Event-related synchronisation responses to N-back memory tasks discriminate between healthy ageing, mild cognitive impairment, and mild Alzheimer's disease

Fraga, Francisco J.; Ferreira, Luiz Alves; Falk, Tiago H.; Johns, Erin; Phillips, Natalie

doi:10.1109/icassp.2017.7952299

Cited by 11 publications

(26 citation statements)

References 23 publications

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“…Consistent with previous reports in resting-state EEG studies (Babiloni et al 2006) and studies with a visual memory task (F. J. Fraga et al 2017), we observed univariate differences between HC and MCI in the temporal and the fronto-central electrodes.…”

Section: Discussionsupporting

confidence: 92%

“…Previous resting-state and task-based EEG studies have focused on univariate changes (e.g., ERP, frequency bands, connectivity) in patients with MCI and individuals with mild to moderate AD (P. Missonnier et al 2007; F. J. Fraga et al 2017; Pijnenburg et al 2004; Pascal Missonnier et al 2005; Vecchio et al 2014; Francisco J. Fraga et al 2018; Babiloni et al 2016).…”

Section: Discussionmentioning

confidence: 99%

“…A few studies have also used EEG to associate abnormalities in memory function with cognitive impairment during both encoding and decoding stages of working memory (Pijnenburg et al 2004; P. Missonnier et al 2007; Francisco J. Fraga et al 2018; F. J. Fraga et al 2017) as well as episodic memory tasks (Han et al 2017).…”

Section: Introductionmentioning

confidence: 99%

“…Electroencephalography (EEG) is widely used to study the resting-state neural activity in the brain of patients with MCI and mild AD (5)(6)(7)(8)(9)(10)(11). A few studies have also used EEG to associate abnormalities in memory function with cognitive impairment during both encoding and decoding stages of working memory (7,(12)(13)(14) as well as episodic memory tasks (15).…”

Section: Introductionmentioning

confidence: 99%

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Temporal dynamics of animacy categorization in the brain of patients with mild cognitive impairment

Karimi¹,

Marefat²,

Khanbagi³

et al. 2020

Preprint

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Electroencephalography (EEG) has been commonly used to measure brain alterations in Alzheimer’s Disease (AD). However, reported changes are limited to those obtained from using univariate measures, including activation level and frequency bands. To look beyond the activation level, we used multivariate pattern analysis (MVPA) to elicit the pattern of information processing from EEG responses to an animacy categorization task. Comparing healthy controls (HC) with patients with mild cognitive impairment (MCI), we found that the neural speed of animacy information processing is decreased in MCI patients. Moreover, we found critical time-points during which the representational pattern of animacy for MCI patients was significantly discriminable from that of HC, while the activation level remained unchanged. Together, these results suggest that the speed and pattern of animacy information processing provide clinically useful information as a potential biomarker for detecting early changes in MCI and AD patients.

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Section: Discussionsupporting

confidence: 92%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Temporal dynamics of animacy categorization in the brain of patients with mild cognitive impairment

Karimi¹,

Marefat²,

Khanbagi³

et al. 2020

Preprint

View full text Add to dashboard Cite

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“…Besides being time locked, EEG activity is also phase locked and thus receives the name of event-related potentials (ERP). When the EEG activity is not phase locked, it is called induced activity [ 59 , 60 ] and can be analyzed either by event-related (de) synchronization (ERD/ERS) [ 44 , 61 ] or by event-related oscillations (ERO) [ 62 ]. Events can be related to sensorial perceptive, motor, and cognitive processes [ 43 , 45 , 62 ].…”

Section: Introductionmentioning

confidence: 99%

Systematic Review on Resting-State EEG for Alzheimer’s Disease Diagnosis and Progression Assessment

et al. 2018

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Alzheimer's disease (AD) is a neurodegenerative disorder that accounts for nearly 70% of the more than 46 million dementia cases estimated worldwide. Although there is no cure for AD, early diagnosis and an accurate characterization of the disease progression can improve the quality of life of AD patients and their caregivers. Currently, AD diagnosis is carried out using standardized mental status examinations, which are commonly assisted by expensive neuroimaging scans and invasive laboratory tests, thus rendering the diagnosis time consuming and costly. Notwithstanding, over the last decade, electroencephalography (EEG) has emerged as a noninvasive alternative technique for the study of AD, competing with more expensive neuroimaging tools, such as MRI and PET. This paper reports on the results of a systematic review on the utilization of resting-state EEG signals for AD diagnosis and progression assessment. Recent journal articles obtained from four major bibliographic databases were analyzed. A total of 112 journal articles published from January 2010 to February 2018 were meticulously reviewed, and relevant aspects of these papers were compared across articles to provide a general overview of the research on this noninvasive AD diagnosis technique. Finally, recommendations for future studies with resting-state EEG were presented to improve and facilitate the knowledge transfer among research groups.

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Treatment effects on event-related EEG potentials and oscillations in Alzheimer's disease

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et al. 2022

International Journal of Psychophysiology

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Event-related synchronisation responses to N-back memory tasks discriminate between healthy ageing, mild cognitive impairment, and mild Alzheimer's disease

Cited by 11 publications

References 23 publications

Temporal dynamics of animacy categorization in the brain of patients with mild cognitive impairment

Temporal dynamics of animacy categorization in the brain of patients with mild cognitive impairment

Systematic Review on Resting-State EEG for Alzheimer’s Disease Diagnosis and Progression Assessment

Treatment effects on event-related EEG potentials and oscillations in Alzheimer's disease

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