RESUMEN
Prediction of cognitive ability latent factors such as general intelligence from neuroimaging has elucidated questions pertaining to their neural origins. However, predicting general intelligence from functional connectivity limit hypotheses to that specific domain, being agnostic to time-distributed features and dynamics. We used an ensemble of recurrent neural networks to circumvent this limitation, bypassing feature extraction, to predict general intelligence from resting-state functional magnetic resonance imaging regional signals of a large sample (n = 873) of Human Connectome Project adult subjects. Ablating common resting-state networks (RSNs) and measuring degradation in performance, we show that model reliance can be mostly explained by network size. Using our approach based on the temporal variance of saliencies, that is, gradients of outputs with regards to inputs, we identify a candidate set of networks that more reliably affect performance in the prediction of general intelligence than similarly sized RSNs. Our approach allows us to further test the effect of local alterations on data and the expected changes in derived metrics such as functional connectivity and instantaneous innovations.
Asunto(s)
Encéfalo/diagnóstico por imagen , Encéfalo/fisiología , Conectoma/métodos , Aprendizaje Profundo , Inteligencia/fisiología , Imagen por Resonancia Magnética/métodos , Red Nerviosa/diagnóstico por imagen , Red Nerviosa/fisiología , Conectoma/normas , Humanos , Imagen por Resonancia Magnética/normasRESUMEN
Psychopathy is a disorder characterized by severe and frequent moral violations in multiple domains of life. Numerous studies have shown psychopathy-related limbic brain abnormalities during moral processing; however, these studies only examined negatively valenced moral stimuli. Here, we aimed to replicate prior psychopathy research on negative moral judgments and to extend this work by examining psychopathy-related abnormalities in the processing of controversial moral stimuli and positive moral processing. Incarcerated adult males (N = 245) completed a functional magnetic resonance imaging protocol on a mobile imaging system stationed at the prison. Psychopathy was assessed using the Hare Psychopathy Checklist-Revised (PCL-R). Participants were then shown words describing three types of moral stimuli: wrong (e.g., stealing), not wrong (e.g., charity), and controversial (e.g., euthanasia). Participants rated each stimulus as either wrong or not wrong. PCL-R total scores were correlated with not wrong behavioral responses to wrong moral stimuli, and were inversely related to hemodynamic activity in the anterior cingulate cortex in the contrast of wrong > not wrong. In the controversial > noncontroversial comparison, psychopathy was inversely associated with activity in the temporal parietal junction and dorsolateral prefrontal cortex. These results indicate that psychopathy-related abnormalities are observed during the processing of complex, negative, and positive moral stimuli.
Asunto(s)
Trastorno de Personalidad Antisocial/fisiopatología , Encéfalo/fisiopatología , Principios Morales , Adolescente , Adulto , Anciano , Trastorno de Personalidad Antisocial/diagnóstico por imagen , Encéfalo/diagnóstico por imagen , Circulación Cerebrovascular/fisiología , Criminales , Toma de Decisiones/fisiología , Humanos , Entrevista Psicológica , Imagen por Resonancia Magnética , Masculino , Persona de Mediana Edad , Pruebas Neuropsicológicas , Prisioneros , Escalas de Valoración Psiquiátrica , Tiempo de Reacción , Lectura , Percepción Visual/fisiología , Adulto JovenRESUMEN
AIMS: The objectives of the present study are to describe the algorithm for VH(®) IVUS using the 45-MHz rotational IVUS catheter and the associated ex vivo validation in comparison to the gold standard histology. METHODS AND RESULTS: The first phase of the present study was to construct the 45 MHz VH IVUS algorithm by using a total of 55 human coronary artery specimens [111 independent coronary lesions and 510 homogenous regions of interest (ROIs)], obtained at autopsy. Regions were selected from histology and matched with their corresponding IVUS data to build the plaque classification system using spectral analysis and statistical random forests. In the second phase, the ex vivo validation of the VH IVUS algorithm assessed a total of 1060 ROIs (120 lesions from 60 coronary arteries) in comparison with histology. In an independent manner, two interventional cardiologists also classified a randomly selected subset of the ROIs for assessment of inter- and intra-observer reproducibility of VH IVUS image interpretation.When including all ROIs, the predictive accuracies were 90.8% for fibrous tissue, 85.8% for fibro fatty tissue, 88.3% for necrotic core, and 88.0% for dense calcium. The exclusion of ROIs in the acoustically attenuated areas improved the predictive accuracies, ranging from 91.9 to 96.8%. The independent analysis of randomly selected 253 ROIs showed substantial agreement for inter-observer (k = 0.66) and intra-observer (k = 0.88) reproducibility. CONCLUSION: Tissue classification by 45 MHz VH IVUS technology, when not influenced by calcium-induced acoustic attenuation, provided combined tissue accuracy >88% to identify tissue types compared with the gold standard histologic assessment, with high inter- and intra-observer reproducibility.
Asunto(s)
Algoritmos , Vasos Coronarios/diagnóstico por imagen , Placa Aterosclerótica/diagnóstico por imagen , Ultrasonografía Intervencional/métodos , Autopsia , Catéteres Cardíacos , Vasos Coronarios/patología , Humanos , Procesamiento de Imagen Asistido por Computador , Técnicas In Vitro , Placa Aterosclerótica/patología , Reproducibilidad de los Resultados , Rotación , Ultrasonografía Intervencional/instrumentaciónRESUMEN
Altered functional connectivity has been associated with acute and chronic nicotine use. Connectivity alterations, specifically in the right and left executive control networks (RECN/LECN) and the default mode network (DMN), may contribute to the addiction cycle. The objective of this study was to determine if executive control network (ECN) and DMN connectivity is different between non-smokers and smokers and whether reductions in connectivity are related to chronic cigarette use. The RECN, LECN, and DMN were identified in resting state functional magnetic resonance imaging data in 650 subjects. Analyses tested for group differences in network connectivity strength, controlling for age and alcohol use. There was a significant group effect on LECN and DMN connectivity strength with smokers (n = 452) having lower network strengths than non-smokers (n = 198). Smokers had lower connectivity than non-smokers associated with key network hubs: the dorsolateral prefrontal cortex, and parietal nodes within ECNs. Further, ECN connectivity strength was negatively associated with pack years of cigarette use. Our data suggest that chronic nicotine use negatively impacts functional connectivity within control networks that may contribute to the difficulty smokers have in quitting.
Asunto(s)
Mapeo Encefálico/métodos , Función Ejecutiva/fisiología , Red Nerviosa/fisiopatología , Lóbulo Parietal/fisiopatología , Corteza Prefrontal/fisiopatología , Fumar/fisiopatología , Adulto , Femenino , Humanos , Imagen por Resonancia Magnética , Masculino , Fumar/efectos adversosRESUMEN
Though previous examinations of intrinsic resting-state networks (RSNs) in healthy populations have consistently identified several RSNs that represent connectivity patterns evoked by cognitive and sensory tasks, the effects of different analytic approaches on the reliability and reproducibility of these RSNs have yet to be fully explored. Thus, the primary aim of the current study was to investigate the effect of method (independent component analyses [ICA] vs. seed-based analyses) on RSN reproducibility (independent datasets) for ICA and reliability (independent time points) in both methods using functional magnetic resonance imaging. Good to excellent reproducibility was observed in 9 out of 10 commonly identified RSNs, indicating the robustness of these intrinsic fluctuations at the group level. Reliability analyses showed that results were dependent on three main methodological factors: (1) group versus subject-level analyses (group>subject); (2) whether data from different visits were analyzed separately or jointly with ICA (combined>separate ICA); and (3) whether ICA output was used to directly assess reliability or to inform seed-based analyses (seed-based>ICA). These results suggest that variations in the analytic technique have a significant impact on individual reliability measurements, but do not significantly affect the reproducibility or reliability of RSNs at the group level. Further investigation into the effect of the analytic technique on RSN quantification is warranted to increase the utility of RSN analyses in clinical studies.