Pharmacological Modulation of Noradrenergic Arousal Circuitry Disrupts Functional Connectivity of the Locus Ceruleus in Humans

State-dependent activity of locus ceruleus (LC) neurons has long suggested a role for noradrenergic modulation of arousal. However, in vivo insights into noradrenergic arousal circuitry have been constrained by the fundamental inaccessibility of the human brain for invasive studies. Functional magnetic resonance imaging (fMRI) studies performed during site-specific pharmacological manipulations of arousal levels may be used to study brain arousal circuitry. Dexmedetomidine is an anesthetic that alters the level of arousal by selectively targeting α2 adrenergic receptors on LC neurons, resulting in reduced firing rate and norepinephrine release. Thus, we hypothesized that dexmedetomidine-induced altered arousal would manifest with reduced functional connectivity between the LC and key brain regions involved in the regulation of arousal. To test this hypothesis, we acquired resting-state fMRI data in right-handed healthy volunteers 18–36 years of age (n = 15, 6 males) at baseline, during dexmedetomidine-induced altered arousal, and recovery states. As previously reported, seed-based resting-state fMRI analyses revealed that the LC was functionally connected to a broad network of regions including the reticular formation, basal ganglia, thalamus, posterior cingulate cortex (PCC), precuneus, and cerebellum. Functional connectivity of the LC to only a subset of these regions (PCC, thalamus, and caudate nucleus) covaried with the level of arousal. Functional connectivity of the PCC to the ventral tegmental area/pontine reticular formation and thalamus, in addition to the LC, also covaried with the level of arousal. We propose a framework in which the LC, PCC, thalamus, and basal ganglia comprise a functional arousal circuitry

Brain Age from the Electroencephalogram of Sleep

The human electroencephalogram (EEG) of sleep undergoes profound changes with age. These changes can be conceptualized as "brain age", which can be compared to an age norm to reflect the deviation from normal aging process. Here, we develop an interpretable machine learning model to predict brain age based on two large sleep EEG datasets: the Massachusetts General Hospital sleep lab dataset (MGH, N = 2,621) covering age 18 to 80; and the Sleep Hearth Health Study (SHHS, N = 3,520) covering age 40 to 80. The model obtains a mean absolute deviation of 8.1 years between brain age and chronological age in the healthy participants in the MGH dataset. As validation, we analyze a subset of SHHS containing longitudinal EEGs 5 years apart, which shows a 5.5 years difference in brain age. Participants with neurological and psychiatric diseases, as well as diabetes and hypertension medications show an older brain age compared to chronological age. The findings raise the prospect of using sleep EEG as a biomarker for healthy brain aging

The human burst suppression electroencephalogram of deep hypothermia

Objective: Deep hypothermia induces 'burst suppression' (BS), an electroencephalogram pattern with low-voltage 'suppressions' alternating with high-voltage 'bursts'. Current understanding of BS comes mainly from anesthesia studies, while hypothermia-induced BS has received little study. We set out to investigate the electroencephalogram changes induced by cooling the human brain through increasing depths of BS through isoelectricity. Methods: We recorded scalp electroencephalograms from eleven patients undergoing deep hypothermia during cardiac surgery with complete circulatory arrest, and analyzed these using methods of spectral analysis. Results: Within patients, the depth of BS systematically depends on the depth of hypothermia, though responses vary between patients except at temperature extremes. With decreasing temperature, burst lengths increase, and burst amplitudes and lengths decrease, while the spectral content of bursts remains constant. Conclusions: These findings support an existing theoretical model in which the common mechanism of burst suppression across diverse etiologies is the cyclical diffuse depletion of metabolic resources, and suggest the new hypothesis of local micro-network dropout to explain decreasing burst amplitudes at lower temperatures. Significance: These results pave the way for accurate noninvasive tracking of brain metabolic state during surgical procedures under deep hypothermia, and suggest new testable predictions about the network mechanisms underlying burst suppression.National Institutes of Health (U.S.) (Grant DP2-OD006454)National Institutes of Health (U.S.) (Grant DP1-OD003646)National Institutes of Health (U.S.) (Grant TR01-GM104948

Automated tracking of level of consciousness and delirium in critical illness using deep learning

Over- and under-sedation are common in the ICU, and contribute to poor ICU outcomes including delirium. Behavioral assessments, such as Richmond Agitation-Sedation Scale (RASS) for monitoring levels of sedation and Confusion Assessment Method for the ICU (CAM-ICU) for detecting signs of delirium, are often used. As an alternative, brain monitoring with electroencephalography (EEG) has been proposed in the operating room, but is challenging to implement in ICU due to the differences between critical illness and elective surgery, as well as the duration of sedation. Here we present a deep learning model based on a combination of convolutional and recurrent neural networks that automatically tracks both the level of consciousness and delirium using frontal EEG signals in the ICU. For level of consciousness, the system achieves a median accuracy of 70% when allowing prediction to be within one RASS level difference across all patients, which is comparable or higher than the median technician-nurse agreement at 59%. For delirium, the system achieves an AUC of 0.80 with 69% sensitivity and 83% specificity at the optimal operating point. The results show it is feasible to continuously track level of consciousness and delirium in the ICU

A transient cortical state with sleep-like sensory responses precedes emergence from general anesthesia in humans

During awake consciousness, the brain intrinsically maintains a dynamical state in which it can coordinate complex responses to sensory input. How the brain reaches this state spontaneously is not known. General anesthesia provides a unique opportunity to examine how the human brain recovers its functional capabilities after profound unconsciousness. We used intracranial electrocorticography and scalp EEG in humans to track neural dynamics during emergence from propofol general anesthesia. We identify a distinct transient brain state that occurs immediately prior to recovery of behavioral responsiveness. This state is characterized by large, spatially distributed, slow sensory-evoked potentials that resemble the K-complexes that are hallmarks of stage two sleep. However, the ongoing spontaneous dynamics in this transitional state differ from sleep. These results identify an asymmetry in the neurophysiology of induction and emergence, as the emerging brain can enter a state with a sleep-like sensory blockade before regaining responsivity to arousing stimuli.National Institutes of Health (U.S.) (Grant K99-MH111748)National Institutes of Health (U.S.) (Grant R00-NS080911)National Institutes of Health (U.S.) (Grant DP2-OD006454)National Institutes of Health (U.S.) (Grant S10-RR023401)National Institutes of Health (U.S.) (Grant R01- NS062092)National Institutes of Health (U.S.) (Grant R01AG056015)National Institutes of Health (U.S.) (Grant P01GM118269)National Institutes of Health (U.S.) (Grant R01-EB009282

Spatiotemporal Dynamics of Dexmedetomidine-Induced Electroencephalogram Oscillations

An improved understanding of the neural correlates of altered arousal states is fundamental for precise brain state targeting in clinical settings. More specifically, electroencephalogram recordings are now increasingly being used to relate drug-specific oscillatory dynamics to clinically desired altered arousal states. Dexmedetomidine is an anesthetic adjunct typically administered in operating rooms and intensive care units to produce and maintain a sedative brain state. However, a high-density electroencephalogram characterization of the neural correlates of the dexmedetomidine-induced altered arousal state has not been previously accomplished. Therefore, we administered dexmedetomidine (1mcg/kg bolus over 10 minutes, followed by 0.7mcg/kg/hr over 50 minutes) and recorded high-density electroencephalogram signals in healthy volunteers, 18–36 years old (n = 8). We analyzed the data with multitaper spectral and global coherence methods. We found that dexmedetomidine was associated with increased slow-delta oscillations across the entire scalp, increased theta oscillations in occipital regions, increased spindle oscillations in frontal regions, and decreased beta oscillations across the entire scalp. The theta and spindle oscillations were globally coherent. During recovery from this state, these electroencephalogram signatures reverted towards baseline signatures. We report that dexmedetomidine-induced electroencephalogram signatures more closely approximate the human sleep onset process than previously appreciated. We suggest that these signatures may be targeted by real time visualization of the electroencephalogram or spectrogram in clinical settings. Additionally, these signatures may aid the development of control systems for principled neurophysiological based brain-state targeting

Disruption of thalamic functional connectivity is a neural correlate of dexmedetomidine-induced unconsciousness

Understanding the neural basis of consciousness is fundamental to neuroscience research. Disruptions in cortico-cortical connectivity have been suggested as a primary mechanism of unconsciousness. By using a novel combination of positron emission tomography and functional magnetic resonance imaging, we studied anesthesia-induced unconsciousness and recovery using the α2-agonist dexmedetomidine. During unconsciousness, cerebral metabolic rate of glucose and cerebral blood flow were preferentially decreased in the thalamus, the Default Mode Network (DMN), and the bilateral Frontoparietal Networks (FPNs). Cortico-cortical functional connectivity within the DMN and FPNs was preserved. However, DMN thalamo-cortical functional connectivity was disrupted. Recovery from this state was associated with sustained reduction in cerebral blood flow and restored DMN thalamo-cortical functional connectivity. We report that loss of thalamo-cortical functional connectivity is sufficient to produce unconsciousness. DOI: http://dx.doi.org/10.7554/eLife.04499.00

Increased in vivo glial activation in patients with amyotrophic lateral sclerosis: Assessed with [11C]-PBR28

Evidence from human post mortem, in vivo and animal model studies implicates the neuroimmune system and activated microglia in the pathology of amyotrophic lateral sclerosis. The study aim was to further evaluate in vivo neuroinflammation in individuals with amyotrophic lateral sclerosis using [11C]-PBR28 positron emission tomography. Ten patients with amyotrophic lateral sclerosis (seven males, three females, 38–68 years) and ten age- and [11C]-PBR28 binding affinity-matched healthy volunteers (six males, four females, 33–65 years) completed a positron emission tomography scan. Standardized uptake values were calculated from 60 to 90 min post-injection and normalized to whole brain mean. Voxel-wise analysis showed increased binding in the motor cortices and corticospinal tracts in patients with amyotrophic lateral sclerosis compared to healthy controls (pFWE < 0.05). Region of interest analysis revealed increased [11C]-PBR28 binding in the precentral gyrus in patients (normalized standardized uptake value = 1.15) compared to controls (1.03, p < 0.05). In patients those values were positively correlated with upper motor neuron burden scores (r = 0.69, p < 0.05), and negatively correlated with the amyotrophic lateral sclerosis functional rating scale (r = –0.66, p < 0.05). Increased in vivo glial activation in motor cortices, that correlates with phenotype, complements previous histopathological reports. Further studies will determine the role of [11C]-PBR28 as a marker of treatments that target neuroinflammation