Comparison of power spectra from overnight electroencephalography between patients with Down syndrome and matched control subjects.

Electroencephalograms can capture brain oscillatory activities during sleep as a form of electrophysiological signals. We analysed electroencephalogram recordings from full-night in-laboratory polysomnography from 100 patients with Down syndrome, and 100 age- and sex-matched controls. The ages of patients with Down syndrome spanned 1 month to 31 years (median 4.4 years); 84 were younger than 12 years, and 54 were male. From each electroencephalogram, we extracted relative power in six frequency bands or rhythms (delta, theta, alpha, slow sigma, fast sigma, and beta) from six channels (frontal F3 and F4, central C3 and C4, and occipital O1 and O2) during five sleep stages (N3, N2, N1, R and W)-180 features in all. We examined differences in relative power between Down syndrome and control electroencephalograms for each feature separately. During wake and N1 sleep stages, alpha rhythms (8.0-10.5 Hz) had significantly lower power in patients with Down syndrome than controls. Moreover, the rate of increase in alpha power with age during rapid eye movement sleep was significantly slower in Down syndrome than control subjects. During wake and N1 sleep, delta rhythms (0.25-4.5 Hz) had higher power in patients with Down syndrome than controls. During N2 sleep, slow sigma rhythms (10.5-12.5 Hz) had lower power in patients with DS than controls. These findings extend previous research from routine electroencephalogram studies demonstrating that patients with Down syndrome had reduced circadian amplitude-the difference between wake alpha power and deep sleep delta power was smaller in Down syndrome than control subjects. We envision that these brain oscillatory activities may be used as surrogate markers for clinical trials for patients with Down syndrome.

Noise-robust cortical tracking of attended speech in real-world acoustic scenes.

Selectively attending to one speaker in a multi-speaker scenario is thought to synchronize low-frequency cortical activity to the attended speech signal. In recent studies, reconstruction of speech from single-trial electroencephalogram (EEG) data has been used to decode which talker a listener is attending to in a two-talker situation. It is currently unclear how this generalizes to more complex sound environments. Behaviorally, speech perception is robust to the acoustic distortions that listeners typically encounter in everyday life, but it is unknown whether this is mirrored by a noise-robust neural tracking of attended speech. Here we used advanced acoustic simulations to recreate real-world acoustic scenes in the laboratory. In virtual acoustic realities with varying amounts of reverberation and number of interfering talkers, listeners selectively attended to the speech stream of a particular talker. Across the different listening environments, we found that the attended talker could be accurately decoded from single-trial EEG data irrespective of the different distortions in the acoustic input. For highly reverberant environments, speech envelopes reconstructed from neural responses to the distorted stimuli resembled the original clean signal more than the distorted input. With reverberant speech, we observed a late cortical response to the attended speech stream that encoded temporal modulations in the speech signal without its reverberant distortion. Single-trial attention decoding accuracies based on 40-50s long blocks of data from 64 scalp electrodes were equally high (80-90% correct) in all considered listening environments and remained statistically significant using down to 10 scalp electrodes and short (<30-s) unaveraged EEG segments. In contrast to the robust decoding of the attended talker we found that decoding of the unattended talker deteriorated with the acoustic distortions. These results suggest that cortical activity tracks an attended speech signal in a way that is invariant to acoustic distortions encountered in real-life sound environments. Noise-robust attention decoding additionally suggests a potential utility of stimulus reconstruction techniques in attention-controlled brain-computer interfaces.

Hierarchy, Not Lexical Regularity, Modulates Low-Frequency Neural Synchrony During Language Comprehension.

Neural responses appear to synchronize with sentence structure. However, researchers have debated whether this response in the delta band (0.5-3 Hz) really reflects hierarchical information or simply lexical regularities. Computational simulations in which sentences are represented simply as sequences of high-dimensional numeric vectors that encode lexical information seem to give rise to power spectra similar to those observed for sentence synchronization, suggesting that sentence-level cortical tracking findings may reflect sequential lexical or part-of-speech information, and not necessarily hierarchical syntactic information. Using electroencephalography (EEG) data and the frequency-tagging paradigm, we develop a novel experimental condition to tease apart the predictions of the lexical and the hierarchical accounts of the attested low-frequency synchronization. Under a lexical model, synchronization should be observed even when words are reversed within their phrases (e.g., "sheep white grass eat" instead of "white sheep eat grass"), because the same lexical items are preserved at the same regular intervals. Critically, such stimuli are not syntactically well-formed; thus a hierarchical model does not predict synchronization of phrase- and sentence-level structure in the reversed phrase condition. Computational simulations confirm these diverging predictions. EEG data from N = 31 native speakers of Mandarin show robust delta synchronization to syntactically well-formed isochronous speech. Importantly, no such pattern is observed for reversed phrases, consistent with the hierarchical, but not the lexical, accounts.

Resting-state electroencephalographic delta rhythms may reflect global cortical arousal in healthy old seniors and patients with Alzheimer's disease dementia.

Extending Basar's theory of event-related EEG oscillations, here we hypothesize that even in quiet wakefulness, transient increases in delta rhythms may enhance global cortical arousal as revealed by the desynchronization of alpha rhythms in normal (Nold) seniors with some derangement in Alzheimer's disease dementia (ADD). Clinical and EEG datasets in 100 ADD and 100 Nold individuals matched as demography, education, and gender were taken from an international archive. Standard delta (< 4 Hz) and alpha1 (8-10.5 Hz) bands were used for the main analysis, while alpha2 (10.5-13 Hz), theta (4-8 Hz), beta1 (13-20 Hz), beta2 (20-35 Hz), and gamma (35-40 Hz) served as controls. In the interpretation, the higher the alpha1 power (density), the lower that arousal. As expected, when compared to the Nold group, the ADD group showed higher global (scalp) power density at the delta-theta band and lower global power density at the alpha-beta bands. As novel findings, we observed that: (1) in the Nold group, the global delta and alpha1-2 power were negatively and linearly correlated; (2) in the ADD group, this correlation was just marginal; and (3) in both Nold and AD groups, the EEG epochs with the highest delta power (median value for stratification) were associated with the lowest global alpha1 power. This effect was related to eLORETA freeware solutions showing maximum alpha1 source activations in posterior cortical regions. These results suggest that even in quiet wakefulness, delta and alpha rhythms are related to each other, and ADD partially affects this cross-band neurophysiological mechanism.

Neurophysiological assessment of Alzheimer's disease individuals by a single electroencephalographic marker.

Here we presented a single electroencephalographic (EEG) marker for a neurophysiological assessment of Alzheimer's disease (AD) patients already diagnosed by current guidelines. The ability of the EEG marker to classify 127 AD individuals and 121 matched cognitively intact normal elderly (Nold) individuals was tested. Furthermore, its relationship to AD patients' cognitive status and structural brain integrity was examined. Low-resolution brain electromagnetic tomography (LORETA) freeware estimated cortical sources of resting state eyes-closed EEG rhythms. The EEG marker was defined as the ratio between the activity of parieto-occipital cortical sources of delta (2-4 Hz) and low-frequency alpha (8-10.5 Hz) rhythms. Results showed 77.2% of sensitivity in the recognition of the AD individuals; 65% of specificity in the recognition of the Nold individuals; and 0.75 of area under the receiver-operating characteristic curve. Compared to the AD subgroup with the EEG maker within one standard deviation of the Nold mean (EEG-), the AD subgroup with EEG+ showed lower global cognitive status, as revealed by Mini-Mental State Evaluation score, and more abnormal values of white-matter and cerebrospinal fluid normalized volumes, as revealed by structural magnetic resonance imaging. We posit that cognitive and functional status being equal, AD patients with EEG+ should receive special clinical attention due to a neurophysiological "frailty". EEG+ label can be also used in clinical trials (i) to form homogeneous groups of AD patients diagnosed by current guidelines and (ii) as end-point to evaluate intervention effects.

Antiretroviral therapy affects the z-score index of deviant cortical EEG rhythms in naïve HIV individuals.

OBJECTIVE: Here we tested the effect of combined antiretroviral therapy (cART) on deviant electroencephalographic (EEG) source activity in treatment-naïve HIV individuals. METHODS: Resting state eyes-closed EEG data were recorded before and after 5 months of cART in 48 male HIV subjects, who were naïve at the study start. The EEG data were also recorded in 59 age- and sex-matched healthy subjects as a control group. Frequency bands of interest included delta, theta, alpha1, alpha2 and alpha3, based on alpha frequency peak specific to each individual. They also included beta1 (13-20 Hz) and beta2 (20-30 Hz). Low-resolution brain electromagnetic tomography (LORETA) estimated EEG cortical source activity in frontal, central, temporal, parietal, and occipital regions. RESULTS: Before the therapy, the HIV group showed greater parietal delta source activity and lower spatially diffuse alpha source activity compared to the control group. Thus, the ratio of parietal delta and alpha3 source activity served as an EEG marker. The z-score showed a statistically deviant EEG marker (EEG +) in 50% of the HIV individuals before therapy (p < 0.05). After 5 months of cART, delta source activity decreased, and alpha3 source activity increased in the HIV subjects with EEG + (about 50% of them showed a normalized EEG marker). CONCLUSIONS: This procedure detected a deviant EEG marker before therapy and its post-therapy normalization in naïve HIV single individuals. SIGNIFICANCE: The parietal delta/alpha3 EEG marker may be used to monitor cART effects on brain function in such individuals.

Brain and cognitive functions in two groups of naïve HIV patients selected for a different plan of antiretroviral therapy: A qEEG study.

OBJECTIVE: Cortical sources of electroencephalographic (EEG) rhythms were investigated in two sub-populations of naïve HIV subjects, grouped based on clinical criteria to receive different combination anti-retroviral therapies (cARTs). These EEG sources were hypothesized to reflect beneficial effects of both regimes. METHODS: Eyes-closed resting state EEG data were collected in 19 (Group A) and 39 (Group B) naïve HIV subjects at baseline (i.e. pre-treatment; T0) and after 5months of cART (T5). Compared with the Group A, the Group B was characterized by slightly worse serological parameters and higher cardiovascular risk. At T0, mean viral load (VL) and CD4 count were 87,694copies/ml and 435cells/µl in the Group A and 187,370copies/ml and 331cells/µl in the Group B. The EEG data were also collected in 50 matched control HIV-negative subjects. Cortical EEG sources were assessed by LORETA software. RESULTS: Compared to the Control Group, the HIV Groups showed lower alpha (8-12Hz) source activity at T0 while the Group B also exhibited higher delta source activity. The treatment partially normalized alpha and delta source activity in the Group A and B, respectively, in association with improved VL, CD4, and cognitive functions. CONCLUSIONS: Different cART regimens induced diverse beneficial effects in delta or alpha source activity in the two naïve HIV Groups. SIGNIFICANCE: These sources might unveil different neurophysiological effects of diverse cART on brain function in naïve HIV Groups as a function of clinical status and/or therapeutic compounds.

Classification of Single Normal and Alzheimer's Disease Individuals from Cortical Sources of Resting State EEG Rhythms.

Previous studies have shown abnormal power and functional connectivity of resting state electroencephalographic (EEG) rhythms in groups of Alzheimer's disease (AD) compared to healthy elderly (Nold) subjects. Here we tested the best classification rate of 120 AD patients and 100 matched Nold subjects using EEG markers based on cortical sources of power and functional connectivity of these rhythms. EEG data were recorded during resting state eyes-closed condition. Exact low-resolution brain electromagnetic tomography (eLORETA) estimated the power and functional connectivity of cortical sources in frontal, central, parietal, occipital, temporal, and limbic regions. 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) were the frequency bands of interest. The classification rates of interest were those with an area under the receiver operating characteristic curve (AUROC) higher than 0.7 as a threshold for a moderate classification rate (i.e., 70%). Results showed that the following EEG markers overcame this threshold: (i) central, parietal, occipital, temporal, and limbic delta/alpha 1 current density; (ii) central, parietal, occipital temporal, and limbic delta/alpha 2 current density; (iii) frontal theta/alpha 1 current density; (iv) occipital delta/alpha 1 inter-hemispherical connectivity; (v) occipital-temporal theta/alpha 1 right and left intra-hemispherical connectivity; and (vi) parietal-limbic alpha 1 right intra-hemispherical connectivity. Occipital delta/alpha 1 current density showed the best classification rate (sensitivity of 73.3%, specificity of 78%, accuracy of 75.5%, and AUROC of 82%). These results suggest that EEG source markers can classify Nold and AD individuals with a moderate classification rate higher than 80%.