Taking Synchrony Seriously: A Perceptual-Level Model of Infant Synchrony Detection

Synchrony detection between different sensory and/or motor channels appears critically important for young infant learning and cognitive development. For example, empirical studies demonstrate that audio-visual synchrony aids in language acquisition. In this paper we compare these infant studies with a model of synchrony detection based on the Hershey and Movellan (2000) algorithm augmented with methods for quantitative synchrony estimation. Four infant-model comparisons are presented, using audio-visual stimuli of increasing complexity. While infants and the model showed learning or discrimination with each type of stimuli used, the model was most successful with stimuli comprised of one audio and one visual source, and also with two audio sources and a dynamic-face visual motion source. More difficult for the model were stimuli conditions with two motion sources, and more abstract visual dynamics—an oscilloscope instead of a face. Future research should model the developmental pathway of synchrony detection. Normal audio-visual synchrony detection in infants may be experience-dependent (e.g., Bergeson, et al., 2004)

Density and distinctiveness in early word learning:Evidence from neural network simulations

High phonological neighborhood density has been associated with both advantages and disadvantages in early word learning. High density may support the formation and fine-tuning of new word sound memories; a process termed lexical configuration (e.g. Storkel, 2004). However, new high-density words are also more likely to be misunderstood as instances of known words, and may therefore fail to trigger the learning process (e.g. Swingley & Aslin, 2007). To examine these apparently contradictory effects, we trained an autoencoder neural network on 587,954 word tokens (5497 types; including mono- and multi-syllabic words of all grammatical classes) spoken by 279 caregivers to English-speaking children aged 18 to 24 months. We then simulated a communicative development inventory administration and compared network performance to that of 2292 children aged 18 to 24 months. We argue that autoencoder performance illustrates concurrent density advantages and disadvantages, in contrast to prior behavioural and computational literature treating such effects independently. Low network error rates signal a configuration advantage for high-density words, while high network error rates signal a triggering advantage for low-density words. This interpretation is consistent with the application of autoencoders in academic research and industry, for simultaneous feature extraction (i.e. configuration) and anomaly detection (i.e. triggering). Autoencoder simulation therefore illustrates how apparently contradictory density and distinctiveness effects can emerge from a common learning mechanism

Culture, Embodiment and Genes: Unravelling the Triple Helix

Much recent work stresses the role of embodiment and action in thought and reason, and celebrates the power of transmitted cultural and environmental structures to transform the problem-solving activity required of individual brains. By apparent contrast, much work in evolutionary psychology has stressed the selective fit of the biological brain to an ancestral environment of evolutionary adaptedness, with an attendant stress upon the limitations and cognitive biases that result. On the face of it, this suggests either a tension or, at least, a mismatch, with the symbiotic dyad of cultural evolution and embodied cognition. In what follows, we explore this mismatch by focusing on three key ideas: cognitive niche construction; cognitive modularity; and the existence (or otherwise) of an evolved universal human nature. An appreciation of the power and scope of the first, combined with consequently more nuanced visions of the latter two, allow us to begin to glimpse a much richer vision of the combined interactive potency of biological and cultural evolution for active, embodied agents

Ortholog identification in the presence of domain architecture rearrangement

Ortholog identification is used in gene functional annotation, species phylogeny estimation, phylogenetic profile construction and many other analyses. Bioinformatics methods for ortholog identification are commonly based on pairwise protein sequence comparisons between whole genomes. Phylogenetic methods of ortholog identification have also been developed; these methods can be applied to protein data sets sharing a common domain architecture or which share a single functional domain but differ outside this region of homology. While promiscuous domains represent a challenge to all orthology prediction methods, overall structural similarity is highly correlated with proximity in a phylogenetic tree, conferring a degree of robustness to phylogenetic methods. In this article, we review the issues involved in orthology prediction when data sets include sequences with structurally heterogeneous domain architectures, with particular attention to automated methods designed for high-throughput application, and present a case study to illustrate the challenges in this area

Methods for Minimizing the Confounding Effects of Word Length in the Analysis of Phonotactic Probability and Neighborhood Density

This is the author's accepted manuscript. The original is available at http://jslhr.pubs.asha.org/article.aspx?articleid=1781521&resultClick=3Recent research suggests that phonotactic probability (the likelihood of occurrence of a sound sequence) and neighborhood density (the number of words phonologically similar to a given word) influence spoken language processing and acquisition across the lifespan in both normal and clinical populations. The majority of research in this area has tended to focus on controlled laboratory studies rather than naturalistic data such as spontaneous speech samples or elicited probes. One difficulty in applying current measures of phonotactic probability and neighborhood density to more naturalistic samples is the significant correlation between these variables and word length. This study examines several alternative transformations of phonotactic probability and neighborhood density as a means of reducing or eliminating this correlation with word length. Computational analyses of the words in a large database and reanalysis of archival data supported the use of z scores for the analysis of phonotactic probability as a continuous variable and the use of median transformation scores for the analysis of phonotactic probability as a dichotomous variable. Neighborhood density results were less clear with the conclusion that analysis of neighborhood density as a continuous variable warrants further investigation to differentiate the utility of z scores in comparison to median transformation scores. Furthermore, balanced dichotomous coding of neighborhood density was difficult to achieve, suggesting that analysis of neighborhood density as a dichotomous variable should be approached with caution. Recommendations for future application and analyses are discussed

Evolution of protein domain architectures

This chapter reviews current research on how protein domain architectures evolve. We begin by summarizing work on the phylogenetic distribution of proteins, as this will directly impact which domain architectures can be formed in different species. Studies relating domain family size to occurrence have shown that they generally follow power law distributions, both within genomes and larger evolutionary groups. These findings were subsequently extended to multi-domain architectures. Genome evolution models that have been suggested to explain the shape of these distributions are reviewed, as well as evidence for selective pressure to expand certain domain families more than others. Each domain has an intrinsic combinatorial propensity, and the effects of this have been studied using measures of domain versatility or promiscuity. Next, we study the principles of protein domain architecture evolution and how these have been inferred from distributions of extant domain arrangements. Following this, we review inferences of ancestral domain architecture and the conclusions concerning domain architecture evolution mechanisms that can be drawn from these. Finally, we examine whether all known cases of a given domain architecture can be assumed to have a single common origin (monophyly) or have evolved convergently (polyphyly). We end by a discussion of some available tools for computational analysis or exploitation of protein domain architectures and their evolution

Sound Symbolism Facilitates Word Learning in 14-Month-Olds

Sound symbolism, or the nonarbitrary link between linguistic sound and meaning, has often been discussed in connection with language evolution, where the oral imitation of external events links phonetic forms with their referents (e.g., Ramachandran & Hubbard, 2001). In this research, we explore whether sound symbolism may also facilitate synchronic language learning in human infants. Sound symbolism may be a useful cue particularly at the earliest developmental stages of word learning, because it potentially provides a way of bootstrapping word meaning from perceptual information. Using an associative word learning paradigm, we demonstrated that 14-month-old infants could detect Köhler-type (1947) shape-sound symbolism, and could use this sensitivity in their effort to establish a wordreferent association

Electrophysiological evidence for the understanding of maternal speech by 9-month-old infants

Early word learning in infants relies on statistical, prosodic, and social cues that support speech segmentation and the attachment of meaning to words. It is debated whether such early word knowledge represents mere associations between sound patterns and visual object features, or reflects referential understanding of words. By measuring an event-related brain potential component known as the N400, we demonstrated that 9-month-old infants can detect the mismatch between an object appearing from behind an occluder and a preceding label with which their mother introduces it. Differential N400 amplitudes have been shown to reflect semantic priming in adults, and its absence in infants has been interpreted as a sign of associative word learning. By setting up a live communicative situation for referring to objects, we demonstrated that a similar priming effect also occurs in young infants. This finding may indicate that word meaning is referential from the outset of word learning and that referential expectation drives, rather than results from, vocabulary acquisition in humans

One-year-old infants appreciate the referential nature of deictic gestures and words

One-year-old infants have a small receptive vocabulary and follow deictic gestures, but it is still debated whether they appreciate the referential nature of these signals. Demonstrating understanding of the complementary roles of symbolic (word) and indexical (pointing) reference provides evidence of referential interpretation of communicative signals. We presented 13-month-old infants with video sequences of an actress indicating the position of a hidden object while naming it. The infants looked longer when the named object was revealed not at the location indicated by the actress's gestures, but on the opposite side of the display. This finding suggests that infants expect that concurrently occurring communicative signals co-refer to the same object. Another group of infants, who were shown video sequences in which the naming and the deictic cues were provided concurrently but by two different people, displayed no evidence of expectation of co-reference. These findings suggest that a single communicative source, and not simply co-occurrence, is required for mapping the two signals onto each other. By 13 months of age, infants appreciate the referential nature of words and deictic gestures alike