Sex-specific automatic responses to infant cries: TMS reveals greater excitability in females than males in motor evoked potentials

Neuroimaging reveals that infant cries activate parts of the premotor cortical system. To validate this effect in a more direct way, we used event-related transcranial magnetic stimulation (TMS). Here, we investigated the presence and the time course of modulation of motor cortex excitability in young adults who listened to infant cries. Specifically, we recorded motor evoked potentials (MEPs) from the biceps brachii (BB) and interosseus dorsalis primus (ID1) muscles as produced by TMS delivered from 0 to 250 ms from sound onset in six steps of 50 ms in 10 females and 10 males. We observed an excitatory modulation of MEPs at 100 ms from the onset of the infant cry specific to females and to the ID1 muscle. We regard this modulation as a response to natural cry sounds because it was delayed, attenuated to stimuli increasingly different from natural cry, and was absent in a separate group of females who listened to non-cry stimuli physically matched to natural infant cries. Furthermore, the 100-ms latency of this modulation is not compatible with a voluntary reaction to the stimulus but suggests an automatic, bottom-up audiomotor association. The brains of adult females appear to be tuned to respond to infant cries with automatic motor excitation. This effect may reflect the greater and longstanding burden on females in caregiving infants

Sex stereotypes influence adults' perception of babies' cries

Background: Despite widespread evidence that gender stereotypes influence human parental behavior, their potential effects on adults’ perception of babies’ cries have been overlooked. In particular, whether adult listeners overgeneralize the sex dimorphism that characterizes the voice of adult speakers (men are lower-pitched than women) to their perception of babies’ cries has not been investigated. Methods: We used playback experiments combining natural and re-synthesised cries of 3 month-old babies to investigate whether the interindividual variation in the fundamental frequency (pitch) of cries affected adult listeners’ identification of the baby’s sex, their perception the baby’s femininity and masculinity, and whether these biases interacted with their perception of the level of discomfort expressed by the cry. Results: We show that low-pitched cries are more likely to be attributed to boys and high-pitched cries to girls, despite the absence of sex differences in pitch. Moreover, low-pitched boys are perceived as more masculine and high-pitched girls are perceived as more feminine. Finally, adult men rate relatively low-pitched cries as expressing more discomfort when presented as belonging to boys than to girls. Conclusion: Such biases in caregivers’ responses to babies’ cries may have implications on children’s immediate welfare and on the development of their gender identity

Vocal communication of simulated pain

While evidence suggests that pain cries produced by human babies and other mammal infants communicate acoustic cues to pain intensity, whether the pain vocalisations of human adults also encode pain intensity, and which acoustic characteristics influence listeners’ perceptions, remains unexplored. Here, we investigated how trained actors communicated pain by comparing the acoustic characteristics of nonverbal vocalisations expressing different levels of pain intensity (mild, moderate, and severe). We then performed playback experiments to examine whether vocalisers successfully communicated pain intensity to listeners, and which acoustic characteristics were responsible for variation in pain ratings. We found that the mean and range of voice fundamental frequency (F0, perceived as pitch), the amplitude of the vocalisation, the degree of periodicity of the vocalisation, and the proportion of the signal displaying nonlinear phenomena all increased with the level of simulated pain intensity. In turn, these parameters predicted increases in listeners’ ratings of pain intensity. We also found that while different voice features contributed to increases in pain ratings within each level of expressed pain, a combination of these features explained an impressive amount of the variance in listeners’ pain ratings, both across (76%) and within (31-54%) pain levels. Our results show that adult vocalisers can volitionally simulate and modulate pain vocalisations to influence listeners’ perceptions of pain in a manner consistent with authentic human infant and nonhuman mammal pain vocalisations, and highlight potential for the development of a practical quantitative tool to improve pain assessment in populations unable to self-report their subjective pain experience

Infant Cry Signal Processing, Analysis, and Classification with Artificial Neural Networks

As a special type of speech and environmental sound, infant cry has been a growing research area covering infant cry reason classification, pathological infant cry identification, and infant cry detection in the past two decades. In this dissertation, we build a new dataset, explore new feature extraction methods, and propose novel classification approaches, to improve the infant cry classification accuracy and identify diseases by learning infant cry signals. We propose a method through generating weighted prosodic features combined with acoustic features for a deep learning model to improve the performance of asphyxiated infant cry identification. The combined feature matrix captures the diversity of variations within infant cries and the result outperforms all other related studies on asphyxiated baby crying classification. We propose a non-invasive fast method of using infant cry signals with convolutional neural network (CNN) based age classification to diagnose the abnormality of infant vocal tract development as early as 4-month age. Experiments discover the pattern and tendency of the vocal tract changes and predict the abnormality of infant vocal tract by classifying the cry signals into younger age category. We propose an approach of generating hybrid feature set and using prior knowledge in a multi-stage CNNs model for robust infant sound classification. The dominant and auxiliary features within the set are beneficial to enlarge the coverage as well as keeping a good resolution for modeling the diversity of variations within infant sound and the experimental results give encouraging improvements on two relative databases. We propose an approach of graph convolutional network (GCN) with transfer learning for robust infant cry reason classification. Non-fully connected graphs based on the similarities among the relevant nodes are built to consider the short-term and long-term effects of infant cry signals related to inner-class and inter-class messages. With as limited as 20% of labeled training data, our model outperforms that of the CNN model with 80% labeled training data in both supervised and semi-supervised settings. Lastly, we apply mel-spectrogram decomposition to infant cry classification and propose a fusion method to further improve the infant cry classification performance

Development of Translational Methods in Spectral Analysis of Human Infant Crying and Rat Pup Ultrasonic Vocalizations for Early Neurobehavioral Assessment

The purpose of this article is to describe the development of translational methods by which spectrum analysis of human infant crying and rat pup ultrasonic vocalizations (USVs) can be used to assess potentially adverse effects of various prenatal conditions on early neurobehavioral development. The study of human infant crying has resulted in a rich set of measures that has long been used to assess early neurobehavioral insult due to non-optimal prenatal environments, even among seemingly healthy newborn and young infants. In another domain of study, the analysis of rat put USVs has been conducted via paradigms that allow for better experimental control over correlated prenatal conditions that may confound findings and conclusions regarding the effects of specific prenatal experiences. The development of translational methods by which cry vocalizations of both species can be analyzed may provide the opportunity for findings from the two approaches of inquiry to inform one another through their respective strengths. To this end, we present an enhanced taxonomy of a novel set of common measures of cry vocalizations of both human infants and rat pups based on a conceptual framework that emphasizes infant crying as a graded and dynamic acoustic signal. This set includes latency to vocalization onset, duration and repetition rate of expiratory components, duration of inter-vocalization-intervals and spectral features of the sound, including the frequency and amplitude of the fundamental and dominant frequencies. We also present a new set of classifications of rat pup USV waveforms that include qualitative shifts in fundamental frequency, similar to the presence of qualitative shifts in fundamental frequency that have previously been related to insults to neurobehavioral integrity in human infants. Challenges to the development of translational analyses, including the use of different terminologies, methods of recording, and spectral analyses are discussed, as well as descriptions of automated processes, software solutions, and pitfalls

Adult human perception of distress in the cries of bonobo, chimpanzee, and human infants

Understanding the extent to which humans perceive the emotional state of animals has both theoretical and practical implications. While recent studies indicate that natural selection has led to some convergence of emotion coding among vertebrate species (including humans), highlighting the interspecific value of emotional signals, it has also been argued that interspecific communication of emotions can fail due to species-specific signalling traits impairing information decoding and/or absence of familiarity with heterospecific communication systems. In this article, we show that human listeners pay attention to the mean pitch of vocalizations when asked to rate the distress level expressed by human baby cries, and that they use a similar pitch scale to rate the emotional level of baby non-human ape (bonobo and chimpanzee) distress calls. As a consequence, the very high-pitched bonobo infant calls were systematically rated as expressing overall high distress levels despite being recorded in contexts eliciting various stress intensity. Conversely, chimpanzee infant calls – which are characterized by a relatively lower pitch – were systematically rated as expressing relatively lower distress levels. These results indicate that, in the absence of exposure/familiarity, our spontaneous ability to range the emotional content of vocalizations in closely related ape species remains biased by basic frequency differences, suggesting that the absolute interspecific value of emotional signals should not be overestimated

Speech Communication

Contains research objectives and summary of research on four research projects.National Institutes of Health (Grant 5 RO1 NS04332-14)National Institutes of Health (Grant 5 T32 NS07040-02)National Institutes of Health (Fellowship 1 F22 NS00796-01)National Institutes of Health (Grant 1 ROI NS13028-01)National Institutes of Health (Grant 5 T3Z NS07040-02)National Institutes of Health (Fellowship 1 F22 MH58258-02)U. S. Army- Maryland Procurement Office (Contract MDA904-76-C-0331