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Repeated study improves memory, but the underlying neural mechanisms of this improvement are not well understood. Using functional magnetic resonance imaging and representational similarity analysis of brain activity, we found that, compared with forgotten items, subsequently remembered faces and words showed greater similarity in neural activation across(More)
Making a risky decision is a complex process that involves evaluation of both the value of the options and the associated risk level. Yet the neural processes underlying these processes have not so far been clearly identified. Using functional magnetic resonance imaging and a task that simulates risky decisions, we found that the dorsal region of the medial(More)
Risky decision making is a complex process that involves weighing the probabilities of alternative options that can be desirable, undesirable, or neutral. Individuals vary greatly in how they make decisions either under ambiguity and/or under risk. Such individual differences may have genetic bases. Based on previous studies on the genetic basis of decision(More)
Human decision-making involving independent events is often biased and affected by prior outcomes. Using a controlled task that allows us to manipulate prior outcomes, the present study examined the effect of prior outcomes on subsequent decisions in a group of young adults. We found that participants were more risk-seeking after losing a gamble (riskloss)(More)
This research investigated the cognitive correlates of false memories that are induced by the misinformation paradigm. A large sample of Chinese college students (N=436) participated in a misinformation procedure and also took a battery of cognitive tests. Results revealed sizable and systematic individual differences in false memory arising from exposure(More)
Automatic computation of surface correspondence via harmonic map is an active research field in computer vision, computer graphics and computational geometry. It may help document and understand physical and biological phenomena and also has broad applications in biometrics, medical imaging and motion capture. Although numerous studies have been devoted to(More)
Brain Cortical surface registration is required for inter-subject studies of functional and anatomical data. Harmonic mapping has been applied for brain mapping, due to its existence, uniqueness, regularity and numerical stability. In order to improve the registration accuracy, sculcal landmarks are usually used as constraints for brain registration.(More)
Brain morphometry study plays a fundamental role in medical imaging analysis and diagnosis. This work proposes a novel framework for brain cortical surface classification using Wasserstein distance, based on uniformization theory and Riemannian optimal mass transport theory. By Poincare uniformization theorem, all shapes can be conformally deformed to one(More)
Automatic computation of surface correspondence via harmonic map is an active research field in computer vision, computer graphics and computational geometry. It may help document and understand physical and biological phenomena and also has broad applications in biometrics, medical imaging and motion capture inducstries. Although numerous studies have been(More)
UNLABELLED The neural processes giving rise to human memory strength signals remain poorly understood. Inspired by formal computational models that posit a central role of global matching in memory strength, we tested a novel hypothesis that the strengths of both true and false memories arise from the global similarity of an item's neural activation pattern(More)