The AHA! experience: creativity through emergent binding in neural networks

Many kinds of creativity result from combination of mental representations. This paper provides a computational account of how creative thinking can arise from combining neural patterns into ones that are potentially novel and useful. We defend the hypothesis that such combinations arise from mechanisms that bind together neural activity by a process of convolution, a mathematical operation that interweaves structures. We describe computer simulations that show the feasibility of using convolution to produce emergent patterns of neural activity that can support cognitive and emotional processes underlying human creativity.     

Towards a computational theory of experience

A standing challenge for the science of mind is to account for the datum that every mind faces in the most immediate – that is, unmediated – fashion: its phenomenal experience. The complementary tasks of explaining what it means for a system to give rise to experience and what constitutes the content of experience (qualia) in computational terms are particularly challenging, given the multiple realizability of computation. In this paper, we identify a set of conditions that a computational theory must satisfy for it to constitute not just a sufficient but a necessary, and therefore naturalistic and intrinsic, explanation of qualia. We show that a common assumption behind many neurocomputational theories of the mind, according to which mind states can be formalized solely in terms of instantaneous vectors of activities of representational units such as neurons, does not meet the requisite conditions, in part because it relies on inactive units to shape presently experienced qualia and implies a homogeneous representation space, which is devoid of intrinsic structure. We then sketch a naturalistic computational theory of qualia, which posits that experience is realized by dynamical activity-space trajectories (rather than points) and that its richness is measured by the representational capacity of the trajectory space in which it unfolds.     

Thinking about representations: the case of opaque contexts

To address the question of whether young children are differentially sensitive to referential opacity, an advanced Theory of Mind skill, we assessed 4-, 6-, and 8-year-olds on three types of opaque contexts: epistemic, quotational, and intentional. Children’s performance improved as a function of age and varied significantly by opacity type. Performance was best for epistemic opacity (using the verb “know”) and poorest for intentional opacity (using “mean to”), with quotational opacity (using “said”) falling in-between. Importantly, the current results suggest that children’s sensitivity to referential opacity is not an all-or-nothing competence but rather one that varies across the contexts examined. Possible reasons for this variability are discussed.     

疼痛条件下时间目标对时距估计的影响

本研究采用冷压任务引发疼痛,以健康大学生为被试,试图探讨在疼痛条件下时间目标对时距估计的影响。结果发现：疼痛条件下的时距估计值小于非疼痛条件下时距估计值,疼痛条件下具体时间目标的时距估计值显著大于无目标时距估计值。临床上给患者提供具体的时间目标或许有助于他们应对疼痛。     

Violations of coherence in subjective probability: a representational and assessment processes account

Coherent judgment is a cardinal feature of rational cognition. Six experiments revealed systematic violations of coherence in probability judgment in which participants assigned different probabilities to mathematically equiprobable events. Experiments 1-5 revealed a strict refocusing effect: Compared to an occurrence frame, a non-occurrence frame resulted in higher estimates if base-rate evidence favored occurrence, lower estimates if evidence favored non-occurrence, and similar estimates if evidence supported indifference. Moreover, Experiments 5 and 6 revealed a pessimistic bias in which the less favorable of two equiprobable events was assigned greater probability. The findings support a Representational and Assessment Processes account (RAP) in which subjective probability is influenced by the perceived compatibility between representations of focal events and representations of evidence.     

Formal distinctiveness of high- and low-imageability nouns: analyses and theoretical implications

Words associated with perceptually salient, highly imageable concepts are learned earlier in life, more accurately recalled, and more rapidly named than abstract words (R. W. Brown, 1976; Walker & Hulme, 1999). Theories accounting for this concreteness effect have focused exclusively on semantic properties of word referents. A novel possibility is that word structure may also contribute to the effect. We report a corpus-based analysis of the phonological and morphological structures of a large set of nouns with imageability ratings (N = 2,023). High- and low-imageability nouns differed by length, etymology, prosody, affixation, phonological neighborhood density, and rates of consonant clustering. On average, nouns denoting abstract concepts were longer, more derivationally complex, and emerged in English from a different distribution of languages than did concrete nouns. We address implications for interactivity of word form and meaning as pertain to theories of word concreteness, lexical acquisition, and word processing.     

A cross-order integration hypothesis for the neural correlate of consciousness

One major problem many hypotheses regarding the neural correlate of consciousness (NCC), face is what we might call "the why question": why would this particular neural feature, rather than another, correlate with consciousness? The purpose of the present paper is to develop an NCC hypothesis that answers this question. The proposed hypothesis is inspired by the cross-order integration (COI) theory of consciousness, according to which consciousness arises from the functional integration of a first-order representation of an external stimulus and a second-order representation of that first-order representation. The proposal comes in two steps. The first step concerns the "general shape" of the NCC and can be directly derived from COI theory. The second step is a concrete hypothesis that can be arrived at by combining the general shape with empirical considerations.     

Interactivism: A manifesto

The interactivist model has grown over the last several decades from a narrower initial beginning into an evolving systematic theory and underlying philosophy. It has been induced to do so because the underlying assumptions that framed the beginnings of the model were fundamentally different from those that are dominant throughout psychology, cognitive science, and philosophy. Consequently, the model faced multiple instances of attempting to integrate with literature in neighboring fields, discovering that such integration was not possible because the basic assumptions were not compatible, and having to either give up on the model thus far constructed, or else extend it in a way consistent with those assumptions into those neighboring (and foundational) domains. This manifesto outlines the resultant interactivist framework, presents some of the arguments for its underlying assumptions, and argues that these avoid problems that are fatal for many standard approaches in the literature.     

Gandhi,secularism and social capital in modern India

The partition of the Indian subcontinent in 1947 was witness to Hindu Muslim conflict at its peak. In the 1990s, ethnic conflict was used by right wing ideologues to change the fabric of secular India. Using interview data and within a social representational framework the study demonstrates the processes whereby out-groups/in-groups are formed. Further, it is argued that religious tolerance as envisaged in Gandhian philosophy, needs to be an integral part of the debate on role of religion in the public sphere.     

The role of representation in computation

Reformers urge that representation no longer earns its explanatory keep in cognitive science, and that it is time to discard this troublesome concept. In contrast, we hold that without representation cognitive science is utterly bereft of tools for explaining natural intelligence. In order to defend the latter position, we focus on the explanatory role of representation in computation. We examine how the methods of digital and analog computation are used to model a relatively simple target system, and show that representation plays an in-eliminable explanatory role in both cases. We conclude that, to the extent that biologic systems engage in computation, representation is destined to play an explanatory role in cognitive science.