Learning to Produce Syllabic Speech Sounds via Reward-Modulated Neural Plasticity

The relationship between nighttime exercise and problematic smartphone use before sleep and associated health issues: a cross-sectional study

OBJECTIVE

Physical exercise has the potential to mitigate addictive behaviors and relevant health issues. However, the nighttime exercise has not been studied regarding this research topic. This study aims to explore the association between nocturnal physical exercise and problematic smartphone use before sleep, as well as related health issues.

METHODS

To explore the association between nighttime physical exercise and problematic smartphone use before sleep as well as related health issues, we conducted a cross-sectional survey among 1,334 college students. Their daily exercise behaviors (including timeframe, rationale, frequency, and duration), smartphone use before sleep, sleep quality, smartphone addiction, anxiety, and depression were measured by questionnaires. The associations were assessed using generalized linear models.

RESULTS

Our findings indicate that nearly 70% of participants chose to perform exercise at nighttime. Among these individuals who exercised at nighttime, the frequency and duration of nighttime exercise were significantly associated with decreased probabilities of smartphone use before sleep. Additionally, the frequency and duration of nighttime exercise were associated with lower levels of smartphone addiction and anxiety disorders.

CONCLUSION

Nighttime Exercise behaviors can effectively reduce sleep delays caused by problematic smartphone use before bedtime. These findings contribute to understanding the potential effects of nighttime exercise on problematic smartphone use and relevant health issues. Future research should employ more precise methodologies to examine these associations.

From real-time adaptation to social learning in robot ecosystems

While evolutionary robotics can create novel morphologies and controllers that are well-adapted to their environments, learning is still the most efficient way to adapt to changes that occur on shorter time scales. Learning proposals for evolving robots to date have focused on new individuals either learning a controller from scratch, or building on the experience of direct ancestors and/or robots with similar configurations. Here we propose and demonstrate a novel means for social learning of gait patterns, based on sensorimotor synchronization. Using movement patterns of other robots as input can drive nonlinear decentralized controllers such as CPGs into new limit cycles, hence encouraging diversity of movement patterns. Stable autonomous controllers can then be locked in, which we demonstrate using a quasi-Hebbian feedback scheme. We propose that in an ecosystem of robots evolving in a heterogeneous environment, such a scheme may allow for the emergence of generalist task-solvers from a population of specialists.

Prediction of autism in infants: progress and challenges

Autism spectrum disorder (henceforth autism) is a neurodevelopmental condition that can be reliably diagnosed in children by age 18-24 months. Prospective longitudinal studies of infants aged 1 year and younger who are later diagnosed with autism are elucidating the early developmental course of autism and identifying ways of predicting autism before diagnosis is possible. Studies that use MRI, EEG, and near-infrared spectroscopy have identified differences in brain development in infants later diagnosed with autism compared with infants without autism. Retrospective studies of infants younger than 1 year who received a later diagnosis of autism have also showed an increased prevalence of health conditions, such as sleep disorders, gastrointestinal disorders, and vision problems. Behavioural features of infants later diagnosed with autism include differences in attention, vocalisations, gestures, affect, temperament, social engagement, sensory processing, and motor abilities. Although research findings offer insight on promising screening approaches for predicting autism in infants, individual-level predictions remain a future goal. Multiple scientific challenges and ethical questions remain to be addressed to translate research on early brain-based and behavioural predictors of autism into feasible and reliable screening tools for clinical practice.

On the Emergence of Phonological Knowledge and on Motor Planning and Motor Programming in a Developmental Model of Speech Production

A broad sketch for a model of speech production is outlined which describes developmental aspects of its cognitive-linguistic and sensorimotor components. A description of the emergence of phonological knowledge is a central point in our model sketch. It will be shown that the phonological form level emerges during speech acquisition and becomes an important representation at the interface between cognitive-linguistic and sensorimotor processes. Motor planning as well as motor programming are defined as separate processes in our model sketch and it will be shown that both processes revert to the phonological information. Two computational simulation experiments based on quantitative implementations (simulation models) are undertaken to show proof of principle of key ideas of the model sketch: (i) the emergence of phonological information over developmental stages, (ii) the adaptation process for generating new motor programs, and (iii) the importance of various forms of phonological representation in that process. Based on the ideas developed within our sketch of a production model and its quantitative spell-out within the simulation models, motor planning can be defined here as the process of identifying a succession of executable chunks from a currently activated phoneme sequence and of coding them as raw gesture scores. Motor programming can be defined as the process of building up the complete set of motor commands by specifying all gestures in detail (fully specified gesture score including temporal relations). This full specification of gesture scores is achieved in our model by adapting motor information from phonologically similar syllables (adapting approach) or by assembling motor programs from sub-syllabic units (assembling approach).

Brain-inspired model for early vocal learning and correspondence matching using free-energy optimization

We propose a developmental model inspired by the cortico-basal system (CX-BG) for vocal learning in babies and for solving the correspondence mismatch problem they face when they hear unfamiliar voices, with different tones and pitches. This model is based on the neural architecture INFERNO standing for Iterative Free-Energy Optimization of Recurrent Neural Networks. Free-energy minimization is used for rapidly exploring, selecting and learning the optimal choices of actions to perform (eg sound production) in order to reproduce and control as accurately as possible the spike trains representing desired perceptions (eg sound categories). We detail in this paper the CX-BG system responsible for linking causally the sound and motor primitives at the order of a few milliseconds. Two experiments performed with a small and a large audio database show the capabilities of exploration, generalization and robustness to noise of our neural architecture in retrieving audio primitives during vocal learning and during acoustic matching with unheared voices (different genders and tones).

Effect of maternal depression on infant-directed speech to prelinguistic infants: Implications for language development

The nature and timing of caregivers' speech provides an important foundation for infant attention and language development in the first year of life. Infant-directed speech is a key component of responsive parent-infant communication that is typically characterised by exaggerated intonation and positive affect. This study examines the effect of postnatal depression on the expression of positive vocal affect and pitch, the quantity of mothers' infant-directed speech input and the timing of vocal responses between mother and infant. Postnatal mothers currently experiencing symptoms of depression (n = 13) were matched to postnatal mothers who were not experiencing symptoms of depression (n = 13), and audio-recorded while playing with their 6-month-old infants. Compared with depressed mothers, non-depressed mothers used a higher mean pitch and pitch range, spoke more, gave faster verbal responses and were rated as expressing more positive valence in their voice. These preliminary findings indicate that mothers experiencing low mood use less infant-directed speech and less exaggerated pitch with prelinguistic infants. Postnatal depression is a major health issue that adversely impacts the parent and child. Early interventions for PND may benefit from identifying ways to support the timing of conversations and mothers' use of appropriate vocal pitch and infant-directed speech modifications. Further research is needed to confirm whether these strategies support early conversations.

Generative Adversarial Phonology: Modeling Unsupervised Phonetic and Phonological Learning With Neural Networks

Training deep neural networks on well-understood dependencies in speech data can provide new insights into how they learn internal representations. This paper argues that acquisition of speech can be modeled as a dependency between random space and generated speech data in the Generative Adversarial Network architecture and proposes a methodology to uncover the network's internal representations that correspond to phonetic and phonological properties. The Generative Adversarial architecture is uniquely appropriate for modeling phonetic and phonological learning because the network is trained on unannotated raw acoustic data and learning is unsupervised without any language-specific assumptions or pre-assumed levels of abstraction. A Generative Adversarial Network was trained on an allophonic distribution in English, in which voiceless stops surface as aspirated word-initially before stressed vowels, except if preceded by a sibilant [s]. The network successfully learns the allophonic alternation: the network's generated speech signal contains the conditional distribution of aspiration duration. The paper proposes a technique for establishing the network's internal representations that identifies latent variables that correspond to, for example, presence of [s] and its spectral properties. By manipulating these variables, we actively control the presence of [s] and its frication amplitude in the generated outputs. This suggests that the network learns to use latent variables as an approximation of phonetic and phonological representations. Crucially, we observe that the dependencies learned in training extend beyond the training interval, which allows for additional exploration of learning representations. The paper also discusses how the network's architecture and innovative outputs resemble and differ from linguistic behavior in language acquisition, speech disorders, and speech errors, and how well-understood dependencies in speech data can help us interpret how neural networks learn their representations.

Exploratory dynamics of vocal foraging during infant-caregiver communication

We investigated the hypothesis that infants search in an acoustic space for vocalisations that elicit adult utterances and vice versa, inspired by research on animal and human foraging. Infant-worn recorders were used to collect day-long audio recordings, and infant speech-related and adult vocalisation onsets and offsets were automatically identified. We examined vocalisation-to-vocalisation steps, focusing on inter-vocalisation time intervals and distances in an acoustic space defined by mean pitch and mean amplitude, measured from the child's perspective. Infant inter-vocalisation intervals were shorter immediately following a vocal response from an adult. Adult intervals were shorter following an infant response and adult inter-vocalisation pitch differences were smaller following the receipt of a vocal response from the infant. These findings are consistent with the hypothesis that infants and caregivers are foraging vocally for social input. Increasing infant age was associated with changes in inter-vocalisation step sizes for both infants and adults, and we found associations between response likelihood and acoustic characteristics. Future work is needed to determine the impact of different labelling methods and of automatic labelling errors on the results. The study represents a novel application of foraging theory, demonstrating how infant behaviour and infant-caregiver interaction can be characterised as foraging processes.

Exercise as an Alternative Approach for Treating Smartphone Addiction: A Systematic Review and Meta-Analysis of Random Controlled Trials

BACKGROUND

With the emergence of electronic products, smartphones have become an indispensable tool in our daily life. On the other hand, smartphone addiction has become a public health issue. To help reduce smartphone addiction, cost-effective interventions such as exercise are encouraged.

PURPOSE

We therefore performed a systematic review and meta-analysis evaluating existing literature on the rehabilitative effects of exercise interventions for individuals with a smartphone addiction.

METHODS

We searched PubMed, Web of Science, Scopus, CNKI, and Wanfang from inception to September 2019. Nine eligible randomized controlled trials (RCT) were finally included for meta-analysis (SMD represents the magnitude of effect of exercise) and their methodological quality were assessed using the PEDro scale.

RESULTS

We found significant positive effects of exercise interventions (Taichi, basketball, badminton, dance, run, and bicycle) on reducing the total score (SMD = -1.30, 95% CI -1.53 to -1.07, p < 0.005, I² = 62%) of smartphone addiction level and its four subscales (withdrawal symptom: SMD = -1.40, 95% CI -1.73 to -1.07, p < 0.001, I² = 81%; highlight behavior: SMD = -1.95, 95% CI -2.99 to -1.66, p < 0.001, I² = 79%; social comfort: SMD = -0.99, 95% CI -1.18 to -0.81, p = 0.27, I² = 21%; mood change: SMD = -0.50, 95% CI 0.31 to 0.69, p = 0.25, I² = 25%). Furthermore, we found that individuals with severe addiction level (SMD = -1.19, I² = 0%, 95%CI:-1.19 to -0.98) benefited more from exercise engagement, as compared to those with mild to moderate addiction levels (SMD = - 0.98, I² = 50%, 95%CI:-1.31 to -0.66); individuals with smartphone addiction who participated in exercise programs of 12 weeks and above showed significantly greater reduction on the total score (SMD = -1.70, I² = 31.2%, 95% CI -2.04 to -1.36, p = 0.03), as compared to those who participated in less than 12 weeks of exercise intervention (SMD = -1.18, I² = 0%, 95% CI-1.35 to -1.02, p < 0.00001). In addition, individuals with smartphone addiction who participated in exercise of closed motor skills showed significantly greater reduction on the total score (SMD = -1.22, I² = 0 %, 95% CI -1.41 to -1.02, p = 0.56), as compared to those who participated in exercise of open motor skills (SMD = -1.17, I² = 44%, 95% CI-1.47 to -0.0.87, p = 0.03).

CONCLUSIONS

Exercise interventions may have positive effects on treating smartphone addiction and longer intervention durations may produce greater intervention effects.

The Emergence of Discrete Perceptual-Motor Units in a Production Model That Assumes Holistic Phonological Representations

Intelligible speakers achieve specific vocal tract constrictions in rapid sequence. These constrictions are associated in theory with speech motor goals. Adult-focused models of speech production assume that discrete phonological representations, sequenced into word-length plans for output, define these goals. This assumption introduces a serial order problem for speech. It is also at odds with children's speech. In particular, child phonology and timing control suggest holistic speech plans, and so the hypothesis of whole word production. This hypothesis solves the serial order problem by avoiding it. When the same solution is applied to adult speech the problem becomes how to explain the development of highly intelligible speech. This is the problem addressed here. A modeling approach is used to demonstrate how perceptual-motor units of production emerge over developmental time with the perceptual-motor integration of holistic speech plans that are also phonological representations; the specific argument is that perceptual-motor units are a product of trajectories (nearly) crossing in motor space. The model, which focuses on the integration process, defines the perceptual-motor map as a set of linked pairs of experienced perceptual and motor trajectories. The trajectories are time-based excursions through speaker-defined perceptual and motor spaces. By hypothesis, junctures appear where motor trajectories near or overlap one another in motor space when the shared (or extremely similar) articulatory configurations in these regions are exploited to combine perceptually-linked motor paths along different trajectories. Junctures form in clusters in motor space. These clusters, along with their corresponding (linked) perceptual points, represent perceptual-motor units of production, albeit at the level of speech motor control only. The units serve as pivots in motor space during speaking; they are points of transition from one motor trajectory to another along perceptually-linked paths that are selected to produce best approximations of whole word targets.

Pattern Classification by Spiking Neural Networks Combining Self-Organized and Reward-Related Spike-Timing-Dependent Plasticity

Many recent studies have applied to spike neural networks with spike-timing-dependent plasticity (STDP) to machine learning problems. The learning abilities of dopamine-modulated STDP (DA-STDP) for reward-related synaptic plasticity have also been gathering attention. Following these studies, we hypothesize that a network structure combining self-organized STDP and reward-related DA-STDP can solve the machine learning problem of pattern classification. Therefore, we studied the ability of a network in which recurrent spiking neural networks are combined with STDP for non-supervised learning, with an output layer joined by DA-STDP for supervised learning, to perform pattern classification. We confirmed that this network could perform pattern classification using the STDP effect for emphasizing features of the input spike pattern and DA-STDP supervised learning. Therefore, our proposed spiking neural network may prove to be a useful approach for machine learning problems.

The social functions of babbling: acoustic and contextual characteristics that facilitate maternal responsiveness

What is the social function of babbling? An important function of prelinguistic vocalizing may be to elicit parental behavior in ways that facilitate the infant's own learning about speech and language. Infants use parental feedback to their babbling to learn new vocal forms, but the microstructure of parental responses to babbling has not been studied. To enable precise manipulation of the proximal infant cues that may influence maternal behavior, we used a playback paradigm to assess mothers' responsiveness to prerecorded audiovisual clips of unfamiliar infants' noncry prelinguistic vocalizations and actions. Acoustic characteristics and directedness of vocalizations were manipulated to test their efficacy in structuring social interactions. We also compared maternal responsiveness in the playback paradigm and in free play with their own infants. Maternal patterns of reactions to babbling were stable across both tasks. In the playback task, we found specific vocal cues, such as the degree of resonance and the transition timing of consonant-vowel syllables, predicted contingent maternal responding. Vocalizations directed at objects also facilitated increased responsiveness. The responses mothers exhibited, such as sensitive speech and vocal imitation, are known to facilitate vocal learning and development. Infants, by influencing the behavior of their caregivers with their babbling, create social interactions that facilitate their own communicative development.

From melody to words: The role of sex hormones in early language development

Contribution to Special Issue on Fast effects of steroids. Human infants are the most proficient of the few vocal learner species. Sharing similar principles in terms of the generation and modification of complex sounds, cross-vocal learner comparisons are a suitable strategy when it comes to better understanding the evolution and mechanisms of auditory-vocal learning in human infants. This approach will also help us to understand sex differences in relation to vocal development towards language, the underlying brain mechanisms thereof and sex-specific hormonal effects. Although we are still far from being capable of discovering the "fast effects of steroids" in human infants, we have identified that peripheral hormones (blood serum) are important regulators of vocal behaviour towards language during a transitory hormone surge ("mini-puberty") that is comparable in its extent to puberty. This new area of research in human infants provides a promising opportunity to not only better understand early language acquisition from an ontogenetic and phylogenetic perspective, but to also identify reliable clinical risk-markers in infants for the development of later language disorders.

Does shape affect function? Articulatory skills in babbling of infants with deformational plagiocephaly

PURPOSE

The purpose of this study was to quantitatively analyse pre-speech/early language skills in healthy full-term infants with moderate or severe deformational plagiocephaly (DP) and in infants without any skull asymmetry.

METHODS

At 6 and 12 months, 51 children with DP (41 moderate, 10 severe cases) were studied, along with 15 infants serving as control. Deformational plagiocephaly (DP) was objectively determined based on cranial vault asymmetry (CVA) using 3D stereophotogrammetry (3dMDhead System® and Analytics 4.0, Cranioform®). Articulatory skills in babbling were assessed using the articulatory skill (ART-index) and mean syllable number (MSN). At 12 months, standardized parental questionnaires were used to evaluate early language outcomes.

RESULTS

Overall, 3546 vocalizations were studied. Statistical tests did not reveal any significant differences of the ART-index between the three groups (ANOVA, F[2,63] = 0.24, p = 0.24). MSN likewise did not differ between the three shape groups (Kruskal-Wallis, p = 0.84). Among the children assigned to the at-risk group for language outcomes at 12 months were seven members of the symmetrical shape group (vs. seven assigned to the normally developing group), nine of the moderate DP group (vs. 27), and one of the severe DP group (vs. six). Fisher's exact test was used to analyse whether helmet therapy in the moderate DP group affected the results by influencing language outcomes, but did not reveal any significant influence (p = 0.712).

CONCLUSIONS

The results of this study do not support arguments suggesting that DP is a cognitive risk condition. The suggestion that a direct neurophysiological relationship exists between a DP condition and a cognitive developmental delay remains controversial.