Information processing theories in psychology give rise to executive theories of consciousness. Roughly speaking, these theories maintain that consciousness is a centralized processor that we use when processing novel or complex stimuli. The computational assumptions driving the executive theories are closely tied to the computer metaphor. However, those who take the metaphor serious — as I believe psychologists who advocate the executive theories do — end up accepting too particular a notion of a computing device. In this essay, I examine (...) the arguments from theoretical computational considerations that cognitive psychologists use to support their general approach in order to show that they make unwarranted assumptions about the processing attributes of consciousness. I then go on to examine the assumptions behind executive theories which grow out of the computer metaphor of cognitive psychology and conclude that we may not be the sort of computational machine cognitive psychology assumes and that cognitive psychology''s approach in itself does not buy us anything in developing theories of consciousness. Hence, the state space in which we may locate consciousness is vast, even within an information processing framework. (shrink)

Ethical decision-making research has centered on Rest’s framework that represents a rational, nonaffective model for ethical decision making. However, research in human cognition suggesting a “dual-processing” framework, composed of both rational and affective components, has been relatively ignored in the ethical decision-making literature. Examining dual-processing literature, it seems affect might be an important factor in decision making when a person’s mood is congruent with the task or situational context frame. Given that ethical decisions are serious and complex tasks, it is (...) proposed here that inducing a negative affective state might produce mood congruence, reinforce the salience of emotion for ethical decision makers, and lead to differences in decision processing. Evidence is presented documenting differences in the decisions made by ethical decision makers in a negative affective state as compared to those in either a positive or neutral affective state. (shrink)

Social responsibility is typically examined at the firm level, yet there are instances in which consumers’ social responsibility perceptions of the firm’s product brands differ from social responsibility perceptions with regard to the firm [i.e., corporate social responsibility ]. This article conceptualizes brand social responsibility and delineates it from CSR. Following the development of a BSR scale, this research demonstrates variations in consumers’ social responsibility perceptions across product brands even if they are owned by the same corporation and compete in (...) the same product category. BSR is distinct from CSR, and better predicts consumers’ responses to product brands compared to corporate level measures. Consistent with the conceptual distinction, this research demonstrates the unique contribution of BSR and CSR in predicting product brand and corporate outcomes, respectively. From a theoretical viewpoint, this research is one of the few to examine differences between product brand and CSR. From a managerial viewpoint, the consideration of social responsibility at the product brand level facilitates the assessment of social responsibility perceptions across brands in brand portfolios managed under a mixed-branding or house-of-brands strategy. (shrink)

Novice designers produced a sequence of sketches while inventing a logo for a novel brand of soft drink. The sketches were scored for the presence of specific objects, their local features and global composition. Self‐assessment scores for each sketch and art critics' scores for the end products were collected. It was investigated whether the design evolves in an essentially random fashion or according to an overall heuristic. The results indicated a macrostructure in the evolution of the design, characterized by two (...) stages. For the majority of participants, the first stage is marked by the introduction and modification of novel objects and their local and global aspects; the second stage is characterized by changes in their global composition. The minority that showed the better designs has a different strategy, in which most global changes were made in the beginning. Although participants did not consciously apply these strategies, their self‐assessment scores reflect the stages of the process. (shrink)

Recent literature reported that judgments of semantic coherence are influenced by a positive affective response due to increased fluency of processing. The presented paper investigates whether fluency of processing can be modified by affective responses to the coherent stimuli as well as an automaticity of processes involved in semantic coherence judgments. The studies employed the dyads of triads task in which participants are shown two word triads and asked to solve a semantically coherent one or indicate which of the two (...) is semantically coherent. Across two studies in a dualtask paradigm we show that a) attentional resources moderate insight into semantically coherent word triads, whereas b) judgments of semantic coherence judgments are independent of attentional resources. We discuss implications of our findings for how people might form intuitive judgments of semantic coherence. (shrink)

Previous behavioral studies have identified the significant role of subliminal cues in creative problem solving. However, neural mechanisms of such unconscious processing remain poorly understood. Here we utilized an event-related potential approach and sandwich mask technique to investigate cerebral activities underlying the unconscious processing of cues in creative problem solving. College students were instructed to solve divergent problems under three different conditions . Our data showed that creative problem solving can benefit from unconscious cues, although not as much as from (...) conscious cues. More importantly, we found that there are crucial ERP components associated with unconscious processing of cues in solving divergent problems. Similar to the processing of conscious cues, processing unconscious cues in problem solving involves the semantic activation of unconscious cues in the right inferior parietal lobule , new association formation in the right parahippocampal gyrus , and mental representation transformation in the right superior temporal gyrus . The present results suggest that creative problem solving can be modulated by unconscious processing of enlightening information that is weakly diffused in the semantic network beyond our conscious awareness. (shrink)

Research on cognitive processes has primarily focused on cognitive control and inhibitory processes to the detriment of other psychological processes, such as defense mechanisms, which can be used to modify aggressive impulses as well as self/other images during interpersonal conflicts. First, we conducted an in-depth theoretical analysis of three socio-cognitive models and three psychodynamic models and compared main propositions regarding the source of aggression and processes that influence its enactment. Second, 32 participants completed the Hostile Expectancy Violation Paradigm in which (...) scenarios describe a hostile vs. non-hostile social context followed by a character's ambiguous aversive behavior. The N400 effect to critical words that violate expected hostile vs. non-hostile intent of the behavior was analyzed. Prepotent response inhibition was measured using a Stop Signal task and DMs were assessed with the Defense Style Questionnaire. Results showed that reactive aggression and HIA were not significantly correlated with response inhibition but were significantly positively and negatively correlated with image distorting defense style and adaptive defense style, respectively. The present article has highlighted the importance of integrating socio-cognitive and psychodynamic models to account for the full complexity underlying psychological processes that influence reactive aggressive behavior. (shrink)

Topics in Cognitive Science, Volume 14, Issue 1, Page 163-188, January 2022.

Models of category learning have been extensively studied in cognitive science and primarily tested on perceptual abstractions or artificial stimuli. In this paper, we focus on categories acquired from natural language stimuli, that is, words. We present a Bayesian model that, unlike previous work, learns both categories and their features in a single process. We model category induction as two interrelated subproblems: the acquisition of features that discriminate among categories, and the grouping of concepts into categories based on those features. (...) Our model learns categories incrementally using particle filters, a sequential Monte Carlo method commonly used for approximate probabilistic inference that sequentially integrates newly observed data and can be viewed as a plausible mechanism for human learning. Experimental results show that our incremental learner obtains meaningful categories which yield a closer fit to behavioral data compared to related models while at the same time acquiring features which characterize the learned categories. (shrink)

Children tend to produce words earlier when they are connected to a variety of other words along the phonological and semantic dimensions. Though these semantic and phonological connectivity effects have been extensively documented, little is known about their underlying developmental mechanism. One possibility is that learning is driven by lexical network growth where highly connected words in the child's early lexicon enable learning of similar words. Another possibility is that learning is driven by highly connected words in the external learning (...) environment, instead of highly connected words in the early internal lexicon. The present study tests both scenarios systematically in both the phonological and semantic domains across 10 languages. We show that phonological and semantic connectivity in the learning environment drives growth in both production‐ and comprehension‐based vocabularies, even controlling for word frequency and length. This pattern of findings suggests a word learning process where children harness their statistical learning abilities to detect and learn highly connected words in the learning environment. (shrink)

One of the central issues in cognitive science is the nature of human representations. We argue that symbolic representations are essential for capturing human cognitive capabilities. We start by examining some common misconceptions found in discussions of representations and models. Next we examine evidence that symbolic representations are essential for capturing human cognitive capabilities, drawing on the analogy literature. Then we examine fundamental limitations of feature vectors and other distributed representations that, despite their recent successes on various practical problems, suggest (...) that they are insufficient to capture many aspects of human cognition. After that, we describe the implications for cognitive architecture of our view that analogy is central, and we speculate on roles for hybrid approaches. We close with an analogy that might help bridge the gap. (shrink)

Repetitive negative thinking (RNT) describes a recursive, unproductive pattern of thought that is commonly observed in individuals who experience anxiety and depression. Past research on RNT has primarily relied on self-report, which fails to capture the potential mechanisms that underlie the persistence of maladaptive thought. We investigated whether RNT may be maintained by a negatively biased semantic network. The present study used a modified free association task to assess state RNT. Following the presentation of a valenced (positive, neutral, negative) cue (...) word, participants generated a series of free associates, which allowed for the dynamic progression of responses. State RNT was conceptualised as the length of consecutive, negatively valenced free associates (i.e. chains). Participants also completed two self-report measures that assessed trait RNT and trait negative affect. Within a structural equation model, negative (but not positive or neutral) response chain length positively predicted trait RNT and negative affect, and this was only the case for positive (but not negative or neutral) cue words. These results suggest that RNT tendencies may be reflected in semantic retrieval and can be assessed without self-report. (shrink)

This paper presents a general computational treatment of how mammals are able to deal with visual objects and environments. The model tries to cover the entire range from behavior and phenomenological experience to detailed neural encodings in crude but computationally plausible reductive steps. The problems addressed include perceptual constancies, eye movements and the stable visual world, object descriptions, perceptual generalizations, and the representation of extrapersonal space.The entire development is based on an action-oriented notion of perception. The observer is assumed to (...) be continuously sampling the ambient light for information of current value. The central problem of vision is taken to be categorizing and locating objects in the environment. The critical step in this process is the linking of visual information to symbolic object descriptions; this is calledindexing, from the analogy of identifying a book from index terms. The system must also identifysituationsand use this knowledge to guide movement and other actions in the environment. The treatment focuses on the different representations of information used in the visual system.The four representational frames capture information in the following forms: retinotopic, head-based, symbolic, and allocentric. The functional roles of the four frames, the communication among them, and their suggested neurophysiological realization constitute the core of the paper. The model is perforce crude, but appears to be consistent with all relevant findings. (shrink)

Much of the progress in the fields constituting cognitive science has been based upon the use of explicit information processing models, almost exclusively patterned after conventional serial computers. An extension of these ideas to massively parallel, connectionist models appears to offer a number of advantages. After a preliminary discussion, this paper introduces a general connectionist model and considers how it might be used in cognitive science. Among the issues addressed are: stability and noise‐sensitivity, distributed decision‐making, time and sequence problems, and (...) the representation of complex concepts. (shrink)