Corticobasal ganglia projecting neurons are required for juvenile vocal learning but not for adult vocal plasticity in songbirds.

Birdsong, like human speech, consists of a sequence of temporally precise movements acquired through vocal learning. The learning of such sequential vocalizations depends on the neural function of the motor cortex and basal ganglia. However, it is unknown how the connections between cortical and basal ganglia components contribute to vocal motor skill learning, as mammalian motor cortices serve multiple types of motor action and most experimentally tractable animals do not exhibit vocal learning. Here, we leveraged the zebra finch, a songbird, as an animal model to explore the function of the connectivity between cortex-like (HVC) and basal ganglia (area X), connected by HVC(X) projection neurons with temporally precise firing during singing. By specifically ablating HVC(X) neurons, juvenile zebra finches failed to copy tutored syllable acoustics and developed temporally unstable songs with less sequence consistency. In contrast, HVC(X)-ablated adults did not alter their learned song structure, but generated acoustic fluctuations and responded to auditory feedback disruption by the introduction of song deterioration, as did normal adults. These results indicate that the corticobasal ganglia input is important for learning the acoustic and temporal aspects of song structure, but not for generating vocal fluctuations that contribute to the maintenance of an already learned vocal pattern.

Daily singing of adult songbirds functions to maintain song performance independently of auditory feedback and age.

Many songbirds learn to produce songs through vocal practice in early life and continue to sing daily throughout their lifetime. While it is well-known that adult songbirds sing as part of their mating rituals, the functions of singing behavior outside of reproductive contexts remain unclear. Here, we investigated this issue in adult male zebra finches by suppressing their daily singing for two weeks and examining the effects on song performance. We found that singing suppression decreased the pitch, amplitude, and duration of songs, and that those song features substantially recovered through subsequent free singing. These reversible song changes were not dependent on auditory feedback or the age of the birds, contrasting with the adult song plasticity that has been reported previously. These results demonstrate that adult song structure is not stable without daily singing, and suggest that adult songbirds maintain song performance by preventing song changes through physical act of daily singing throughout their life. Such daily singing likely functions as vocal training to maintain the song production system in optimal conditions for song performance in reproductive contexts, similar to how human singers and athletes practice daily to maintain their performance.

Distinguish the Severity of Illness Associated with Novel Coronavirus (COVID-19) Infection via Sustained Vowel Speech Features.

The authors are currently conducting research on methods to estimate psychiatric and neurological disorders from a voice by focusing on the features of speech. It is empirically known that numerous psychosomatic symptoms appear in voice biomarkers; in this study, we examined the effectiveness of distinguishing changes in the symptoms associated with novel coronavirus infection using speech features. Multiple speech features were extracted from the voice recordings, and, as a countermeasure against overfitting, we selected features using statistical analysis and feature selection methods utilizing pseudo data and built and verified machine learning algorithm models using LightGBM. Applying 5-fold cross-validation, and using three types of sustained vowel sounds of /Ah/, /Eh/, and /Uh/, we achieved a high performance (accuracy and AUC) of over 88% in distinguishing "asymptomatic or mild illness (symptoms)" and "moderate illness 1 (symptoms)". Accordingly, the results suggest that the proposed index using voice (speech features) can likely be used in distinguishing the symptoms associated with novel coronavirus infection.

Estimating Depressive Symptom Class from Voice.

Voice-based depression detection methods have been studied worldwide as an objective and easy method to detect depression. Conventional studies estimate the presence or severity of depression. However, an estimation of symptoms is a necessary technique not only to treat depression, but also to relieve patients' distress. Hence, we studied a method for clustering symptoms from HAM-D scores of depressed patients and by estimating patients in different symptom groups based on acoustic features of their speech. We could separate different symptom groups with an accuracy of 79%. The results suggest that voice from speech can estimate the symptoms associated with depression.

Detection of Major Depressive Disorder Based on a Combination of Voice Features: An Exploratory Approach.

In general, it is common knowledge that people's feelings are reflected in their voice and facial expressions. This research work focuses on developing techniques for diagnosing depression based on acoustic properties of the voice. In this study, we developed a composite index of vocal acoustic properties that can be used for depression detection. Voice recordings were collected from patients undergoing outpatient treatment for major depressive disorder at a hospital or clinic following a physician's diagnosis. Numerous features were extracted from the collected audio data using openSMILE software. Furthermore, qualitatively similar features were combined using principal component analysis. The resulting components were incorporated as parameters in a logistic regression based classifier, which achieved a diagnostic accuracy of ~90% on the training set and ~80% on the test set. Lastly, the proposed metric could serve as a new measure for evaluation of major depressive disorder.

Long-term Devocalization of Zebra Finches.

Songbirds, such as the zebra finch, are a popular animal model for studying the neural basis of vocal and complex skill learning. Adult male zebra finches produce courtship song toward females (referred to as 'directed song') and recording and analyzing sounds of directed song along with underlying neural activity is important for investigating behavioral and neural mechanisms of song production and learning. However, recording of directed song is easily contaminated by calls that are often as loud as directed songs and frequently produced by a female bird is presented in the same sound-recording chamber to elicit directed song. We developed a new surgical procedure to relatively easily and almost completely devocalize female zebra finches semi-permanently, without affecting other behaviors. This procedure enables researchers to record directed songs with almost no contamination by female calls. The procedure can also be used to devocalize male birds as well and, thus, has great potential for a variety of experimental purposes, such as long-term elimination of auditory feedback during singing in male birds.