The semantic pointer theory of emotion: Integrating physiology,appraisal, and construction

Emotion theory needs to explain the relationship of language and emotions, and the embodiment of emotions, by specifying the computational mechanisms underlying emotion generation in the brain. We used Chris Eliasmith’s Semantic Pointer Architecture to develop POEM, a computational model that explains numerous important phenomena concerning emotions, including how some stimuli generate immediate emotional reactions, how some emotional reactions depend on cognitive evaluations, how bodily states influence the generation of emotions, how some emotions depend on interactions between physiological inputs and cognitive appraisals, and how some emotional reactions concern syntactically complex representations. We contrast our theory with current alternatives, and discuss some possible applications to individual and social emotions.     

A deep model with combined losses for person re-identification

Person re-identification (PReID), which aims to re-identity a pedestrian from multiple non-overlapping cameras, has been significantly improved by deep learning system. There exist two popular deep frameworks used for PReID, i.e., identification and triplet models. Since these two frameworks have different loss functions, they have their own advantages and disadvantages. To combine the both advantages of two frameworks, in this paper, we propose using the triplet and Online Instance Matching (OIM) losses to train the carefully designed network. Given a triplet input images, the combined model can output the identities of the input images and learn a corresponding similarity measurement simultaneously. Experiments on CUHK01, CUHK03, Market-1501, and DukeMTMC-reID datasets demonstrate that the proposed model outperforms the compared state-of-the-art methods in most cases.     

从个体关系的角度看文化对社会脑功能的塑造

摘 要 尽管社会认知的内容丰富多样,但其核心在于人们对“自我”、“他人”及两者关系的理解。文化作为一种独特的社会现象,对社会认知有着广泛影响,这一点集中体现在文化对“自我” 与“他人” 信息加工及其大脑机制的影响上。文化神经科学的研究表明：文化显著影响自我相关记忆、自我表征、自我觉知等自我认知过程。这可能主要来源于不同文化人群自我建构方式的不同。上述差异的神经机制主要体现为不同文化人群自我相关加工时,其内侧前额叶功能性变化的不同。与此相对应的是,文化同样显著影响人们对他人,尤其是对他人情绪的认知。这一点集中表现为表情认知的文化优势效应及共情过程的文化差异。在神经机制上这一差异主要体现为杏仁核功能的文化可塑性。文化神经科学的未来研究,可继续探讨主流文化、区域文化、宗教文化等各种形式的文化差异：1）对自我认知与情绪认知相互作用的影响与神经基础;2）对共情（empathy）、社会比较（social comparison）、心理理论（theory of mind）与协同行为（joint action）等多种社会认知过程的影响及其神经机制。 关键词 自我建构 文化神经科学 情绪认知 自我表征 共情     

The influence of asymmetric force requirements on a multi-frequency bimanual coordination task

An experiment was designed to determine the impact of the force requirements on the production of bimanual 1:2 coordination patterns requiring the same (symmetric) or different (asymmetric) forces when Lissajous displays and goal templates are provided. The Lissajous displays have been shown to minimize the influence of attentional and perceptual constraints allowing constraints related to neural crosstalk to be more clearly observed. Participants (N = 20) were randomly assigned to a force condition in which the left or right limb was required to produce more force than the contralateral limb. In each condition participants were required to rhythmically coordinate the pattern of isometric forces in a 1:2 coordination pattern. Participant performed 13 practice trials and 1 test trial per force level. The results indicated that participants were able to effectively coordinate the 1:2 multi-frequency goal patterns under both symmetric and asymmetric force requirements. However, consistent distortions in the force and force velocity time series were observed for one limb that appeared to be associated with the production of force in the contralateral limb. Distortions in the force produced by the left limb occurred regardless of the force requirements of the task (symmetric, asymmetric) or whether the left or right limb had to produce more force than the contralateral limb. However, distinct distortions in the right limb occurred only when the left limb was required to produce 5 times more force than the right limb. These results are consistent with the notion that neural crosstalk can influence both limbs, but may manifest differently for each limb depending on the force requirements of the task.     

Re-framing the characteristics of concepts and their relation to learning and cognition in artificial agents

In this work, the problems of knowledge acquisition and information processing are explored in relation to the definitions of concepts and conceptual processing, and their implications for artificial agents.The discussion focuses on views of cognition as a dynamic property in which the world is actively represented in grounded mental states which only have meaning in the action context. Reasoning is understood as an emerging property consequence of actions-environment couplings achieved through experience, and concepts as situated and dynamic phenomena enabling behaviours.Re-framing the characteristics of concepts is considered crucial to overcoming settled beliefs and reinterpreting new understandings in artificial systems.The first part presents a review of concepts from cognitive sciences. Support is found for views on grounded and embodied cognition, describing concepts as dynamic, flexible, context-dependent, and distributedly coded.That is argued to contrast with many technical implementations assuming concepts as categories, whilst explains limitations when grounding amodal symbols, or in unifying learning, perception and reasoning.The characteristics of concepts are linked to methods of active inference, self-organization, and deep learning to address challenges posed and to reinterpret emerging techniques.In a second part, an architecture based on deep generative models is presented to illustrate arguments elaborated. It is evaluated in a navigation task, showing that sufficient representations are created regarding situated behaviours with no semantics imposed on data. Moreover, adequate behaviours are achieved through a dynamic integration of perception and action in a single representational domain and process.     

Synchrnoic consciousness from a neurological point of view: the philosophical foundations for neuroethics

Daniel Kolak’s theory of synchronic consciousness according to which the entire range of dissociative phenomena, from pathologies such as MPD and schizophrenia to normal dream states, are best explained in terms of consciousness becoming simultaneously identified as many selves, has revolutionary therapeutic implications for neurology and psychiatry. All these selves, according to Kolak—even the purely imaginary ones that exist as such only in our dreams—are not just conscious but also self-conscious, with beliefs, intentions, living lives informed by memories (confabulatory, in the case of the fictional ones) and personal histories. Kolak’s derivation of psychiatrically relevant aspects of his theory—a neurological rendition of a Kantian transcendental argument—can be given a straightforward neurological, and therefore open to scientific scrutiny, interpretation that would then more easily lend itself to the clinical setting in which these perplexing phenomena, along with their purveyors, must live and cope. This will be the main focus of this paper.     

The Scientific Untraceability of Phenomenal Consciousness

It is a common conviction among philosophers who hold that phenomenal properties, qualia, are distinct from any cognitive, intentional, or functional properties, that it is possible to trace the neural correlates of these properties. The main purpose of this paper is to present a challenge to this view, and to show that if “non-cognitive” phenomenal properties exist at all, they lie beyond the reach of neuroscience. In the final section it will be suggested that they also lie beyond the reach of psychology, so that they may be said to lie beyond the reach of science.

Fragile X syndrome: Neural network models of sequencing and memory

A comparative framework of memory processes in males with fragile X syndrome (FXS) and typically developing (TYP) mental age-match children is presented. Results indicate a divergence in sequencing skills, such that males with FXS recall sequences similarly to TYP children around five and a half years of age, but the males with FXS recall significantly worse when compared to TYP children around seven and a half years of age. Performance on one working memory measure, an n-back Card Task, is modeled with a neural network. To date, no network models explicate the sequencing and memory processes in those with FXS. Noise was added to various levels (weight matrices) in the FXS model and outputs approximated human FXS performance. Three models were compared: (1) FXS; (2) younger mental age-TYP matches; (3) older reading level-TYP matches. Modeling can help to reify conceptualizations of deficits and to guide in the creation of more valid, science-based remediations. The FXS model suggested that the levels of phonological representation and sequencing in memory were candidates for targeted therapies in males with FXS.     

Incorporating Demographic Embeddings Into Language Understanding

Meaning depends on context. This applies in obvious cases like deictics or sarcasm as well as more subtle situations like framing or persuasion. One key aspect of this is the identity of the participants in an interaction. Our interpretation of an utterance shifts based on a variety of factors, including personal history, background knowledge, and our relationship to the source. While obviously an incomplete model of individual differences, demographic factors provide a useful starting point and allow us to capture some of this variance. However, the relevance of specific demographic factors varies between situations—where age might be the key factor in one context, ideology might dominate in another. To address this challenge, we introduce a method for combining demographics and context into situated demographic embeddings—mapping representations into a continuous geometric space appropriate for the given domain, showing the resulting representations to be functional and interpretable. We further demonstrate how to make use of related external data so as to apply this approach in low‐resource situations. Finally, we show how these representations can be incorporated into improve modeling of real‐world natural language understanding tasks, improving model performance and helping with issues of data sparsity.     

Persistence and accommodation in short‐term priming and other perceptual paradigms: temporal segregation through synaptic depression

Perceptual input changes constantly in an unpredictable fashion, often changing before our somewhat sluggish perceptual systems have adequately processed this input. This can give rise to source confusion—how do we know whether a given perceptual activation is due to the current input, or a previous input that had yet to be completely processed? We propose that activity‐dependent neural accommodation naturally limits this source confusion by suppressing items once they have been identified. We review behavioral paradigms from different literatures that measure the correlates of persistence and accommodation. Of the various accommodative mechanisms, we focus on synaptic depression, deriving a rate‐coded expression that can be used to produce accommodating dynamics in any neural network with real valued activation. We implement this expression in a hierarchical model of perception termed, “a neural mechanism for responding optimally with unknown sources of evidence” (nROUSE). This model can be viewed as a more detailed version of the more abstract ROUSE model of Huber, Shiffrin, Lyle, and Ruys (2001), which produces accommodated levels of feature evidence through an optimal calculation. We apply nROUSE to three short‐term priming experiments that manipulated prime duration.