Inner-ear abnormalities and their functional consequences in Belgian Waterslager canaries (Serinus canarius)

Recent reports of elevated auditory thresholds in canaries of the Belgian Waterslager strain have shown that this strain has an inherited auditory deficit in which absolute auditory thresholds at high frequencies (i.e. above 2.0 kHz) are as much as 40 dB less sensitive than the thresholds of mixed-breed canaries and those of other strains. The measurement of CAP audiograms showed that the hearing deficit is already present at the level of the auditory nerve (Gleich and Dooling, 1992). Here we show gross abnormalities in the anatomy of the basilar papilla of Belgian Waterslager canaries at the level of the hair cell. The extent of these abnormalities was correlated with the amount of hearing deficit as measured behaviorally

Children’s Learning of a Semantics-Free Artificial Grammar with Center Embedding

Whether non-human animals have an ability to learn and process center embedding, a core property of human language syntax, is still debated. Artificial-grammar learning (AGL) has been used to compare humans and animals in the learning of center embedding. However, up until now, human participants have only included adults, and data on children, who are the key players of natural language acquisition, are lacking. We created a novel game-like experimental paradigm combining the go/no-go procedure often used in animal research with the stepwise learning methods found effective in human adults’ center-embedding learning. Here we report that some children succeeded in learning a semantics-free artificial grammar with center embedding (A2B2 grammar) in the auditory modality. Although their success rate was lower than adults’, the successful children looked as efficient learners as adults. Where children struggled, their memory capacity seemed to have limited their AGL performance

The Non-Hierarchical Nature of the Chomsky Hierarchy-Driven Artificial-Grammar Learning

Recent artificial-grammar learning (AGL) paradigms driven by the Chomsky hierarchy paved the way for direct comparisons between humans and animals in the learning of center embedding ([A[AB]B]). The AnBn grammars used by the first generation of such research lacked a crucial property of center embedding, where the pairs of elements are explicitly matched ([A1 [A2 B2] B1]). This type of indexing is implemented in the second-generation AnBn grammars. This paper reviews recent studies using such grammars. Against the premises of these studies, we argue that even those newer AnBn grammars cannot test the learning of syntactic hierarchy. These studies nonetheless provide detailed information about the conditions under which human adults can learn an AnBn grammar with indexing. This knowledge serves to interpret recent animal studies, which make surprising claims about animals’ ability to handle center embedding

Synchronized tapping facilitates learning sound sequences as indexed by the P300

The purpose of the present study was to determine whether and how single finger tapping in synchrony with sound sequences contributed to the auditory processing of them. The participants learned two unfamiliar sound sequences via different methods. In the tapping condition, they learned an auditory sequence while they tapped in synchrony with each sound onset. In the no tapping condition, they learned another sequence while they kept pressing a key until the sequence ended. After these learning sessions, we presented the two melodies again and recorded event-related potentials (ERPs). During the ERP recordings, 10% of the tones within each melody deviated from the original tones. An analysis of the grand average ERPs showed that deviant stimuli elicited a significant P300 in the tapping but not in the no-tapping condition. In addition, the significance of the P300 effect in the tapping condition increased as the participants showed highly synchronized tapping behavior during the learning sessions. These results indicated that single finger tapping promoted the conscious detection and evaluation of deviants within the learned sequences. The effect was related to individuals’ musical ability to coordinate their finger movements along with external auditory events

Complex sequencing rules of birdsong can be explained by simple hidden Markov processes

Complex sequencing rules observed in birdsongs provide an opportunity to investigate the neural mechanism for generating complex sequential behaviors. To relate the findings from studying birdsongs to other sequential behaviors, it is crucial to characterize the statistical properties of the sequencing rules in birdsongs. However, the properties of the sequencing rules in birdsongs have not yet been fully addressed. In this study, we investigate the statistical propertiesof the complex birdsong of the Bengalese finch (Lonchura striata var. domestica). Based on manual-annotated syllable sequences, we first show that there are significant higher-order context dependencies in Bengalese finch songs, that is, which syllable appears next depends on more than one previous syllable. This property is shared with other complex sequential behaviors. We then analyze acoustic features of the song and show that higher-order context dependencies can be explained using first-order hidden state transition dynamics with redundant hidden states. This model corresponds to hidden Markov models (HMMs), well known statistical models with a large range of application for time series modeling. The song annotation with these models with first-order hidden state dynamics agreed well with manual annotation, the score was comparable to that of a second-order HMM, and surpassed the zeroth-order model (the Gaussian mixture model (GMM)), which does not use context information. Our results imply that the hierarchical representation with hidden state dynamics may underlie the neural implementation for generating complex sequences with higher-order dependencies

Measuring context dependency in birdsong using artificial neural networks

Context dependency is a key feature in sequential structures of human language, which requires reference between words far apart in the produced sequence. Assessing how long the past context has an effect on the current status provides crucial information to understand the mechanism for complex sequential behaviors. Birdsongs serve as a representative model for studying the context dependency in sequential signals produced by non-human animals, while previous reports were upper-bounded by methodological limitations. Here, we newly estimated the context dependency in birdsongs in a more scalable way using a modern neural-network-based language model whose accessible context length is sufficiently long. The detected context dependency was beyond the order of traditional Markovian models of birdsong, but was consistent with previous experimental investigations. We also studied the relation between the assumed/auto-detected vocabulary size of birdsong (i.e., fine- vs. coarse-grained syllable classifications) and the context dependency. It turned out that the larger vocabulary (or the more fine-grained classification) is assumed, the shorter context dependency is detected

The integration hypothesis of human language evolution and the nature of contemporary languages

How human language arose is a mystery in the evolution of Homo sapiens. Miyagawa et al. (2013) put forward a proposal, which we will call the Integration Hypothesis of human language evolution, that holds that human language is composed of two components, E for expressive, and L for lexical. Each component has an antecedent in nature: E as found, for example, in birdsong, and L in, for example, the alarm calls of monkeys. E and L integrated uniquely in humans to give rise to language. A challenge to the Integration Hypothesis is that while these non-human systems are finite-state in nature, human language is known to require characterization by a non-finite state grammar. Our claim is that E and L, taken separately, are in fact finite-state; when a grammatical process crosses the boundary between E and L, it gives rise to the non-finite state character of human language. We provide empirical evidence for the Integration Hypothesis by showing that certain processes found in contemporary languages that have been characterized as non-finite state in nature can in fact be shown to be finite-state. We also speculate on how human language actually arose in evolution through the lens of the Integration Hypothesis

Parvovirus-derived endogenous viral elements in two South American rodent genomes

We describe endogenous viral elements (EVEs) derived from parvoviruses (family <i>Parvoviridae</i>) in the long-tailed chinchilla (<i>Chinchilla lanigera</i>) and degu (<i>Octodon degus</i>) genomes. The novel EVEs include Dependovirus-related elements, and representatives of a clearly distinct parvovirus lineage that also has endogenous representatives in marsupial genomes. In the degu, one dependovirus-derived EVEs was found to encode an intact reading frame, and was differentially expressed <i>in vivo</i>, with increased expression in the liver