain Responses

Khatun

Morshed

Bidelman

2019

IEEE Trans. Neural Syst. Rehabil. Eng.

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Mild cognitive impairment (MCI) is the preliminary stage of dementia, which may lead to Alzheimer's disease (AD) in the elderly people. Therefore, early detection of MCI has the potential to minimize the risk of AD by ensuring the proper mental health care before it is too late. In this paper, we demonstrate a single-channel EEG-based MCI detection method, which is costeffective and portable, and thus suitable for regular home-based patient monitoring. We collected the scalp EEG data from 23 subjects, while they were stimulated with five auditory speech signals. The cognitive state of the subjects was evaluated by the Montreal cognitive assessment test (MoCA). We extracted 590 features from the event-related potential (ERP) of the collected EEG signals, which included time and spectral domain characteristics of the response. The top 25 features, ranked by the random forest method, were used for classification models to identify subjects with MCI. Robustness of our model was tested using leave-one-out cross-validation while training the classifiers. Best results (leave-one-out cross-validation accuracy 87.9%, sensitivity 84.8%, specificity 95%, and F score 85%) were obtained using support vector machine (SVM) method with radial basis kernel (RBF) (sigma = 10/cost = 10 2). Similar performances were also observed with logistic regression (LR), further validating the results. Our results suggest that single-channel EEG could provide a robust biomarker for early detection of MCI.

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Section: Introductionmentioning

confidence: 99%

A Single-Channel EEG-Based Approach to Detect Mild Cognitive Impairment via Speech-Evoked Brain Responses

Khatun

Morshed

Bidelman

2019

IEEE Trans. Neural Syst. Rehabil. Eng.

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“…Similarly, Kaiser et al identified significant positive correlations between frontal and parietal beta powers and delayed memory recall ( 95 ). Additionally, through time-frequency analysis, Axmacher et al found that reduced slow hippocampal activity in the delta frequency range supported long-term memory formation ( 96 ).…”

Section: Discussionmentioning

confidence: 90%

“…Jiang et al demonstrated that successful long-term memory encoding corresponds to decreased alpha power in the sensory region of the attended target and increased power in the region of the ignored target, thereby suppressing distractions during the rehearsal period (94). Similarly, Kaiser et al identified significant positive correlations between frontal and parietal beta powers and delayed memory recall (95). Additionally, through time-frequency analysis, Axmacher et al found that reduced slow hippocampal activity in the delta frequency range supported long-term memory formation (96).…”

Section: Higher Delayed Recall and Diminished Sw In Ad Under Eo In De...mentioning

confidence: 99%

Eyes-state-dependent alterations of magnetoencephalographic connectivity associated with delayed recall in Alzheimer’s disease via graph theory approach

Yuasa,

Hirosawa,

Soma

et al. 2023

Front. Psychiatry

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IntroductionAlzheimer’s disease (AD) is a neurodegenerative disorder characterized by memory impairment and cognitive decline. Electroencephalography (EEG) and magnetoencephalography (MEG) studies using graph theory show altered “Small-Worldness (SW)” properties in AD. This study aimed to investigate whether eye-state-dependent alterations in SW differ between patients with AD and healthy controls, considering the symptoms of AD.MethodsNineteen patients with AD and 24 healthy controls underwent MEG under different conditions (eyes-open [EO] and eyes-closed [EC]) and the Wechsler Memory Scale-Revised (WMS-R) with delayed recall. After the signal sources were mapped onto the Desikan–Killiany brain atlas, the statistical connectivity of five frequency bands (delta, theta, alpha, beta, and gamma) was calculated using the phase lag index (PLI), and binary graphs for each frequency band were constructed based on the PLI. Next, we measured SW as a graph metric and evaluated three points: the impact of AD and experimental conditions on SW, the association between SW and delayed recall, and changes in SW across experimental conditions correlated with delayed recall.ResultsSW in the gamma band was significantly lower in patients with AD (z = −2.16, p = 0.031), but the experimental conditions did not exhibit a significant effect in any frequency band. Next, in the AD group, higher scores on delayed recall correlated with diminished SW across delta, alpha, and beta bands in the EO condition. Finally, delayed recall scores significantly predicted relative differences in the SW group in the alpha band (t = −2.98, p = 0.009).DiscussionGiven that network studies could corroborate the results of previous power spectrum studies, our findings contribute to a multifaceted understanding of functional brain networks in AD, emphasizing that the SW properties of these networks change according to disease status, cognitive function, and experimental conditions.

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“…The comparable beta power in the frontal region between conditions demonstrated that learners had involved similar cognitive resources in vocabulary encoding and comprehension, whether with generated or provided contextual clues. However, higher parietal beta power was associated with internal-generated contextual clues since learners' recall processes typically involve retrieving contextual clues from their prior knowledge, alongside cognitive involvement during semantic processing (Tschentscher and Hauk, 2016;Kaiser et al, 2017). Besides the expected regions, greater beta power was also observed in the fronto-central, occipital, and temporoparietal regions when learners generated contexts themselves.…”

Section: The Impact Of Contextual Clues On Efl Learners' Mental Effor...mentioning

confidence: 89%

The impact of internal-generated contextual clues on EFL vocabulary learning: insights from EEG

Zhou,

2024

Front. Psychol.

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With the popularity of learning vocabulary online among English as a Foreign Language (EFL) learners today, educators and researchers have been considering ways to enhance the effectiveness of this approach. Prior research has underscored the significance of contextual clues in vocabulary acquisition. However, few studies have compared the context provided by instructional materials and that generated by learners themselves. Hence, this present study sought to explore the impact of internal-generated contextual clues in comparison to those provided by instructional materials on EFL learners’ online vocabulary acquisition. A total of 26 university students were enrolled and underwent electroencephalography (EEG). Based on a within-subjects design, all participants learned two groups of vocabulary words through a series of video clips under two conditions: one where the contexts were externally provided and the other where participants themselves generated the contexts. In this regard, participants were tasked with either viewing contextual clues presented on the screen or creating their own contextual clues for word comprehension. EEG signals were recorded during the learning process to explore neural activities, and post-tests were conducted to assess learning performance after each vocabulary learning session. Our behavioral results indicated that comprehending words with internal-generated contextual clues resulted in superior learning performance compared to using context provided by instructional materials. Furthermore, EEG data revealed that learners expended greater cognitive resources and mental effort in semantically integrating the meaning of words when they self-created contextual clues, as evidenced by stronger alpha and beta-band oscillations. Moreover, the stronger alpha-band oscillations and lower inter-subject correlation (ISC) among learners suggested that the generative task of creating context enhanced their top-down attentional control mechanisms and selective visual processing when learning vocabulary from videos. These findings underscored the positive effects of internal-generated contextual clues, indicating that instructors should encourage learners to construct their own contexts in online EFL vocabulary instruction rather than providing pre-defined contexts. Future research should aim to explore the limits and conditions of employing these two types of contextual clues in online EFL vocabulary learning. This could be achieved by manipulating the quality and understandability of contexts and considering learners’ language proficiency levels.

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EEG beta 2 power as surrogate marker for memory impairment: a pilot study

Cited by 11 publications

References 28 publications

A Single-Channel EEG-Based Approach to Detect Mild Cognitive Impairment via Speech-Evoked Brain Responses

A Single-Channel EEG-Based Approach to Detect Mild Cognitive Impairment via Speech-Evoked Brain Responses

Eyes-state-dependent alterations of magnetoencephalographic connectivity associated with delayed recall in Alzheimer’s disease via graph theory approach

The impact of internal-generated contextual clues on EFL vocabulary learning: insights from EEG

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