Lhát znamená vyslovit nepravdivý výrok s úmyslem podvést. Podvádět znamená záměrně dovést druhou osobu k mylnému přesvědčení. Poznat, že někdo lže, není jednoduché. Klíčové je sledování neverbálního chování, tváře, řeči a jazyka a fyziologických změn podezřelého jedince. To vyžaduje zkušenost a má svá omezení. Vyšetřování polygrafem má nízkou senzitivitu a specificitu. Značné limity má i současné užití funkční zobrazovacích metod. Je zatíženo čtyřmi okruhy problémů včetně niterné „sebeobrany“.

To lie is to make a false statement with the intention to deceive. To deceive means to intentionally cause another person to have a false belief. To discover whether, or not a person is lying is difficult find, monitoring their nonverbal behaviour is of key importance. It requires experience and has its limits. Examination by polygraph has low sensitivity and specificity. Use of contemporary functional imaging methods has considerable limits too. The burden of these methods is connected with four types of problems including inner „self-defence“.

• Keywords
• lhaní, polygraf, funkční zobrazovací metody,
• MeSH
• Lie Detection MeSH
• Emotions physiology   MeSH
• Cognition physiology   MeSH
• Humans MeSH
• Magnetic Resonance Imaging utilization   MeSH
• Brain Mapping MeSH
• Brain physiology   MeSH
• Cerebral Cortex physiology   MeSH
• Neuropsychological Tests MeSH
• Observer Variation MeSH
• Cues MeSH
• Deception MeSH
• Observation MeSH
• Social Behavior MeSH
• Choice Behavior physiology   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Introductory Journal Article MeSH

BACKGROUND: Patients suffering from functional neurological disorder (FND) experience disabling neurological symptoms not caused by an underlying classical neurological disease (such as stroke or multiple sclerosis). The diagnosis is made based on reliable positive clinical signs, but clinicians often require additional time- and cost consuming medical tests and examinations. Resting-state functional connectivity (RS FC) showed its potential as an imaging-based adjunctive biomarker to help distinguish patients from healthy controls and could represent a "rule-in" procedure to assist in the diagnostic process. However, the use of RS FC depends on its applicability in a multi-centre setting, which is particularly susceptible to inter-scanner variability. The aim of this study was to test the robustness of a classification approach based on RS FC in a multi-centre setting. METHODS: This study aimed to distinguish 86 FND patients from 86 healthy controls acquired in four different centres using a multivariate machine learning approach based on whole-brain resting-state functional connectivity. First, previously published results were replicated in each centre individually (intra-centre cross-validation) and its robustness across inter-scanner variability was assessed by pooling all the data (pooled cross-validation). Second, we evaluated the generalizability of the method by using data from each centre once as a test set, and the data from the remaining centres as a training set (inter-centre cross-validation). RESULTS: FND patients were successfully distinguished from healthy controls in the replication step (accuracy of 74%) as well as in each individual additional centre (accuracies of 73%, 71% and 70%). The pooled cross validation confirmed that the classifier was robust with an accuracy of 72%. The results survived post-hoc adjustment for anxiety, depression, psychotropic medication intake, and symptom severity. The most discriminant features involved the angular- and supramarginal gyri, sensorimotor cortex, cingular- and insular cortex, and hippocampal regions. The inter-centre validation step did not exceed chance level (accuracy below 50%). CONCLUSIONS: The results demonstrate the applicability of RS FC to correctly distinguish FND patients from healthy controls in different centres and its robustness against inter-scanner variability. In order to generalize its use across different centres and aim for clinical application, future studies should work towards optimization of acquisition parameters and include neurological and psychiatric control groups presenting with similar symptoms.

• MeSH
• Conversion Disorder * diagnostic imaging   physiopathology   MeSH
• Humans MeSH
• Magnetic Resonance Imaging * methods   MeSH
• Brain * diagnostic imaging   physiopathology   MeSH
• Reproducibility of Results MeSH
• Case-Control Studies MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Multicenter Study MeSH
• Research Support, Non-U.S. Gov't MeSH

• MeSH
• European Union MeSH
• Research MeSH
• Publication type
• Abstracts MeSH
• Geographicals
• Europe MeSH

• Conspectus
• Veřejné zdraví a hygiena
• NML Fields
• veřejné zdravotnictví
• politologie, politika, zdravotní politika

• About
• Commission of the European Communities. Biomedical and Health Research Programme Authority