Regular paperMCI patients’ EEGs show group differences between those who progress and those who do not progress to AD
Introduction
Mild cognitive impairment (MCI) is a state of the elderly brain intermediate between normal cognition and dementia, being mainly characterized by objective evidence of memory impairment not yet encompassing the definition of dementia (Petersen et al., 1995, Petersen et al., 2001, Petersen and Negash, 2008).
In order to plan optimal therapeutic, organizational and rehabilitative interventions for MCI, a reliable prognostic indicator on the likelihood of progression to dementia would be required (Portet et al., 2006). Along this line, electroencephalogram (EEG) would be an ideal candidate to this issue, since it is a widely diffused, non-invasive and low-cost procedure.
It has been recently evidenced that EEG theta power (3.5–7.5 Hz) is higher in MCI subjects who will convert to Alzheimer's disease (AD) compared with MCI subjects who will not (Prichep et al., 2006). In an independent study of the same year it was showed that delta (temporal), theta (parietal, occipital and temporal), and alpha1 (central, parietal, occipital, temporal and limbic) sources were stronger in MCI converted in AD than in stable subjects and the risk of progression could be calculated on annual basis (Gauthier et al., 2006, Rossini et al., 2006). A recent study showed that converters MCI were differentiated from stable MCI subjects by a reduction of alpha power over posterior leads. Reduction of alpha power and mean frequency were significantly correlated with poorer cognitive performance in psychometric tests (Luckhaus et al., 2008). More recently, individual risk of progression to AD has been identified by using a supervised artificial network EEG analysis (Rossini et al., 2008).
Selective modifications of individual rhythms could be more related to behavioural paradigms such as stimulus onset and motor response (Canolty et al., 2006, Missonnier et al., 2007) as well as to various recording artifacts (Moretti et al., 2003). In contrast, when the ratio between frequencies is considered, the events of interest are features of the ongoing oscillatory activity itself. That is, frequency ratio refers to reciprocal dependence between distinct frequency bands of the ongoing EEG rather than dependence between the EEG and an external/internal events and/or undesired artifacts. For this reason it could be a useful tool in the analysis of rest EEG, together with the single frequency bands power analysis.
A large body of the literature has previously demonstrated that in subjects with cognitive decline is present an increase of theta relative power (Moretti et al., 2007a, Moretti et al., 2007b, Moretti et al., 2009b), a decrease of gamma relative power (Stam et al., 2003, Moretti et al., 2009b) as well as an increase of high alpha as compared to low alpha band (Moretti et al., 2007b). On the whole theta/gamma ratio and alpha3/alpha2 ratio could be considered reliable EEG markers of cognitive decline.
As a working hypothesis, EEG markers like theta/gamma and alpha3/alpha2 power ratio could show different modifications in patients with MCI who convert in AD from patients who will not. In the present study the possibility of two EEG markers of cognitive decline (increase of theta/gamma and increase of alpha3/alpha2 relative power ratio) to predict conversion to AD was investigated in subjects with MCI, also characterized by hippocampal volume measures and neuropsychological (NPS) test scores.
Section snippets
Subjects
For the present study, 76 subjects with MCI were recruited from the memory Clinic of the Scientific Institute for Research and Care (IRCCS) of Alzheimer's and psychiatric diseases ‘Fatebenefratelli’ in Brescia, Italy. All experimental protocols had been approved by the local Ethics Committee. Informed consent was obtained from all participants or their caregivers, according to the Code of Ethics of the World Medical Association (Declaration of Helsinki).
Diagnostic criteria
Patients were taken from a prospective
Results
Table 1 summarizes the ANOVA results of demographic variables (age, education and MMSE score), morphostructural measurements (hippocampal and WMHs volume) and EEG markers (theta/gamma and alpha3/alpha2 ratio). No statistical difference was found in age, education and the WMHs volume. MMSE score and hippocampal volume showed significant statistical difference (F2,73 = 7.31; p < 0.001 and F2,73 = 4.65; p < 0.01, respectively). Duncan post hoc analysis found that both the MMSE score and hippocampal volume
MCI patient, hippocampal volume and NPS tests
MCI subjects who will convert to AD showed the lowest MMSE score and the smallest total hippocampal volume at diagnosis. These findings are in agreement with well-known features of MCI patients at risk for AD (Portet et al., 2006, Dubois et al., 2007). On the whole, stable MCI had the best NPS performances, confirming the reliability of our results. Moreover, MCI-AD patients show a different NPS profile impairment as regards to MCI non-AD converters. Indeed, they were impaired in memory test
Conclusion
Theta/gamma and alpha3/alpha2 ratio could be promising prognostic markers in MCI patients. In particular, the increase of high alpha frequency seems to be associated with conversion in AD. The integration of EEG markers together with other diagnostic tools could allow a better classification of MCI patients.
Conflict of interest
Authors have no conflict of interests.
Acknowledgment
We thank Dr. Carlo Miniussi, for the precious help in the collection of the data used in the present study.
References (69)
- et al.
Sources of cortical rhythms change as a function of cognitive impairment in pathological aging: a multi-centric study
Clin. Neurophysiol.
(2006) - et al.
Research criteria for the diagnosis of Alzheimer's disease: revising the NINCDS–ADRDA criteria
Lancet Neurol.
(2007) - et al.
Mini mental state’: a practical method for grading the cognitive state of patients for clinician
J. Psychiatr. Res.
(1975) - et al.
In vivo neuropathology of the hippocampal formation in AD: a radial mapping MR-based study
Neuroimage
(2006) - et al.
International Psychogeriatric Association Expert Conference on mild cognitive impairment
Lancet
(2006) - et al.
Discrimination of Alzheimer's disease and mild cognitive impairment by equivalent EEG sources: a cross-sectional and longitudinal study
Clin. Neurophysiol.
(2000) - et al.
Quantitative electroencephalography in mild cognitive impairment: longitudinal changes and possible prediction of Alzheimer's disease
Neurobiol. Aging
(2000) - et al.
Cortical responses to sustained and divided attention in Alzheimer's disease
Neuroimage
(1999) EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis
Brain Res. Rev.
(1999)- et al.
EEG alpha oscillations: the inhibition timing hypothesis
Brain Res. Rev.
(2007)
Hippocampus in Alzheimer's disease: a 3-year follow-up MRI study
Biol. Psychiatry
Alpha rhythms: noise, dynamics and models
Int. J. Psychophysiol.
Working memory load-related electroencephalographic parameters can differentiate progressive from stable mild cognitive impairment
Neuroscience
Computerized processing of EEG–EOG–EMG artifacts for multi-centric studies in EEG oscillations and event-related potentials
Int. J. Psychophysiol.
Individual analysis of EEG frequency and band power in mild Alzheimer's disease
Clin. Neurophysiol.
Vascular damage and EEG markers in subjects with mild cognitive impairment
Clin. Neurophysiol.
Hippocampal atrophy and EEG markers in subjects with mild cognitive impairment
Clin. Neurophysiol.
Increase of theta/gamma ratio is associated with memory impairment
Clin. Neurophysiol.
New vistas for alpha-frequency band oscillations
Trends Neurosci.
Prediction of longitudinal cognitive decline in normal elderly with subjective complaints using electrophysiological imaging
Neurobiol. Aging
Conversion from mild cognitive impairment to Alzheimer's disease is predicted by sources and coherence of brain electroencephalography rhythms
Neuroscience
Clinical neurophysiology of aging brain: from normal aging to neurodegeneration
Prog. Neurobiol.
Is it possible to automatically distinguish resting EEG data of normal elderly vs. mild cognitive impairment subjects with high degree of accuracy?
Clin. Neurophysiol.
The brain circuitry of attention
Trends Cogn. Sci.
Grouping of brain rhythms in corticothalamic systems
Neuroscience
EEG correlates in the spectrum of cognitive decline
Clin. Neurophysiol.
Transient induced gamma-band response in EEG as a manifestation of miniature saccades
Neuron
Diagnostic and Statistical Manual of Mental Disorders
3D comparison of hippocampal atrophy in amnestic mild cognitive impairment and Alzheimer's disease
Brain
Spatial and temporal deficits are regionally dissociable in patients with pulvinar lesions
Brain
Mild cognitive impairment is related to Alzheimer disease pathology and cerebral infarctions
Neurology
The thalamus and schizophrenia: current status of research
Acta Neuropathol.
High gamma power is phase-locked to theta oscillations in human neocortex
Science
The Mental Deterioration Battery: normative data, diagnostic reliability and qualitative analyses of cognitive impairment. The Group for the Standardization of the Mental Deterioration Battery
Eur. Neurol.
Cited by (90)
STCGRU: A hybrid model based on CNN and BiGRU for mild cognitive impairment diagnosis
2024, Computer Methods and Programs in BiomedicineA mild cognitive impairment diagnostic model based on IAAFT and BiLSTM
2023, Biomedical Signal Processing and ControlToward noninvasive brain stimulation 2.0 in Alzheimer's disease
2022, Ageing Research ReviewsCitation Excerpt :Indeed, in healthy older adults, preserved theta-gamma coupling over parietal sites has been associated with higher accuracy and better delayed recall at multiple memory tasks (Park et al., 2011). In contrast, the progressive increase of theta frequencies over gamma oscillations was reported in MCI to dementia progression (Moretti et al., 2011; Musaeus et al., 2020). The loss of long-range connections observed during aging is considered responsible for the gradual uncoupling of the gamma-theta bands; furthermore, the increase in the gamma-theta ratio appears to be associated with the progressive atrophy of the amygdala-hippocampal axis, possibly reflecting an early limbic involvement that might account for the behavioral disturbances seen in dementia (Moretti et al., 2011, 2009).
EEG feature fusion for motor imagery: A new robust framework towards stroke patients rehabilitation
2021, Computers in Biology and MedicineStacked autoencoders as new models for an accurate Alzheimer's disease classification support using resting-state EEG and MRI measurements
2021, Clinical NeurophysiologyCitation Excerpt :Furthermore, Adler et al. (2003) reported that in the classification of Nold and ADD individuals, the left temporal alpha coherence and the global theta power density returned an accuracy of 80%. Moretti et al. (2011) showed that enhanced global theta/gamma and alpha 3/alpha 2 power density ratios resulted in an accuracy of 88% in the prediction from MCI to ADD or non-ADD. Trambaiolli et al. (2011) reported that the temporal energy modulation in the delta, theta, alpha, beta, and gamma bands resulted in an accuracy of 91% in the classification of Nold and ADD individuals.