How sleep affects the developmental learning of bird song

Abstract

Sleep affects learning and development in humans and other animals, but the role of sleep in developmental learning has never been examined. Here we show the effects of night-sleep on song development in the zebra finch by recording and analysing the entire song ontogeny. During periods of rapid learning we observed a pronounced deterioration in song structure after night-sleep. The song regained structure after intense morning singing. Daily improvement in similarity to the tutored song occurred during the late phase of this morning recovery; little further improvement occurred thereafter. Furthermore, birds that showed stronger post-sleep deterioration during development achieved a better final imitation. The effect diminished with age. Our experiments showed that these oscillations were not a result of sleep inertia or lack of practice, indicating the possible involvement of an active process, perhaps neural song-replay during sleep. We suggest that these oscillations correspond to competing demands of plasticity and consolidation during learning, creating repeated opportunities to reshape previously learned motor skills.

Sleep in children improves memory performance on declarative but not procedural tasks

“…Although surprising at a first glance, our finding in children of greater gains in finger motor skill across a wake retention interval than a sleep retention interval agrees with two previous human studies indicating likewise relatively diminished sleepdependent gains in motor sequence learning and language skills (exact recognition of artificial words), respectively (Gomez et al 2006;Fischer et al 2007). In combination with equivalent findings in young birds showing deteriorated song performance after sleep (Deregnaucourt et al 2005), these findings strongly speak for the notion that sleep during development exerts a specific effect on the offline learning of a skill that differs from that in adults and manifests itself in a relatively impaired performance at retrieval, if compared with performance after a wake control interval. However, an immediate lack of overnight gains in skill does not necessarily exclude an improving influence of posttraining sleep on the long term: The birds that showed stronger post-sleep deterioration during development achieved a better final imitation at the end of the 3-mo study epoch (Deregnaucourt et al 2005).…”

“…In combination with equivalent findings in young birds showing deteriorated song performance after sleep (Deregnaucourt et al 2005), these findings strongly speak for the notion that sleep during development exerts a specific effect on the offline learning of a skill that differs from that in adults and manifests itself in a relatively impaired performance at retrieval, if compared with performance after a wake control interval. However, an immediate lack of overnight gains in skill does not necessarily exclude an improving influence of posttraining sleep on the long term: The birds that showed stronger post-sleep deterioration during development achieved a better final imitation at the end of the 3-mo study epoch (Deregnaucourt et al 2005).…”

Differential effects of global versus local testosterone on singing behavior and its underlying neural substrate

“…Each day, video and audio recordings were made from 800 to 930 hours (lights on at 800 hours), 1300 to 1430 hours, and 1600 to 1730 hours. The following song behaviors were quantified from recordings made every other day during 11 d, starting after 3 d of treatment: song rate (songs per hour), mean duration of each song, percentage of time spent singing, entropy variance, energy, fundamental frequency, and bandwidth (56,57). Songs were defined as vocalizations being longer than or equal to 1 s in duration and separated by 500 ms of silence (58,59).…”

Quantification of developmental birdsong learning from the subsyllabic scale to cultural evolution

“…It is now easy to record and store the entire development of a song and explore the fine structure of millions of sounds produced during song learning. Therefore, instead of studying individual behavioral events, it became possible to study the distributions of continuous features over many sounds, and it became easier to investigate multiple time scales of song learning-from moment to moment (7,47), over cycles of night sleep and morning singing (48), and over the entire learning trajectory (8). The analysis of the stereotyped adult song gained as well from analytic approaches based on large data sets of continuous features, revealing details of fine structure and variation that were not detectable via classical analysis (49,50).…”