Intangible features extraction in the processing of abstract concepts: Evidence from picture-word priming

Over the last decade, hypotheses ranging from linguistic symbol processing to embodiment have been formulated to account for the content and mechanisms responsible for the representation of abstract concepts. Results of recent studies have suggested that abstract concepts, just like concrete ones, can benefit from knowledge of real-world situational context, but that they can also be processed based on abstract pictures devoid of such situational features. This paper presents two semantic priming experiments to explore such mechanisms further. The first experiment replicates Kuipers, Jones, and Thierry (2018) in a cross-linguistic setting which shows that abstract concepts can be processed from abstract pictures devoid of tangible features. In the second experiment, we studied extraction mechanisms that come into play when participants are presented with abstract and concrete pictures that provide situational information to illustrate target abstract concepts. We expected this facilitatory effect to be limited to concrete picture primes. Our data analysed with both Bayesian and Frequentist tests showed however that even when presented with tangible situational information, the extraction of features still occurred for abstract pictures. We discuss the implications of this with respect to future avenues for studying the processing of abstract concepts.

Exploring the symbol processing ‘time interval’ parametric constraint in a Belousov–Zhabotinsky operated chemical Turing machine

Chemical reactions are powerful molecular recognition machines.

A SUFISM PSYCHOLOGICAL ANALYSIS OF ISMᾹ’ÎL’S INTRAPERSONAL COMMUNICATION IN SURAH AL-SᾹFFᾹT [37]: 102

Dialogue between Ismā’îl and Ibrāhîm in Q.S. al-S{affāt [37]: 102, is not only focused on the polemic of the determination about child referred in the verse. Likewise, the discussion about this verse is not only abaout ideal model of education for children. Another discussion no less interesting is regarding the response of the Ismā'îl when listening to the slaughtering order from Ibra>hi>m. Although there is no indication in the verse that reffer to communicative process in Ismā'îl to response that command. But in the context of communication, the reception of the message conveyed, allows him to respond the message. To provide a response, symbol processing is needed. So that it can provide an appropriate response. Therefore, to find this process, this study uses a text analysis method with a Sufi Psychological approach. By using these methods and approaches, this study concludes that intrapersonal communication in Ismā’îl involves self-entities consisting of al-rûh}, al-‘aql, and al-qalb. These three entities have their respective concepts of knowledge which clarify one another. In Ismā’îl, the concept of reason knowledge gained from his experiences gives confidence to the truth of the command. Likewise, the maturity of the soul makes it easy for the heart to gain intuitive knowledge that is affirmed by reason, giving rise to an acceptance response to the order.

Same-different judgments with alphabetic characters: The case of literal symbol processing

Learning mathematics requires fluency with symbols that convey numerical magnitude. Algebra and higher-level mathematics involve literal symbols, such as "x", that often represent numerical magnitude. Compared to other symbols, such as Arabic numerals, literal symbols may require more complex processing because they have strong pre-existing associations in literacy. The present study tested this notion using same-different tasks that produce less efficient judgments for different magnitudes that are closer together compared to farther apart (i.e., same-different distance effects). Twenty-four adolescents completed three same-different tasks using Arabic numerals, literal symbols, and artificial symbols. All three symbolic formats produced same-different distance effects, showing literal and artificial symbol processing of numerical magnitude. Importantly, judgments took longer for literal symbols than artificial symbols on average, suggesting a cost specific to literal symbol processing. Taken together, results suggest that literal symbol processing differs from processing of other symbols that represent numerical magnitude.

Same-Different Judgments with Alphabetic Characters: The Case of Literal Symbol Processing

Learning mathematics requires fluency with symbols that convey numerical magnitude. Algebra and higher-level mathematics involve literal symbols, such as "x", that often represent numerical magnitude. Compared to other symbols, such as Arabic numerals, literal symbols may require more complex processing because they have strong pre-existing associations in literacy. The present study tested this notion using same-different tasks that produce less efficient judgments for different magnitudes that are closer together compared to farther apart (i.e., same-different distance effects). Twenty-four adolescents completed three same-different tasks using Arabic numerals, literal symbols, and artificial symbols. All three symbolic formats produced same-different distance effects, showing literal and artificial symbol processing of numerical magnitude. Importantly, judgments took longer for literal symbols than artificial symbols on average, suggesting a cost specific to literal symbol processing. Taken together, results suggest that literal symbol processing differs from processing of other symbols that represent numerical magnitude.

Levels of Explanation and Translation Expertise

The observable activity of translation, the series of text comprehension and text production bursts we identify as translation, is the result of the activation of complex underlying cognitive systems. In the conduct of research it is often useful to approach such complex systems using a ‘levels of explanation’ framework. This paper considers David Marr’s (1982) three levels of explanation as they might apply to understanding translation and translation expertise more robustly. In cognitive translation studies to date, we have not really extended our understanding of expertise much past the second (algorithmic/representational) level in Marr’s scheme; we have failed to grapple as effectively as we might with the problem of how the second generation computationalist expertise constructs we adopted almost twenty years ago could be integrated with, for instance, connectionist neural network models of the mind, creating a third generation of expertise models. This paper offers some frameworks laying out how that end might be achieved using, for instance, symbolic connectionism and implementational connectivism. Further, it argues that given the overtly symbolic nature of translation language processing, cognitively-oriented translation scholars are uniquely suited to benefit from approaches that bridge the divide between symbol processing models and connectionist ones.

Cognition is Embodied

With the motivation to develop computational and algorithmic levels of understanding how the mind comes into being, this chapter considers computer science, artificial intelligence, and cognitive systems perspectives. Questions are addressed, such as what ‘intelligence’ may actually be and how, and when an artificial system may be considered to be intelligent and to have a mind on its own. May it even be alive? Out of these considerations, the chapter derives three fundamental problems for cognitive systems: the symbol grounding problem, the frame problem, and the binding problem. We show that symbol-processing artificial systems cannot solve these problems satisfactorily. Neural networks and embodied systems offer alternatives. Moreover, biological observations and studies with embodied robotic systems imply that behavioral capabilities can foster and facilitate the development of suitably abstracted, symbolic structures. We finally consider Alan Turing’s question “Can machines think?” and emphasize that such machines must at least solve the three considered fundamental cognitive systems problems. The rest of the book addresses how the human brain, equipped with a suitably-structured body and body–brain interface, manages to solve these problems, and thus manages to develop a mind.