Postoperative delirium is associated with increased plasma neurofilament light

While delirium is associated with cognitive decline and dementia, there is limited evidence to support causality for this relationship. Clarification of how delirium may cause cognitive decline, perhaps through evidence of contemporaneous neuronal injury, would enhance plausibility for a causal relationship. Dose-dependence of neuronal injury with delirium severity would further enhance the biological plausibility for this relationship. We tested whether delirium is associated with neuronal injury in 114 surgical patients recruited to a prospective biomarker cohort study. Patients underwent perioperative testing for changes in neurofilament light, a neuronal injury biomarker, as well as a panel of 10 cytokines, with contemporaneous assessment of delirium severity and incidence. A subset of patients underwent preoperative MRI. Initially we confirmed prior reports that neurofilament light levels correlated with markers of neurodegeneration [hippocampal volume (ΔR2 = 0.129, P = 0.015)] and white matter changes including fractional anisotropy of white matter (ΔR2 = 0.417, P < 0.001) with similar effects on mean, axial and radial diffusivity) in our cohort and that surgery was associated with increasing neurofilament light from preoperative levels [mean difference (95% confidence interval, CI) = 0.240 (0.178, 0.301) log10 (pg/ml), P < 0.001], suggesting putative neuronal injury. Next, we tested the relationship with delirium. Neurofilament light rose more sharply in participants with delirium compared to non-sufferers [mean difference (95% CI) = 0.251 (0.136, 0.367) log10 (pg/ml), P < 0.001]. This relationship showed dose-dependence, such that neurofilament light rose proportionately to delirium severity (ΔR2 = 0.199, P < 0.001). Given that inflammation is considered an important driver of postoperative delirium, next we tested whether neurofilament light, as a potential marker of neurotoxicity, may contribute to the pathogenesis of delirium independent of inflammation. From a panel of 10 cytokines, the pro-inflammatory cytokine IL-8 exhibited a strong correlation with delirium severity (ΔR2 = 0.208, P < 0.001). Therefore, we tested whether the change in neurofilament light contributed to delirium severity independent of IL-8. Neurofilament light was independently associated with delirium severity after adjusting for the change in inflammation (ΔR2 = 0.040, P = 0.038). These data suggest delirium is associated with exaggerated increases in neurofilament light and that this putative neurotoxicity may contribute to the pathogenesis of delirium itself, independent of changes in inflammation

Ipsilesional Mu Rhythm Desynchronization and Changes in Motor Behavior Following Post Stroke BCI Intervention for Motor Rehabilitation

Loss of motor function is a common deficit following stroke insult and often manifests as persistent upper extremity (UE) disability which can affect a survivor’s ability to participate in activities of daily living. Recent research suggests the use of brain–computer interface (BCI) devices might improve UE function in stroke survivors at various times since stroke. This randomized crossover-controlled trial examines whether intervention with this BCI device design attenuates the effects of hemiparesis, encourages reorganization of motor related brain signals (EEG measured sensorimotor rhythm desynchronization), and improves movement, as measured by the Action Research Arm Test (ARAT). A sample of 21 stroke survivors, presenting with varied times since stroke and levels of UE impairment, received a maximum of 18–30 h of intervention with a novel electroencephalogram-based BCI-driven functional electrical stimulator (EEG-BCI-FES) device. Driven by spectral power recordings from contralateral EEG electrodes during cued attempted grasping of the hand, the user’s input to the EEG-BCI-FES device modulates horizontal movement of a virtual cursor and also facilitates concurrent stimulation of the impaired UE. Outcome measures of function and capacity were assessed at baseline, mid-therapy, and at completion of therapy while EEG was recorded only during intervention sessions. A significant increase in r-squared values [reflecting Mu rhythm (8–12 Hz) desynchronization as the result of attempted movements of the impaired hand] presented post-therapy compared to baseline. These findings suggest that intervention corresponds with greater desynchronization of Mu rhythm in the ipsilesional hemisphere during attempted movements of the impaired hand and this change is related to changes in behavior as a result of the intervention. BCI intervention may be an effective way of addressing the recovery of a stroke impaired UE and studying neuromechanical coupling with motor outputs.Clinical Trial Registration:ClinicalTrials.gov, identifier NCT02098265

Behavioral Outcomes Following Brain–Computer Interface Intervention for Upper Extremity Rehabilitation in Stroke: A Randomized Controlled Trial

Stroke is a leading cause of persistent upper extremity (UE) motor disability in adults. Brain–computer interface (BCI) intervention has demonstrated potential as a motor rehabilitation strategy for stroke survivors. This sub-analysis of ongoing clinical trial (NCT02098265) examines rehabilitative efficacy of this BCI design and seeks to identify stroke participant characteristics associated with behavioral improvement. Stroke participants (n = 21) with UE impairment were assessed using Action Research Arm Test (ARAT) and measures of function. Nine participants completed three assessments during the experimental BCI intervention period and at 1-month follow-up. Twelve other participants first completed three assessments over a parallel time-matched control period and then crossed over into the BCI intervention condition 1-month later. Participants who realized positive change (≥1 point) in total ARAT performance of the stroke affected UE between the first and third assessments of the intervention period were dichotomized as “responders” (&lt;1 = “non-responders”) and similarly analyzed. Of the 14 participants with room for ARAT improvement, 64% (9/14) showed some positive change at completion and approximately 43% (6/14) of the participants had changes of minimal detectable change (MDC = 3 pts) or minimally clinical important difference (MCID = 5.7 points). Participants with room for improvement in the primary outcome measure made significant mean gains in ARATtotal score at completion (ΔARATtotal = 2, p = 0.028) and 1-month follow-up (ΔARATtotal = 3.4, p = 0.0010), controlling for severity, gender, chronicity, and concordance. Secondary outcome measures, SISmobility, SISadl, SISstrength, and 9HPTaffected, also showed significant improvement over time during intervention. Participants in intervention through follow-up showed a significantly increased improvement rate in SISstrength compared to controls (p = 0.0117), controlling for severity, chronicity, gender, as well as the individual effects of time and intervention type. Participants who best responded to BCI intervention, as evaluated by ARAT score improvement, showed significantly increased outcome values through completion and follow-up for SISmobility (p = 0.0002, p = 0.002) and SISstrength (p = 0.04995, p = 0.0483). These findings may suggest possible secondary outcome measure patterns indicative of increased improvement resulting from this BCI intervention regimen as well as demonstrating primary efficacy of this BCI design for treatment of UE impairment in stroke survivors.Clinical Trial Registration:ClinicalTrials.gov, NCT02098265

Data_Sheet_1_Multi-pathological contributions toward atrophy patterns in the Alzheimer’s disease continuum.pdf

IntroductionHeterogeneity in downstream atrophy in Alzheimer’s disease (AD) is predominantly investigated in relation to pathological hallmarks (Aβ, tau) and co-pathologies (cerebrovascular burden) independently. However, the proportional contribution of each pathology in determining atrophy pattern remains unclear. We assessed heterogeneity in atrophy using two recently conceptualized dimensions: typicality (typical AD atrophy at the center and deviant atypical atrophy on either extreme including limbic predominant to hippocampal sparing patterns) and severity (overall neurodegeneration spanning minimal atrophy to diffuse typical AD atrophy) in relation to Aβ, tau, and cerebrovascular burden.MethodsWe included 149 Aβ + individuals on the AD continuum (cognitively normal, prodromal AD, AD dementia) and 163 Aβ− cognitively normal individuals from the ADNI. We modeled heterogeneity in MRI-based atrophy with continuous-scales of typicality (ratio of hippocampus to cortical volume) and severity (total gray matter volume). Partial correlation models investigated the association of typicality/severity with (a) Aβ (global Aβ PET centiloid), tau (global tau PET SUVR), cerebrovascular (total white matter hypointensity volume) burden (b) four cognitive domains (memory, executive function, language, visuospatial composites). Using multiple regression, we assessed the association of each pathological burden and typicality/severity with cognition.Results(a) In the AD continuum, typicality (r = −0.31, p ConclusionIn the AD continuum, atrophy-based severity was more strongly associated with tau burden than typicality after accounting for Aβ and cerebrovascular burden. Cognitive performance in memory, executive function and language domains was explained by typicality and/or severity and additionally tau pathology. Typicality and severity may differentially reflect burden arising from tau pathology but not Aβ or cerebrovascular pathologies which need to be accounted for when investigating AD heterogeneity.</p

Neuropathologic Features of Antemortem Atrophy-Based Subtypes of Alzheimer Disease.

To investigate whether antemortem MRI-based atrophy subtypes of Alzheimer's disease (AD) differ in neuropathological features and comorbid non-AD pathologies at postmortem. From the ADNI cohort, we included individuals with: antemortem MRI evaluating brain atrophy within 2y before death; antemortem diagnosis of AD dementia/mild cognitive impairment; postmortem-confirmed AD neuropathologic change. Antemortem atrophy subtypes were modeled as continuous phenomena based on a recent conceptual framework: typicality (spanning limbic-predominant AD to hippocampal-sparing AD) and severity (spanning typical AD to minimal atrophy AD). Postmortem neuropathological evaluation included AD hallmarks, amyloid-beta and tau as well as non-AD pathologies, alpha-synuclein and TAR DNA-binding protein-43 (TDP-43). We also investigated the overall concomitance across these pathologies. Partial correlations assessed the associations between antemortem atrophy subtypes and postmortem neuropathological outcomes. In 31 individuals (26 AD dementia/5 mild cognitive impaired, mean age=80y, 26% females), antemortem typicality was significantly negatively associated with neuropathological features, including amyloid-beta (rho=-0.39 overall), tau (rho=-0.38 regionally), alpha-synuclein (rho=-0.39 regionally), TDP-43 (rho=-0.49 overall), and concomitance of pathologies (rho=-0.59 regionally). Limbic-predominant AD was associated with higher Thal phase, neuritic plaque density, and presence of TDP-43 compared to hippocampal-sparing AD. Regionally, limbic-predominant AD showed higher presence of tau and alpha-synuclein pathologies in medial temporal structures, higher presence of TDP-43 and concomitance of pathologies subcortically/cortically compared to hippocampal-sparing AD. Antemortem severity was significantly negatively associated with concomitance of pathologies (rho=-0.43 regionally), such that typical AD showed higher concomitance of pathologies than minimal atrophy AD. We provide a direct antemortem-to-postmortem validation, highlighting the importance of understanding atrophy-based heterogeneity in AD relative to AD and non-AD pathologies. We suggest that: (a) typicality and severity in atrophy reflect differential aspects of susceptibility of the brain to AD and non-AD pathologies; (b) limbic-predominant AD and typical AD subtypes share similar biological pathways, making them more vulnerable to AD and non-AD pathologies compared to hippocampal-sparing AD, which may follow a different biological pathway. Our findings provide a deeper understanding of associations of atrophy subtypes in AD with different pathologies, enhancing prevailing knowledge of biological heterogeneity in AD and could contribute towards tracking disease progression and designing clinical trials in the future

Cohort study into the neural correlates of postoperative delirium: the role of connectivity and slow-wave activity

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 (r2=0.491; P=0.0012). 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 (r2=0.257; P<0.0001), delirium severity rating (r2=0.195; P<0.001), interleukin 10 (r2=0.152; P=0.008), and monocyte chemoattractant protein 1 (r2=0.253; 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

Differential response to donepezil in MRI subtypes of mild cognitive impairment

Abstract Background Donepezil is an approved therapy for the treatment of Alzheimer’s disease (AD). Results across clinical trials have been inconsistent, which may be explained by design-methodological issues, the pathophysiological heterogeneity of AD, and diversity of included study participants. We investigated whether response to donepezil differs in mild cognitive impaired (MCI) individuals demonstrating different magnetic resonance imaging (MRI) subtypes. Methods From the Hippocampus Study double-blind, randomized clinical trial, we included 173 MCI individuals (donepezil = 83; placebo = 90) with structural MRI data, at baseline and at clinical follow-up assessments (6–12-month). Efficacy outcomes were the annualized percentage change (APC) in hippocampal, ventricular, and total grey matter volumes, as well as in the AD cortical thickness signature. Participants were classified into MRI subtypes as typical AD, limbic-predominant, hippocampal-sparing, or minimal atrophy at baseline. We primarily applied a subtyping approach based on continuous scale of two subtyping dimensions. We also used the conventional categorical subtyping approach for comparison. Results Donepezil-treated MCI individuals showed slower atrophy rates compared to the placebo group, but only if they belonged to the minimal atrophy or hippocampal-sparing subtypes. Importantly, only the continuous subtyping approach, but not the conventional categorical approach, captured this differential response. Conclusions Our data suggest that individuals with MCI, with hippocampal-sparing or minimal atrophy subtype, may have improved benefit from donepezil, as compared with MCI individuals with typical or limbic-predominant patterns of atrophy. The newly proposed continuous subtyping approach may have advantages compared to the conventional categorical approach. Future research is warranted to demonstrate the potential of subtype stratification for disease prognosis and response to treatment. Trial registration ClinicalTrial.gov NCT00403520. Submission Date: November 21, 2006

Machine Learning Classification to Identify the Stage of Brain-Computer Interface Therapy for Stroke Rehabilitation Using Functional Connectivity

Interventional therapy using brain-computer interface (BCI) technology has shown promise in facilitating motor recovery in stroke survivors; however, the impact of this form of intervention on functional networks outside of the motor network specifically is not well-understood. Here, we investigated resting-state functional connectivity (rs-FC) in stroke participants undergoing BCI therapy across stages, namely pre- and post-intervention, to identify discriminative functional changes using a machine learning classifier with the goal of categorizing participants into one of the two therapy stages. Twenty chronic stroke participants with persistent upper-extremity motor impairment received neuromodulatory training using a closed-loop neurofeedback BCI device, and rs-functional MRI (rs-fMRI) scans were collected at four time points: pre-, mid-, post-, and 1 month post-therapy. To evaluate the peak effects of this intervention, rs-FC was analyzed from two specific stages, namely pre- and post-therapy. In total, 236 seeds spanning both motor and non-motor regions of the brain were computed at each stage. A univariate feature selection was applied to reduce the number of features followed by a principal component-based data transformation used by a linear binary support vector machine (SVM) classifier to classify each participant into a therapy stage. The SVM classifier achieved a cross-validation accuracy of 92.5% using a leave-one-out method. Outside of the motor network, seeds from the fronto-parietal task control, default mode, subcortical, and visual networks emerged as important contributors to the classification. Furthermore, a higher number of functional changes were observed to be strengthening from the pre- to post-therapy stage than the ones weakening, both of which involved motor and non-motor regions of the brain. These findings may provide new evidence to support the potential clinical utility of BCI therapy as a form of stroke rehabilitation that not only benefits motor recovery but also facilitates recovery in other brain networks. Moreover, delineation of stronger and weaker changes may inform more optimal designs of BCI interventional therapy so as to facilitate strengthened and suppress weakened changes in the recovery process