BACKGROUND AND PURPOSE: Cognitive impairment (CI) in multiple sclerosis (MS) is associated with bidirectional changes in resting-state centrality measures. However, practicable functional magnetic resonance imaging (fMRI) biomarkers of CI are still lacking. The aim of this study was to assess the graph-theory-based degree rank order disruption index (kD) and its association with cognitive processing speed as a marker of CI in patients with MS (PwMS) in a secondary cross-sectional fMRI analysis. METHODS: Differentiation between PwMS and healthy controls (HCs) using kD and its correlation with CI (Symbol Digit Modalities Test) was compared to established imaging biomarkers (regional degree, volumetry, diffusion-weighted imaging, lesion mapping). Additional associations were assessed for fatigue (Fatigue Scale for Motor and Cognitive Functions), gait and global disability. RESULTS: Analysis in 56 PwMS and 58 HCs (35/27 women, median age 45.1/40.5 years) showed lower kD in PwMS than in HCs (median -0.30/-0.06, interquartile range 0.55/0.54; p = 0.009, Mann-Whitney U test), yielding acceptable yet non-superior differentiation (area under curve 0.64). kD and degree in medial prefrontal cortex (MPFC) correlated with CI (kD/MPFC Spearman's ρ = 0.32/-0.45, p = 0.019/0.001, n = 55). kD also explained fatigue (ρ = -0.34, p = 0.010, n = 56) but neither gait nor disability. CONCLUSIONS: kD is a potential biomarker of CI and fatigue warranting further validation.

• MeSH
• Adult MeSH
• Cognitive Dysfunction etiology   physiopathology   diagnostic imaging   MeSH
• Middle Aged MeSH
• Humans MeSH
• Magnetic Resonance Imaging * MeSH
• Cross-Sectional Studies MeSH
• Multiple Sclerosis * complications   diagnostic imaging   physiopathology   MeSH
• Processing Speed MeSH
• Fatigue * physiopathology   etiology   diagnostic imaging   MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

Robust scientific knowledge is contingent upon replication of original findings. However, replicating researchers are constrained by resources, and will almost always have to choose one replication effort to focus on from a set of potential candidates. To select a candidate efficiently in these cases, we need methods for deciding which out of all candidates considered would be the most useful to replicate, given some overall goal researchers wish to achieve. In this article we assume that the overall goal researchers wish to achieve is to maximize the utility gained by conducting the replication study. We then propose a general rule for study selection in replication research based on the replication value of the set of claims considered for replication. The replication value of a claim is defined as the maximum expected utility we could gain by conducting a replication of the claim, and is a function of (a) the value of being certain about the claim, and (b) uncertainty about the claim based on current evidence. We formalize this definition in terms of a causal decision model, utilizing concepts from decision theory and causal graph modeling. We discuss the validity of using replication value as a measure of expected utility gain, and we suggest approaches for deriving quantitative estimates of replication value. Our goal in this article is not to define concrete guidelines for study selection, but to provide the necessary theoretical foundations on which such concrete guidelines could be built. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

• MeSH
• Humans MeSH
• Uncertainty MeSH
• Models, Theoretical * MeSH
• Knowledge * MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH

Alcohol Use Disorder (AUD) adversely affects the lives of millions of people, but still lacks effective treatment options. Recent advancements in psychedelic research suggest psilocybin to be potentially efficacious for AUD. However, major knowledge gaps remain regarding (1) psilocybin's general mode of action and (2) AUD-specific alterations of responsivity to psilocybin treatment in the brain that are crucial for treatment development. Here, we conducted a randomized, placebo-controlled crossover pharmaco-fMRI study on psilocybin effects using a translational approach with healthy rats and a rat model of alcohol relapse. Psilocybin effects were quantified with resting-state functional connectivity using data-driven whole-brain global brain connectivity, network-based statistics, graph theory, hypothesis-driven Default Mode Network (DMN)-specific connectivity, and entropy analyses. Results demonstrate that psilocybin induced an acute wide-spread decrease in different functional connectivity domains together with a distinct increase of connectivity between serotonergic core regions and cortical areas. We could further provide translational evidence for psilocybin-induced DMN hypoconnectivity reported in humans. Psilocybin showed an AUD-specific blunting of DMN hypoconnectivity, which strongly correlated to the alcohol relapse intensity and was mainly driven by medial prefrontal regions. In conclusion, our results provide translational validity for acute psilocybin-induced neural effects in the rodent brain. Furthermore, alcohol relapse severity was negatively correlated with neural responsivity to psilocybin treatment. Our data suggest that a clinical standard dose of psilocybin may not be sufficient to treat severe AUD cases; a finding that should be considered for future clinical trials.

• MeSH
• Alcoholism * diagnostic imaging   drug therapy   MeSH
• Default Mode Network MeSH
• Ethanol MeSH
• Hallucinogens * pharmacology   MeSH
• Rats MeSH
• Humans MeSH
• Magnetic Resonance Imaging methods   MeSH
• Brain diagnostic imaging   MeSH
• Psilocybin pharmacology   MeSH
• Recurrence MeSH
• Animals MeSH
• Check Tag
• Rats MeSH
• Humans MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Randomized Controlled Trial MeSH

BACKGROUND: The Symptom Checklist (SCL) developed by the Health Behaviour in School-aged Children (HBSC) study is a non-clinical measure of psychosomatic complaints (e.g., headache and feeling low) that has been used in numerous studies. Several studies have investigated the psychometric characteristics of this scale; however, some psychometric properties remain unclear, among them especially a) dimensionality, b) adequacy of the Graded Response Model (GRM), and c) measurement invariance across countries. METHODS: Data from 229,906 adolescents aged 11, 13 and 15 from 46 countries that participated in the 2018 HBSC survey were analyzed. Adolescents were selected using representative sampling and surveyed by questionnaire in the classroom. Dimensionality was investigated using exploratory graph analysis. In addition, we investigated whether the GRM provided an adequate description of the data. Reliability over the latent variable continuum and differential test functioning across countries were also examined. RESULTS: Exploratory graph analyses showed that SCL can be considered as one-dimensional in 16 countries. However, a comparison of the unidimensional with a post-hoc bifactor GRM showed that deviation from a hypothesized one-dimensional structure was negligible in most countries. Multigroup invariance analyses supported configural and metric invariance, but not scalar invariance across 32 countries. Alignment analysis showed non-invariance especially for the items irritability, feeling nervous/bad temper and feeling low. CONCLUSION: HBSC-SCL appears to represent a consistent and reliable unidimensional instrument across most countries. This bodes well for population health analyses that rely on this scale as an early indicator of mental health status.

• MeSH
• Child MeSH
• Emotions MeSH
• Checklist * MeSH
• Humans MeSH
• Adolescent MeSH
• Surveys and Questionnaires MeSH
• Psychometrics MeSH
• Reproducibility of Results MeSH
• Schools * MeSH
• Check Tag
• Child MeSH
• Humans MeSH
• Adolescent MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

BACKGROUND: The European Association for Endoscopic Surgery Bariatric Guidelines Group identified a gap in bariatric surgery recommendations with a structured, contextualized consideration of multiple bariatric interventions. OBJECTIVE: To provide evidence-informed, transparent and trustworthy recommendations on the use of sleeve gastrectomy, Roux-en-Y gastric bypass, adjustable gastric banding, gastric plication, biliopancreatic diversion with duodenal switch, one anastomosis gastric bypass, and single anastomosis duodeno-ileal bypass with sleeve gastrectomy in patients with severe obesity and metabolic diseases. Only laparoscopic procedures in adults were considered. METHODS: A European interdisciplinary panel including general surgeons, obesity physicians, anesthetists, a psychologist and a patient representative informed outcome importance and minimal important differences. We conducted a systematic review and frequentist fixed and random-effects network meta-analysis of randomized-controlled trials (RCTs) using the graph theory approach for each outcome. We calculated the odds ratio or the (standardized) mean differences with 95% confidence intervals for binary and continuous outcomes, respectively. We assessed the certainty of evidence using the CINeMA and GRADE methodologies. We considered the risk/benefit outcomes within a GRADE evidence to decision framework to arrive at recommendations, which were validated through an anonymous Delphi process of the panel. RESULTS: We identified 43 records reporting on 24 RCTs. Most network information surrounded sleeve gastrectomy and Roux-en-Y gastric bypass. Under consideration of the certainty of the evidence and evidence to decision parameters, we suggest sleeve gastrectomy or laparoscopic Roux-en-Y gastric bypass over adjustable gastric banding, biliopancreatic diversion with duodenal switch and gastric plication for the management of severe obesity and associated metabolic diseases. One anastomosis gastric bypass and single anastomosis duodeno-ileal bypass with sleeve gastrectomy are suggested as alternatives, although evidence on benefits and harms, and specific selection criteria is limited compared to sleeve gastrectomy and Roux-en-Y gastric bypass. The guideline, with recommendations, evidence summaries and decision aids in user friendly formats can also be accessed in MAGICapp: https://app.magicapp.org/#/guideline/Lpv2kE CONCLUSIONS: This rapid guideline provides evidence-informed, pertinent recommendations on the use of bariatric and metabolic surgery for the management of severe obesity and metabolic diseases. The guideline replaces relevant recommendations published in the EAES Bariatric Guidelines 2020.

• MeSH
• Bariatric Surgery * methods   MeSH
• Adult MeSH
• Motion Pictures MeSH
• Gastrectomy methods   MeSH
• Consensus MeSH
• Laparoscopy * methods   MeSH
• Humans MeSH
• Obesity, Morbid * surgery   MeSH
• Network Meta-Analysis as Topic MeSH
• GRADE Approach MeSH
• Treatment Outcome MeSH
• Gastric Bypass * methods   MeSH
• Check Tag
• Adult MeSH
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Practice Guideline MeSH

The degree of response to subthalamic nucleus deep brain stimulation (STN-DBS) is individual and hardly predictable. We hypothesized that DBS-related changes in cortical network organization are related to the clinical effect. Network analysis based on graph theory was used to evaluate the high-density electroencephalography (HDEEG) recorded during a visual three-stimuli paradigm in 32 Parkinson's disease (PD) patients treated by STN-DBS in stimulation "off" and "on" states. Preprocessed scalp data were reconstructed into the source space and correlated to the behavioral parameters. In the majority of patients (n = 26), STN-DBS did not lead to changes in global network organization in large-scale brain networks. In a subgroup of suboptimal responders (n = 6), identified according to reaction times (RT) and clinical parameters (lower Unified Parkinson's Disease Rating Scale [UPDRS] score improvement after DBS and worse performance in memory tests), decreased global connectivity in the 1-8 Hz frequency range and regional node strength in frontal areas were detected. The important role of the supplementary motor area for the optimal DBS response was demonstrated by the increased node strength and eigenvector centrality in good responders. This response was missing in the suboptimal responders. Cortical topologic architecture is modified by the response to STN-DBS leading to a dysfunction of the large-scale networks in suboptimal responders.

• MeSH
• Electroencephalography MeSH
• Deep Brain Stimulation * MeSH
• Outcome Assessment, Health Care MeSH
• Middle Aged MeSH
• Humans MeSH
• Cerebral Cortex physiopathology   MeSH
• Nerve Net physiopathology   MeSH
• Subthalamic Nucleus physiopathology   MeSH
• Parkinson Disease physiopathology   therapy   MeSH
• Psychomotor Performance physiology   MeSH
• Aged MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

BACKGROUND: Cognitive impairment in Parkinson's disease (PD) is associated with altered connectivity of the resting state networks (RSNs). Longitudinal studies in well cognitively characterized PD subgroups are missing. OBJECTIVES: To assess changes of the whole-brain connectivity and between-network connectivity (BNC) of large-scale functional networks related to cognition in well characterized PD patients using a longitudinal study design and various analytical methods. METHODS: We explored the whole-brain connectivity and BNC of the frontoparietal control network (FPCN) and the default mode, dorsal attention, and visual networks in PD with normal cognition (PD-NC, n = 17) and mild cognitive impairment (PD-MCI, n = 22) as compared to 51 healthy controls (HC). We applied regions of interest-based, partial least squares, and graph theory based network analyses. The differences among groups were analyzed at baseline and at the one-year follow-up visit (37 HC, 23 PD all). RESULTS: The BNC of the FPCN and other RSNs was reduced, and the whole-brain analysis revealed increased characteristic path length and decreased average node strength, clustering coefficient, and global efficiency in PD-NC compared to HC. Values of all measures in PD-MCI were between that of HC and PD-NC. After one year, the BNC was further increased in the PD-all group; no changes were detected in HC. No cognitive domain z-scores deteriorated in either group. CONCLUSION: As compared to HC, PD-NC patients display a less efficient transfer of information globally and reduced BNC of the visual and frontoparietal control network. The BNC increases with time and MCI status, reflecting compensatory efforts.

• MeSH
• Adult MeSH
• Cognitive Dysfunction etiology   pathology   psychology   MeSH
• Middle Aged MeSH
• Humans MeSH
• Longitudinal Studies MeSH
• Magnetic Resonance Imaging MeSH
• Brain diagnostic imaging   pathology   MeSH
• Nerve Net diagnostic imaging   pathology   MeSH
• Neuroimaging MeSH
• Parkinson Disease complications   pathology   psychology   MeSH
• Prefrontal Cortex pathology   MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Case-Control Studies MeSH
• Parietal Lobe pathology   MeSH
• Mental Status and Dementia Tests MeSH
• Visual Cortex pathology   MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

Clinical symptoms of Parkinson's disease (PD) are accompanied by pathological phenomena detected locally in the basal ganglia (BG) as changes in local field potentials (LFPs) and also in cortical regions by electroencephalography (EEG). The literature published mainly between 2000 and 2017 was reviewed with an emphasis on approaches emerging after 2000, in particular on oscillatory dynamics, connectivity studies, and deep brain stimulation. Eighty-five articles were reviewed. The main observations were a general slowing of background activity, excessive synchronization of beta activity, and disturbed movement-related gamma oscillations in the BG and in the cortico-subcortical and cortico-cortical motor loops, suppressible by dopaminergic medication as well as by high-frequency deep brain stimulation (DBS). Non-motor symptoms are related mainly to changes in the alpha frequency range. EEG parameters can be useful in defining the risk of dementia in PD. Further progress was reported recently using advanced analytical technologies and high-performance computing (graph theory). Detailed knowledge of LFPs in PD enabled progress particularly in DBS therapy, which requires optimizing the clinical effect and minimizing adverse side effects. The neurocognitive networks and their dysfunction in PD and DBS therapy are promising targets for future research.

• MeSH
• Electroencephalography methods   MeSH
• Deep Brain Stimulation methods   MeSH
• Humans MeSH
• Brain physiopathology   MeSH
• Nerve Net physiopathology   MeSH
• Parkinson Disease diagnosis   physiopathology   therapy   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Review MeSH

Přibližně 30% pacientů s epilepsií neodpovídá na farmakologickou léčbu a lze u nich zvážit chirugické řešení. Určení oblasti oblasti, jejíž resekce je nezbytná, aby došlo k vymizení záchvatů, vyžaduje u řady pacientů implantaci intrakraniálních elektrod. Zrakové hodnocení dlouhodobých intrakraniálních záznamů představuje velmi komplikovaný a zdlouhavý proces, který je zatížený subjektivní chybou. Zvýšení informační výtěžnosti záznamů vyžaduje nové metodické postupy, které umožní rychlou a objektivní analýzu. Nejnovější poznatky prokazují, že záchvaty jsou projevem abnormální funkce mozkových sítí. Na základě těchto znalostí využijeme analýz z oboru komplexní dynamiky sítí a teorie grafů k vývoji inovativních diagnostických algoritmů, které zvýší klinickou výtěžnost intrakraniálních záznamů a zkvalitní předoperační diagnostiku. Nalezení síťových ukazatelů oblasti vzniku záchvatů umožní přesněji lokalizovat klíčové oblasti resekce. Vytvoření algoritmu, který modeluje epileptické sítě na základě pacientských dat, umožní predikci funkčního vlivu resekce a výsledku chirurgické léčby.; Epilepsy is a substantial disease burden and ~30% of patients do not respond to drug therapy. For these patients the only option is epilepsy surgery. Localization of the seizure generating areas of the brain often requires implantation of intracranial electrodes. Visual analysis of long-term recordings from large number of electrodes is extremely laborious and introduces significant human bias. Improving the presurgical diagnosis and increasing the information yield of invasive recordings requires faster and more objective quantitative analysis. It is well established that seizures emerge within functionally altered brain networks. In the proposed project we will apply complex network methods to quantify the organization of epileptic networks and develop innovative and more precise presurgical diagnostic tools. Identification of key components of the epileptic network will improve localization of seizure-generating regions, and patient-oriented network modelling approach will allow us to predict surgical outcomes.

• MeSH
• Diagnostic Techniques, Neurological MeSH
• Diagnosis, Computer-Assisted MeSH
• Electroencephalography MeSH
• Epilepsy surgery   MeSH
• Intracranial Pressure MeSH
• Neurosurgical Procedures MeSH
• Preoperative Care MeSH

• Conspectus
• Patologie. Klinická medicína
• NML Fields
• neurochirurgie
• NML Publication type
• závěrečné zprávy o řešení grantu AZV MZ ČR