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Impact of clinical phenotypes on management and outcomes in European atrial fibrillation patients: a report from the ESC-EHRA EURObservational Research Programme in AF (EORP-AF) General Long-Term Registry.
BACKGROUND: Epidemiological studies in atrial fibrillation (AF) illustrate that clinical complexity increase the risk of major adverse outcomes. We aimed to describe European AF patients' clinical phenotypes and analyse the differential clinical course. METHODS: We performed a hierarchical cluster analysis based on Ward's Method and Squared Euclidean Distance using 22 clinical binary variables, identifying the optimal number of clusters. We investigated differences in clinical management, use of healthcare resources and outcomes in a cohort of European AF patients from a Europe-wide observational registry. RESULTS: A total of 9363 were available for this analysis. We identified three clusters: Cluster 1 (n = 3634; 38.8%) characterized by older patients and prevalent non-cardiac comorbidities; Cluster 2 (n = 2774; 29.6%) characterized by younger patients with low prevalence of comorbidities; Cluster 3 (n = 2955;31.6%) characterized by patients' prevalent cardiovascular risk factors/comorbidities. Over a mean follow-up of 22.5 months, Cluster 3 had the highest rate of cardiovascular events, all-cause death, and the composite outcome (combining the previous two) compared to Cluster 1 and Cluster 2 (all P < .001). An adjusted Cox regression showed that compared to Cluster 2, Cluster 3 (hazard ratio (HR) 2.87, 95% confidence interval (CI) 2.27-3.62; HR 3.42, 95%CI 2.72-4.31; HR 2.79, 95%CI 2.32-3.35), and Cluster 1 (HR 1.88, 95%CI 1.48-2.38; HR 2.50, 95%CI 1.98-3.15; HR 2.09, 95%CI 1.74-2.51) reported a higher risk for the three outcomes respectively. CONCLUSIONS: In European AF patients, three main clusters were identified, differentiated by differential presence of comorbidities. Both non-cardiac and cardiac comorbidities clusters were found to be associated with an increased risk of major adverse outcomes.
GABA and glutamate deficits from frontotemporal lobar degeneration are associated with disinhibition.
Behavioural disinhibition is a common feature of the syndromes associated with frontotemporal lobar degeneration (FTLD). It is associated with high morbidity and lacks proven symptomatic treatments. A potential therapeutic strategy is to correct the neurotransmitter deficits associated with FTLD, thereby improving behaviour. Reductions in the neurotransmitters glutamate and GABA correlate with impulsive behaviour in several neuropsychiatric diseases and there is post-mortem evidence of their deficit in FTLD. Here, we tested the hypothesis that prefrontal glutamate and GABA levels are reduced by FTLD in vivo, and that their deficit is associated with impaired response inhibition. Thirty-three participants with a syndrome associated with FTLD (15 patients with behavioural variant frontotemporal dementia and 18 with progressive supranuclear palsy, including both Richardson's syndrome and progressive supranuclear palsy-frontal subtypes) and 20 healthy control subjects were included. Participants undertook ultra-high field (7 T) magnetic resonance spectroscopy and a stop-signal task of response inhibition. We measured glutamate and GABA levels using semi-LASER magnetic resonance spectroscopy in the right inferior frontal gyrus, because of its strong association with response inhibition, and in the primary visual cortex, as a control region. The stop-signal reaction time was calculated using an ex-Gaussian Bayesian model. Participants with frontotemporal dementia and progressive supranuclear palsy had impaired response inhibition, with longer stop-signal reaction times compared with controls. GABA concentration was reduced in patients versus controls in the right inferior frontal gyrus, but not the occipital lobe. There was no group-wise difference in partial volume corrected glutamate concentration between patients and controls. Both GABA and glutamate concentrations in the inferior frontal gyrus correlated inversely with stop-signal reaction time, indicating greater impulsivity in proportion to the loss of each neurotransmitter. We conclude that the glutamatergic and GABAergic deficits in the frontal lobe are potential targets for symptomatic drug treatment of frontotemporal dementia and progressive supranuclear palsy.
Functional Interactions between Sensory and Memory Networks for Adaptive Behavior.
The brain's capacity to adapt to sensory inputs is key for processing sensory information efficiently and interacting in new environments. Following repeated exposure to the same sensory input, brain activity in sensory areas is known to decrease as inputs become familiar, a process known as adaptation. Yet, the brain-wide mechanisms that mediate adaptive processing remain largely unknown. Here, we combine multimodal brain imaging (functional magnetic resonance imaging [fMRI], magnetic resonance spectroscopy) with behavioral measures of orientation-specific adaptation (i.e., tilt aftereffect) to investigate the functional and neurochemical mechanisms that support adaptive processing. Our results reveal two functional brain networks: 1) a sensory-adaptation network including occipital and dorsolateral prefrontal cortex regions that show decreased fMRI responses for repeated stimuli and 2) a perceptual-memory network including regions in the parietal memory network (PMN) and dorsomedial prefrontal cortex that relate to perceptual bias (i.e., tilt aftereffect). We demonstrate that adaptation relates to increased occipito-parietal connectivity, while decreased connectivity between sensory-adaptation and perceptual-memory networks relates to GABAergic inhibition in the PMN. Thus, our findings provide evidence that suppressive interactions between sensory-adaptation (i.e., occipito-parietal) and perceptual-memory (i.e., PMN) networks support adaptive processing and behavior, proposing a key role of memory systems in efficient sensory processing.
Cultural differences in visual perceptual learning.
Cultural differences in visual perceptual learning (VPL) could be attributed to differences in the way that people from individualistic and collectivistic cultures preferentially attend to local objects (analytic) or global contexts (holistic). Indeed, individuals from different cultural backgrounds can adopt distinct processing styles and learn to differentially construct meaning from the environment. Therefore, the present work investigates if cross-cultural differences in VPL can vary as a function of holistic processing. A shape discrimination task was used to investigate whether the individualistic versus collectivistic backgrounds of individuals affected the detection of global shapes embedded in cluttered backgrounds. Seventy-seven participants-including Asian (collectivistic background) and European (individualistic background) students-were trained to discriminate between radial and concentric patterns. Singelis's self-construal scale was also used to assess whether differences in learning could be attributed to independent or interdependent self-construal. Results showed that collectivists had faster learning rates and better accuracy performance than individualists following training-thereby reflecting their tendency to attend holistically when learning to extract global forms. Further, we observed a negative association between independent self-construal-which has previously been linked to analytic processing-with performance. This study provides insight into how socio-cultural backgrounds affect VPL.
Microstructural and neurochemical plasticity mechanisms interact to enhance human perceptual decision-making.
Experience and training are known to boost our skills and mold the brain's organization and function. Yet, structural plasticity and functional neurotransmission are typically studied at different scales (large-scale networks, local circuits), limiting our understanding of the adaptive interactions that support learning of complex cognitive skills in the adult brain. Here, we employ multimodal brain imaging to investigate the link between microstructural (myelination) and neurochemical (GABAergic) plasticity for decision-making. We test (in males, due to potential confounding menstrual cycle effects on GABA measurements in females) for changes in MRI-measured myelin, GABA, and functional connectivity before versus after training on a perceptual decision task that involves identifying targets in clutter. We demonstrate that training alters subcortical (pulvinar, hippocampus) myelination and its functional connectivity to visual cortex and relates to decreased visual cortex GABAergic inhibition. Modeling interactions between MRI measures of myelin, GABA, and functional connectivity indicates that pulvinar myelin plasticity interacts-through thalamocortical connectivity-with GABAergic inhibition in visual cortex to support learning. Our findings propose a dynamic interplay of adaptive microstructural and neurochemical plasticity in subcortico-cortical circuits that supports learning for optimized decision-making in the adult human brain.
Beta-band frequency peaks inside the subthalamic nucleus as a biomarker for motor improvement after deep brain stimulation in Parkinson's disease.
Deep brain stimulation (DBS) of the subthalamic nucleus (STN) remains an empirical, yet highly effective, surgical treatment for advanced Parkinson's disease (PD). DBS outcome depends on accurate stimulation of the STN sensorimotor area which is a trial-and-error procedure taking place during and after surgery. Pathologically enhanced beta-band (13-35 Hz) oscillatory activity across the cortico-basal ganglia pathways is a prominent neurophysiological phenomenon associated with PD. We hypothesized that weighing together beta-band frequency peaks from simultaneous microelectrode recordings in "off-state" PD patients could map the individual neuroanatomical variability and serve as a biomarker for the location of the STN sensorimotor neurons. We validated our hypothesis with 9 and 11 patients that, respectively, responded well and poorly to bilateral DBS, after at least two years of follow up. We categorized "good" and "poor" DBS responders based on their clinical assessment alongside a > 40% and <30% change, respectively, in "off" unified PD rating scale motor scores. Good (poor) DBS responders had, in average, 1 mm (3.5 mm) vertical distance between the maximum beta-peak weighted across the parallel microelectrodes and the center of the stimulation area. The distances were statistically different in the two groups ( p = 0.0025 ). Our biomarker could provide personalized intra- and postoperative support in stimulating the STN sensorimotor area associated with optimal long-term clinical benefits.
GABA, not BOLD, reveals dissociable learning-dependent plasticity mechanisms in the human brain.
Experience and training have been shown to facilitate our ability to extract and discriminate meaningful patterns from cluttered environments. Yet, the human brain mechanisms that mediate our ability to learn by suppressing noisy and irrelevant signals remain largely unknown. To test the role of suppression in perceptual learning, we combine fMRI with MR Spectroscopy measurements of GABA, as fMRI alone does not allow us to discern inhibitory vs. excitatory mechanisms. Our results demonstrate that task-dependent GABAergic inhibition relates to functional brain plasticity and behavioral improvement. Specifically, GABAergic inhibition in the occipito-temporal cortex relates to dissociable learning mechanisms: decreased GABA for noise filtering, while increased GABA for feature template retuning. Perturbing cortical excitability during training with tDCs alters performance in a task-specific manner, providing evidence for a direct link between suppression and behavioral improvement. Our findings propose dissociable GABAergic mechanisms that optimize our ability to make perceptual decisions through training.
Neurochemical and functional interactions for improved perceptual decisions through training.
Learning and experience are known to improve our ability to make perceptual decisions. Yet, our understanding of the brain mechanisms that support improved perceptual decisions through training remains limited. Here, we test the neurochemical and functional interactions that support learning for perceptual decisions in the context of an orientation identification task. Using magnetic resonance spectroscopy (MRS), we measure neurotransmitters (i.e., glutamate, GABA) that are known to be involved in visual processing and learning in sensory [early visual cortex (EV)] and decision-related [dorsolateral prefrontal cortex (DLPFC)] brain regions. Using resting-state functional magnetic resonance imaging (rs-fMRI), we test for functional interactions between these regions that relate to decision processes. We demonstrate that training improves perceptual judgments (i.e., orientation identification), as indicated by faster rates of evidence accumulation after training. These learning-dependent changes in decision processes relate to lower EV glutamate levels and EV-DLPFC connectivity, suggesting that glutamatergic excitation and functional interactions between visual and dorsolateral prefrontal cortex facilitate perceptual decisions. Further, anodal transcranial direct current stimulation (tDCS) in EV impairs learning, suggesting a direct link between visual cortex excitation and perceptual decisions. Our findings advance our understanding of the role of learning in perceptual decision making, suggesting that glutamatergic excitation for efficient sensory processing and functional interactions between sensory and decision-related regions support improved perceptual decisions.NEW & NOTEWORTHY Combining multimodal brain imaging [magnetic resonance spectroscopy (MRS), functional connectivity] with interventions [transcranial direct current stimulation (tDCS)], we demonstrate that glutamatergic excitation and functional interactions between sensory (visual) and decision-related (dorsolateral prefrontal cortex) areas support our ability to optimize perceptual decisions through training.
β-band peak in local field potentials as a marker of clinical improvement in Parkinson's Disease after Deep Brain Stimulation
Although locating the stimulation contact in Deep Brain Stimulation (DBS) requires a sub-mm-precision, it remains a trial-and-error, patient-specific procedure that is usually the main cause of post-operational side-effects. In this work, we used microelectrode recordings from Parkinson's disease (PD) patients, acquired at the Neurosurgery Clinic, Evangelismos Hospital, Athens, Greece, to relate the β-band peak, a known neurophysiological signature of the sensorimotor pathways with the clinical outcome of DBS, as assessed by an expert neurologist after a follow-up of at least 1 year. By combining recordings from 5 microelectrodes, we estimated a summed β-band amplitude peak, per recording depth. We suggest that the maximum aggregate β-band peak is related to the stimulation target. We verified our method in 6 patients that responded well in a bilateral DBS treatment (average increase of Unified Parkinson's Disease Rating scale by 32.6 ± 5.4). In 7 out of 12 hemispheres, the distance between the stimulation depth and that of the maximum β-band peak was 0 and for the rest cases that distance was smaller than 2 mm which is a typical effective radius of a stimulation point. Our method needs to be further supported by data acquired from patients with good and poor clinical responses after DBS. © Springer International Publishing Switzerland 2014.
Brain stimulation boosts perceptual learning by altering sensory GABAergic plasticity and functional connectivity
AbstractInterpreting cluttered scenes —a key skill for successfully interacting with our environment— relies on our ability to select relevant sensory signals while filtering out noise. Training is known to improve our ability to make these perceptual judgements by altering local processing in sensory brain areas. Yet, the brain-wide network mechanisms that mediate our ability for perceptual learning remain largely unknown. Here, we combine transcranial direct current stimulation (tDCS) with multi-modal brain measures to modulate cortical excitability during training on a signal-in-noise task (i.e. detection of visual patterns in noise) and test directly the link between processing in visual cortex and its interactions with decision-related areas (i.e. posterior parietal cortex). We test whether brain stimulation alters inhibitory processing in visual cortex, as measured by magnetic resonance spectroscopy (MRS) of GABA and functional connectivity between visual and posterior parietal cortex, as measured by resting state functional magnetic resonance imaging (rs-fMRI). We show that anodal tDCS during training results in faster learning and decreased GABA+ during training, before these changes occur for training without stimulation (i.e. sham). Further, anodal tDCS decreases occipito-parietal interactions and time-varying connectivity across the visual cortex. Our findings demonstrate that tDCS boosts learning by accelerating visual GABAergic plasticity and altering interactions between visual and decision-related areas, suggesting that training optimises gain control mechanisms (i.e. GABAergic inhibition) and functional inter-areal interactions to support perceptual learning.
Learning to optimize perceptual decisions through suppressive interactions in the human brain
AbstractTranslating noisy sensory signals to perceptual decisions is critical for successful interactions in complex environments. Learning is known to improve perceptual judgments by filtering external noise and task-irrelevant information. Yet, little is known about the brain mechanisms that mediate learning-dependent suppression. Here, we employ ultra-high field magnetic resonance spectroscopy of GABA to test whether suppressive processing in decision-related and visual areas facilitates perceptual judgments during training. We demonstrate that parietal GABA relates to suppression of task-irrelevant information, while learning-dependent changes in visual GABA relate to enhanced performance in target detection and feature discrimination tasks. Combining GABA measurements with functional brain connectivity demonstrates that training on a target detection task involves local connectivity and disinhibition of visual cortex, while training on a feature discrimination task involves inter-cortical interactions that relate to suppressive visual processing. Our findings provide evidence that learning optimizes perceptual decisions through suppressive interactions in decision-related networks.
Where functional MRI stops, metabolism starts.
Combining techniques that track blood oxygenation and biochemicals during neuronal activity reveals how the brain computes perceived and unperceived stimuli.
Peripheral blood DNA methylation and neuroanatomical responses to HDACi treatment that rescues neurological deficits in a Kabuki syndrome mouse model.
BACKGROUND: Recent findings from studies of mouse models of Mendelian disorders of epigenetic machinery strongly support the potential for postnatal therapies to improve neurobehavioral and cognitive deficits. As several of these therapies move into human clinical trials, the search for biomarkers of treatment efficacy is a priority. A potential postnatal treatment of Kabuki syndrome type 1 (KS1), caused by pathogenic variants in KMT2D encoding a histone-lysine methyltransferase, has emerged using a mouse model of KS1 (Kmt2d+/βGeo). In this mouse model, hippocampal memory deficits are ameliorated following treatment with the histone deacetylase inhibitor (HDACi), AR-42. Here, we investigate the effect of both Kmt2d+/βGeo genotype and AR-42 treatment on neuroanatomy and on DNA methylation (DNAm) in peripheral blood. While peripheral blood may not be considered a "primary tissue" with respect to understanding the pathophysiology of neurodevelopmental disorders, it has the potential to serve as an accessible biomarker of disease- and treatment-related changes in the brain. METHODS: Half of the KS1 and wildtype mice were treated with 14 days of AR-42. Following treatment, fixed brain samples were imaged using MRI to calculate regional volumes. Blood was assayed for genome-wide DNAm at over 285,000 CpG sites using the Illumina Infinium Mouse Methylation array. DNAm patterns and brain volumes were analyzed in the four groups of animals: wildtype untreated, wildtype AR-42 treated, KS1 untreated and KS1 AR-42 treated. RESULTS: We defined a DNAm signature in the blood of KS1 mice, that overlapped with the human KS1 DNAm signature. We also found a striking 10% decrease in total brain volume in untreated KS1 mice compared to untreated wildtype, which correlated with DNAm levels in a subset KS1 signature sites, suggesting that disease severity may be reflected in blood DNAm. Treatment with AR-42 ameliorated DNAm aberrations in KS1 mice at a small number of signature sites. CONCLUSIONS: As this treatment impacts both neurological deficits and blood DNAm in mice, future KS clinical trials in humans could be used to assess blood DNAm as an early biomarker of therapeutic efficacy.
Reliability of the global cortical atrophy visual rating scale applied to computed tomography versus magnetic resonance imaging scans in acute stroke.
IntroductionResearch using magnetic resonance imaging (MRI) suggests regional cerebral atrophy measures (e.g., frontal lobe, temporal lobe) may predict post-stroke outcomes. Clinical CT scans have excellent potential for use in research but it is unclear whether regional atrophy measures from CT are reliable compared to MRI reference standards.MethodsWe used the Global Cortical Atrophy (GCA) scale to investigate reliability of atrophy measures on CT versus MRI scans from stroke patients originally recruited to the Oxford Cognitive Screening programme. Two raters provided standardised visual ratings at two timepoints. Weighted Kappa statistics assessed the reliability of regional atrophy scores. Spearman's correlation and a two-way repeated measures ANOVA assessed the reliability of the total score.ResultsOn clinically acquired neuroimaging from 98 stroke patients (mean/SD age = 70.97/11.99, 42 female, 84 ischaemic stroke), regional GCA scores on CT versus MRI showed fair to almost perfect intra-rater agreement (κ = .50-.87), substantial to almost perfect intra-rater agreement on CT (κ = .67-.88), and moderate to almost perfect intra-rater reliability on MRI (κ = .50-.89). Regional GCA scores showed mostly moderate to substantial inter-rater reliability on both CT and MRI (κ = .43-.69), except the temporal horns and parieto-occipital region. There was a strong correlation between total GCA scores on CT and MRI (r (96) = .87-.88, p ConclusionsThese results support the use of cerebral atrophy measures from CT in clinical research, as visual ratings showed generally good agreement between CT and MRI, between raters, and between timepoints.
Characterization of neurocognitive deficits in patients with post-COVID-19 syndrome: persistence, patients' complaints, and clinical predictors.
IntroductionCognitive symptoms persisting beyond 3 months following COVID-19 present a considerable disease burden. We aimed to establish a domain-specific cognitive profile of post-COVID-19 syndrome (PCS). We examined the deficits' persistence, relationships with subjective cognitive complaints, and clinical variables, to identify the most relevant cognitive deficits and their predictors.MethodsThis cross-sectional study examined cognitive performance and patient-reported and clinical predictors of cognitive deficits in PCS patients (n = 282) and socio-demographically comparable healthy controls (n = 52).ResultsOn the Oxford Cognitive Screen-Plus, the patient group scored significantly lower in delayed verbal memory, attention, and executive functioning than the healthy group. In each affected domain, 10 to 20% of patients performed more than 1.5 SD below the control mean. Delayed memory was particularly affected, with a small effect of hospitalization and age. Attention scores were predicted by hospitalization and fatigue.DiscussionThus, PCS is associated with long-term cognitive dysfunction, particularly in delayed memory, attention, and executive functioning. Memory deficits seem to be of particular relevance to patients' experience of subjective impairment. Hospitalization, fatigue, and age seem to predict cognitive deficits, while time since infection, depression, and pre-existing conditions do not.
The association of insomnia with long COVID: An international collaborative study (ICOSS-II).
OBJECTIVE: There is evidence of a strong association between insomnia and COVID-19, yet few studies have examined the relationship between insomnia and long COVID. This study aimed to investigate whether COVID-19 patients with pre-pandemic insomnia have a greater risk of developing long COVID and whether long COVID is in turn associated with higher incident rates of insomnia symptoms after infection. METHODS: Data were collected cross-sectionally (May-Dec 2021) as part of an international collaborative study involving participants from 16 countries. A total of 2311 participants (18-99 years old) with COVID-19 provided valid responses to a web-based survey about sleep, insomnia, and health-related variables. Log-binomial regression was used to assess bidirectional associations between insomnia and long COVID. Analyses were adjusted for age, sex, and health conditions, including sleep apnea, attention and memory problems, chronic fatigue, depression, and anxiety. RESULTS: COVID-19 patients with pre-pandemic insomnia showed a higher risk of developing long COVID than those without pre-pandemic insomnia (70.8% vs 51.4%; adjusted relative risk [RR]: 1.33, 95% confidence interval [CI]: 1.07-1.65). Among COVID-19 cases without pre-pandemic insomnia, the rates of incident insomnia symptoms after infection were 24.1% for short COVID cases and 60.6% for long COVID cases (p