Time underlies many interesting human behaviors. Thus, the question of how to represent time in connectionist models is very important. One approach is to represent time implicitly by its effects on processing rather than explicitly (as in a spatial representation). The current report develops a proposal along these lines first described by Jordan (1986) which involves the use of recurrent links in order to provide networks with a dynamic memory. In this approach, hidden unit patterns are fed back to themselves: (...) the internal representations which develop thus reflect task demands in the context of prior internal states. A set of simulations is reported which range from relatively simple problems (temporal version of XOR) to discovering syntactic/semantic features for words. The networks are able to learn interesting internal representations which incorporate task demands with memory demands: indeed, in this approach the notion of memory is inextricably bound up with task processing. These representations reveal a rich structure, which allows them to be highly context‐dependent, while also expressing generalizations across classes of items. These representations suggest a method for representing lexical categories and the type/token distinction. (shrink)

It is widely assumed that human learning and the structure of human languages are intimately related. This relationship is frequently suggested to derive from a language-specific biological endowment, which encodes universal, but communicatively arbitrary, principles of language structure (a Universal Grammar or UG). How might such a UG have evolved? We argue that UG could not have arisen either by biological adaptation or non-adaptationist genetic processes, resulting in a logical problem of language evolution. Specifically, as the processes of language change (...) are much more rapid than processes of genetic change, language constitutes a both over time and across different human populations, and, hence, cannot provide a stable environment to which language genes could have adapted. We conclude that a biologically determined UG is not evolutionarily viable. Instead, the original motivation for UG arises because language has been shaped to fit the human brain, rather than vice versa. Following Darwin, we view language itself as a complex and interdependent which evolves under selectional pressures from human learning and processing mechanisms. That is, languages themselves are shaped by severe selectional pressure from each generation of language users and learners. This suggests that apparently arbitrary aspects of linguistic structure may result from general learning and processing biases deriving from the structure of thought processes, perceptuo-motor factors, cognitive limitations, and pragmatics. (shrink)

Originally a keynote address at the International Society for Research on Emotion (ISRE) 2013 convention, this article surveys many nonobvious ways that emotion phenomena show up in natural language. One conclusion is that no classical Aristotelian definition of “emotion” in terms of necessary and sufficient conditions is possible. The brain naturally creates radial, not classical categories. As a result, “emotion” is a contested concept. There is no one correct, classical definition of “emotion.” There are real emotion phenomena that can be (...) precisely studied, and language is an important area to look at for such phenomena. (shrink)

Wilson et al. focus on one class of AGL tasks: the cognitively demanding task of detecting non‐adjacent dependencies (NADs) among items. They provide a typology of the different types of NADs in natural languages and in AGL tasks. A range of cues affect NAD learning, ranging from the variability and number of intervening elements to the presence of shared prosodic cues between the dependent items. These cues, important for humans to discover non‐adjacent dependencies, are also found to facilitate NAD learning (...) in several nonhuman animal species. (shrink)

Human development takes place in a social context. Two pervasive sources of social information are faces and hands. Here, we provide the first report of the visual frequency of faces and hands in the everyday scenes available to infants. These scenes were collected by having infants wear head cameras during unconstrained everyday activities. Our corpus of 143 hours of infant-perspective scenes, collected from 34 infants aged 1 month to 2 years, was sampled for analysis at 1/5 Hz. The major finding (...) from this corpus is that the faces and hands of social partners are not equally available throughout the first two years of life. Instead, there is an earlier period of dense face input and a later period of dense hand input. At all ages, hands in these scenes were primarily in contact with objects and the spatio-temporal co-occurrence of hands and faces was greater than expected by chance. The orderliness of the shift from faces to hands suggests a principled transition in the contents of visual experiences and is discussed in terms of the role of developmental gates on the timing and statistics of visual experiences. (shrink)

Improbable events are surprising. However, it is unknown whether children consider probability when attributing surprise to other people. We conducted four experiments that investigate this issue. In the first three experiments, children saw stories in which two characters received a red gumball from two gumball machines with different distributions, and children then judged which character was more surprised. Experiment 1 shows development in children’s use of probability to infer surprise. Children aged 7 correctly inferred that the character with a lower (...) chance of getting a red gumball would be more surprised, but 4- to 6-year-olds did not. Experiment 2 shows that children’s performance does not improve when the probability of getting a red gumball is zero and should be maximally surprising. Experiment 3 demonstrates that 6-year-olds’ performance improves when they are prompted to consider probabilities, but not when they are prompted to consider the characters’ beliefs. Experiment 4 replicates this finding, but using a new design in which children attributed emotions to just a single character. Together these findings suggest that by age 6, a conceptual shift occurs, in which children begin to integrate their understanding of probability with their understanding of surprise. 2018 APA, all rights reserved). (shrink)

Memory is fleeting. New material rapidly obliterates previous material. How, then, can the brain deal successfully with the continual deluge of linguistic input? We argue that, to deal with this “Now-or-Never” bottleneck, the brain must compress and recode linguistic input as rapidly as possible. This observation has strong implications for the nature of language processing: (1) the language system must “eagerly” recode and compress linguistic input; (2) as the bottleneck recurs at each new representational level, the language system must build (...) a multilevel linguistic representation; and (3) the language system must deploy all available information predictively to ensure that local linguistic ambiguities are dealt with “Right-First-Time”; once the original input is lost, there is no way for the language system to recover. This is “Chunk-and-Pass” processing. Similarly, language learning must also occur in the here and now, which implies that language acquisition is learning to process, rather than inducing, a grammar. Moreover, this perspective provides a cognitive foundation for grammaticalization and other aspects of language change. Chunk-and-Pass processing also helps explain a variety of core properties of language, including its multilevel representational structure and duality of patterning. This approach promises to create a direct relationship between psycholinguistics and linguistic theory. More generally, we outline a framework within which to integrate often disconnected inquiries into language processing, language acquisition, and language change and evolution. (shrink)

The author argues that the so-called “basic emotions”, such as happiness, fear or anger, are in fact cultural artifacts of the English language, just as the Ilongot concept of liget, or the Ifaluk concept of song, are the cultural artifacts of Ilongot and Ifaluk. It is therefore as inappropriate to talk about human emotions in general in terms of happiness, fear, or anger as it would be to talk about them in terms of liget or song. However, this does not (...) mean that we cannot penetrate into the emotional world of speakers of languages other than our own. Nor does it mean that there cannot be any universal human emotions. Universality of emotions is an open issue which requires further investigation. For this further investigation to be fully productive, it has to be undertaken from a universal, language and culture-independent perspective; and it has to be carried out in a universalist framework that is language and culture-independent. The author proposes for this purpose the “natural semantic metalanguage” based on universal (or near-universal) semantic primitives (or near-primitives), developed over two decades by herself and colleagues, and she argues that the use of this metalanguage facilitates such a perspective and offers such a framework. (shrink)

An ongoing debate in affective science concerns whether certain discrete, “basic” emotions have evolutionarily based signals that are easily, universally, and innatel...

The process by which emotion concepts are learned is largely unexplored. Hoemann, Devlin, and Barrett and Shablack, Stein, and Lindquist argue that emotion concepts are learned throug...

Wilson et al. focus on one class of AGL tasks: the cognitively demanding task of detecting non‐adjacent dependencies (NADs) among items. They provide a typology of the different types of NADs in natural languages and in AGL tasks. A range of cues affect NAD learning, ranging from the variability and number of intervening elements to the presence of shared prosodic cues between the dependent items. These cues, important for humans to discover non‐adjacent dependencies, are also found to facilitate NAD learning (...) in several nonhuman animal species. (shrink)