视觉形状知觉在近似数量系统和计算流畅性关系中的作用

已有大量研究揭示了近似数量系统与计算流畅性的相关关系, 但缺少对二者关系原因的系统检验与论证。视觉形状知觉假设有别于传统的数量领域特异性解释, 认为对形状的快速知觉是近似数量系统与计算流畅性的共同认知机制, 即视觉形状的快速知觉能力可以解释二者之间的相关关系。近似数量系统和计算流畅性在加工过程中依赖对形状的快速知觉, 二者在加工过程中都涉及了复杂视觉刺激的快速处理。视觉形状知觉假设得到了一系列研究结果的支持, 但局限在视觉形状知觉与二者关系的探讨上, 视觉形状知觉在二者关系中作用的加工机制仍不清楚。未来研究需要结合多种研究方法和技术, 多角度深入探讨视觉形状知觉在二者关系中作用的认知与脑机制, 并将研究结果应用于数学课堂教学和计算困难的干预中。     

Disentangling the neural mechanisms involved in Hinduism- and Buddhism-related meditations

The most diffuse forms of meditation derive from Hinduism and Buddhism spiritual traditions. Different cognitive processes are set in place to reach these meditation states. According to an historical-philological hypothesis (Wynne, 2009) the two forms of meditation could be disentangled. While mindfulness is the focus of Buddhist meditation reached by focusing sustained attention on the body, on breathing and on the content of the thoughts, reaching an ineffable state of nothigness accompanied by a loss of sense of self and duality (Samadhi) is the main focus of Hinduism-inspired meditation. It is possible that these different practices activate separate brain networks. We tested this hypothesis by conducting an activation likelihood estimation (ALE) meta-analysis of functional magnetic resonance imaging (fMRI) studies. The network related to Buddhism-inspired meditation (16 experiments, 263 subjects, and 96 activation foci) included activations in some frontal lobe structures associated with executive attention, possibly confirming the fundamental role of mindfulness shared by many Buddhist meditations. By contrast, the network related to Hinduism-inspired meditation (8 experiments, 54 activation foci and 66 subjects) triggered a left lateralized network of areas including the postcentral gyrus, the superior parietal lobe, the hippocampus and the right middle cingulate cortex. The dissociation between anterior and posterior networks support the notion that different meditation styles and traditions are characterized by different patterns of neural activation.     

SAwSu: An Integrated Model of Associative and Reinforcement Learning

Successfully explaining and replicating the complexity and generality of human and animal learning will require the integration of a variety of learning mechanisms. Here, we introduce a computational model which integrates associative learning (AL) and reinforcement learning (RL). We contrast the integrated model with standalone AL and RL models in three simulation studies. First, a synthetic grid‐navigation task is employed to highlight performance advantages for the integrated model in an environment where the reward structure is both diverse and dynamic. The second and third simulations contrast the performances of the three models in behavioral experiments, demonstrating advantages for the integrated model in accounting for behavioral data.     

应用分子靶向治疗的时机选择

分子靶向药物的出现显示出肿瘤治疗传统模式的重要进展。与传统放疗、化疗相比,分子靶向治疗因其特异性高、不良反应轻微,在恶性肿瘤个体化治疗中扮演重要角色。十五年来,分子靶向药物的出现,给肿瘤的治疗模式带来重大改变,也给临床医生带来新的挑战。准确把握分子靶向药物应用时机,获得最大临床效果,已成为肿瘤治疗领域关注热点。本文就非小细胞肺癌、消化系统肿瘤、乳腺癌、肾癌治疗中分子靶向药物如何选择应用时机进行阐述。     

医学影像学见习应用PACS教学法与传统读片教学法的对比研究

将中南大学湘雅医学院2010级临床医学五年制197名学生随机分成两组,在医学影像学见习教学过程中分别应用影像存储及传输系统（PACS）教学法（98人）及传统读片教学法（99人）,学期结束时对两组学生考试成绩进行分析,并对PACS组学生进行问卷调查及结果分析.统计数据显示,PACS组学生读片测验及卷面考试中,病例分析题成绩显著高于传统读片组,问卷调查显示PACS组学生大多数认可该教学方法.因此,应用PACS教学有助于提高学生的临床分析能力及主动学习的能力,是学生欢迎的教学方式.但对医学影像学基本知识的传授,应用PACS法较传统读片法并无明显优势.     

人工肝支持系统治疗肝衰竭的研究进展

目前肝衰竭发病率和病死率仍然较高,肝衰竭成为威胁患者生命的严重疾病。基于肝脏具有强大再生能力,人工肝支持系统作为一种“过渡”措施,为肝衰竭患者的肝功能恢复赢得时间。人工肝支持系统根据性质不同分为非生物型人工肝、生物型人工肝和混合型人工肝。目前非生物型人工肝已在肝病治疗领域被广泛应用,但生物型及混合型人工肝的临床应用还存在很多问题需要进一步研究和解决。因此本文对人工肝的作用、临床应用现状、存在问题及研究进展进行综述。     

Natural language semantics in biproduct dagger categories

Biproduct dagger categories serve as models for natural language. In particular, the biproduct dagger category of finite dimensional vector spaces over the field of real numbers accommodates both the extensional models of predicate calculus and the intensional models of quantum logic. The morphisms representing the extensional meanings of a grammatical string are translated to morphisms representing the intensional meanings such that truth is preserved. Pregroup grammars serve as the tool that transforms a grammatical string into a morphism. The chosen linguistic examples concern negation, relative noun phrases, comprehension and quantifiers.