Background: Understanding the neural basis of behavior requires insight into how different brain systems coordinate with each other. Existing connectomes for various species have highlighted brain systems essential to various aspects of behavior, yet their application to complex learned behaviors remains limited. Research on vocal learning in songbirds has extensively focused on the vocal control network, though recent work implicates a variety of circuits in contributing to important aspects of vocal behavior. Thus, a more comprehensive understanding of brain-wide connectivity is essential to further assess the totality of circuitry underlying this complex learned behavior.
Results: We present the Oscine Structural Connectome for Investigating NEural NETwork ORGanization (OSCINE-NET.ORG), the first interactive mesoscale connectome for any vocal learner. This comprehensive digital map includes all known connectivity data, covering major brain superstructures and functional networks. Our analysis reveals that the songbird brain exhibits small-world properties, with highly connected communities functionally designated as motor, visual, associative, vocal, social, and auditory. Moreover, there is a small set of significant connections across these communities, including from social and auditory sub-communities to vocal sub-communities, which highlight ethologically relevant facets of vocal learning and production. Notably, the vocal community contains the majority of the canonical vocal control network, as well as a variety of other nodes that are highly interconnected with it, meriting further evaluation for their inclusion in this network. A subset of nodes forms a "rich broker club," highly connected across the brain and forming a small circuit amongst themselves, indicating they may play a key role in information transfer broadly. Collectively, their bidirectional connectivity with multiple communities indicates they may act as liaisons across multiple functional circuits for a variety of complex behaviors.
Conclusions: OSCINE-NET.ORG offers unprecedented access to detailed songbird connectivity data, promoting insight into the neural circuits underlying complex behaviors. This data emphasizes the importance of brain-wide integration in vocal learning, facilitating a potential reevaluation of the canonical vocal control network. Furthermore, we computationally identify a small, previously unidentified circuit-one which may play an impactful role in brain-wide coordination of multiple complex behaviors.
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http://dx.doi.org/10.1186/s12868-024-00919-3 | DOI Listing |
Ultrasound Med Biol
December 2024
Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China. Electronic address:
Purpose: To explore the efficacy of interventional ultrasound treatment for hoarseness caused by nondisconnected recurrent laryngeal nerve injury after thyroidectomy.
Materials And Methods: In this retrospective study, we analysed the clinical data of 21 patients who underwent interventional ultrasound therapy (ultrasound-guided injection of a Diprospan and saline mixture) for postthyroidectomy hoarseness at our hospital between August 1, 2023, and January 31, 2024 (the Diprospan group) and randomly selected 21 patients who did not receive any treatment for postthyroidectomy hoarseness during the same period as the control group. The average vocal cord activity improvement time for the Diprospan group was calculated and compared with that of untreated patients from previous studies.
BMC Neurosci
December 2024
Department of Medicine, The University of Chicago, 5841 S Maryland Ave, Chicago, IL, 60637, USA.
Background: Understanding the neural basis of behavior requires insight into how different brain systems coordinate with each other. Existing connectomes for various species have highlighted brain systems essential to various aspects of behavior, yet their application to complex learned behaviors remains limited. Research on vocal learning in songbirds has extensively focused on the vocal control network, though recent work implicates a variety of circuits in contributing to important aspects of vocal behavior.
View Article and Find Full Text PDFAm J Otolaryngol
December 2024
Department of Otorhinolaryngology Head and Neck Surgery, Tianjin First Central Hospital, Tianjin 300192, China; Institute of Otolaryngology of Tianjin, Tianjin, China; Key Laboratory of Auditory Speech and Balance Medicine, Tianjin, China; Key Clinical Discipline of Tianjin (Otolaryngology), Tianjin, China; Otolaryngology Clinical Quality Control Centre, Tianjin, China.
Purpose: To use deep learning technology to design and implement a model that can automatically classify laryngoscope images and assist doctors in diagnosing laryngeal diseases.
Materials And Methods: The experiment was based on 3057 images (normal, glottic cancer, granuloma, Reinke's Edema, vocal cord cyst, leukoplakia, nodules and polyps) from the dataset Laryngoscope8. A classification model based on deep neural networks was developed and tested.
J Voice
December 2024
Department of Music, Faculty of Human Ecology, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia. Electronic address:
Background/objectives: The coronavirus disease (COVID-19) pandemic has significantly impacted global health, with Malaysia reporting over 5 million cases as of May 2024. While symptoms like fatigue and breathlessness are commonly reported among COVID-19 patients, limited research exists on the vocal and pulmonary conditions of individuals with long COVID symptoms. This study aims to assess vocal impairments and pulmonary function differences between long COVID patients and healthy controls, addressing gaps in understanding how long COVID affects vocal and respiratory health.
View Article and Find Full Text PDFJ Voice
December 2024
Neurology Department II, Fuyang People's Hospital, Fuyang, China. Electronic address:
Purpose: Parkinson disease (PD) is a progressive neurodegenerative disease. The aim of this study is to investigate the association between acoustic and cortical brain features in Parkinson's disease patients.
Methods: We recruited 19 (eight females, 11 males) Parkinson's disease patients and 19 (eight females, 11 males) healthy subjects to participate in the experiment.
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