Background: Delirium frequently affects older patients, increasing morbidity and mortality; however, the pathogenesis is poorly understood. Herein, we tested the cognitive disintegration model, which proposes that a breakdown in frontoparietal connectivity, provoked by increased slow-wave activity (SWA), causes delirium. Methods: We recruited 70 surgical patients to have preoperative and postoperative cognitive testing, EEG, blood biomarkers, and preoperative MRI. To provide evidence for causality, any putative mechanism had to differentiate on the diagnosis of delirium; change proportionally to delirium severity; and correlate with a known precipitant for delirium, inflammation. Analyses were adjusted for multiple corrections (MCs) where appropriate. Results: In the preoperative period, subjects who subsequently incurred postoperative delirium had higher alpha power, increased alpha band connectivity (MC P<0.05), but impaired structural connectivity (increased radial diffusivity; MC P<0.05) on diffusion tensor imaging. These connectivity effects were correlated (r 2 ¼0.491; P¼0.0012). Postoperatively, local SWA over frontal cortex was insufficient to cause delirium. Rather, delirium was associated with increased SWA involving occipitoparietal and frontal cortex, with an accompanying breakdown in functional connectivity. Changes in connectivity correlated with SWA (r 2 ¼0.257; P<0.0001), delirium severity rating (r 2 ¼0.195; P<0.001), interleukin 10 (r 2 ¼0.152; P¼0.008), and monocyte chemoattractant protein 1 (r 2 ¼0.253; P<0.001). Conclusions: Whilst frontal SWA occurs in all postoperative patients, delirium results when SWA progresses to involve posterior brain regions, with an associated reduction in connectivity in most subjects. Modifying SWA and connectivity may offer a novel therapeutic approach for delirium. Clinical trial registration: NCT03124303, NCT02926417

Background Consciousness is supported by integrated brain activity across widespread functionally segregated networks. The functional magnetic resonance imaging–derived global brain signal is a candidate marker for a conscious state, and thus the authors hypothesized that unconsciousness would be accompanied by a loss of global temporal coordination, with specific patterns of decoupling between local regions and global activity differentiating among various unconscious states. Methods Functional magnetic resonance imaging global signals were studied in physiologic, pharmacologic, and pathologic states of unconsciousness in human natural sleep (n = 9), propofol anesthesia (humans, n = 14; male rats, n = 12), and neuropathological patients (n = 21). The global signal amplitude as well as the correlation between global signal and signals of local voxels were quantified. The former reflects the net strength of global temporal coordination, and the latter yields global signal topography. Results A profound reduction of global signal amplitude was seen consistently across the various unconscious states: wakefulness (median [1st, 3rd quartile], 0.46 [0.21, 0.50]) versus non-rapid eye movement stage 3 of sleep (0.30 [0.24, 0.32]; P = 0.035), wakefulness (0.36 [0.31, 0.42]) versus general anesthesia (0.25 [0.21, 0.28]; P = 0.001), healthy controls (0.30 [0.27, 0.37]) versus unresponsive wakefulness syndrome (0.22 [0.15, 0.24]; P &lt; 0.001), and low dose (0.07 [0.06, 0.08]) versus high dose of propofol (0.04 [0.03, 0.05]; P = 0.028) in rats. Furthermore, non-rapid eye movement stage 3 of sleep was characterized by a decoupling of sensory and attention networks from the global network. General anesthesia and unresponsive wakefulness syndrome were characterized by a dissociation of the majority of functional networks from the global network. This decoupling, however, was dominated by distinct neuroanatomic foci (e.g., precuneus and anterior cingulate cortices). Conclusions The global temporal coordination of various modules across the brain may distinguish the coarse-grained state of consciousness versus unconsciousness, while the relationship between the global and local signals may define the particular qualities of a particular unconscious state. Editor’s Perspective What We Already Know about This Topic What This Article Tells Us That Is New

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Altered predictive coding may underlie the reduced auditory mismatch negativity amplitude observed in patients with dementia. We hypothesized that accumulating dementia-associated pathologies, including amyloid and tau, lead to disturbed predictions of our sensory environment. This would manifest as increased reliance on “observed” sensory information with an associated increase in feedforward, and decrease in feedback, signaling. To test this hypothesis, we studied a cross-sectional cohort of participants who underwent positron emission tomography imaging and high-density EEG during an odd-ball paradigm, and used dynamic casual modeling and Bayesian statistics to make inferences about the neuronal architectures (generators) and mechanisms (effective connectivity) underlying the observed auditory evoked responses. Amyloid-β imaging with [C-11] Pittsburgh Compound-B PET were qualitatively rated using established criteria. Tau-positive PET scans, with [F-18]MK6240, were defined by a MK-6240 standardized uptake value ratio positivity threshold at two standard deviations above the mean of the Amyloid(−) group in the entorhinal cortex (entorhinal MK-6240 SUVR &gt; 1.27). The cross-sectional cohort included a total of 56 participants (9 and 13 participants in the Tau(+) and Amyloid(+) subgroups, respectively: age interquartile range of [73.50 - 75.34] and [70.5–75.34] years, 56% and 69% females, respectively; 46 and 43 participants in the Tau(-) and Amyloid(-) subgroups, respectively: age interquartile range of [62.72–72.5] and [62.64–72.48] years, 67% and 65% females, respectively). Mismatch negativity amplitudes were significantly smaller in Tau+ subgroup than Tau- subgroup (cluster statistics corrected for multiple comparisons: p = 0.028). Dynamic causal modelling showed that tau pathology was associated with increased feedforward connectivity and decreased feedback connectivity, with increased excitability of superior temporal gyrus but not inferior frontal regions. This effect on superior temporal gyrus was consistent with the distribution of tau disease on PET in these participants, indicating that the observed differences in mismatch negativity reflect pathological changes evolving in preclinical dementia. Exclusion of participants with diagnosed mild cognitive impairment or dementia did not affect the results. These observational data provide proof of concept that abnormalities in predictive coding may be detected in the preclinical phase of Alzheimer’s disease. This framework also provides a construct to understand how progressive impairments lead to loss of orientation to the sensory world in dementia. Based on our modeling results, plus animal models indicating that Alzheimer’s disease pathologies produce hyperexcitability of higher cortical regions through local disinhibition, mismatch negativity might be a useful monitor to deploy as strategies that target interneuron dysfunction are developed.

The scale-free dynamics of human brain activity, characterized by an elaborate temporal structure with scale-free properties, can be quantified using the power-law exponent (PLE) as an index. Power laws are well documented in nature in general, particularly in the brain. Some previous fMRI studies have demonstrated a lower PLE during cognitive-task-evoked activity than during resting state activity. However, PLE modulation during cognitive-task-evoked activity and its relationship with an associated behavior remain unclear. In this functional fMRI study in the resting state and face processing + control task, we investigated PLE during both the resting state and task-evoked activities, as well as its relationship with behavior measured using mean reaction time (mRT) during the task. We found that (1) face discrimination-induced BOLD signal changes in the medial prefrontal cortex (mPFC), posterior cingulate cortex (PCC), amygdala, and fusiform face area; (2) PLE significantly decreased during task-evoked activity specifically in mPFC compared with resting state activity; (3) most importantly, in mPFC, mRT significantly negatively correlated with both resting state PLE and the resting-task PLE difference. These results may lead to a better understanding of the associations between task performance parameters (e.g., mRT) and the scale-free dynamics of spontaneous and task-evoked brain activities.

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