Elsevier

NeuroImage

Volume 59, Issue 4, 15 February 2012, Pages 4132-4140
NeuroImage

Induced oscillatory responses during the Sternberg's visual memory task in patients with Alzheimer's disease and mild cognitive impairment

https://doi.org/10.1016/j.neuroimage.2011.10.061Get rights and content

Abstract

In this study we used magnetoencephalography during a modified version of the Sternberg's memory recognition task performed by patients with early Alzheimer's disease (AD), mild cognitive impairment (MCI), and by age-matched healthy controls to identify differences in induced oscillatory responses. For analyses, we focused on the retention period of the working memory task. Multiple-source beamformer and Brain Voyager were used for localization of source-power changes across the cortex and for statistic group analyses, respectively. We found significant differences in oscillatory response during the task, specifically in beta and gamma frequency bands: patients with AD showed reduced beta event-related desynchronization (ERD) in the right central area compared to controls, and reduced gamma ERD in the left prefrontal and medial parietal cortex compared to patients with MCI. Our findings suggest that reduced oscillatory responses over certain brain regions in high frequency bands (i.e., beta, gamma), and especially in the beta band that was significantly different between AD patients and healthy subjects, may represent brain electromagnetic changes underlying visual-object working memory dysfunction in early AD, and a neurophysiological indicator of cognitive decline.

Highlights

► We explored MEG performance during working memory in AD, MCI and controls. ► We focused on induced-oscillatory response during working-memory retention. ► Reduced beta ERD in right central and prefrontal cortex in AD vs. Controls. ► Reduced gamma ERD in left precuneus and prefrontal cortex in AD vs. MCI. ► Beta and gamma power changes as neurophysiological markers of cognitive decline.

Introduction

Alzheimer's disease (AD) is the most common type of dementia and one of the main health problems in the elderly worldwide. Its overall prevalence is more than 1% of the general population and reaches 20% for those aged 80 or over (Ramaroson et al., 2003). AD is characterized by neuronal degeneration in several brain regions with widespread neuronal cell loss and the presence of neurofibrillary tangles and senile plaques. In the early stages of the disease, the most commonly recognized symptom is memory loss, in particular difficulty in remembering recently learned facts, as well as problems with thinking and concentration. In addition, the concept of a prodromal stage of AD, termed mild cognitive impairment (MCI), has been proposed (Petersen, 2004). Recent studies have demonstrated that pharmacological treatment for early AD and MCI can slow the progression of the disease (Feldman and Jacova, 2005). Therefore, an early diagnosis and treatment appear to be a very important factor for improving prognosis in patients with AD.

Magnetoencephalography (MEG) is a technique specifically designed to measure neural activity noninvasively featuring high time and spatial resolution. Unlike other neurophysiological techniques (e.g., electroencephalography — EEG), MEG can directly detect the electromagnetic activity of the brain without interferences of skin, skull and cerebral fluid, which act as a low pass filter (Hämäläinen, 1992). Thus, MEG is more suitable to explore brain oscillations, especially fast activity in beta and gamma bands, compared to EEG. However, MEG has not extensively been used for diagnosis of AD. Most MEG studies on AD and MCI have employed single dipole as their core method of analysis (Fernández et al., 2002, Fernández et al., 2006, Maestú et al., 2001, Maestú et al., 2006). This method has proven useful for studying focal brain activity, particularly epileptic discharges. However, findings from several neuroimaging and neurophysiological studies suggest that a wide area of the brain is activated in higher information processing such as memorization (Cohen et al., 1997, Jokisch and Jensen, 2007), and that induced oscillatory activity may be the key to understanding functional communication in the brain, especially with regard to memory and integrated functions (Başar et al., 2001, Ishii et al., 2009, Pfurtscheller and Lopes da Silva, 1999). Thus, applying MEG-dipole modeling, which identifies center of gravity rather than the volume of activation might not be sufficient to visualize abnormal activity in an extended network of sources underlying cognitive dysfunction in AD.

In the last decades, different approaches have been used to analyze MEG activity during cognitive task performance. For instance, minimum norm estimation (MNE) procedure has extensively been used to estimate the cortical origin of the brain electromagnetic response. MNE models have already been applied for source reconstruction of MEG data in patients with dementia or in healthy elderly with subjective memory complaints (Maestú et al., 2008, Maestú et al., 2011). Beamformers approach is a spatial filtering method which has also become increasingly valuable for source reconstruction of MEG activity (Ishii et al., 1999, Robinson and Rose, 1992). Although beamformers analyses are unable to distinguish two sources if their time-courses are 100% correlated, unlike MNE, they can easily handle both superficial and deep sources, and a variety of statistical analyses can be easily implemented (Huang et al., 2004). These approaches have been most successful in identifying induced changes in cortical oscillatory power that do not result in a strong average signal (Hillebrand et al., 2005). Beamformers, in particular, have given us an insight into the dynamics of oscillatory changes across the cortex not explored previously with traditional analysis that rely on averaged evoked responses (Ishii et al., 2009). By using MEG beamformer, the topographic mapping of source-power changes across the brain is obtained and locations with significant neuronal activation can be detected (Chen et al., 2006). In particular, multiple source beamformer (MSBF), a modified version of the linearly constrained minimum variance vector beamformer in the time frequency domain, has proven to be of great value in the identification of oscillatory activity source-power changes induced by sensory and cognitive tasks in dementia (Kurimoto et al., 2008) and other neuropsychiatric disorders such as psychosis (Canuet et al., 2010) and autism (Honaga et al., 2010).

The assessment of EEG/MEG induced oscillatory response in different frequency bands in terms of power decrease or event-related desynchronization (ERD) and power increase or event-related synchronization (ERS) is a valuable way to reveal different aspects of information processing in the normal and pathological brain (Pfurtscheller and Lopes da Silva, 1999). Earlier ERD/ERS studies during a memory task focused mainly on changes in theta (4–8 Hz), alpha (8–15 Hz) and beta (15–30 Hz) frequency bands. Induced oscillatory responses in theta and alpha activity, for example, have been reported associated with working memory (Bastiaansen et al., 2002, Jensen and Tesche, 2002) and attention (Kahana et al., 2001), while event-related beta oscillatory response, in particular beta ERD, extensively investigated in relation to motor function, has been proposed to underlie working memory processes, as well (Karrasch et al., 2004, Pesonen et al., 2007). In addition, EEG and MEG research on cognitive function has recently shifted to high frequency oscillations (i.e., gamma frequency band). This fast cortical oscillatory activity is thought to be associated with various cognitive processes, and therefore its alteration appears to be an important mechanism underlying psychiatric and neurological disorders (Grabska-Barwińska and Zygierewicz, 2006, Jokisch and Jensen, 2007, Uhlhaas and Singer, 2006).

Based on the fact that memory impairment is a cardinal clinical feature of AD and MCI, and that task-induced oscillatory brain activity in different frequency bands provide important clues to underlying cognitive processes (Başar et al., 2001, Pfurtscheller and Lopes da Silva, 1999), several studies have investigated abnormal event-related responses during memory tasks in demented patients. An MEG study by Babiloni et al. (2005) reported that patients with dementia showed increased alpha ERD during the retention period of a memory task. Meanwhile, Karrasch et al. (2006) study using EEG found that patients with MCI showed increased ERD in the frequency range of 10–20 Hz during the encoding period compared to controls, whereas patients with AD showed decreased ERD in the 7–17 Hz frequencies during the retrieval period compared to controls. This activity was observed particularly in anterior and left temporal electrodes (Karrasch et al., 2006). In addition, another EEG study reported decreased 15–25 Hz ERS in parietal electrodes during a 2-back task in patients with progressive MCI and AD relative to controls (Missonnier et al., 2007). However, there are only few functional imaging studies evaluating ERD/ERS during a memory task in patients with AD and MCI in the frequency range from theta to gamma.

In the present study, we used MEG beamformer during a visual working memory task in patients with early AD and compared the results with those of patients with MCI and normal controls using Brain Voyager to identify abnormal spatial patterns of oscillatory activity in the wide frequency range.

Section snippets

Subjects

Thirteen patients with early AD, thirteen with amnestic MCI, and fourteen normal elderly controls were enrolled in this study. All patients were recruited from the outpatient clinic of Psychiatry at Osaka University Hospital. The study was carried out in accordance with the Declaration of Helsinki, and approved by the Hospital Ethics Committee. Written informed consent was obtained from all participants. The diagnosis of probable AD was established according to the National Institute of

Demographic, clinical and behavioral results

The demographic data are shown in Table. 1. No significant differences were indicated in either age (d.f. = 38, p = 0.25) or sex (d.f. = 2, T = 0.43, p = 0.81) across the three groups. The neuropsychological assessment revealed significant differences in MMSE scores between AD and MCI patients (Kruskal–Wallis test, p < 0.01), as well as between AD patients and controls (Kruskal–Wallis test, p < 0.01). For the ADAS-Cog and CDR scores a significant difference was found between AD and MCI patients

Discussion

In the present study, we compared induced oscillatory activity during the retention period of a modified version of the Sternberg's memory recognition task in patients with early AD and MCI, and in normal controls in an attempt to detect early brain electromagnetic changes underlying memory impairment in AD. We found pronounced power changes (i.e., decrease in power or ERD) exceeding 10% in theta, alpha and beta frequency bands in patients and controls, with a similar topographic pattern. This

Funding sources

This study was supported in part by the Grant-in-Aid for Scientific Research (No. 21591516) from the Japan Society for the Promotion of Science (JSPS).

Conflicts of interest

None.

References (55)

  • E. Honaga et al.

    Post-movement beta rebound abnormality as indicator of mirror neuron system dysfunction in autistic spectrum disorder: an MEG study

    Neurosci. Lett.

    (2010)
  • N.F. Ince et al.

    Classification of schizophrenia with spectro-temporo-spatial MEG patterns in working memory

    Clin. Neurophysiol.

    (2009)
  • R. Ishii et al.

    Cortical oscillatory power changes during auditory oddball task revealed by spatially filtered magnetoencephalography

    Clin. Neurophysiol.

    (2009)
  • B.W. Johnson et al.

    Measurement of brain function in pre-school children using a custom sized whole-head MEG sensor array

    Clin. Neurophysiol.

    (2010)
  • M.J. Kahana et al.

    Theta returns

    Curr. Opin. Neurobiol.

    (2001)
  • M. Karrasch et al.

    Effects of normal aging on event-related desynchronization/synchronization during a memory task in humans

    Neurosci. Lett.

    (2004)
  • M. Karrasch et al.

    Brain oscillatory responses to an auditory-verbal working memory task in mild cognitive impairment and Alzheimer's disease

    Int. J. Psychophysiol.

    (2006)
  • R. Kurimoto et al.

    Event-related synchronization of alpha activity in early Alzheimer's disease and mild cognitive impairment: an MEG study combining beamformer and group comparison

    Neurosci. Lett.

    (2008)
  • S.C. Li et al.

    Aging condition: from neuromodulation to representation

    Trends Cogn. Sci.

    (2001)
  • F. Maestú et al.

    Medial temporal lobe neuromagnetic hypoactivation and risk for developing cognitive decline in elderly population: a 2-year follow-up study

    Neurobiol. Aging

    (2006)
  • F. Maestú et al.

    Increased biomagnetic activity in the ventral pathway in mild cognitive impairment

    Clin. Neurophysiol.

    (2008)
  • F. Maestú et al.

    Increased biomagnetic activity in healthy elderly with subjective memory complaints

    Clin. Neurophysiol.

    (2011)
  • P. Missonnier et al.

    Working memory load-related electroencephalographic parameters can differentiate progressive from stable mild cognitive impairment

    Neuroscience

    (2007)
  • S. Oshino et al.

    Magnetoencephalographic analysis of cortical oscillatory activity in patients with brain tumors: synthetic aperture magnetometry (SAM) functional imaging of delta band activity

    Neuroimage

    (2007)
  • M. Pesonen et al.

    Brain oscillatory 1–30 Hz EEG ERD/ERS responses during the different stages of an auditory memory search task

    Neurosci. Lett.

    (2006)
  • M. Pesonen et al.

    Brain oscillatory 4–30 Hz responses during a visual n-back memory task with varying memory load

    Brain Res.

    (2007)
  • G. Pfurtscheller et al.

    Event-related EEG/MEG synchronization and desynchronization: basic principles (review)

    Clin. Neurophysiol.

    (1999)
  • Cited by (0)

    1

    Fax: + 81 6 6879 3059.

    View full text