Claudio Del Percio

Mapping distributed sources of cortical rhythms in mild Alzheimer's disease. A multicentric EEG study

The study aimed at mapping (i) the distributed electroencephalographic (EEG) sources specific for mild Alzheimers disease (AD) compared to vascular dementia (VaD) or normal elderly people (Nold) and (ii) the distributed EEG sources sensitive to the mild AD at different stages of severity. Resting EEG (10-20 electrode montage) was recorded from 48 mild AD, 20 VaD, and 38 Nold subjects. Both AD and VaD patients had 24-17 of mini mental state examination (MMSE). EEG rhythms 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), and beta 2 (20-30 Hz). Cortical EEG sources were modeled by low resolution brain electromagnetic tomography (LORETA). Regarding issue i, there was a decline of central, parietal, temporal, and limbic alpha 1 (low alpha) sources specific for mild AD group with respect to Nold and VaD groups. Furthermore, occipital alpha 1 sources showed a strong decline in mild AD compared to VaD group. Finally, distributed theta sources were largely abnormal in VaD but not in mild AD group. Regarding issue ii, there was a lower power of occipital alpha 1 sources in mild AD subgroup having more severe disease. Compared to previous field studies, this was the first investigation that illustrated the power spectrum profiles at the level of cortical (macroregions) EEG sources in mild AD patients having different severity of the disease with respect to VaD and normal subjects. Future studies should evaluate the clinical usefulness of this approach in early differential diagnosis, disease staging, and therapy monitoring.

Sources of Cortical Rhythms in Adults During Physiological Aging: A Multicentric EEG Study

This electroencephalographic (EEG) study tested whether cortical EEG rhythms (especially delta and alpha) show a progressive increasing or decreasing trend across physiological aging. To this aim, we analyzed the type of correlation (linear and nonlinear) between cortical EEG rhythms and age. Resting eyes‐closed EEG data were recorded in 108 young (Nyoung; age range: 18–50 years, mean age 27.3 ± 7.3 SD) and 107 elderly (Nold; age range: 51–85 years, mean age 67.3 ± 9.2 SD) subjects. The 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), and beta 2 (20–30 Hz). EEG cortical sources were estimated by low‐resolution brain electromagnetic tomography (LORETA). Statistical results showed that delta sources in the occipital area had significantly less magnitude in Nold compared to Nyoung subjects. Similarly, alpha 1 and alpha 2 sources in the parietal, occipital, temporal, and limbic areas had significantly less magnitude in Nold compared to Nyoung subjects. These nine EEG sources were given as input for evaluating the type (linear, exponential, logarithmic, and power) of correlation with age. When subjects were considered as a single group there was a significant linear correlation of age with the magnitude of delta sources in the occipital area and of alpha 1 sources in occipital and limbic areas. The same was true for alpha 2 sources in the parietal, occipital, temporal, and limbic areas. In general, the EEG sources showing significant linear correlation with age also supported a nonlinear correlation with age. These results suggest that the occipital delta and posterior cortical alpha rhythms decrease in magnitude during physiological aging with both linear and nonlinear trends. In conclusion, this new methodological approach holds promise for the prediction of dementia in mild cognitive impairment by regional source rather than surface EEG data and by both linear and nonlinear predictors. Hum Brain Mapp, 2005.

Golf putt outcomes are predicted by sensorimotor cerebral EEG rhythms

It is not known whether frontal cerebral rhythms of the two hemispheres are implicated in fine motor control and balance. To address this issue, electroencephalographic (EEG) and stabilometric recordings were simultaneously performed in 12 right‐handed expert golfers. The subjects were asked to stand upright on a stabilometric force platform placed at a golf green simulator while playing about 100 golf putts. Balance during the putts was indexed by body sway area. Cortical activity was indexed by the power reduction in spatially enhanced alpha (8–12 Hz) and beta (13–30 Hz) rhythms during movement, referred to as the pre‐movement period. It was found that the body sway area displayed similar values in the successful and unsuccessful putts. In contrast, the high‐frequency alpha power (about 10–12 Hz) was smaller in amplitude in the successful than in the unsuccessful putts over the frontal midline and the arm and hand region of the right primary sensorimotor area; the stronger the reduction of the alpha power, the smaller the error of the unsuccessful putts (i.e. distance from the hole). These results indicate that high‐frequency alpha rhythms over associative, premotor and non‐dominant primary sensorimotor areas subserve motor control and are predictive of the golfers performance.

Resting EEG sources correlate with attentional span in mild cognitive impairment and Alzheimer's disease

Previous evidence has shown that resting delta and alpha electroencephalographic (EEG) rhythms are abnormal in patients with Alzheimers disease (AD) and its potential preclinical stage (mild cognitive impairment, MCI). Here, we tested the hypothesis that these EEG rhythms are correlated with memory and attention in the continuum across MCI and AD. Resting eyes‐closed EEG data were recorded in 34 MCI and 53 AD 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), and beta 2 (20–30 Hz). EEG cortical sources were estimated by low‐resolution brain electromagnetic tomography (LORETA). These sources were correlated with neuropsychological measures such as Rey list immediate recall (word short‐term memory), Rey list delayed recall (word medium‐term memory), Digit span forward (immediate memory for digits probing focused attention), and Corsi span forward (visuo‐spatial immediate memory probing focused attention). A statistically significant negative correlation (Bonferroni corrected, P < 0.05) was observed between Corsi span forward score and amplitude of occipital or temporal delta sources across MCI and AD subjects. Furthermore, a positive correlation was shown between Digit span forward score and occipital alpha 1 sources (Bonferroni corrected, P < 0.05). These results suggest that cortical sources of resting delta and alpha rhythms correlate with neuropsychological measures of immediate memory based on focused attention in the continuum of MCI and AD subjects.

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 Alzheimers 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.

Mobile phone emission modulates interhemispheric functional coupling of EEG alpha rhythms

We tested the working hypothesis that electromagnetic fields from mobile phones (EMFs) affect interhemispheric synchronization of cerebral rhythms, an important physiological feature of information transfer into the brain. Ten subjects underwent two electroencephalographic (EEG) recordings, separated by 1 week, following a crossover double‐blind paradigm in which they were exposed to a mobile phone signal (global system for mobile communications; GSM). The mobile phone was held on the left side of the subject head by a modified helmet, and orientated in the normal position for use over the ear. The microphone was orientated towards the corner of the mouth, and the antenna was near the head in the parietotemporal area. In addition, we positioned another similar phone (but without battery) on the right side of the helmet, to balance the weight and to prevent the subject localizing the side of GSM stimulation (and consequently lateralizing attention). In one session the exposure was real (GSM) while in the other it was Sham; both sessions lasted 45 min. Functional interhemispheric connectivity was modelled using the analysis of EEG spectral coherence between frontal, central and parietal electrode pairs. Individual EEG rhythms of interest were delta (about 2–4 Hz), theta (about 4–6 Hz), alpha 1 (about 6–8 Hz), alpha 2 (about 8–10 Hz) and alpha 3 (about 10–12 Hz). Results showed that, compared to Sham stimulation, GSM stimulation modulated the interhemispheric frontal and temporal coherence at alpha 2 and alpha 3 bands. The present results suggest that prolonged mobile phone emission affects not only the cortical activity but also the spread of neural synchronization conveyed by interhemispherical functional coupling of EEG rhythms.

Visuo-attentional and sensorimotor alpha rhythms are related to visuo-motor performance in athletes

This study tested the two following hypotheses: (i) compared with non‐athletes, elite athletes are characterized by a reduced cortical activation during the preparation of precise visuo‐motor performance; (ii) in elite athletes, an optimal visuo‐motor performance is related to a low cortical activation. To this aim, electroencephalographic (EEG; 56 channels; Be Plus EB‐Neuro) data were recorded in 18 right‐handed elite air pistol shooters and 10 right‐handed non‐athletes. All subjects performed 120 shots. The EEG data were spatially enhanced by surface Laplacian estimation. With reference to a baseline period, power decrease/increase of alpha rhythms during the preshot period indexed the cortical activation/deactivation (event‐related desynchronization/synchronization, ERD/ERS). Regarding the hypothesis (i), low‐ (about 8–10 Hz) and high‐frequency (about 10–12 Hz) alpha ERD was lower in amplitude in the elite athletes than in the non‐athletes over the whole scalp. Regarding the hypothesis (ii), the elite athletes showed high‐frequency alpha ERS (about 10–12 Hz) larger in amplitude for high score shots (50%) than for low score shots; this was true in right parietal and left central areas. A control analysis confirmed these results with another indicator of cortical activation (beta ERD, about 20 Hz). The control analysis also showed that the amplitude reduction of alpha ERD for the high compared with low score shots was not observed in the non‐athletes. The present findings globally suggest that in elite athletes (experts), visuo‐motor performance is related to a global decrease of cortical activity, as a possible index of spatially selective cortical processes (“neural efficiency”). Hum Brain Mapp, 2009.

Brain neural synchronization and functional coupling in Alzheimer's disease as revealed by resting state EEG rhythms.

Alzheimers disease (AD) is the most common type of neurodegenerative disorder, typically causing dementia along aging. AD is mainly characterized by a pathological extracellular accumulation of amyloid-beta peptides that affects excitatory and inhibitory synaptic transmission, inducing aberrant patterns in neuronal circuits. Growing evidence shows that AD targets cortical neuronal networks related to cognitive functions including episodic memory and visuospatial attention. This is partially reflected by the abnormal mechanisms of cortical neural synchronization and coupling that generate resting state electroencephalographic (EEG) rhythms. The cortical neural synchronization is typically indexed by EEG power density. The EEG coupling between electrode pairs probes functional (inter-relatedness of EEG signals) and effective (casual effect from one over the other electrode) connectivity. The former is typically indexed by synchronization likelihood (linear and nonlinear) or spectral coherence (linear), the latter by granger causality or information theory indexes. Here we reviewed literature concerning EEG studies in condition of resting state in AD and mild cognitive impairment (MCI) subjects as a window on abnormalities of the cortical neural synchronization and functional and effective connectivity. Results showed abnormalities of the EEG power density at specific frequency bands (<12Hz) in the MCI and AD populations, associated with an altered functional and effective EEG connectivity among long range cortical networks (i.e. fronto-parietal and fronto-temporal). These results suggest that resting state EEG rhythms reflect the abnormal cortical neural synchronization and coupling in the brain of prodromal and overt AD subjects, possibly reflecting dysfunctional neuroplasticity of the neural transmission in long range cortical networks.

Human cortical responses during one-bit short-term memory. A high-resolution EEG study on delayed choice reaction time tasks.

OBJECTIVE We investigated whether a very simple short-term memory (STM) demand induces a visible change of EEG rhythms over the two hemispheres. METHODS High-resolution EEG was obtained in young adults during two delayed choice reaction time tasks. In the STM condition, a simple cue stimulus (one bit) was memorized along a brief delay period (3.5-5.5 s). The task was visuo-spatial in nature. RESULTS In the control (NSTM) condition, the cue stimulus remained available along the delay period. Compared to the control condition, the theta power (4-6 Hz) decreased in left frontal and bilateral parietal areas (delay period). Furthermore, low alpha power (6-8 Hz) decreased in bilateral frontal and left parietal areas, while high alpha power (10-12 Hz) decreased in the left fronto-parietal areas. CONCLUSIONS The decrease of the alpha power is as an expression of the efficient information transfer within thalamo-cortical pathways. The significance of the study stands in the fact that even a very simple STM task (only one bit to be memorized) revealed changes in fronto-parietal theta and alpha rhythms.

Genotype (cystatin C) and EEG phenotype in Alzheimer disease and mild cognitive impairment: a multicentric study.

Previous findings demonstrated that haplotype B of CST3, the gene coding for cystatin C, is a recessive risk factor for late-onset Alzheimers disease (AD; Finckh, U., von der Kammer, H., Velden, J., Michel, T., Andresen, B., Deng, A., Zhang, J., Muller-Thomsen, T., Zuchowski, K., Menzer, G., Mann, U., Papassotiropoulos, A., Heun, R., Zurdel, J., Holst, F., Benussi, L., Stoppe, G., Reiss, J., Miserez, A.R., Staehelin, H.B., Rebeck, G.W., Hyman, B.T., Binetti, G., Hock, C., Growdon, J.H., Nitsch, R.M., 2000. Genetic association of the cystatin C gene with late-onset Alzheimer disease. Arch. Neurol. 57, 1579-1583). In the present multicentric electroencephalographic (EEG) study, we analyzed the effects of CST3 haplotypes on resting cortical rhythmicity in subjects with AD and mild cognitive impairment (MCI) with the hypothesis that sources of resting EEG rhythms are more impaired in carriers of the CST3 B haplotype than non-carriers. We enrolled a population of 84 MCI subjects (42% with the B haplotype) and 65 AD patients (40% with the B haplotype). Resting eyes-closed EEG data were recorded in all 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), and beta 2 (20-30 Hz). EEG cortical sources were estimated by low-resolution brain electromagnetic tomography (LORETA). Results showed that the amplitude of alpha 1 (parietal, occipital, temporal areas) and alpha 2 (occipital area) was statistically lower in CST3 B carriers than non-carriers (P < 0.01). Whereas there was a trend towards statistical significance that amplitude of occipital delta sources was stronger in CST3 B carriers than in non-carriers. This was true for both MCI and AD subjects. The present findings represent the first demonstration of relationships between the AD genetic risk factor CST3 B and global neurophysiological phenotype (i.e., cortical delta and alpha rhythmicity) in MCI and AD subjects, prompting future genotype-EEG phenotype studies for the early prediction of AD conversion in individual MCI subjects.