0000000000459962
AUTHOR
Xiaoying Sun
Common and separable behavioral and neural mechanisms underlie the generalization of fear and disgust
Generalization represents the transfer of a conditioned responses to stimuli that resemble the conditioned stimulus (CS). Previous studies on generalization of defensive avoidance responses have primarily focused on fear and have neglected disgust generalization, which represents a key pathological mechanism in some anxiety disorders. In the present study we examined common and distinct mechanisms of fear and disgust generalization by means of a fear or disgust multi-CS conditioning and generalization paradigm with concomitant event-related potential (ERPs) acquisition in n = 62 subjects. We demonstrate that compared to fear, disgust-relevant generalized stimuli (GS) elicited larger expecta…
Generalization gradients for fear and disgust in human associative learning
AbstractPrevious research indicates that excessive fear is a critical feature in anxiety disorders; however, recent studies suggest that disgust may also contribute to the etiology and maintenance of some anxiety disorders. It remains unclear if differences exist between these two threat-related emotions in conditioning and generalization. Evaluating different patterns of fear and disgust learning would facilitate a deeper understanding of how anxiety disorders develop. In this study, 32 college students completed threat conditioning tasks, including conditioned stimuli paired with frightening or disgusting images. Fear and disgust were divided into two randomly ordered blocks to examine di…
Development and Validation of a New Clinical Prediction Model of Catheter-Related Thrombosis Based on Vascular Ultrasound Diagnosis in Cancer Patients
Background: Central venous catheters are convenient for drug delivery and improved comfort for cancer patients, but they also cause serious complications. The most common complication is catheter-related thrombosis (CRT). Objectives: This study aimed to evaluate the incidence and risk factors for CRT in cancer patients and develop an effective prediction model for CRT in cancer patients. Methods: The development of our prediction model was based on a retrospective cohort (n = 3,131) from the National Cancer Center. Our prediction model was confirmed in a prospective cohort from the National Cancer Center (n = 685) and a retrospective cohort from the Hunan Cancer Hospital (n = 61). The predi…