Amnesic Mild Cognitive Impairment Subjects Research Articles

ID 284 – Abnormal delta cortical sources of resting state eyes closed EEG rhythms correlate with cerebrospinal fluid (CSF) ® amyloid (A®) level in amnesic MCI subjects

Aim In the framework of IMI PharmaCog project (Grant Agreement no. 115009), this study evaluated whether abnormal cortical sources of resting state electroencephalographic (EEG) rhythms are correlated to cerebrospinal fluid (CSF) ® amyloid (A®) level in amnesic Mild Cognitive Impairment (MCI) subjects. Methods Artifact-free resting state eyes-closed EEG rhythms (19 electrodes) were recorded. Individual datasets were divided into those with high CSF A® level (81 A®-negative, CSF A ® > 550 pg / ml ) and those with low CSF A® level (46 A®-positive, CSF A ® 550 pg / ml ). Regional normalized cortical sources of EEG rhythms at frequency bands of interest were estimated by LORETA package. ANOVA compared these sources between the two MCI groups ( p Results Statistical results showed: (1) source pattern Nold p r =−0.26; p =0.003) across all MCI subjects. Conclusions These results suggest a relationship between the brain amyloid charge, as revealed by CSF A® level, and pathological delta cortical sources indicating cortical disconnection in amnesic MCI subjects. EEG delta sources could represent a promising early diagnostic marker of Alzheimer's disease (AD).

ID 286 – Auditory oddball event-related potentials cortical sources are related to cerebrospinal fluid (CSF)® amyloid (A®) level in amnesic MCI subjects

Aim In the framework of IMI PharmaCog project (Grant Agreement no. 115009), this study evaluated whether cortical sources of AO-ERPs are related to cerebrospinal fluid (CSF)® amyloid (A®) level in amnesic Mild Cognitive Impairment (MCI) subjects. Methods Artifact-free AO-ERPs (19 electrodes) were recorded in 115 MCI subjects. Individual datasets were divided into those with high CSF A® level (61 A®-negative, CSF A® > 550 pg/ml) and those with low CSF A® level (43 A®-positive, CSF A® Results The ANOVA for the P3a peak illustrate a statistically significant interaction effect (F = 2.87; p = 0.006) between the factors Group and Brodmann Area (BA 10 and 11). The ANOVA for the P3b peak illustrate a statistically significant interaction effect (F = 2.745; p = 0.008) between the factors Group and BA (BA 5,7,23,31). Conclusions The present study provides support to the hypothesis that specific neurophysiological markers may enrich the discrimination of aMCI subjects in an early stage of prodromal Alzheimer’s disease (AD) for early diagnosis and preventive treatments.

Gaussian process classification of Alzheimer's disease and mild cognitive impairment from resting-state fMRI

Multivariate pattern analysis and statistical machine learning techniques are attracting increasing interest from the neuroimaging community. Researchers and clinicians are also increasingly interested in the study of functional-connectivity patterns of brains at rest and how these relations might change in conditions like Alzheimer's disease or clinical depression. In this study we investigate the efficacy of a specific multivariate statistical machine learning technique to perform patient stratification from functional-connectivity patterns of brains at rest. Whilst the majority of previous approaches to this problem have employed support vector machines (SVMs) we investigate the performance of Bayesian Gaussian process logistic regression (GP-LR) models with linear and non-linear covariance functions. GP-LR models can be interpreted as a Bayesian probabilistic analogue to kernel SVM classifiers. However, GP-LR methods confer a number of benefits over kernel SVMs. Whilst SVMs only return a binary class label prediction, GP-LR, being a probabilistic model, provides a principled estimate of the probability of class membership. Class probability estimates are a measure of the confidence the model has in its predictions, such a confidence score may be extremely useful in the clinical setting. Additionally, if miss-classification costs are not symmetric, thresholds can be set to achieve either strong specificity or sensitivity scores. Since GP-LR models are Bayesian, computationally expensive cross-validation hyper-parameter grid-search methods can be avoided. We apply these methods to a sample of 77 subjects; 27 with a diagnosis of probable AD, 50 with a diagnosis of a-MCI and a control sample of 39. All subjects underwent a MRI examination at 3T to obtain a 7minute and 20second resting state scan. Our results support the hypothesis that GP-LR models can be effective at performing patient stratification: the implemented model achieves 75% accuracy disambiguating healthy subjects from subjects with amnesic mild cognitive impairment and 97% accuracy disambiguating amnesic mild cognitive impairment subjects from those with Alzheimer's disease, accuracies are estimated using a held-out test set. Both results are significant at the 1% level.

Frontal delta event-related oscillations relate to frontal volume in mild cognitive impairment and healthy controls

Amnesic mild cognitive impairment (MCI) represents a risk of developing Alzheimer's disease (AD), but not all MCI subjects progress to dementia of AD type. Magnetic resonance imaging (MRI) of cortical and hippocampal atrophy supports early diagnosis of AD in MCI subjects, while frontal event-related oscillations (EROs) at delta frequencies (<4Hz) are appealing markers for this purpose, as they are both cost-effective and largely available. The present study tested the hypothesis that these EROs reflect cortical frontal neurodegeneration in the continuum between normal and amnesic MCI subjects.EROs and volumetric MRI data were recorded in 28 amnesic MCI and in 28 healthy elderly controls (HCs). EROs were collected during a standard visual oddball paradigm including frequent (66.6%) and rare (33.3%; targets to be mentally counted) stimuli. Peak-to-peak amplitude of delta target EROs (<4Hz) was measured. Volume of frontal cortex was estimated from MRIs.Frontal volume was lower in MCI compared to the HC group. Furthermore, widespread delta target EROs were lower in amplitude in the former than in the latter group. Finally, there was a positive correlation between frontal volume and frontal delta target EROs in MCI and HC subjects as a whole group. These results suggest that frontal delta EROs reflect frontal neurodegeneration in the continuum between normal and amnesic MCI subjects.

65. Cortical sources of resting state EEG rhythms reflect disease progression over 1 year in mild cognitive impairment and Alzheimer’s disease patients

Cortical sources of resting state electroencephalographic (EEG) rhythms are abnormal in subjects with mild cognitive impairment (MCI) and in patients with Alzheimer’s disease (AD). Here, we tested the hypothesis that they reflect disease progression for future clinical trials. Resting state eyes-closed EEG data were recorded in 54 amnesic MCI subjects and in 88 mild AD patients at baseline and at 1-year follow up. LORETA was used for data analysis. In the mild AD patients, the follow-up EEG recordings showed increased power of widespread delta sources as well as decreased power of widespread alpha and posterior beta 1 sources ( p < 0.05). In the MCI subjects, these recordings indicated a decreased power of posterior alpha 1 and alpha 2 sources ( p < 0.05). Cortical sources of EEG rhythms reflect the disease progression in amnesic MCI and in AD patients. Cortical sources of resting state EEG rhythms may be used as secondary “surrogate” end points for drug discovery in prodromal and manifest AD patients.

Cortical sources of resting state electroencephalographic alpha rhythms deteriorate across time in subjects with amnesic mild cognitive impairment

Cortical sources of resting state electroencephalographic (EEG) rhythms are abnormal in subjects with mild cognitive impairment (MCI). Here, we tested the hypothesis that these sources in amnesic MCI subjects further deteriorate over 1 year. To this aim, the resting state eyes-closed EEG data were recorded in 54 MCI subjects at baseline (Mini Mental State Examination I = 26.9; standard error [SE], 0.2) and at approximately 1-year follow-up (13.8 months; SE, 0.5; Mini Mental State Examination II = 25.8; SE, 0.2). As a control, EEG recordings were also performed in 45 normal elderly and in 50 mild Alzheimer's disease subjects. EEG rhythms of interest were delta (2–4 Hz), theta (4–8 Hz), alpha1 (8–10.5 Hz), alpha2 (10.5–13 Hz), beta1 (13–20 Hz), and beta2 (20–30 Hz). Cortical EEG sources were estimated using low-resolution brain electromagnetic tomography. Compared with the normal elderly and mild Alzheimer's disease subjects, the MCI subjects were characterized by an intermediate power of posterior alpha1 sources. In the MCI subjects, the follow-up EEG recordings showed a decreased power of posterior alpha1 and alpha2 sources. These results suggest that the resting state EEG alpha sources were sensitive—at least at the group level—to the cognitive decline occurring in the amnesic MCI group over 1 year, and might represent cost-effective, noninvasive and widely available markers to follow amnesic MCI populations in large clinical trials.

Stability of clinical condition in mild cognitive impairment is related to cortical sources of alpha rhythms: an electroencephalographic study.

Previous evidence has shown that resting eyes-closed cortical alpha rhythms are higher in amplitude in mild cognitive impairment (MCI) than Alzheimer's disease (AD) subjects (Babiloni et al. [2006a]: Human Brain Mapp 27:162-172; [2006b]: Clin Neurophysiol 117:252-268; [2006c]: Neuroimage 29:948-964; [2006d]: Ann Neurol 59:323-334; [2006e]: Clin Neurophysiol 117:1113-1129; [2006f]: Neuroimage 31:1650-1665). This study tested the hypothesis that, in amnesic MCI subjects, high amplitude of baseline cortical alpha rhythms is related to long-term stability of global cognition on clinical follow-up. Resting electroencephalographic (EEG) data were recorded in 100 amnesic MCI subjects during eyes-closed condition. EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha1 (8-10.5 Hz), alpha2 (10.5-13 Hz), beta1 (13-20 Hz), and beta2 (20-30 Hz). Cortical EEG sources were estimated by low-resolution brain electromagnetic tomography (LORETA). Global cognition was indexed by mini mental state evaluation (MMSE) score at the time of EEG recordings (baseline) and about after 1 year. Based on the MMSE percentage difference between baseline and 1-year follow-up (MMSEvar), the MCI subjects were retrospectively divided into three arbitrary groups: DECREASED (MMSEvar ≤ -4%; N = 43), STABLE (MMSEvar ≈ 0; N = 27), and INCREASED (MMSEvar ≥ +4%; N = 30). Subjects' age, education, individual alpha frequency, gender, and MMSE scores were used as covariates for statistical analysis. Baseline posterior cortical sources of alpha 1 rhythms were higher in amplitude in the STABLE than in the DECREASED and INCREASED groups. These results suggest that preserved resting cortical neural synchronization at alpha frequency is related to a long-term (1 year) stable cognitive function in MCI subjects. Future studies should use serial MMSE measurements to confirm and refine the present results.

P37-5 Global functional coupling of resting EEG related to white-matter lesions along the cholinergic tracts in amnesic mild cognitive impairment subjects

P37-5 Global functional coupling of resting EEG related to white-matter lesions along the cholinergic tracts in amnesic mild cognitive impairment subjects

The I.F.A.S.T. Model Allows the Prediction of Conversion to Alzheimer Disease in Patients with Mild Cognitive Impairment with High Degree of Accuracy

This paper presents the results obtained with the innovative use of special types of artificial neural networks (ANNs) assembled in a novel methodology named IFAST (implicit function as squashing time) capable of compressing the temporal sequence of electroencephalographic (EEG) data into spatial invariants. The aim of this study is to test the potential of this parallel and nonlinear EEG analysis technique in providing an automatic classification of mild cognitive impairment (MCI) subjects who will convert to Alzheimer's disease (AD) with a high degree of accuracy. Eyes-closed resting EEG data (10-20 electrode montage) were recorded in 143 amnesic MCI subjects. Based on 1-year follow up, the subjects were retrospectively classified to MCI converted to AD and MCI stable. The EEG tracks were successively filtered according to four different frequency ranges, in order to evaluate the hypotheses that a specific range, corresponding to specific brain wave type, could provide a better classification (0.12 Hz, 12.2 - 29.8 Hz; 30.2 - 40 Hz, and finally Notch Filter 48 - 50 Hz). The spatial content of the EEG voltage was extracted by IFAST step-wise procedure using ANNs. The data input for the classification operated by ANNs were not the EEG data, but the connections weights of a nonlinear auto-associative ANN trained to reproduce the recorded EEG tracks. These weights represented a good model of the peculiar spatial features of the EEG patterns at scalp surface. The classification based on these parameters was binary and performed by a supervised ANN. The best results distinguishing between MCI stable and MCI/AD reached to 85.98%.(012 Hz band). And confirmed the working hypothesis that a correct automatic classification can be obtained extracting spatial information content of the resting EEG voltage by ANNs and represent the basis for research aimed at integrating spatial and temporal information content of the EEG. These results suggest that this low-cost procedure can reliably distinguish eyes-closed resting EEG data in individual MCI subjects who will have different prognosis at 1-year follow up, and is promising for a large-scale periodic screening of large populations at amnesic MCI subjects at risk of AD.

Cortical sources of resting EEG rhythms in mild cognitive impairment and subjective memory complaint

Are cortical electroencephalographic (EEG) rhythms altered in amnesic and non-amnesic mild cognitive impairment (MCI), subjective memory complaint (SMC), and healthy elderly (Nold) subjects? Eyes-closed resting EEG was recorded in 79 Nold, 53 SMC, 51 non-amnesic MCI, and 92 amnesic MCI subjects. EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), beta 2 (20-30 Hz) and gamma (30-40 Hz). Cortical EEG sources were estimated by standardized low resolution brain electromagnetic tomography (sLORETA). Results showed that (i) the frontal delta sources were greater in amplitude in the amnesic MCI and SMC subjects than in the Nold subjects (p<0.05-0.01); (ii) the parietal and occipital theta sources were lower in amplitude in the SMC subjects than in the Nold subjects (p<0.046); (iii) the occipital theta sources were greater in amplitude in the amnesic MCI subjects than in the SMC and non-amnesic MCI subjects (p<0.02-0.01); (iv) the parietal and occipital alpha 1 sources were greater in amplitude in the Nold subjects than in the SMC, non-amnesic MCI and amnesic MCI subjects (p<0.00001); (v) the central alpha 1 sources were lower in amplitude in the SMC subjects than in the non-amnesic MCI subjects (p<0.002); (vi) the occipital alpha 1 sources were greater in amplitude in the SMC subjects than in the amnesic MCI subjects (p<0.0003); (vii) the parietal and occipital alpha 2 sources were greater in amplitude in the Nold subjects than in the non-amnesic MCI subjects (p<0.041-0.0004); (viii) the occipital alpha 2 sources were greater in the SMC subjects than in the non-amnesic MCI subjects (p<0.02). These results suggest that amnesic MCI and SMC subjects present some of the typical alterations of brain neural synchronization as revealed by resting cortical EEG rhythms in Alzheimer's disease patients.

Is it possible to automatically distinguish resting EEG data of normal elderly vs. mild cognitive impairment subjects with high degree of accuracy?

Objective It has been shown that a new procedure (implicit function as squashing time, IFAST) based on artificial neural networks (ANNs) is able to compress eyes-closed resting electroencephalographic (EEG) data into spatial invariants of the instant voltage distributions for an automatic classification of mild cognitive impairment (MCI) and Alzheimer’s disease (AD) subjects with classification accuracy of individual subjects higher than 92%. Methods Here we tested the hypothesis that this is the case also for the classification of individual normal elderly (Nold) vs. MCI subjects, an important issue for the screening of large populations at high risk of AD. Eyes-closed resting EEG data (10–20 electrode montage) were recorded in 171 Nold and in 115 amnesic MCI subjects. The data inputs for the classification by IFAST were the weights of the connections within a nonlinear auto-associative ANN trained to generate the instant voltage distributions of 60-s artifact-free EEG data. Results The most relevant features were selected and coincidently the dataset was split into two halves for the final binary classification (training and testing) performed by a supervised ANN. The classification of the individual Nold and MCI subjects reached 95.87% of sensitivity and 91.06% of specificity (93.46% of accuracy). Conclusions These results indicate that IFAST can reliably distinguish eyes-closed resting EEG in individual Nold and MCI subjects. Significance IFAST may be used for large-scale periodic screening of large populations at risk of AD and personalized care.

White matter vascular lesions are related to parietal‐to‐frontal coupling of EEG rhythms in mild cognitive impairment

Do cerebrovascular and Alzheimer's disease (AD) lesions represent additive factors in the development of mild cognitive impairment (MCI) as a putative preclinical stage of AD? Here we tested the hypothesis that directionality of fronto-parietal functional coupling of electroencephalographic (EEG) rhythms is relatively preserved in amnesic MCI subjects in whom the cognitive decline is mainly explained by white-matter vascular load. Resting EEG was recorded in 40 healthy elderly (Nold) and 78 amnesic MCI. In the MCI subjects, white-matter vascular load was quantified based on magnetic resonance images (0-30 visual rating scale). EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha1 (8-10.5 Hz), alpha2 (10.5-13 Hz), beta1 (13-20 Hz), and beta2 (20-30 Hz). Directionality of fronto-parietal functional coupling of EEG rhythms was estimated by directed transfer function software. As main results, (i) fronto-parietal functional coupling of EEG rhythms was higher in magnitude in the Nold than in the MCI subjects; (ii) more interestingly, that coupling was higher at theta, alpha1, alpha2, and beta1 in MCI V+ (high vascular load; N = 42; MMSE = 26) than in MCI V- group (low vascular load; N = 36; MMSE= 26.7). These results are interpreted as supporting the additive model according to which MCI state would result from the combination of cerebrovascular and neurodegenerative lesions.

Short latency afferent inhibition is not impaired in mild cognitive impairment

Objective To determine whether cortical cholinergic circuit impairment exists in the mild cognitive impairment (MCI) brain. Methods Fifteen healthy elderly controls (NC), 16 amnesic MCI subjects and 12 probable Alzheimer’s disease (AD) subjects were recruited. Conditioning stimuli were delivered at the right wrist followed by test transcranial magnetic stimulation (TMS) of the left motor cortex. The center of the linear contiguous segment of the coil was placed over a point 5 cm lateral to the vertex on the interaural line. The interstimulus intervals (ISIs) between the conditioning stimuli and the test stimuli were set at 20, 40, 100, 200 and 600 ms. An inhibitory effect that occurred at ISIs as short as 20 ms was defined as short-latency afferent inhibition (SAI). Results SAI was significantly reduced in subjects with AD compared with NC, but it was not reduced in subjects with MCI. Conclusions A difference in cortical excitability between subjects with AD and subjects with MCI could be captured by an in vivo neurophysiological method. Significance The state of the neurotransmitter systems, including the cortical cholinergic system, is thought by some compensatory mechanisms to be kept at the normal level in subjects with MCI.

P.6.014 Psychomotor and cognitive effects of lorazepam and d-amphetamine in healthy subjects: Development of sensitive screening tests of psychomotor- and cognitive functions

Cortical sources of resting state electroencephalographic (EEG) rhythms are abnormal in subjects with mild cognitive impairment (MCI). Here, we tested the hypothesis that these sources in amnesic MCI subjects further deteriorate over 1 year. To this aim, the resting state eyes-closed EEG data were recorded in 54 MCI subjects at baseline (Mini Mental State Examination I = 26.9; standard error [SE], 0.2) and at approximately 1-year follow-up (13.8 months; SE, 0.5; Mini Mental State Examination II = 25.8; SE, 0.2). As a control, EEG recordings were also performed in 45 normal elderly and in 50 mild Alzheimer's disease subjects. EEG rhythms of interest were delta (2–4 Hz), theta (4–8 Hz), alpha1 (8–10.5 Hz), alpha2 (10.5–13 Hz), beta1 (13–20 Hz), and beta2 (20–30 Hz). Cortical EEG sources were estimated using low-resolution brain electromagnetic tomography. Compared with the normal elderly and mild Alzheimer's disease subjects, the MCI subjects were characterized by an intermediate power of posterior alpha1 sources. In the MCI subjects, the follow-up EEG recordings showed a decreased power of posterior alpha1 and alpha2 sources. These results suggest that the resting state EEG alpha sources were sensitive—at least at the group level—to the cognitive decline occurring in the amnesic MCI group over 1 year, and might represent cost-effective, noninvasive and widely available markers to follow amnesic MCI populations in large clinical trials.

Effects of isoflurane on motor evoked potential recorde in the epidural space

Cortical sources of resting state electroencephalographic (EEG) rhythms are abnormal in subjects with mild cognitive impairment (MCI). Here, we tested the hypothesis that these sources in amnesic MCI subjects further deteriorate over 1 year. To this aim, the resting state eyes-closed EEG data were recorded in 54 MCI subjects at baseline (Mini Mental State Examination I = 26.9; standard error [SE], 0.2) and at approximately 1-year follow-up (13.8 months; SE, 0.5; Mini Mental State Examination II = 25.8; SE, 0.2). As a control, EEG recordings were also performed in 45 normal elderly and in 50 mild Alzheimer's disease subjects. EEG rhythms of interest were delta (2–4 Hz), theta (4–8 Hz), alpha1 (8–10.5 Hz), alpha2 (10.5–13 Hz), beta1 (13–20 Hz), and beta2 (20–30 Hz). Cortical EEG sources were estimated using low-resolution brain electromagnetic tomography. Compared with the normal elderly and mild Alzheimer's disease subjects, the MCI subjects were characterized by an intermediate power of posterior alpha1 sources. In the MCI subjects, the follow-up EEG recordings showed a decreased power of posterior alpha1 and alpha2 sources. These results suggest that the resting state EEG alpha sources were sensitive—at least at the group level—to the cognitive decline occurring in the amnesic MCI group over 1 year, and might represent cost-effective, noninvasive and widely available markers to follow amnesic MCI populations in large clinical trials.