Infants segment words from songs - an EEG study

Children’s songs are omnipresent and highly attractive stimuli in infants’ input. Previous work suggests that infants process linguistic–phonetic information from simplified sung melodies. The present study investigated whether infants learn words from ecologically valid children’s songs. Testing 40 Dutch-learning 10-month-olds in a familiarization-then-test electroencephalography (EEG) paradigm, this study asked whether infants can segment repeated target words embedded in songs during familiarization and subsequently recognize those words in continuous speech in the test phase. To replicate previous speech work and compare segmentation across modalities, infants participated in both song and speech sessions. Results showed a positive event-related potential (ERP) familiarity effect to the final compared to the first target occurrences during both song and speech familiarization. No evidence was found for word recognition in the test phase following either song or speech. Comparisons across the stimuli of the present and a comparable previous study suggested that acoustic prominence and speech rate may have contributed to the polarity of the ERP familiarity effect and its absence in the test phase. Overall, the present study provides evidence that 10-month-old infants can segment words embedded in songs, and it raises questions about the acoustic and other factors that enable or hinder infant word segmentation from songs and speech

Infants’ implicit rhyme perception in child songs and its relationship with vocabulary

Rhyme perception is an important predictor for future literacy. Assessing rhyme abilities, however, commonly requires children to make explicit rhyme judgements on single words. Here we explored whether infants already implicitly process rhymes in natural rhyming contexts (child songs) and whether this response correlates with later vocabulary size. In a passive listening ERP study, 10.5 month-old Dutch infants were exposed to rhyming and non-rhyming child songs. Two types of rhyme effects were analysed: (1) ERPs elicited by the first rhyme occurring in each song (rhyme sensitivity) and (2) ERPs elicited by rhymes repeating after the first rhyme in each song (rhyme repetition). Only for the latter a tentative negativity for rhymes from 0 to 200 ms after the onset of the rhyme word was found. This rhyme repetition effect correlated with productive vocabulary at 18 months-old, but not with any other vocabulary measure (perception at 10.5 or 18 months-old). While awaiting future replication, the study indicates precursors of phonological awareness already during infancy and with ecologically valid linguistic stimuli

Infants' sensitivity to rhyme in songs

Children’s songs often contain rhyming words at phrase endings. In this study, we investigated whether infants can already recognize this phonological pattern in songs. Earlier studies using lists of spoken words were equivocal on infants’ spontaneous processing of rhymes (Hayes, Slater, & Brown, 2000; Jusczyk, Goodman, & Baumann, 1999). Songs, however, constitute an ecologically valid rhyming stimulus, which could allow for spontaneous processing of this phonological pattern in infants. Novel children’s songs with rhyming and non-rhyming lyrics using pseudo-words were presented to 35 9-month-old Dutch infants using the Headturn Preference Procedure. Infants on average listened longer to the non-rhyming songs, with around half of the infants however exhibiting a preference for the rhyming songs. These results highlight that infants have the processing abilities to benefit from their natural rhyming input for the development of their phonological abilities

Controlling the uncontrolled: Are there incidental experimenter effects on physiologic responding?

The degree to which experimenters shape participant behavior has long been of interest in experimental social science research. Here, we extend this question to the domain of peripheral psychophysiology, where experimenters often have direct, physical contact with participants, yet researchers do not consistently test for their influence. We describe analytic tools for examining experimenter effects in peripheral physiology. Using these tools, we investigate nine data sets totaling 1,341 participants and 160 experimenters across different roles (e.g., lead research assistants, evaluators, confederates) to demonstrate how researchers can test for experimenter effects in participant autonomic nervous system activity during baseline recordings and reactivity to study tasks. Our results showed (a) little to no significant variance in participants' physiological reactivity due to their experimenters, and (b) little to no evidence that three characteristics of experimenters that are well known to shape interpersonal interactions-status (using five studies with 682 total participants), gender (using two studies with 359 total participants), and race (in two studies with 554 total participants)-influenced participants' physiology. We highlight several reasons that experimenter effects in physiological data are still cause for concern, including the fact that experimenters in these studies were already restricted on a number of characteristics (e.g., age, education). We present recommendations for examining and reducing experimenter effects in physiological data and discuss implications for replication

Extended h-Index Parameterized Data Structures for Computing Dynamic Subgraph Statistics

We present techniques for maintaining subgraph frequencies in a dynamic graph, using data structures that are parameterized in terms of h, the h-index of the graph. Our methods extend previous results of Eppstein and Spiro for maintaining statistics for undirected subgraphs of size three to directed subgraphs and to subgraphs of size four. For the directed case, we provide a data structure to maintain counts for all 3-vertex induced subgraphs in O(h) amortized time per update. For the undirected case, we maintain the counts of size-four subgraphs in O(h^2) amortized time per update. These extensions enable a number of new applications in Bioinformatics and Social Networking research

The statistical mechanics of networks

We study the family of network models derived by requiring the expected properties of a graph ensemble to match a given set of measurements of a real-world network, while maximizing the entropy of the ensemble. Models of this type play the same role in the study of networks as is played by the Boltzmann distribution in classical statistical mechanics; they offer the best prediction of network properties subject to the constraints imposed by a given set of observations. We give exact solutions of models within this class that incorporate arbitrary degree distributions and arbitrary but independent edge probabilities. We also discuss some more complex examples with correlated edges that can be solved approximately or exactly by adapting various familiar methods, including mean-field theory, perturbation theory, and saddle-point expansions.Comment: 15 pages, 4 figure

Employment insecurity and life satisfaction: The moderating influence of labour market policies across Europe

This article tests whether the link between employment insecurity and life satisfaction is moderated by the generosity of labour market policies across Europe. Employment insecurity provokes anxieties about (a) the difficulties of finding a new job and (b) alternative sources of non-work income. These components can be related to active and passive labour market policies, respectively. Generous policy support is thus expected to buffer the negative consequences of employment insecurity by lowering the perceived difficulty of finding a similar job or providing income maintenance during unemployment. Based on data for 22 countries from the 2010 European Social Survey, initial support for this hypothesis is found. Perceived employment insecurity is negatively associated with life satisfaction but the strength of the relationship is inversely related to the generosity of labour market policies. Employment insecurity, in other words, is more harmful in countries where labour market policies are less generous

Short-term efficacy and usage recommendations for a large-scale implementation of the math-whizz tutor

This paper adds to the evidence of the efficacy of intelligent tutoring systems (ITS) in mathematics learning by evaluating a large-scale intervention at the state of Aguascalientes, Mexico. We report the results of a quasi-experimental study, addressing at the same a particular request of the decision-makers responsible for the rollout to provide, from early stages of the intervention, independent evidence of the efficacy of Math-Whizz Tutor beyond its internal metrics, and recommendations in terms of the expected weekly usage levels to guide the blended learning approach

Solution of the 2-star model of a network

The p-star model or exponential random graph is among the oldest and best-known of network models. Here we give an analytic solution for the particular case of the 2-star model, which is one of the most fundamental of exponential random graphs. We derive expressions for a number of quantities of interest in the model and show that the degenerate region of the parameter space observed in computer simulations is a spontaneously symmetry broken phase separated from the normal phase of the model by a conventional continuous phase transition.Comment: 5 pages, 3 figure