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The objectives of this machine-learning (ML) resting-state magnetoencephalography (rs-MEG) study involving children with mild traumatic brain injury (mTBI) and orthopedic injury (OI) controls were to define a neural injury signature of mTBI and to delineate the pattern(s) of neural injury that determine behavioral recovery. Children ages 8-15 years with mTBI (n = 59) and OI (n = 39) from consecutive admissions to an emergency department were studied prospectively for parent-rated post-concussion symptoms (PCS) at: 1) baseline (average of 3 weeks post-injury) to measure pre-injury symptoms and also concurrent symptoms; and 2) at 3-months post-injury. rs-MEG was conducted at the baseline assessment. The ML algorithm predicted cases of mTBI versus OI with sensitivity of 95.5 ± 1.6% and specificity of 90.2 ± 2.7% at 3-weeks post-injury for the combined delta-gamma frequencies. The sensitivity and specificity were significantly better (p < 0.0001) for the combined delta-gamma frequencies compared with the delta-only and gamma-only frequencies. There were also spatial differences in rs-MEG activity between mTBI and OI groups in both delta and gamma bands in frontal and temporal lobe, as well as more widespread differences in the brain. The ML algorithm accounted for 84.5% of the variance in predicting recovery measured by PCS changes between 3 weeks and 3 months post-injury in the mTBI group, and this was significantly lower (p < 10-4) in the OI group (65.6%). Frontal lobe pole (higher) gamma activity was significantly (p < 0.001) associated with (worse) PCS recovery exclusively in the mTBI group. These findings demonstrate a neural injury signature of pediatric mTBI and patterns of mTBI-induced neural injury related to behavioral recovery.

Combat-related mild traumatic brain injury (cmTBI) is a leading cause of sustained physical, cognitive, emotional, and behavioral disabilities in Veterans and active-duty military personnel. Accurate diagnosis of cmTBI is challenging since the symptom spectrum is broad and conventional neuroimaging techniques are insensitive to the underlying neuropathology. The present study developed a novel deep-learning neural network method, 3D-MEGNET, and applied it to resting-state magnetoencephalography (rs-MEG) source-magnitude imaging data from 59 symptomatic cmTBI individuals and 42 combat-deployed healthy controls (HCs). Analytic models of individual frequency bands and all bands together were tested. The All-frequency model, which combined delta-theta (1-7 Hz), alpha (8-12 Hz), beta (15-30 Hz), and gamma (30-80 Hz) frequency bands, outperformed models based on individual bands. The optimized 3D-MEGNET method distinguished cmTBI individuals from HCs with excellent sensitivity (99.9 ± 0.38%) and specificity (98.9 ± 1.54%). Receiver-operator-characteristic curve analysis showed that diagnostic accuracy was 0.99. The gamma and delta-theta band models outperformed alpha and beta band models. Among cmTBI individuals, but not controls, hyper delta-theta and gamma-band activity correlated with lower performance on neuropsychological tests, whereas hypo alpha and beta-band activity also correlated with lower neuropsychological test performance. This study provides an integrated framework for condensing large source-imaging variable sets into optimal combinations of regions and frequencies with high diagnostic accuracy and cognitive relevance in cmTBI. The all-frequency model offered more discriminative power than each frequency-band model alone. This approach offers an effective path for optimal characterization of behaviorally relevant neuroimaging features in neurological and psychiatric disorders.

Combat-related mild traumatic brain injury (cmTBI) is a leading cause of sustained physical, cognitive, emotional, and behavioral disabilities in Veterans and active-duty military personnel. Accurate diagnosis of cmTBI is challenging since the symptom spectrum is broad and conventional neuroimaging techniques are insensitive to the underlying neuropathology. The present study developed a novel deep-learning neural network method, 3D-MEGNET, and applied it to resting-state magnetoencephalography (rs-MEG) source-magnitude imaging data from 59 symptomatic cmTBI individuals and 42 combat-deployed healthy controls (HCs). Analytic models of individual frequency bands and all bands together were tested. The All-frequency model, which combined delta-theta (1-7 Hz), alpha (8-12 Hz), beta (15-30 Hz), and gamma (30-80 Hz) frequency bands, outperformed models based on individual bands. The optimized 3D-MEGNET method distinguished cmTBI individuals from HCs with excellent sensitivity (99.9 ± 0.38%) and specificity (98.9 ± 1.54%). Receiver-operator-characteristic curve analysis showed that diagnostic accuracy was 0.99. The gamma and delta-theta band models outperformed alpha and beta band models. Among cmTBI individuals, but not controls, hyper delta-theta and gamma-band activity correlated with lower performance on neuropsychological tests, whereas hypo alpha and beta-band activity also correlated with lower neuropsychological test performance. This study provides an integrated framework for condensing large source-imaging variable sets into optimal combinations of regions and frequencies with high diagnostic accuracy and cognitive relevance in cmTBI. The all-frequency model offered more discriminative power than each frequency-band model alone. This approach offers an effective path for optimal characterization of behaviorally relevant neuroimaging features in neurological and psychiatric disorders.

ObjectiveTo determine the best of commonly used methods for computing the rate of decline in non-rapid eye movement (NREM) sleep EEG delta power overnight (Delta Decline) in terms of vulnerability to missing data and to evaluate whether this rate is slower in insomnia patients than healthy controls (HC).MethodsFifty-one insomnia patients and 53 HC underwent 6 nights of polysomnography. Four methods for estimating Delta Decline were compared (exponential and linear best-fit functions using NREM (1) episode mean, (2) peak, and (3) total delta power and (4) delta power for all available NREM epochs). The best method was applied to compare groups on linear and exponential rates of Delta Decline.ResultsBest-fit models using all available NREM epochs were significantly less vulnerable to deviation due to missing data than other methods. Insomnia patients displayed significantly slower linear and exponential Delta Decline than HC.ConclusionsComputing Delta Decline using all available NREM epochs was the best of the methods studied for minimizing the effects of missing data. Insomnia patients display slower Delta Decline, which is not explained by differences in total sleep time or wake after sleep onset.SignificanceThis study supports using all available NREM epochs in Delta Decline computation and suggests a slower rate in insomnia.

The functional consequences of ischemic stroke in the remote brain regions are not well characterized. The current study sought to determine changes in hippocampal oscillatory activity that may underlie the cognitive impairment observed following distal middle cerebral artery occlusion (dMCAO) without causing hippocampal structural damage. Local field potentials were recorded from the dorsal hippocampus and cortex in urethane-anesthetized rats with multichannel silicon probes during dMCAO and reperfusion, or mild ischemia induced by bilateral common carotid artery occlusion (CCAO). Bilateral change of brain state was evidenced by reduced theta/delta amplitude ratio and shortened high theta duration following acute dMCAO but not CCAO. An aberrant increase in the occurrence of sharp-wave-associated ripples (150-250 Hz), crucial for memory consolidation, was only detected after dMCAO reperfusion, coinciding with an increased occurrence of high-frequency discharges (250-450 Hz). dMCAO also significantly affected the modulation of gamma amplitude in the cortex coupled to hippocampal theta phase, although both hippocampal theta and gamma power were temporarily decreased during dMCAO. Our results suggest that MCAO may disrupt the balance between excitatory and inhibitory circuits in the hippocampus and alter the function of cortico-hippocampal network, providing a novel insight in how cortical stroke affects function in remote brain regions.

Sleep disordered breathing (SDB) in children has significant effects on daytime functioning and cardiovascular control; attributed to sleep fragmentation and repetitive hypoxia. Associations between electroencephalograph (EEG) spectral power, autonomic cardiovascular control and cerebral oxygenation have been identified in adults with SDB. To date, there have been no studies in children. We aimed to assess associations between EEG spectral power and heart rate variability as a measure of autonomic control, with cerebral oxygenation in children with SDB. Method(s): One hundred sixteen children (3-12 years) with SDB and 42 controls underwent overnight polysomnography including measurement of cerebral oxygenation. Power spectral analysis of the EEG derived from C4-M1 and F4-M1, quantified delta, theta, alpha, and beta waveforms during sleep. Multiple regression tested whether age, SDB severity, heart rate (HR), HR variability (HRV), and cerebral oxygenation were determinants of EEG spectral power. Result(s): There were no differences in EEG spectral power derived from either central or frontal regions for any frequency between children with different severities of SDB so these were combined. Age, HR, and HRV low frequency power were significant determinants of EEG spectral power depending on brain region and sleep stage. Conclusion(s): The significant findings of this study were that age and autonomic control, rather than cerebral oxygenation and SDB severity, were predictive of EEG spectral power in children. Further research is needed to elucidate how the physiology that underlies the relationship between autonomic control and EEG impacts on the cardiovascular sequelae in children with SDB.Copyright © 2019 Sleep Research Society 2019. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved.

Sleep disordered breathing (SDB) in children has significant effects on daytime functioning and cardiovascular control; attributed to sleep fragmentation and repetitive hypoxia. Associations between electroencephalograph (EEG) spectral power, autonomic cardiovascular control and cerebral oxygenation have been identified in adults with SDB. To date, there have been no studies in children. We aimed to assess associations between EEG spectral power and heart rate variability as a measure of autonomic control, with cerebral oxygenation in children with SDB. Method(s): One hundred sixteen children (3-12 years) with SDB and 42 controls underwent overnight polysomnography including measurement of cerebral oxygenation. Power spectral analysis of the EEG derived from C4-M1 and F4-M1, quantified delta, theta, alpha, and beta waveforms during sleep. Multiple regression tested whether age, SDB severity, heart rate (HR), HR variability (HRV), and cerebral oxygenation were determinants of EEG spectral power. Result(s): There were no differences in EEG spectral power derived from either central or frontal regions for any frequency between children with different severities of SDB so these were combined. Age, HR, and HRV low frequency power were significant determinants of EEG spectral power depending on brain region and sleep stage. Conclusion(s): The significant findings of this study were that age and autonomic control, rather than cerebral oxygenation and SDB severity, were predictive of EEG spectral power in children. Further research is needed to elucidate how the physiology that underlies the relationship between autonomic control and EEG impacts on the cardiovascular sequelae in children with SDB.Copyright © 2019 Sleep Research Society 2019. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved.

Genome-wide association studies have implicated many ion channels in schizophrenia pathophysiology. Although the functions of these channels are relatively well characterized by single-cell studies, the contributions of common variation in these channels to neurophysiological biomarkers and symptoms of schizophrenia remain elusive. Here, using computational modeling, we show that a common biomarker of schizophrenia, namely, an increase in delta-oscillation power, may be a direct consequence of altered expression or kinetics of voltage-gated ion channels or calcium transporters. Our model of a circuit of layer V pyramidal cells highlights multiple types of schizophrenia-related variants that contribute to altered dynamics in the delta-frequency band. Moreover, our model predicts that the same membrane mechanisms that increase the layer V pyramidal cell network gain and response to delta-frequency oscillations may also cause a deficit in a single-cell correlate of the prepulse inhibition, which is a behavioral biomarker highly associated with schizophrenia.

Cross-modal perception allows olfactory information to integrate with other sensory modalities. Olfactory representations are processed by multisensory cortical pathways, where the aspects related to the haptic sensations are integrated. This complex reality allows the development of an integrated perception, where olfactory aspects compete with haptic and/or trigeminal activations. It is assumed that this integration involves both perceptive electrophysiological and metabolic/hemodynamic aspects, but there are no studies evaluating these activations in parallel. The aim of this study was to investigate brain dynamics during a cross-modal olfactory and haptic attention task, preceded by an exploratory session. The assessment of cross-modal dynamics was conducted through simultaneous electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) recording, evaluating both electrophysiological and hemodynamic activities. The study consisted of two experimental sessions and was conducted with a sample of ten healthy subjects (mean age 25 ± 5.2 years). In Session 1, the subjects were trained to manipulate 3D haptic models (HC) and to smell different scents (SC). In Session 2, the subjects were tested during an attentive olfactory task, in order to investigate the olfactory event-related potentials (OERP) N1 and late positive component (LPC), and EEG rhythms associated with fNIRS components (oxy-Hb and deoxy-Hb). The main results of this study highlighted, in Task 1, a higher fNIRS oxy-Hb response during SC and a positive correlation with the delta rhythm in the central and parietal EEG region of interest. In Session 2, the N1 OERP highlighted a greater amplitude in SC. A negative correlation was found in HC for the deoxy-Hb parietal with frontal and central N1, and for the oxy-Hb frontal with N1 in the frontal, central and parietal regions of interests (ROIs). A negative correlation was found in parietal LPC amplitude with central deoxy-Hb. The data sugg

Background:Angelman syndrome (AS) is a neurodevelopmental disorder characterized by intellectual disability, speech and motor impairments, epilepsy, abnormal sleep, and phenotypic overlap with autism. Individuals with AS display characteristic EEG patterns including high-amplitude rhythmic delta waves. Here, we sought to quantitatively explore EEG architecture in AS beyond known spectral power phenotypes. We were motivated by studies of functional connectivity and sleep spindles in autism to study these EEG readouts in children with AS. Methods:We analyzed retrospective wake and sleep EEGs from children with AS (age 4-11) and age-matched neurotypical controls. We assessed long-range and short-range functional connectivity by measuring coherence across multiple frequencies during wake and sleep. We quantified sleep spindles using automated and manual approaches. Results:During wakefulness, children with AS showed enhanced long-range EEG coherence across a wide range of frequencies. During sleep, children with AS showed increased long-range EEG coherence specifically in the gamma band. EEGs from children with AS contained fewer sleep spindles, and these spindles were shorter in duration than their neurotypical counterparts. Conclusions:We demonstrate two quantitative readouts of dysregulated sleep composition in children with AS-gamma coherence and spindles-and describe how functional connectivity patterns may be disrupted during wakefulness. Quantitative EEG phenotypes have potential as biomarkers and readouts of target engagement for future clinical trials and provide clues into how neural circuits are dysregulated in children with AS.

Background:Angelman syndrome (AS) is a neurodevelopmental disorder characterized by intellectual disability, speech and motor impairments, epilepsy, abnormal sleep, and phenotypic overlap with autism. Individuals with AS display characteristic EEG patterns including high-amplitude rhythmic delta waves. Here, we sought to quantitatively explore EEG architecture in AS beyond known spectral power phenotypes. We were motivated by studies of functional connectivity and sleep spindles in autism to study these EEG readouts in children with AS. Methods:We analyzed retrospective wake and sleep EEGs from children with AS (age 4-11) and age-matched neurotypical controls. We assessed long-range and short-range functional connectivity by measuring coherence across multiple frequencies during wake and sleep. We quantified sleep spindles using automated and manual approaches. Results:During wakefulness, children with AS showed enhanced long-range EEG coherence across a wide range of frequencies. During sleep, children with AS showed increased long-range EEG coherence specifically in the gamma band. EEGs from children with AS contained fewer sleep spindles, and these spindles were shorter in duration than their neurotypical counterparts. Conclusions:We demonstrate two quantitative readouts of dysregulated sleep composition in children with AS-gamma coherence and spindles-and describe how functional connectivity patterns may be disrupted during wakefulness. Quantitative EEG phenotypes have potential as biomarkers and readouts of target engagement for future clinical trials and provide clues into how neural circuits are dysregulated in children with AS.

During connected speech listening, brain activity tracks speech rhythmicity at delta (∼0.5 Hz) and theta (4-8 Hz) frequencies. Here, we compared the potential of magnetoencephalography (MEG) and high-density electroencephalography (EEG) to uncover such speech brain tracking. Ten healthy right-handed adults listened to two different 5-min audio recordings, either without noise or mixed with a cocktail-party noise of equal loudness. Their brain activity was simultaneously recorded with MEG and EEG. We quantified speech brain tracking channel-by-channel using coherence, and with all channels at once by speech temporal envelope reconstruction accuracy. In both conditions, speech brain tracking was significant at delta and theta frequencies and peaked in the temporal regions with both modalities (MEG and EEG). However, in the absence of noise, speech brain tracking estimated from MEG data was significantly higher than that obtained from EEG. Furthemore, to uncover significant speech brain tracking, recordings needed to be ∼3 times longer in EEG than MEG, depending on the frequency considered (delta or theta) and the estimation method. In the presence of noise, both EEG and MEG recordings replicated the previous finding that speech brain tracking at delta frequencies is stronger with attended speech (i.e. the sound subjects are attending to) than with the global sound (i.e. the attended speech and the noise combined). Other previously reported MEG findings were replicated based on MEG but not EEG recordings: 1) speech brain tracking at theta frequencies is stronger with attended speech than with the global sound, 2) speech brain tracking at delta frequencies is stronger in noiseless than noisy conditions, and 3) when noise is added, speech brain tracking at delta frequencies dampens less in the left hemisphere than in the right hemisphere. Finally, sources of speech brain tracking reconstructed from EEG data were systematically deeper and more posterior than those derived, SCOPUS: ar.j, info:eu-repo/semantics/published

Genetic generalized epilepsy (GGE) consists of several syndromes diagnosed and classified on the basis of clinical features and electroencephalographic (EEG) abnormalities. The main EEG feature of GGE is bilateral, synchronous, symmetric, and generalized spike-wave complex. Other classic EEG abnormalities are polyspikes, epileptiform K-complexes and sleep spindles, polyspike-wave discharges, occipital intermittent rhythmic delta activity, eye-closure sensitivity, fixation-off sensitivity, and photoparoxysmal response. However, admixed with typical changes, atypical epileptiform discharges are also commonly seen in GGE. There are circadian variations of generalized epileptiform discharges. Sleep, sleep deprivation, hyperventilation, intermittent photic stimulation, eye closure, and fixation-off are often used as activation techniques to increase the diagnostic yield of EEG recordings. Reflex seizure-related EEG abnormalities can be elicited by the use of triggers such as cognitive tasks and pattern stimulation during the EEG recording in selected patients. Distinct electrographic abnormalities to help classification can be identified among different electroclinical syndromes.Copyright © 2017 Seneviratne, Cook and D'Souza.

Power spectral analysis of the electroencephalogram (EEG) is a non-invasive method to examine infant brain maturation. Preterm fetal growth restricted (p-FGR) neonates display an altered EEG power spectrum compared to appropriate-for-gestational-age (AGA) peers, suggesting delayed brain maturation. Longitudinal studies investigating EEG power spectrum maturation in p-FGR infants are lacking, however. We thus aimed to investigate brain maturation using sleep EEG power spectral analysis in p-FGR infants compared to preterm and term AGA controls (p-AGA and t-AGA, respectively). EEG was recorded during spontaneous sleep in 13 p-FGR, 17 p-AGA and 19 t-AGA infants at 1 and 6 months post-term age. Infant sleep states (active and quiet sleep) were scored using standard criteria. Power spectral analysis of a single-channel EEG (C3-M2/C4-M1) was performed using Fast Fourier Transform. The EEG power spectrum was divided into delta (0.5-4 Hz), theta (4-8 Hz), alpha (8-12 Hz), sigma (12-14 Hz) and beta (14-30 Hz) frequency bands. Relative (%) powers and the spectral edge frequency were calculated. The spectral edge frequency was significantly higher in p-FGR infants compared to p-AGA controls in quiet sleep at 1 month post-term age (p <.01). This was due to significantly reduced %-delta and significantly increased %-theta, %-alpha and %-beta power (p <.01 for all) compared to p-AGA infants. p-FGR infants also showed significantly increased %-beta power compared to t-AGA infants (p <.05). No group differences were observed in active sleep or at 6 months post-term age. In conclusion, p-FGR infants show altered sleep EEG power spectrum maturation compared to AGA peers. However, changes resolved by 6 months post-term age.Copyright © 2017

The purpose of this article is to describe the clinical and electroencephalographic features of patients diagnosed with non-convulsive status epilepticus (NCSE) with uncommon cognitive and behavioral involvement. We present two cases with sub-acute cognitive impairment and neuropsychiatric disorders (including anxiety and transient behavioral changes) as their first manifestation of NCSE. A neuropsychological profile demonstrated executive dysfunction. In addition, the neurological examination revealed automatisms and 24-hour video EEG showed epileptiform activity. Although neuroimaging studies showed frontotemporal abnormalities, both neurophysiological and cognitive improvement after specific antiseizure drug treatment confirmed the diagnosis of non-convulsive status. Theoretical considerations between mental status changes and focal epilepsy will be reviewed. Our cases raise awareness of the importance of considering NCSE, a treatable condition, in the differential diagnosis of rapidly-progressive cognitive impairment with neuropsychiatric symptoms. © 2016 The Authors

Genetic generalized epilepsy (GGE) consists of several syndromes diagnosed and classified on the basis of clinical features and electroencephalographic (EEG) abnormalities. The main EEG feature of GGE is bilateral, synchronous, symmetric, and generalized spike-wave complex. Other classic EEG abnormalities are polyspikes, epileptiform K-complexes and sleep spindles, polyspike-wave discharges, occipital intermittent rhythmic delta activity, eye-closure sensitivity, fixation-off sensitivity, and photoparoxysmal response. However, admixed with typical changes, atypical epileptiform discharges are also commonly seen in GGE. There are circadian variations of generalized epileptiform discharges. Sleep, sleep deprivation, hyperventilation, intermittent photic stimulation, eye closure, and fixation-off are often used as activation techniques to increase the diagnostic yield of EEG recordings. Reflex seizure-related EEG abnormalities can be elicited by the use of triggers such as cognitive tasks and pattern stimulation during the EEG recording in selected patients. Distinct electrographic abnormalities to help classification can be identified among different electroclinical syndromes.Copyright © 2017 Seneviratne, Cook and D'Souza.

Power spectral analysis of the electroencephalogram (EEG) is a non-invasive method to examine infant brain maturation. Preterm fetal growth restricted (p-FGR) neonates display an altered EEG power spectrum compared to appropriate-for-gestational-age (AGA) peers, suggesting delayed brain maturation. Longitudinal studies investigating EEG power spectrum maturation in p-FGR infants are lacking, however. We thus aimed to investigate brain maturation using sleep EEG power spectral analysis in p-FGR infants compared to preterm and term AGA controls (p-AGA and t-AGA, respectively). EEG was recorded during spontaneous sleep in 13 p-FGR, 17 p-AGA and 19 t-AGA infants at 1 and 6 months post-term age. Infant sleep states (active and quiet sleep) were scored using standard criteria. Power spectral analysis of a single-channel EEG (C3-M2/C4-M1) was performed using Fast Fourier Transform. The EEG power spectrum was divided into delta (0.5-4 Hz), theta (4-8 Hz), alpha (8-12 Hz), sigma (12-14 Hz) and beta (14-30 Hz) frequency bands. Relative (%) powers and the spectral edge frequency were calculated. The spectral edge frequency was significantly higher in p-FGR infants compared to p-AGA controls in quiet sleep at 1 month post-term age (p <.01). This was due to significantly reduced %-delta and significantly increased %-theta, %-alpha and %-beta power (p <.01 for all) compared to p-AGA infants. p-FGR infants also showed significantly increased %-beta power compared to t-AGA infants (p <.05). No group differences were observed in active sleep or at 6 months post-term age. In conclusion, p-FGR infants show altered sleep EEG power spectrum maturation compared to AGA peers. However, changes resolved by 6 months post-term age.Copyright © 2017

Common-phase synchronization of neuronal oscillations is a mechanism by which distributed brain regions can be integrated into transiently stable networks. Based on the hypothesis that schizophrenia is characterized by deficits in functional integration within neuronal networks, this study aimed to explore whether psychotic patients exhibit differences in brain regions involved in integrative mechanisms. We report an electroencephalography (EEG)-informed functional magnetic resonance imaging analysis of eyes-open resting-state data collected from patients and healthy controls at two study sites. Global field synchronization (GFS) was chosen as an EEG measure indicating common-phase synchronization across electrodes. Several brain clusters appeared to be coupled to GFS differently in patients and controls. Activation in brain areas belonging to the default mode network was negatively associated to GFS delta (1-3.5 Hz) and positively to GFS beta (13-30 Hz) bands in patients, whereas controls showed an opposite pattern for both GFS frequency bands in those regions; activation in the extrastriate visual cortex was inversely related to GFS alpha1 (8.5-10.5 Hz) band in healthy controls, while patients had a tendency toward a positive relationship. Taken together, the GFS measure might be useful for detecting additional aspects of deficient functional network integration in psychosis.

Our objective was to define the EEG features during sleep of children with neurodevelopmental disorders due to copy number gains of 15q11-q13 (Dup15q). We retrospectively reviewed continuous EEG recordings of 42 children with Dup15q (mean age: eight years, 32 with idic15), and data collected included background activity, interictal epileptiform discharges, sleep organization, and ictal activity. Three patterns were recognized: Pattern 1: Alpha–delta sleep was noted in 14 children (33%), not associated with any clinical changes. Pattern 2: Electrical status epilepticus in sleep was noted in 15 children (35%), all diagnosed with treatmentresistant epilepsy. Thirteen of the 15 children had clinical seizures. Pattern 3: Frequent bursts of high amplitude bifrontal predominant, paroxysmal fast activity (12–15 Hz) during non-REM sleep was noted in 15 children (35%). All 15 children had treatment-resistant epilepsy. This is the first report of electroencephalographic patterns during sleep of children with Dup15q reporting alpha-delta rhythms, CSWS, and high amplitude fast frequencies. Alpha-delta rhythms are described in children with dysautonomia and/or mood disorders and CSWS in children with developmental regression. The significance of these findings in cognitive function and epilepsy for the children in our cohort needs to be determined with follow-up studies.

Objective: To provide a quantitative evaluation of typical electroencephalographic (EEG) abnormalities in genetic generalized epilepsy (GGE). Method(s): We prospectively performed 24-ambulatory EEG recordings in a cohort of patients with GGE. The diagnosis was established according to the International League Against Epilepsy criteria. Details of all epileptiform discharges across the 24-time scale were entered into an electronic database. We carried out descriptive statistics to provide a quantitative breakdown of typical EEG abnormalities. Result(s): A total of 6923 epileptiform discharges from 105 abnormal 24-ambulatory EEGs were analyzed. 96% of discharges were symmetric in amplitude with fronto-central maximum topographically. Only 24% of the paroxysms had typical morphology while 43% were regular. Photoparoxysmal response, eye-closure sensitivity and hyperventilation-induced generalized paroxysms were less common in around 10%, whereas occipital intermittent rhythmic delta activity was very rare (2%). Conclusion(s): Our results indicate that generalized discharges with symmetric amplitude and fronto-central maxima are the most consistent findings in GGE, and other features are observed less frequently. Significance: Epileptiform discharges displaying highly consistent amplitude symmetry coupled with fronto-central topography should provoke consideration of GGE. Recognition of variations from typical abnormalities is important to avoid the risk of misdiagnosis and delayed diagnosis.Copyright © 2015 Published by Elsevier Ireland Ltd.

Background It has been suggested that impaired dissipation of slow-wave activity (SWA) in children with sleep-disordered breathing (SDB) may be a potential mechanism for daytime dysfunction. We aimed to examine whether resolution of SDB resulted in normalisation of SWA dissipation and whether this was associated with improved cognition and behaviour. Methods Children (aged 3-6 y) diagnosed with SDB and age-matched non-snoring control children were followed up for 3 y after a baseline study. At the follow-up, children were categorised into control (N = 13), resolved SDB (N = 15) and unresolved SDB (N = 14). Delta activity on the electroencephalogram over the sleep period was used to calculate SWA and a battery of cognitive assessments and behaviour questionnaires were conducted at both time points. Results There was no change in the average SWA between the baseline and follow-up and no differences between the groups. Cognitive and behavioural performance in the resolved group did not improve to control levels. However, decreased SWA at the beginning of the sleep period (beta = -0.04, p = 0.002) and a decrease in obstructive apnoea-hypopnoea index (beta = -2.2, p = 0.022) between the baseline and follow-up predicted improvements in measures of sustained attention. Increased SWA at the beginning of the sleep period between the baseline and follow-up predicted worsening of externalising behaviour (beta = 0.02, p = 0.039). Conclusions This study suggests that resolution of SDB is not associated with changes in the dissipation of SWA. However, the association between decreases in SWA and improvements in cognitive and behavioural outcomes suggest that irrespective of disease, children whose quantitative sleepiness improves have improved attention and reduced externalising behaviours.Copyright © 2016 Elsevier B.V.

Objective: To provide a quantitative evaluation of typical electroencephalographic (EEG) abnormalities in genetic generalized epilepsy (GGE). Method(s): We prospectively performed 24-ambulatory EEG recordings in a cohort of patients with GGE. The diagnosis was established according to the International League Against Epilepsy criteria. Details of all epileptiform discharges across the 24-time scale were entered into an electronic database. We carried out descriptive statistics to provide a quantitative breakdown of typical EEG abnormalities. Result(s): A total of 6923 epileptiform discharges from 105 abnormal 24-ambulatory EEGs were analyzed. 96% of discharges were symmetric in amplitude with fronto-central maximum topographically. Only 24% of the paroxysms had typical morphology while 43% were regular. Photoparoxysmal response, eye-closure sensitivity and hyperventilation-induced generalized paroxysms were less common in around 10%, whereas occipital intermittent rhythmic delta activity was very rare (2%). Conclusion(s): Our results indicate that generalized discharges with symmetric amplitude and fronto-central maxima are the most consistent findings in GGE, and other features are observed less frequently. Significance: Epileptiform discharges displaying highly consistent amplitude symmetry coupled with fronto-central topography should provoke consideration of GGE. Recognition of variations from typical abnormalities is important to avoid the risk of misdiagnosis and delayed diagnosis.Copyright © 2015 Published by Elsevier Ireland Ltd.

Background It has been suggested that impaired dissipation of slow-wave activity (SWA) in children with sleep-disordered breathing (SDB) may be a potential mechanism for daytime dysfunction. We aimed to examine whether resolution of SDB resulted in normalisation of SWA dissipation and whether this was associated with improved cognition and behaviour. Methods Children (aged 3-6 y) diagnosed with SDB and age-matched non-snoring control children were followed up for 3 y after a baseline study. At the follow-up, children were categorised into control (N = 13), resolved SDB (N = 15) and unresolved SDB (N = 14). Delta activity on the electroencephalogram over the sleep period was used to calculate SWA and a battery of cognitive assessments and behaviour questionnaires were conducted at both time points. Results There was no change in the average SWA between the baseline and follow-up and no differences between the groups. Cognitive and behavioural performance in the resolved group did not improve to control levels. However, decreased SWA at the beginning of the sleep period (beta = -0.04, p = 0.002) and a decrease in obstructive apnoea-hypopnoea index (beta = -2.2, p = 0.022) between the baseline and follow-up predicted improvements in measures of sustained attention. Increased SWA at the beginning of the sleep period between the baseline and follow-up predicted worsening of externalising behaviour (beta = 0.02, p = 0.039). Conclusions This study suggests that resolution of SDB is not associated with changes in the dissipation of SWA. However, the association between decreases in SWA and improvements in cognitive and behavioural outcomes suggest that irrespective of disease, children whose quantitative sleepiness improves have improved attention and reduced externalising behaviours.Copyright © 2016 Elsevier B.V.

Our objective was to define the EEG features during sleep of children with neurodevelopmental disorders due to copy number gains of 15q11-q13 (Dup15q). We retrospectively reviewed continuous EEG recordings of 42 children with Dup15q (mean age: eight years, 32 with idic15), and data collected included background activity, interictal epileptiform discharges, sleep organization, and ictal activity. Three patterns were recognized: Pattern 1: Alpha–delta sleep was noted in 14 children (33%), not associated with any clinical changes. Pattern 2: Electrical status epilepticus in sleep was noted in 15 children (35%), all diagnosed with treatmentresistant epilepsy. Thirteen of the 15 children had clinical seizures. Pattern 3: Frequent bursts of high amplitude bifrontal predominant, paroxysmal fast activity (12–15 Hz) during non-REM sleep was noted in 15 children (35%). All 15 children had treatment-resistant epilepsy. This is the first report of electroencephalographic patterns during sleep of children with Dup15q reporting alpha-delta rhythms, CSWS, and high amplitude fast frequencies. Alpha-delta rhythms are described in children with dysautonomia and/or mood disorders and CSWS in children with developmental regression. The significance of these findings in cognitive function and epilepsy for the children in our cohort needs to be determined with follow-up studies.

Our aim was to enhance the spontaneous slow-frequency EEG activity during the resting state using oscillating transcranial direct currents (tDCS) with a stimulation frequency that resembles the spontaneous oscillations of sleep onset. Accordingly, in this preliminary study, we assessed EEG after-effects of a frontal oscillatory tDCS with different frequency (0.8 vs. 5 Hz) and polarity (anodal, cathodal, and sham).Two single-blind experiments compared the after effects on the resting EEG of oscillatory tDCS [Exp. 1 = 0.8 Hz, 10 subjects (26.2 ± 2.5 years); Exp. 2 = 5 Hz, 10 subjects (27.4 ± 2.4 years)] by manipulating its polarity.EEG signals recorded (28 scalp derivations) before and after stimulation [slow oscillations (0.5-1 Hz), delta (1-4 Hz), theta (5-7 Hz), alpha (8-12 Hz), beta 1 (13-15 Hz) and beta 2 (16-24 Hz)] were compared between conditions as a function of polarity (anodal vs. cathodal vs. sham) and frequency of stimulation (0.8 vs. 5 Hz).We found a significant relative enhancement of the delta activity after the anodal tDCS at 5 Hz compared to that at 0.8 Hz. This increase, even though not reaching the statistical significance compared to sham, is concomitant to a significant increase of subjective sleepiness, as assessed by a visual analog scale. These two phenomena are linearly related with a regional specificity, correlations being restricted to cortical areas perifocal to the stimulation site.We have shown that a frontal oscillating anodal tDCS at 5 Hz results in an effective change of both subjective sleepiness and spontaneous slow-frequency EEG activity. These changes are critically associated to both stimulation polarity (anodal) and frequency (5 Hz). However, evidence of frequency-dependence seems more unequivocal than evidence of polarity-dependence.

We tested the hypothesis that 5months of combined anti-retroviral therapy (cART) affect cortical sources of resting state cortical electroencephalographic (EEG) rhythms in naïve HIV subjects.

Purpose: To analyze clinical features and EEG changes in patients with sporadic Creutzfeldt-Jakob disease and study the association between different EEG patterns and clinical stages. Methods: We retrospectively analyzed the clinical features and EEG patterns of 3 patients with clinical stage II and 10 patients with stage III sporadic Creutzfeldt-Jakob disease (EEG n = 17). Chi-square test was used to study the association between EEG features and disease stages. Results: Diffuse slowing of the background was the dominant EEG pattern in stage II disease. All stage III patients showed additional abnormalities, such as frontal intermittent rhythmic delta activity, periodic discharges, and nonperiodic triphasic waves. Periodic discharges had significant association with stage III disease, present in 64% of EEGs in this group. Sixty-seven percentage of periodic discharges had a peculiar pattern labeled by us as posterior-anterior-posterior lag. Conclusions: The EEG of stage II sporadic Creutzfeldt-Jakob disease is characterized by background slowing while the presence of periodic discharge has a significant association with stage III of the disease. The posterior- anterior-posterior lag of periodic discharge is a new observation.Copyright © 2014 by the American Clinical Neurophysiology Society.

Purpose: To analyze clinical features and EEG changes in patients with sporadic Creutzfeldt-Jakob disease and study the association between different EEG patterns and clinical stages. Methods: We retrospectively analyzed the clinical features and EEG patterns of 3 patients with clinical stage II and 10 patients with stage III sporadic Creutzfeldt-Jakob disease (EEG n = 17). Chi-square test was used to study the association between EEG features and disease stages. Results: Diffuse slowing of the background was the dominant EEG pattern in stage II disease. All stage III patients showed additional abnormalities, such as frontal intermittent rhythmic delta activity, periodic discharges, and nonperiodic triphasic waves. Periodic discharges had significant association with stage III disease, present in 64% of EEGs in this group. Sixty-seven percentage of periodic discharges had a peculiar pattern labeled by us as posterior-anterior-posterior lag. Conclusions: The EEG of stage II sporadic Creutzfeldt-Jakob disease is characterized by background slowing while the presence of periodic discharge has a significant association with stage III of the disease. The posterior- anterior-posterior lag of periodic discharge is a new observation.Copyright © 2014 by the American Clinical Neurophysiology Society.

The aim of the study was to test the hypothesis that cortical sources of resting-state electroencephalographic (EEG) rhythms show peculiar frequency/spatial features in naïve human subjects with human immunodeficiency virus (HIV) compared to healthy control subjects.

The aim of the study was to test the hypothesis that cortical sources of resting-state electroencephalographic (EEG) rhythms show peculiar frequency/spatial features in naïve human subjects with human immunodeficiency virus (HIV) compared to healthy control subjects.

People aged 90 years and older (oldest old), the fastest growing segment of the United States population, are known to have high rates of spells of all types, including strokes, transient ischemic attacks, and seizures. This study examined the prevalence of EEG abnormalities in 12 physically and cognitively healthy oldest old (mean age = 94 years) with no history of seizures or spells. Abnormalities were found in 83% of participants: temporal intermittent polymorphic slowing was seen in 67%, background slowing (alpha rhythm <8 Hz) was present in 33%, and temporal intermittent rhythmic delta was found in 17%. The high rates of EEG abnormalities found in these physically and cognitively healthy participants prompt reappraisal of pathologic significance in this unique population.

People aged 90 years and older (oldest old), the fastest growing segment of the United States population, are known to have high rates of spells of all types, including strokes, transient ischemic attacks, and seizures. This study examined the prevalence of EEG abnormalities in 12 physically and cognitively healthy oldest old (mean age = 94 years) with no history of seizures or spells. Abnormalities were found in 83% of participants: temporal intermittent polymorphic slowing was seen in 67%, background slowing (alpha rhythm <8 Hz) was present in 33%, and temporal intermittent rhythmic delta was found in 17%. The high rates of EEG abnormalities found in these physically and cognitively healthy participants prompt reappraisal of pathologic significance in this unique population.

Locked-in syndrome (LIS) is a state of complete paralysis, except for ocular movements, which results from ventral brainstem lesions. Patients typically are fully conscious. Here we tested the hypothesis that electroencephalographic (EEG) rhythms are abnormal in LIS patients, possibly due to an impaired neural synchronization between brainstem and cerebral cortex.

Aims: To investigate the changes in the electroencephalographic (EEG) spectrum in smokers during exposure to a neutral and a smoking-related cue to determine whether these EEG changes are still present in ex-smokers after prolonged abstinence and to examine the relationship between the power in each spectral bandwidth and subjective craving. Methods: EEG frequencies in response to a smoking-related and a neutral cue were examined in 23 smokers and 21 ex-smokers, who quit smoking for 1.4 years on average. Additionally, self-report measures of cigarette craving and nicotine dependence were obtained. The spectral power of each bandwidth was computed, log-transformed, and analyzed using a within-subject design. Differences between EEG activity under neutral and smoking conditions were correlated with differences between pre- and postexperimental subjective craving. Results: Increases in reward craving (desire and intention to smoke) were associated with reduced theta activity, whereas increases in withdrawal craving (reduction of negative affect and withdrawal symptoms) were correlated with increases in both delta and higher alpha power. Furthermore, in smokers, but not in ex-smokers, a significant beta power increase was observed between the neutral condition and the smoking condition. Conclusion: Since the beta band is associated with arousal, attention, and alertness, it is suggested that the beta increase in response to the smoking cue might reflect an enhanced allocation of resources to smoking-related stimuli, i.e. a processing bias, which is an important feature of substance abuse. Since ex-smokers do not respond to the smoking cue with beta activity enhancement, we preliminarily conclude that smoking cues do not arouse ex-smokers or capture their attention as much as they do in smokers.

OBJECTIVE: To determine if chronic insomnia alters the relationship between heart rate variability and delta sleep determined at the EEG. METHODS: After one night of accommodation, polysomnography was performed in 14 male patients with chronic primary insomnia matched with 14 healthy men. ECG and EEG recordings allowed the determination of High Frequency (HF) power of RR-interval and delta sleep EEG power across the first three Non Rapid Eye Movement (NREM)-REM cycles. Interaction between normalized HF RR-interval variability and normalized delta sleep EEG power was studied by coherency analysis. RESULTS: Patients showed increased total number of awakenings, longer sleep latency and wake durations and shorter sleep efficiency and REM duration than controls (p<.01). Heart rate variability across first three NREM-REM cycles and sleep stages (NREM, REM and awake) were similar between both groups. In each group, normalized HF variability of RR-interval decreased from NREM to both REM and awake. Patients showed decreased linear relationship between normalized HF RR-interval variability and delta EEG power, expressed by decreased coherence, in comparison to controls (p<.05). Gain and phase shift between these signals were similar between both groups. CONCLUSIONS: Interaction between changes in cardiac autonomic activity and delta power is altered in chronic primary insomniac patients, even in the absence of modifications in heart rate variability and cardiovascular diseases. SIGNIFICANCE: This altered interaction could reflect the first step to cardiovascular disorders., Journal Article, Research Support, Non-U.S. Gov't, SCOPUS: ar.j, info:eu-repo/semantics/published

Recent evidence suggests that problems in information processing within neural networks may underlie depressive disease. In this study, we investigated whether sleep functional brain networks are abnormally organized during a major depressive episode (MDE). We characterized spatial patterns of functional connectivity by computing the "synchronization likelihood" (SL) of 19 sleep EEG channels in 11 acutely depressed patients [42 (20-51) years] and 14 healthy controls [32.9 (27-42) years]. To test whether disrupting an optimal pattern ["small-world network" (SWN)] of functional brain connectivity underlies MDE, graph theoretical measures were then applied to the resulting synchronization matrices, and a clustering coefficient (C, measure of local connectedness) and a shortest path length (L, measure of overall network integration) were determined. In the depressed group, the mean SL was lower in the delta, theta and sigma frequency bands. Acutely depressed patients showed a significantly lower path length in the theta and delta frequency bands, whereas the cluster coefficient showed no significant changes. The present study provides further support that sleep functional brain networks exhibit "small-world" properties. Sleep neuronal functional networks in depressed patients are characterized by a functional reorganization with a lower mean level of global synchronization and loss of SWN characteristics. These results argue for considering an MDE as a problem of neuronal network organization and a problem of information processing., Journal Article, Research Support, Non-U.S. Gov't, FLWIN, info:eu-repo/semantics/published

OBJECTIVE: To determine if chronic insomnia alters the relationship between heart rate variability and delta sleep determined at the EEG. METHODS: After one night of accommodation, polysomnography was performed in 14 male patients with chronic primary insomnia matched with 14 healthy men. ECG and EEG recordings allowed the determination of High Frequency (HF) power of RR-interval and delta sleep EEG power across the first three Non Rapid Eye Movement (NREM)-REM cycles. Interaction between normalized HF RR-interval variability and normalized delta sleep EEG power was studied by coherency analysis. RESULTS: Patients showed increased total number of awakenings, longer sleep latency and wake durations and shorter sleep efficiency and REM duration than controls (p<.01). Heart rate variability across first three NREM-REM cycles and sleep stages (NREM, REM and awake) were similar between both groups. In each group, normalized HF variability of RR-interval decreased from NREM to both REM and awake. Patients showed decreased linear relationship between normalized HF RR-interval variability and delta EEG power, expressed by decreased coherence, in comparison to controls (p<.05). Gain and phase shift between these signals were similar between both groups. CONCLUSIONS: Interaction between changes in cardiac autonomic activity and delta power is altered in chronic primary insomniac patients, even in the absence of modifications in heart rate variability and cardiovascular diseases. SIGNIFICANCE: This altered interaction could reflect the first step to cardiovascular disorders., Journal Article, Research Support, Non-U.S. Gov't, SCOPUS: ar.j, info:eu-repo/semantics/published

Recent evidence suggests that problems in information processing within neural networks may underlie depressive disease. In this study, we investigated whether sleep functional brain networks are abnormally organized during a major depressive episode (MDE). We characterized spatial patterns of functional connectivity by computing the "synchronization likelihood" (SL) of 19 sleep EEG channels in 11 acutely depressed patients [42 (20-51) years] and 14 healthy controls [32.9 (27-42) years]. To test whether disrupting an optimal pattern ["small-world network" (SWN)] of functional brain connectivity underlies MDE, graph theoretical measures were then applied to the resulting synchronization matrices, and a clustering coefficient (C, measure of local connectedness) and a shortest path length (L, measure of overall network integration) were determined. In the depressed group, the mean SL was lower in the delta, theta and sigma frequency bands. Acutely depressed patients showed a significantly lower path length in the theta and delta frequency bands, whereas the cluster coefficient showed no significant changes. The present study provides further support that sleep functional brain networks exhibit "small-world" properties. Sleep neuronal functional networks in depressed patients are characterized by a functional reorganization with a lower mean level of global synchronization and loss of SWN characteristics. These results argue for considering an MDE as a problem of neuronal network organization and a problem of information processing., Journal Article, Research Support, Non-U.S. Gov't, FLWIN, info:eu-repo/semantics/published

We hypothesize that sleep apnea-hypopnea alters interaction between cardiac vagal modulation and sleep delta EEG. Sleep apnea-hypopnea syndrome (SAHS) is related to cardiovascular complications in men. SAHS patients show higher sympathetic activity than normal subjects. In healthy men, non-rapid eye movement (NREM) sleep is associated with cardiac vagal influence, whereas rapid eye movement (REM) sleep is linked to cardiac sympathetic activity. Interaction between cardiac autonomic modulation and delta sleep EEG is not altered across a life span nor is the delay between appearances of modifications in both signals. Healthy controls, moderate SAHS, and severe SAHS patients were compared across the first three NREM-REM cycles. Spectral analysis was applied to ECG and EEG signals. High frequency (HF) and low frequency (LF) of heart rate variability (HRV), ratio of LF/HF, and normalized (nu) delta power were obtained. A coherency analysis between HF(nu) and delta was performed, as well as a correlation analysis between obstructive apnea index (AI) or hypopnea index (HI) and gain, coherence, or phase shift. HRV components were similar between groups. In each group, HF(nu) was larger during NREM, while LF(nu) predominated across REM and wake stages. Coherence and gain between HF(nu) and delta decreased from controls to severe SAHS patients. In SAHS patients, the delay between modifications in HF(nu) and delta did not differ from zero. AI and HI correlated negatively with coherence, while HI correlated negatively with gain only. Apneas-hypopneas affect the link between cardiac sympathetic and vagal modulation and delta EEG demonstrated by the loss of cardiac autonomic activity fluctuations across shifts in sleep stages. Obstructive apneas and hypopneas alter the interaction between both signals differently., Journal Article, Research Support, Non-U.S. Gov't, info:eu-repo/semantics/published

We hypothesize that sleep apnea-hypopnea alters interaction between cardiac vagal modulation and sleep delta EEG. Sleep apnea-hypopnea syndrome (SAHS) is related to cardiovascular complications in men. SAHS patients show higher sympathetic activity than normal subjects. In healthy men, non-rapid eye movement (NREM) sleep is associated with cardiac vagal influence, whereas rapid eye movement (REM) sleep is linked to cardiac sympathetic activity. Interaction between cardiac autonomic modulation and delta sleep EEG is not altered across a life span nor is the delay between appearances of modifications in both signals. Healthy controls, moderate SAHS, and severe SAHS patients were compared across the first three NREM-REM cycles. Spectral analysis was applied to ECG and EEG signals. High frequency (HF) and low frequency (LF) of heart rate variability (HRV), ratio of LF/HF, and normalized (nu) delta power were obtained. A coherency analysis between HF(nu) and delta was performed, as well as a correlation analysis between obstructive apnea index (AI) or hypopnea index (HI) and gain, coherence, or phase shift. HRV components were similar between groups. In each group, HF(nu) was larger during NREM, while LF(nu) predominated across REM and wake stages. Coherence and gain between HF(nu) and delta decreased from controls to severe SAHS patients. In SAHS patients, the delay between modifications in HF(nu) and delta did not differ from zero. AI and HI correlated negatively with coherence, while HI correlated negatively with gain only. Apneas-hypopneas affect the link between cardiac sympathetic and vagal modulation and delta EEG demonstrated by the loss of cardiac autonomic activity fluctuations across shifts in sleep stages. Obstructive apneas and hypopneas alter the interaction between both signals differently., Journal Article, Research Support, Non-U.S. Gov't, info:eu-repo/semantics/published

Objective: To test the hypothesis that there is increased low-frequency activity located predominantly in the frontal lobe in patients with major depressive disorder using magnetoencephalography. Methods: We carried out an unmatched or separate sampling case-control study of 31 medication-free patients who met the Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV), criteria for major depressive disorder and were outpatients of the Hospital Central de la Defensa, Madrid, and 22 healthy control subjects with no history of mental illness. A logistic regression analysis was employed to examine the predictive value of magnetoencephalography dipole density scores in the diagnosis of depression. We attempted to locate generators of focal magnetic slow waves by employing a single moving dipole model and by calculating dipole densities in prefrontal, frontal, parietal, temporal and occipital areas. The study lasted from February 2001 to January 2003. Results: Only 2 dipole density scores, right occipital delta and left temporal delta, were significantly related to depression. According to the comparison of univariate and multivariate models and odds ratios, the right occipital delta dipole density is the factor with the greatest predictive power for depression, and the only one to show a significant correlation with severity of depression. Conclusions: We did not find any frontal lobe functional alteration. Our study provides, to the best of our knowledge, the first evidence of abnormal focal magnetic low-frequency activity in the occipital lobe of untreated patients with depression. Increased occipital lobe delta dipole density seems to be a reliable risk factor for depression, which correlates with disease severity according to the Hamilton Rating Scale for Depression., Depto. de Estadística e Investigación Operativa, Depto. de Medicina Legal, Psiquiatría y Patología, Fac. de Ciencias Matemáticas, Fac. de Medicina, TRUE, pub

We aimed at characterizing the neural correlates of delta activity during Non Rapid Eye Movement (NREM) sleep in non-sleep-deprived normal young adults, based on the statistical analysis of a positron emission tomography (PET) sleep data set. One hundred fifteen PET scans were obtained using H(2)(15)O under continuous polygraphic monitoring during stages 2-4 of NREM sleep. Correlations between regional cerebral blood flow (rCBF) and delta power (1.5-4 Hz) spectral density were analyzed using statistical parametric mapping (SPM2). Delta power values obtained at central scalp locations negatively correlated during NREM sleep with rCBF in the ventromedial prefrontal cortex, the basal forebrain, the striatum, the anterior insula, and the precuneus. These regions embrace the set of brain areas in which rCBF decreases during slow wave sleep (SWS) as compared to Rapid Eye Movement (REM) sleep and wakefulness (Maquet, P. Degueldre, C. Delfiore, G. Aerts, J. Peters, J.M. Luxen, A. Franck, G. 1997. Functional neuroanatomy of human slow wave sleep. J. Neurosci. 17, 2807-S2812), supporting the notion that delta activity is a valuable prominent feature of NREM sleep. A strong association was observed between rCBF in the ventromedial prefrontal regions and delta power, in agreement with electrophysiological studies. In contrast to the results of a previous PET study investigating the brain correlates of delta activity (Hofle, N. Paus, T. Reutens, D. Fiset, P. Gotman, J. Evans, A.C. Jones, B.E. 1997. Regional cerebral blood flow changes as a function of delta and spindle activity during slow wave sleep in humans. J. Neurosci. 17, 4800-4808), in which waking scans were mixed with NREM sleep scans, no correlation was found with thalamus activity. This latter result stresses the importance of an extra-thalamic delta rhythm among the synchronous NREM sleep oscillations. Consequently, this rCBF distribution might preferentially reflect a particular modulation of the cellular processes, Journal Article, Meta-Analysis, Research Support, Non-U.S. Gov't, info:eu-repo/semantics/published

We aimed at characterizing the neural correlates of delta activity during Non Rapid Eye Movement (NREM) sleep in non-sleep-deprived normal young adults, based on the statistical analysis of a positron emission tomography (PET) sleep data set. One hundred fifteen PET scans were obtained using H(2)(15)O under continuous polygraphic monitoring during stages 2-4 of NREM sleep. Correlations between regional cerebral blood flow (rCBF) and delta power (1.5-4 Hz) spectral density were analyzed using statistical parametric mapping (SPM2). Delta power values obtained at central scalp locations negatively correlated during NREM sleep with rCBF in the ventromedial prefrontal cortex, the basal forebrain, the striatum, the anterior insula, and the precuneus. These regions embrace the set of brain areas in which rCBF decreases during slow wave sleep (SWS) as compared to Rapid Eye Movement (REM) sleep and wakefulness (Maquet, P. Degueldre, C. Delfiore, G. Aerts, J. Peters, J.M. Luxen, A. Franck, G. 1997. Functional neuroanatomy of human slow wave sleep. J. Neurosci. 17, 2807-S2812), supporting the notion that delta activity is a valuable prominent feature of NREM sleep. A strong association was observed between rCBF in the ventromedial prefrontal regions and delta power, in agreement with electrophysiological studies. In contrast to the results of a previous PET study investigating the brain correlates of delta activity (Hofle, N. Paus, T. Reutens, D. Fiset, P. Gotman, J. Evans, A.C. Jones, B.E. 1997. Regional cerebral blood flow changes as a function of delta and spindle activity during slow wave sleep in humans. J. Neurosci. 17, 4800-4808), in which waking scans were mixed with NREM sleep scans, no correlation was found with thalamus activity. This latter result stresses the importance of an extra-thalamic delta rhythm among the synchronous NREM sleep oscillations. Consequently, this rCBF distribution might preferentially reflect a particular modulation of the cellular processes, Journal Article, Meta-Analysis, Research Support, Non-U.S. Gov't, info:eu-repo/semantics/published

OBJECTIVE: We investigated the interactions between heart rate variability and sleep electroencephalogram power spectra. METHODS: Heart rate and sleep electroencephalogram signals were recorded in 8 healthy young men. Spectral analysis was applied to electrocardiogram and electroencephalogram recordings. Spectral components of RR intervals were studied across sleep stages. The cross-spectrum maximum was determined as well as coherencies, gains and phase shifts between normalized high frequency of RR intervals and all electroencephalographic frequency bands, calculated over the first 3 NREM-REM cycles. RESULTS: RR intervals increased from awake to NREM and decreased during REM. Normalized low frequency decreased from awake to NREM and increased during REM while normalized high frequency evolved conversely. Low to high frequency ratio developed in opposition to RR intervals. Coherencies between normalized high frequency and power spectra were high for all bands. The gain was highest for delta band. Phase shift between normalized high frequency and delta differed from zero and modifications in normalized high frequency preceded changes in delta by 41+/-14 degrees. CONCLUSIONS: Our study demonstrates that: (1) all electroencephalographic power bands are linked to normalized high frequency; (2) modifications in cardiac vagal activity show predominantly parallel changes and precede changes in delta band by a phase shift corresponding to a lead of 12+/-5 min., Journal Article, Research Support, Non-U.S. Gov't, info:eu-repo/semantics/published

OBJECTIVE: We investigated the interactions between heart rate variability and sleep electroencephalogram power spectra. METHODS: Heart rate and sleep electroencephalogram signals were recorded in 8 healthy young men. Spectral analysis was applied to electrocardiogram and electroencephalogram recordings. Spectral components of RR intervals were studied across sleep stages. The cross-spectrum maximum was determined as well as coherencies, gains and phase shifts between normalized high frequency of RR intervals and all electroencephalographic frequency bands, calculated over the first 3 NREM-REM cycles. RESULTS: RR intervals increased from awake to NREM and decreased during REM. Normalized low frequency decreased from awake to NREM and increased during REM while normalized high frequency evolved conversely. Low to high frequency ratio developed in opposition to RR intervals. Coherencies between normalized high frequency and power spectra were high for all bands. The gain was highest for delta band. Phase shift between normalized high frequency and delta differed from zero and modifications in normalized high frequency preceded changes in delta by 41+/-14 degrees. CONCLUSIONS: Our study demonstrates that: (1) all electroencephalographic power bands are linked to normalized high frequency; (2) modifications in cardiac vagal activity show predominantly parallel changes and precede changes in delta band by a phase shift corresponding to a lead of 12+/-5 min., Journal Article, Research Support, Non-U.S. Gov't, info:eu-repo/semantics/published

The distribution of delta activity across successive nonrapid eye movement (NREM) sleep episodes and its night-to-night stability across three consecutive nights were investigated by studying delta power with spectral analysis in 31 healthy young men. Repeated-measures analysis of variance (ANOVA) with polynomial contrast was applied to grouped data of absolute delta power and three indexes: (1) the rate of delta power per NREM episode to its duration, 2) the standardized rate for the last NREM episode, and 3) the logarithm of the standardized rate. A significant linear decrease across NREM episodes was observed for each variable in each successive night. In addition, using night as a second within-subjects factor, no night effect was observed. Yet, the subsequent analysis of the logarithmic data yielded greater F values in all three nights' data as well as a linear function that accounted for a greater proportion of total variance than the analysis of the nonlogarithmic data. Since a linear decline for the logarithm of a variable implies an exponential distribution for that variable, we conclude that delta activity is distributed exponentially across NREM episodes, and this finding shows a remarkable night-to-night stability., Journal Article, Research Support, Non-U.S. Gov't, info:eu-repo/semantics/published

The distribution of delta activity across successive nonrapid eye movement (NREM) sleep episodes and its night-to-night stability across three consecutive nights were investigated by studying delta power with spectral analysis in 31 healthy young men. Repeated-measures analysis of variance (ANOVA) with polynomial contrast was applied to grouped data of absolute delta power and three indexes: (1) the rate of delta power per NREM episode to its duration, 2) the standardized rate for the last NREM episode, and 3) the logarithm of the standardized rate. A significant linear decrease across NREM episodes was observed for each variable in each successive night. In addition, using night as a second within-subjects factor, no night effect was observed. Yet, the subsequent analysis of the logarithmic data yielded greater F values in all three nights' data as well as a linear function that accounted for a greater proportion of total variance than the analysis of the nonlogarithmic data. Since a linear decline for the logarithm of a variable implies an exponential distribution for that variable, we conclude that delta activity is distributed exponentially across NREM episodes, and this finding shows a remarkable night-to-night stability., Journal Article, Research Support, Non-U.S. Gov't, info:eu-repo/semantics/published

Quantitative scalp EEG from 32 channels and the cerebral glucose metabolic rate from the 32 underlying cortical positions as assessed by positron emission tomography (PET) with 18F-2-deoxyglucose (FDG) were obtained on 36 patients with mild to moderate senile dementia of the Alzheimer type and 17 age- and sex-matched normal control subjects. Subjects performed a verbal memory task during uptake of FDG. There were significant correlations between both delta amplitude and metabolic rate and memory performance during FDG uptake. Patients with Alzheimer's disease had significantly greater left temporal delta amplitude and lower glucose metabolic rates. Both EEG delta in microvolts and metabolic rate had similar diagnostic sensitivity, but PET had fewer false positives among normals. The left amygdala had the highest sensitivity and percent correct diagnosis of any brain area. Temporal lobe EEG delta activity showed higher correlations with hippocampal metabolic rate than metabolic rate directly under the electrode.