Is predictive processing a theory of perceptual consciousness?

Predictive Processing theory, hotly debated in neuroscience, psychology and philosophy, promises to explain a number of perceptual and cognitive phenomena in a simple and elegant manner. In some of its versions, the theory is ambitiously advertised as a new theory of conscious perception. The task of this paper is to assess whether this claim is realistic. We will be arguing that the Predictive Processing theory cannot explain the transition from unconscious to conscious perception in its proprietary terms. The explanations offered by PP theorists mostly concern the preconditions of conscious perception, leaving the genuine material substrate of consciousness untouched.     

Modeling adaptive cooperative and competitive metaphors as mental models for joint decision making

In this paper, joint decision making processes are studied and the role of cognitive metaphors as mental models in them. A second-order self-modeling network model is introduced based on mechanisms known from cognitive and social neuroscience and cognitive metaphor and mental model literature. The cognitive metaphors were modeled as specific forms of mental models providing a form of modulation within the joint decision making process. The model addresses not only the use of these mental models in the decision making, but also their hebbian learning and the control over the learning. The obtained self-modeling network model was applied to two types of metaphors that affect joint decision making in different manners: a cooperative metaphor and a competitive metaphor. By a number of scenarios it was shown how the obtained self-modeling network model can be used to simulate and analyze joint decision processes and how they are influenced by such cognitive metaphors.     

时间与金钱概念对消费者购买决策的不同影响及其心理机制

时间与金钱是影响人们消费行为决策的两种不同的重要资源。消费者在进行产品购买时, 常常会受到商家广告语和购物环境中所隐含的时间或金钱概念的影响, 从而做出不同的决策。具体而言, 时间与金钱概念会对消费者的购前决策、购中决策及购后决策三个方面产生不同的影响。从双加工理论的角度来看, 产生这种不同影响背后的心理机制在于时间与金钱概念启动了个体不同的认知加工方式和思维定势, 进而影响了消费者不同的购买决策。未来的研究方向有：(1)细化时间和金钱概念启动对消费者购买决策的不同影响; (2)考虑时间与金钱的权衡对购买决策的影响; (3)进一步探究时间和金钱概念的激活对购前决策的不同影响; (4)探讨时间概念与金钱概念对购买决策不同影响的神经机制。     

个体采纳与群体采纳：决策过程中的两类建议采纳行为

决策者借助外界的建议通常能够获得更好的决策结果, 但是个体和群体对待建议的态度和行为却不尽相同。基于已有研究, 阐述了个体和群体在建议采纳过程中的特点并分析了造成二者差异的因素, 主要包括二者在面对决策任务和外界建议时的不同表现。此外, 根据群体动力理论, 未来研究可以从群体的动力源因素(凝聚力, 驱动力, 耗散力)来解释和预测群体的建议采纳及其与个体建议采纳的差异, 以期为不同决策情景下决策人员的合理安排和配置提供参考。     

前瞻性情绪作为社会风险的信息源假说：公共场景下风险决策的情绪及文化机制探讨

本研究从梳理决策的情绪理论入手, 在综合几种主要理论的基础上提出了“前瞻性情绪作为社会风险信息源”的假说。前瞻性情绪是在决策过程中产生的, 由于对决策选择的预期而感受到的, 进而影响决策行为的情绪。社会环境下的风险事件具有突发和稍纵即逝的特征, 如果一个公民对这类风险事件做出反应, 其结果的概率难于量化。在这种情况下, 前瞻性情绪能够为决策者快速提供有关信息, 并形成对决策预期结果严重性和可能性的综合表征, 从而成为公众场景下风险决策的有效线索。不同前瞻性情绪的组合在面对社会性风险事件时具有针对性的作用。近年来在文化比较中对于面子、荣誉和尊严文化的划分, 也为我们研究文化的情绪特征和行为效应提供了理论框架。本研究拟通过四项研究和多个实验探讨前瞻性情绪如何影响公众场景下人们的风险应对行为, 并对三种文化的情绪特征进行比较, 探索情绪性决策中个人因素、群体因素、及文化因素如何共同决定公共场景下风险决策(如亲社会行为或反社会行为)的发生与发展, 同时也期望为公共政策的制定及风险管理提供科学依据。     

Guiding Decision Makers' Eye Movements with (Un)Predictable Object Locations

We propose a new approach for guiding eye movements by controlling the predictability of object locations. We hypothesize that when a high (low) relevance object has a predictable location, observers are more (less) likely to fixate it compared with objects in unpredictable locations. We tested this hypothesis in three decision‐making studies, manipulating the location of a product label in an unpredictable, a predictable, and a mixed visual environment. In Study 1 and Study 2, we find that participants are less likely to fixate a low and medium relevance label in a predictable location, and in Study 3, we find that participants are more likely to fixate a high relevance label in a predictable location. Our findings suggest that predictable locations increase while unpredictable locations decrease top‐down control. The approach can be used to increase or decrease eye movements towards specific information depending on the goals of the choice architect. Copyright © 2017 John Wiley & Sons, Ltd.     

Using Statistical Models of Morphology in the Search for Optimal Units of Representation in the Human Mental Lexicon

Determining optimal units of representing morphologically complex words in the mental lexicon is a central question in psycholinguistics. Here, we utilize advances in computational sciences to study human morphological processing using statistical models of morphology, particularly the unsupervised Morfessor model that works on the principle of optimization. The aim was to see what kind of model structure corresponds best to human word recognition costs for multimorphemic Finnish nouns: a model incorporating units resembling linguistically defined morphemes, a whole‐word model, or a model that seeks for an optimal balance between these two extremes. Our results showed that human word recognition was predicted best by a combination of two models: a model that decomposes words at some morpheme boundaries while keeping others unsegmented and a whole‐word model. The results support dual‐route models that assume that both decomposed and full‐form representations are utilized to optimally process complex words within the mental lexicon.     

A model‐based process to improve robustness in Multicriteria Decision Aiding interventions

A model‐based process is a methodological approach that facilitates interventions in new and ill or not structured problem situations. It is oriented towards improving the robustness of the intervention and its results in an incremental definition of both the problem formulation and the model, in order to reduce the uncertainty that is not only associated with the model parameters but also with the model structure, and sometimes also with the problem formulation. The nature and results of this approach, which consider the interaction between an analyst and the actors of the decision system as the decision aiding core, are proposed in relation to some actual interventions.