Neural network processing of natural language: II. Towards a unified model of corticostriatal function in learning sentence comprehension and non-linguistic sequencing

A central issue in cognitive neuroscience today concerns how distributed neural networks in the brain that are used in language learning and processing can be involved in non-linguistic cognitive sequence learning. This issue is informed by a wealth of functional neurophysiology studies of sentence comprehension, along with a number of recent studies that examined the brain processes involved in learning non-linguistic sequences, or artificial grammar learning (AGL). The current research attempts to reconcile these data with several current neurophysiologically based models of sentence processing, through the specification of a neural network model whose architecture is constrained by the known cortico-striato-thalamo-cortical (CSTC) neuroanatomy of the human language system. The challenge is to develop simulation models that take into account constraints both from neuranatomical connectivity, and from functional imaging data, and that can actually learn and perform the same kind of language and artificial syntax tasks. In our proposed model, structural cues encoded in a recurrent cortical network in BA47 activate a CSTC circuit to modulate the flow of lexical semantic information from BA45 to an integrated representation of meaning at the sentence level in BA44/6. During language acquisition, corticostriatal plasticity is employed to allow closed class structure to drive thematic role assignment. From the AGL perspective, repetitive internal structure in the AGL strings is encoded in BA47, and activates the CSTC circuit to predict the next element in the sequence. Simulation results from Caplan's [Caplan, D., Baker, C., & Dehaut, F. (1985). Syntactic determinants of sentence comprehension in aphasia. Cognition, 21, 117-175] test of syntactic comprehension, and from Gomez and Schvaneveldts' [Gomez, R. L., & Schvaneveldt, R. W. (1994). What is learned from artificial grammars?. Transfer tests of simple association. Journal of Experimental Psychology: Learning, Memory and Cognition, 20, 396-410] artificial grammar learning experiments are presented. These results are discussed in the context of a brain architecture for learning grammatical structure for multiple natural languages, and non-linguistic sequences.     

Lexical organization and competition in first and second languages: computational and neural mechanisms

How does a child rapidly acquire and develop a structured mental organization for the vast number of words in the first years of life? How does a bilingual individual deal with the even more complicated task of learning and organizing two lexicons? It is only until recently have we started to examine the lexicon as a dynamical system with regard to its acquisition, representation, and organization. In this article, I outline a proposal based on our research that takes the dynamical approach to the lexicon, and I discuss how this proposal can be applied to account for lexical organization, structural representation, and competition within and between languages. In particular, I provide computational evidence based on the DevLex model, a self-organizing neural network model, and neuroimaging evidence based on functional magnetic resonance imaging (fMRI) studies, to illustrate how children and adults learn and represent the lexicon in their first and second languages. In the computational research, our goal has been to identify, through linguistically and developmentally realistic models, detailed cognitive mechanisms underlying the dynamic self-organizing processes in monolingual and bilingual lexical development; in the neuroimaging research, our goal has been to identify the neural substrates that subserve lexical organization and competition in the monolingual and the bilingual brain. In both cases, our findings lead to a better understanding of the interactive dynamics involved in the acquisition and representation of one or multiple languages.     

THE THIRD WAY OF RELIGIOUS STUDIES: BEYOND SUI GENERIS RELIGIOUS STUDIES AND THE POSTMODERNISTS

This essay advocates dual-inheritance theory for the renewal of Religious Studies. Not by Genes Alone , by Peter J. Richerson and Robert Boyd (2005), presents this approach in an admirably clear manner. To make my case, I survey the development of Religious Studies since the Enlightenment, with special attention to the American context. The historical survey brings us to the dawn of the twenty-first century, where Religious Studies is often unnecessarily limited to sui generis Religious Studies and its postmodern critics. Neither approach engages regnant Darwinian theoretical frameworks of gene-culture coevolution productively. In this context, I situate the contributions of dual-inheritance theory as presented by Richerson and Boyd and offer examples of its utility for progress in Religious Studies, its ability to open cooperation across disciplinary boundaries, and its salutary demystification of religion as a culturally unique and coherent phenomenon. I conclude by addressing concerns scholars of religion might entertain regarding the issue of reductionism and how an emergent science of religion might contribute to the traditional concerns of religion-and-science dialogue as it has evolved in the English-speaking context.     

考试抄袭识别的心理测量学研究回顾

考试抄袭是最难识别的作弊方式。抄袭统计量（ACS）和人员拟合统计量（PFS）是识别抄袭的两类主要统计方法。ACS是根据被怀疑抄袭者与被抄袭者实际得分模式相似的概率来识别抄袭者。PFS 则把一个观察的项目得分模式与一定的测量模型相对比,来检验被试得分模式是否与测量模型预测的模式相吻合。其中,PFS由于在识别异常得分模式时存在一些干扰因素,所以对结果的解释存在多样性,应用较少。ACS是专门用于识别抄袭的统计方法,研究表明其识别率更高。目前ACS指标在美国的SAT和一些资格认证考试中已经得到广泛应用     

The neural correlates of consciousness: New experimental approaches needed?

It appears that consciousness science is progressing soundly, in particular in its search for the neural correlates of consciousness. There are two main approaches to this search, one is content-based (focusing on the contrast between conscious perception of, e.g., faces vs. houses), the other is state-based (focusing on overall conscious states, e.g., the contrast between dreamless sleep vs. the awake state). Methodological and conceptual considerations of a number of concrete studies show that both approaches are problematic: the content-based approach seems to set aside crucial aspects of consciousness; and the state-based approach seems over-inclusive in a way that is hard to rectify without losing sight of the crucial conscious–unconscious contrast. Consequently, the search for the neural correlates of consciousness is in need of new experimental paradigms.     

Multiple realization and methodological pluralism

Multiple realization was once taken to be a challenge to reductionist visions, especially within cognitive science, and a foundation of the “antireductionist consensus.” More recently, multiple realization has come to be challenged on naturalistic grounds, as well as on more “metaphysical” grounds. Within cognitive science, one focal issue concerns the role of neural plasticity for addressing these issues. If reorganization maintains the same cognitive functions, that supports claims for multiple realization. I take up the reorganization involved in language dysfunctions to deal with questions concerned with multiple realization and neural plasticity. Beginning with Broca’s case for localization and the nineteenth century discussion of “reorganization,” and returning to more recent evidence for neural plasticity, I argue that, in the end, there is substantial support for multiple realization in cognitive systems; I further argue that this is wholly consistent with a recognition of methodological pluralism in cognitive science.     

Layer and regional effects of environmental enrichment on the pyramidal neuron morphology of the rat

The environmental enrichment (EE) paradigm is widely used to study experience-dependent brain plasticity. Several studies have investigated functional and anatomical EE effects. However, as EE effects are different according to cerebral region, cortical layer, dendritic field and morphological index considered, a univocal characterization of neuronal morphological changes following rearing in enriched environments is lacking.Aim of the present study was to characterize in the rat the effects of EE on the neuronal morphology of frontal and parietal cortical regions, the main target areas of the stimulation provided by the paradigm. Male Wistar rats were housed in an enriched environment for 3.5 months from the 21st postnatal day. For the morphological analysis, biotinylated dextran amine (BDA)-labeled pyramidal neurons were selected from frontal (M1–M2) and parietal (S1–S2) cortical layers III and V. Apical and basal dendritic branching and spines were analyzed using the Sholl method.Results showed that EE increased branching and spines in both layers of frontal cortex, but had a greater effect on apical arborization. In parietal cortex, EE significantly affected branching and spines in layer III but not layer V neurons, in which only a tendency to be influenced by the rearing conditions was observed in basal arborization.It is hypothesized that these multifaceted morphological EE effects are connected to the heavy involvement of a sensory-motor circuit engaged in the guidance of voluntary action and in motor learning activated by EE stimulation.     

ERP and MEG correlates of visual consciousness: The second decade

The first decade of event-related potential (ERP) research had established that the most consistent correlates of the onset of visual consciousness are the early visual awareness negativity (VAN), a posterior negative component in the N2 time range, and the late positivity (LP), an anterior positive component in the P3 time range. Two earlier extensive reviews ten years ago had concluded that VAN is the earliest and most reliable correlate of visual phenomenal consciousness, whereas LP probably reflects later processes associated with reflective/access consciousness. This article provides an update to those earlier reviews. ERP and MEG studies that have appeared since 2010 and directly compared ERPs between aware and unaware conditions are reviewed, and important new developments in the field are discussed. The result corroborates VAN as the earliest and most consistent signature of visual phenomenal consciousness, and casts further doubt on LP as an ERP correlate of phenomenal consciousness.     

A real‐world rational agent: unifying old and new AI

Explanations of cognitive processes provided by traditional artificial intelligence were based on the notion of the knowledge level. This perspective has been challenged by new AI that proposes an approach based on embodied systems that interact with the real‐world. We demonstrate that these two views can be unified. Our argument is based on the assumption that knowledge level explanations can be defined in the context of Bayesian theory while the goals of new AI are captured by using a well established robot based model of learning and problem solving, called Distributed Adaptive Control (DAC). In our analysis we consider random foraging and we prove that minor modifications of the DAC architecture renders a model that is equivalent to a Bayesian analysis of this task. Subsequently, we compare this enhanced, “rational,” model to its “non‐rational” predecessor and a further control condition using both simulated and real robots, in a variety of environments. Our results show that the changes made to the DAC architecture, in order to unify the perspectives of old and new AI, also lead to a significant improvement in random foraging.     

Consciousness as a concrete physical phenomenon

The typical empirical approach to studying consciousness holds that we can only observe the neural correlates of experiences, not the experiences themselves. In this paper we argue, in contrast, that experiences are concrete physical phenomena that can causally interact with other phenomena, including observers. Hence, experiences can be observed and scientifically modelled. We propose that the epistemic gap between an experience and a scientific model of its neural mechanisms stems from the fact that the model is merely a theoretical construct based on observations, and distinct from the concrete phenomenon it models, namely the experience itself. In this sense, there is a gap between any natural phenomenon and its scientific model. On this approach, a neuroscientific theory of the constitutive mechanisms of an experience is literally a model of the subjective experience itself. We argue that this metatheoretical framework provides a solid basis for the empirical study of consciousness.