The present study aimed to explore the connection between the acoustic parameters of dog sounds and the morphometric characteristics of the laryngeal cartilages in dogs with various body sizes. We compared the measurements of the laryngeal cartilages (n=15) of equal number of small, medium, and large size dog cadavers with the acoustic parameters recorded from other dogs of similar size and number. The morphometry was performed with a digital caliper. Animal sounds were analysed with Raven Pro 1.6 software. Waveform and spectrogram graphs were displayed for each sound with 512-point Hann window 50% overlap time. Sound selections were manually verified. Our findings confirmed that small-sized dogs generate the highest pitched barks in every measured frequency (5%-95% and peak). In addition, their vocal signals are of the lowest tonality expressed in sound-to-noise ratio (SNR). The Frequency parameters (F) 5%, 25%, and 95% showed significant correlations with the morphometric values of the laryngeal cartilages, which indicates their role in the sound formation. These acoustic parameters had strong to moderate negative correlations with the thyroid cartilage (TC) width and height; arytenoid cartilage (AC) – distance between proc. corniculatus and proc. cuneiformis (corn-cun) , depth of ventricle and distance between the two proc. cuneiformis (cun-cun) ; width, height and depth of cricoid cartilage (CC); width and height of the epiglottis (EP). Our finding suggested that F5%, F25% and F95% can be reliable parameters and can be used in the classification methods of dogs’ sounds as it varies predictably with laryngeal cartilages size.

In domestic dogs, vocal behaviour is influenced by morphology, social context, domestication, and interaction with humans. This chapter will review the anatomical and physiological basis of vocal production in dogs and the relationship between laryngeal morphology, body size, and acoustic characteristics of vocal signals. Different types of canine vocalizations will be discussed in relation to their behavioural meaning, emotional background, and communicative function. A comparative perspective through acoustic analysis of jackal vocalizations will also be presented for examining vocal signals closely related to territoriality, group cohesion, and long-distance communication. This may help distinguish vocal features shaped primarily by anatomy and phylogeny from those modified by humans, as well as the distinction between instinctive vocal patterns and flexible, socially modulated vocal behaviour. Finally, practical applications of acoustic analysis in ethology, behavioural medicine, and wildlife monitoring will be described. By integrating anatomophysiological, acoustic, behavioural, and comparative perspectives, the chapter aims to contribute to a broader understanding of canid vocal communication as a system positioned between instinctive expression and adaptive social signalling.

Development of modern veterinary neurology requires non-invasive and reliable methods for studying brain activity in animals. Electroencephalography (EEG) is a fundamental method for registering and analyzing the electrical activity of the brain and is increasingly used both in clinical practice and in experimental studies in dogs. This book chapter reviews the basic principles of non-invasive EEG monitoring in dogs, with a focus on the application of EEG to assess the functional state of the central nervous system (CNS). The physiological mechanisms underlying the EEG signal, the features of its recording in dogs, as well as the basic methods for analyzing and interpreting EEG data, are presented. Attention is given to the physiology of sleep in dogs and the characteristic EEG patterns observed in different stages of sleep. The neurophysiological mechanisms associated with dreaming are also reviewed, as well as the potential role of sleep in the processes of neuronal plasticity, recovery, and neuroprotection. The chapter also discusses the main clinical applications of non-invasive neurophysiological monitoring in dogs, including the diagnosis and follow-up of epilepsy, sleep disorders, and other neurological diseases. The importance of integrating EEG with other physiological monitoring methods, modern approaches for more accurate assessment of brain function, and future prospects are emphasized.