A PRESCRIPTION FOR GENERATING A NEW PARADIGM IN THE CONTEXT OF SCIENCE AND THEOLOGY

Abstract. Many centers are now active in the study of the interaction between science on the one hand and theology on the other. Suggestions are made as to how such study might be furthered. The central proposal in this paper is based on the author's experience in founding and, over many years, operating the Neurosciences Research Program (NRP). The "faculty" of this group were highly competent in many fields of science and were able to deal with many of the major issues. It is here further suggested that if an NRP-like organization were established, capable of productively interacting with both science and theology, it might well generate new concepts and possibly a new paradigm in this context.     

Two Books for Teachers

Murphy, Nancey and Ellis, George F. R. On the Moral Nature of the Universe: Theology, Cosmology, and Ethics
Haught, John F. Science and Religion: From Conflict to Conversation     

Jungian Psychology, the Body, and the Future

Impressive reaffirmation of Jung's archetypal hypothesis has come from developments in behavioural biology (Tinbergen 1951; Cosmides 1985), psycholinguistics (Chomsky 1965), structural anthropology (Lévi-Strauss 1967), developmental psychology (Bowlby 1969), dream research (Jouvet 1975). neuroscience (MacLean 1976), sociobiology (Wilson 1978), and evolutionary psychiatry (Gardner 1988; Gilbert 1989). A close correspondence exists between Jungian theories of dreaming in human beings and modern biological theories of dreaming in animals. A paradigm shift is under way in the direction of a growing cross-disciplinary awareness that all human sciences are about archetypal manifestations and that these apply as much to the body as to the mind. Jungian psychology must keep abreast of these developments if it is not to be sidelined and superseded by less humane therapeutic philosophies.     

On computing time-to-collision for automation scenarios

Time to collision (TTC) has been a key vehicle safety metric for decades. With the increasing prevalence of advanced driver assistance systems and vehicle automation, TTC and many related metrics are being applied to the analysis of more complicated scenarios, as well as being integrated into automation algorithms. While the TTC metric was originally conceived to be inclusive of generic two-dimensional situations, its applications has been mostly limited to one-dimensional scenarios. This paper derives general equations and algorithms using two-dimensional information. Additionally, methods from computational geometry, a field that didn’t exist when TTC was first used, are employed for the general case of computing TTC between bounding boxes. Parametric equations for lines play a prominent role and offer an elegant way to express the geometry of the scenarios described in this paper. Throughout, the approach is not to derive specific algebraic conditions as in previous efforts. Rather, the focus in on developing general algorithms for computation. The techniques presented are not necessary for traditional car following scenarios; but offer options for more complex situations that trade off analytic solutions for computational flexibility.     

Psychosis,symbol, affectivity 1: etiopathogenesis and treatment through analytical psychology

This is the first of two papers concerning our study into an integrated approach to psychotic disorders, conducted at the University of Palermo’s Psychiatry Unit Polyclinic over approximately 15 years. Here we will explore and reflect upon the acute psychotic condition mainly from a theoretical and conceptual perspective, while in the second paper we will explore the clinical perspective. From the point of view of psychopathology, and in the light of C.G. Jung’s conceptualization of analytical psychology, as well as calling on contributions from other authors from the systemic-relational and post-psychoanalytic field, we will clarify the ideas developed over these last few years by our team. From a more speculative perspective we will advance new interpretive hypotheses in an attempt to thoroughly understand the nature of the psychotic condition, both on a psychodynamic relational and a neuroscientific level. The paper describes how we revised our understanding of psychosis from a brain disease to a process aimed at the rearrangement of psychic functioning, as anticipated by John Weir Perry nearly 40 years ago.     

Parsing as a Cue-Based Retrieval Model

This paper develops a novel psycholinguistic parser and tests it against experimental and corpus reading data. The parser builds on the recent research into memory structures, which argues that memory retrieval is content-addressable and cue-based. It is shown that the theory of cue-based memory systems can be combined with transition-based parsing to produce a parser that, when combined with the cognitive architecture ACT-R, can model reading and predict online behavioral measures (reading times and regressions). The parser's modeling capacities are tested against self-paced reading experimental data (Grodner & Gibson, 2005), eye-tracking experimental data (Staub, 2011), and a self-paced reading corpus (Futrell et al., 2018).     

Linguistic Distributional Knowledge and Sensorimotor Grounding both Contribute to Semantic Category Production

The human conceptual system comprises simulated information of sensorimotor experience and linguistic distributional information of how words are used in language. Moreover, the linguistic shortcut hypothesis predicts that people will use computationally cheaper linguistic distributional information where it is sufficient to inform a task response. In a pre-registered category production study, we asked participants to verbally name members of concrete and abstract categories and tested whether performance could be predicted by a novel measure of sensorimotor similarity (based on an 11-dimensional representation of sensorimotor strength) and linguistic proximity (based on word co-occurrence derived from a large corpus). As predicted, both measures predicted the order and frequency of category production but, critically, linguistic proximity had an effect above and beyond sensorimotor similarity. A follow-up study using typicality ratings as an additional predictor found that typicality was often the strongest predictor of category production variables, but it did not subsume sensorimotor and linguistic effects. Finally, we created a novel, fully grounded computational model of conceptual activation during category production, which best approximated typical human performance when conceptual activation was allowed to spread indirectly between concepts, and when candidate category members came from both sensorimotor and linguistic distributional representations. Critically, model performance was indistinguishable from typical human performance. Results support the linguistic shortcut hypothesis in semantic processing and provide strong evidence that both linguistic and grounded representations are inherent to the functioning of the conceptual system. All materials, data, and code are available at https://osf.io/vaq56/ .     

Computational models of the “active self” and its disturbances in schizophrenia

The notion that self-disorders are at the root of the emergence of schizophrenia rather than a symptom of the disease, is getting more traction in the cognitive sciences. This is in line with philosophical approaches that consider an enactive self, constituted through action and interaction with the environment. We thereby analyze different definitions of the self and evaluate various computational theories lending to these ideas. Bayesian and predictive processing are promising approaches for computational modeling of the “active self”. We evaluate their implementation and challenges in computational psychiatry and cognitive developmental robotics. We describe how and why embodied robotic systems provide a valuable tool in psychiatry to assess, validate, and simulate mechanisms of self-disorders. Specifically, mechanisms involving sensorimotor learning, prediction, and self-other distinction, can be assessed with artificial agents. This link can provide essential insights to the formation of the self and new avenues in the treatment of psychiatric disorders.     

教与学的大脑：人际神经科学助推教育研究

如何从神经生理层面刻画教育活动的人际互动模式和动态性是教育神经科学面临的一个重要挑战。人际神经科学视角为其提供了可能的解决途径; 这一新兴的视角通过记录和分析进行同一认知活动时两人或多人大脑活动之间的关联, 来揭示大脑活动的群体模式。目前, 人际神经科学方法已被应用于教育研究, 例如监控教学过程、预测教学效果和识别教学影响因素, 相应的研究成果对教育活动具有重要启示。未来的研究者可以更多地关注不同学习水平的学生大脑的互动机制及人际神经科学方法应用于技能教学及线上教学评估的巨大潜力。     

EARSHOT: A Minimal Neural Network Model of Incremental Human Speech Recognition

Despite the lack of invariance problem (the many-to-many mapping between acoustics and percepts), human listeners experience phonetic constancy and typically perceive what a speaker intends. Most models of human speech recognition (HSR) have side-stepped this problem, working with abstract, idealized inputs and deferring the challenge of working with real speech. In contrast, carefully engineered deep learning networks allow robust, real-world automatic speech recognition (ASR). However, the complexities of deep learning architectures and training regimens make it difficult to use them to provide direct insights into mechanisms that may support HSR. In this brief article, we report preliminary results from a two-layer network that borrows one element from ASR, long short-term memory nodes, which provide dynamic memory for a range of temporal spans. This allows the model to learn to map real speech from multiple talkers to semantic targets with high accuracy, with human-like timecourse of lexical access and phonological competition. Internal representations emerge that resemble phonetically organized responses in human superior temporal gyrus, suggesting that the model develops a distributed phonological code despite no explicit training on phonetic or phonemic targets. The ability to work with real speech is a major advance for cognitive models of HSR.