Development and Upgrade of a Robot That Enables Three-Dimensional Trunk Motion and Lower Limb Exercise for Stroke Patients: A Pilot Clinical Investigation Including a User Feasibility Test.

Vocal signals are important and efficient means of communication, as they are diverse enough to convey a wide range of information and can be transmitted over long distances (Rivera‐Gutierrez et al. ; Titze and Riede ; Aubin and Mathevon ). Among vocal signals, bird song is the best studied model due to its central role in intra‐ and intersexual selection (Gil and Gahr ; Catchpole and Slater ). Although bird song has a genetic basis (Forstmeier et al. ; Lewis et al. ; Jablonszky, Canal, Hegyi, Herényi, et al. ), it is partly learned, to a degree that varies among species (Beecher and Brenowitz ; Mets and Brainard ). This dual nature introduces uncertainty about the extent to which songs function as reliable signals of genetic quality or compatibility for potential mates (Payne and Westneat ; Tregenza and Wedell ; Garamszegi et al. ) and contribute to sexual selection and population divergence (Lachlan and Servedio ; Ribot et al. ; Verzijden et al. ). A strong link between genetics and song can accelerate divergence, while weak association can hinder evolutionary change in song (Ribot et al. ; Verzijden et al. ; Ore et al. ), and although song learning can decouple song and genetic divergence between populations (Ellers and Slabbekoorn ), it may also facilitate speciation if initial song differences emerged between populations (Slabbekoorn and Smith ; Lachlan and Servedio ; Nicholls and Goldizen ). Consequently, the relationship between genetic and song variation is complex and can have major evolutionary implications (Fisher ; Ellegren and Sheldon ). The heritability of song has often been examined for spectro‐temporal traits such as song length or frequency (Forstmeier et al. ; Labra and Lampe ; Jablonszky, Canal, Hegyi, Herényi, et al. ), yet these traits typically show low heritability and sometimes unclear biological relevance (Garamszegi and Møller ; Hegyi et al. ). By contrast, song content—the syllable composition of the songs—have been scarcely studied despite its key role in the context of cultural evolution, syllables and set syllable sequences forming its basis (Lynch and Baker ; Podos et al. ; Garrido Coria et al. ) and sexual selection, as song content can reflect local knowledge, familiarity and can facilitate communication (Wilson et al. ; Garamszegi et al. ; Nelson and Poesel ). Thus, the link between song content and genetic structure can reflect genetic constraints on vocal learning. Unlike continuous or binary traits, song content cannot be analysed with standard quantitative genetic models (‘animal model’; Kruuk and Hadfield ; Wilson et al. ), instead an appropriate approach is to compare matrices of genetic and song‐content similarity. Previous studies on the association between genetic similarity and song‐content similarity have shown mixed results with significant associations in some species (MacDougall‐Shackleton and MacDougall‐Shackleton ; Sosa‐López et al. ), but no association in others (Soha et al. ; Saranathan et al. ; González and Ornelas ). These heterogeneous findings suggest that additional factors, such as species‐specific learning differences (e.g., timing and extent of learning (Beecher and Brenowitz )) or the specific genetic regions and vocal elements examined may play a role (Ribot et al. ; Ore et al. ; García et al. ; Marck et al. ). As both genetics and song vary across spatial and temporal scales (Slater ; Hoffmann and Merilä ), a major source of variation in their relationship may arise from spatial and temporal heterogeneity of the data. For example, limited natal dispersal (Wheelwright and Mauck ; Ishibashi and Saitoh ; Szulkin and Sheldon ) can generate a relationship between genetic and geographic distance (Moore et al. ; Danner et al. ; Ore et al. ) that can vary among species (MacDougall‐Shackleton and MacDougall‐Shackleton ; McDonald ; Searfoss et al. ) or sexes (Graham et al. ; Cayuela et al. ). The spatial patterns of song similarity have been extensively studied (Marler and Tamura ; Koetz et al. ), with dialects or clinal variation in song traits and degree of song sharing commonly reported (Janes and Ryker ; Budka et al. ; Lee et al. ) as a function of the geographical scale (Bradbury et al. ; Snijders et al. ; Graham et al. ). Typically, closer birds sing more similar songs (Beecher et al. ; Briefer et al. ; Price and Yuan ), although the opposite pattern has also been observed (Hultsch and Todt ; Laiolo ; Foote et al. ; Vargas‐Castro ). The drivers of geographic variation in song are not well established, but include sexual selection, signalling group membership, adaptation to habitat characteristics and cultural drift (Wright and Dahlin ). The timing and extent of song learning essentially influence the geographic pattern of song (Beecher et al. ; Nelson et al. ; Koetz et al. ). Temporally, the genetic structure of the populations changes due to adaptive evolution or genetic drift (Kimura ), as does the song content due to genetic changes, but here c