EEG abnormalities are not associated with poor antidepressant treatment outcome - A NeuroPharm study.

EEG brain abnormalities, such as slowing and isolated epileptiform discharges (IEDs), has previously been associated with non-response to antidepressant treatment with escitalopram and venlafaxine, suggesting a potential need for treatment with anticonvulsant property in some patients. The current study aims to replicate the reported association of EEG abnormality and treatment outcomes in an open-label trial of escitalopram for major depressive disorder (MDD) and explore its relationship to mood and cognition. Pretreatment, 6 min eyes-closed resting-state 256-channel EEG was recorded in 91 patients with MDD (age 18-57) who were treated with 10-20 mg escitalopram for 12 weeks; patients could switch to duloxetine after four weeks. A certified clinical neurophysiologist rated the EEGs. IED and EEG slowing was seen in 13.2%, and in 6.6% there were findings with unclear significance (i.e., Wicket spikes and theta activity). We saw no group-difference in remission or response rates after 8 and 12 weeks of treatment or switching to duloxetine. Patients with EEG abnormalities had higher pretreatment mood disturbances driven by greater anger (p=.039) and poorer verbal memory (p=.012). However, EEG abnormality was not associated with improved mood or verbal memory after treatment. Our findings should be interpreted in light of the rarity of EEG abnormalities and the sample size. While we cannot confirm that EEG abnormalities are associated with non-response to treatment, including escitalopram, abnormal EEG activity is associated with poor mood and verbal memory. The clinical utility of EEG abnormality in antidepressant treatment selection needs careful evaluation before deciding if useful for clinical implementation.

Ageing and sleep.

This review focuses on ageing and sleep. A key focus in aging is to improve senescence by extending good health, optimal cognitive function, and medical and social assistance into later life. Given that one third of the human lifespan is spent sleeping, the importance of maintaining deep, stable, and consistent sleep is self-evident for the good life quality expected and optimal daytime functioning, which the aging process always curtails. For this reason, employees in the health system should know and focus on the expected changes in sleep patterns and disturbances from young adults to old age, including possible disorders and treatments.

Power and distribution of evoked gamma oscillations in brain aging and cognitive performance.

AIMS: Gamma oscillations (≈25-100 Hz) are believed to play an essential role in cognition, and aberrant gamma oscillations occur in brain aging and neurodegeneration. This study examined age-related changes in visually evoked gamma oscillations at two different time points 5 years apart and tested the hypothesis that the power of gamma oscillations correlated to cognitive skills. METHODS: The cohort consists of elderly males belonging to the Metropolit 1953 Danish Male Birth Cohort (first visit, N=124; second visit, N=88) over a 5-year period from 63 to 68 years of age. Cognitive functions were assessed using a neuropsychological test battery measuring global cognition, intelligence, memory, and processing speed. The power of steady-state visual evoked potentials (SSVEP) was measured at 8 Hz (alpha) and 36 Hz (gamma) frequencies using EEG scalp electrodes. RESULTS: Over the 5-year period cognitive performance remained relatively stable while the power of visually evoked gamma oscillations shifted from posterior to anterior brain regions with increasing age. A higher-than-average cognitive score was correlated with higher gamma power in parieto-occipital areas and lower in frontocentral areas, i.e., preserved distribution of the evoked activity. CONCLUSIONS: Our data reveal that the distribution of visually evoked gamma activity becomes distributed with age. Preserved posterior-occipital gamma power in participants with a high level of cognitive performance is consistent with a close association between the ability to produce gamma oscillations and cognition. The data may contribute to our understanding of the mechanisms that link evoked gamma activity and cognition in the aging brain.

Subclinical cognitive deficits are associated with reduced cerebrovascular response to visual stimulation in mid-sixties men.

Reduced cerebrovascular response to neuronal activation is observed in patients with neurodegenerative disease. In the present study, we examined the correlation between reduced cerebrovascular response to visual activation (ΔCBFVis.Act) and subclinical cognitive deficits in a human population of mid-sixties individuals without neurodegenerative disease. Such a correlation would suggest that impaired cerebrovascular function occurs before overt neurodegenerative disease. A total of 187 subjects (age 64-67 years) of the Metropolit Danish Male Birth Cohort participated in the study. ΔCBFVis.Act was measured using arterial spin labelling (ASL) MRI. ΔCBFVis.Act correlated positively with cognitive performance in: Global cognition (p = 0.046), paired associative memory (p = 0.025), spatial recognition (p = 0.026), planning (p = 0.016), simple processing speed (p < 0.01), and with highly significant correlations with current intelligence (p < 10-5), and more complex processing speed (p < 10-3), the latter two explaining approximately 11-13% of the variance. Reduced ΔCBFVis.Act was independent of brain atrophy. Our findings suggest that inhibited cerebrovascular response to neuronal activation is an early deficit in the ageing brain and associated with subclinical cognitive deficits. Cerebrovascular dysfunction could be an early sign of a trajectory pointing towards the development of neurodegenerative disease. Future efforts should elucidate if maintenance of a healthy cerebrovascular function can protect against the development of dementia.

Automatic continuous EEG signal analysis for diagnosis of delirium in patients with sepsis.

OBJECTIVE: In critical care, continuous EEG (cEEG) monitoring is useful for delirium diagnosis. Although visual cEEG analysis is most commonly used, automatic cEEG analysis has shown promising results in small samples. Here we aimed to compare visual versus automatic cEEG analysis for delirium diagnosis in septic patients. METHODS: We obtained cEEG recordings from 102 septic patients who were scored for delirium six times daily. A total of 1252 cEEG blocks were visually analyzed, of which 805 blocks were also automatically analyzed. RESULTS: Automatic cEEG analyses revealed that delirium was associated with 1) high mean global field power (p < 0.005), mainly driven by delta activity; 2) low average coherence across all electrode pairs and all frequencies (p < 0.01); 3) lack of intrahemispheric (fronto-temporal and temporo-occipital regions) and interhemispheric coherence (p < 0.05); and 4) lack of cEEG reactivity (p < 0.005). Classification accuracy was assessed by receiver operating characteristic (ROC) curve analysis, revealing a slightly higher area under the curve for visual analysis (0.88) than automatic analysis (0.74) (p < 0.05). CONCLUSIONS: Automatic cEEG analysis is a useful supplement to visual analysis, and provides additional cEEG diagnostic classifiers. SIGNIFICANCE: Automatic cEEG analysis provides useful information in septic patients.

Continuous EEG Monitoring in a Consecutive Patient Cohort with Sepsis and Delirium.

BACKGROUND: Delirium is common during sepsis, although under-recognized. We aimed to assess the value of continuous electroencephalography (cEEG) to aid in the diagnosis of delirium in septic patients. METHODS: We prospectively evaluated 102 consecutive patients in a medical intensive care unit (ICU), who had sepsis or septic shock, without evidence of acute primary central nervous system disease. We initiated cEEG recording immediately after identification. The median cEEG time per patient was 44 h (interquartile range 21-99 h). A total of 6723 h of cEEG recordings were examined. The Confusion Assessment Method for the ICU (CAM-ICU) was administered six times daily to identify delirium. We analyzed the correlation between cEEG and delirium using 1252 two-minute EEG sequences recorded simultaneously with the CAM-ICU scorings. RESULTS: Of the 102 included patients, 66 (65%) had at least one delirium episode during their ICU stay, 30 (29%) remained delirium-free, and 6 (6%) were not assessable due to deep sedation or coma. The absence of delirium was independently associated with preserved high-frequency beta activity (> 13 Hz) (P < 10-7) and cEEG reactivity (P < 0.001). Delirium was associated with preponderance of low-frequency cEEG activity and absence of high-frequency cEEG activity. Sporadic periodic cEEG discharges occurred in 15 patients, 13 of whom were delirious. No patient showed clinical or electrographic evidence of non-convulsive status epilepticus. CONCLUSIONS: Our findings indicate that cEEG can help distinguish septic patients with delirium from non-delirious patients.