Neural Control of Birdsong

Marc F Schmidt, University of Pennsylvania, Philadelphia, Pennsylvania, USA

Published online: December 2009

DOI: 10.1002/9780470015902.a0021400

Birdsong is a learned behaviour that displays a remarkable level of acoustic and temporal complexity. It is controlled by a well-defined neural circuit, known as the song system, which receives highly processed auditory information from specialized higher-order auditory areas. Over the past decade, sophisticated new song analysis tools coupled with the ability to record from identified neurons in adult and juvenile singing birds have revealed many fundamental insights into the neural mechanisms that underlie vocal production, storage of auditory memories and sensorimotor learning. Some of these include an understanding of how sleep drives song acquisition and how circuits homologous to the mammalian basal ganglia generate the motor variability that enables sensorimotor learning. The tractable nature of this system coupled with its shared similarities with human speech make birdsong a unique model for understanding the neural bases of vocal production and learning.

Key Concepts:

  • Sophisticated new methodologies in song quantification have made it possible to provide quantitative descriptions of the entire vocal imitation process in juvenile birds.
  • Storage of the song template likely occurs in specialized higher-order auditory forebrain areas rather than in the song system proper.
  • The song system is a specialized neural circuit that is necessary for song production and sensorimotor learning.
  • Neurons that form part of the descending motor pathway produce short (approximately 5 ms) bursts of action potentials that are precisely time locked to specific time segment of the song.
  • The portion of the song system necessary for song production is organized as a recurrent pathway with structures in the thalamus and respiratory brainstem projecting back up to the forebrain.
  • Neural variability from the basal ganglia circuit onto RA is thought to contribute to the observed motor variability in juvenile birds and likely enables the motor exploration strategy that is critical for song learning in juveniles.
  • Sleep plays a critical role in vocal learning by allowing offline processing of sensory and motor information.

Keywords: songbirds; song system; basal ganglia; sensorimotor learning; sparse coding; sleep

Figure 1. Schematic representation of the avian song system and its auditory inputs. The avian song system can be divided into three main divisions. The descending motor pathway (shown in black) includes telencephalic areas HVC and RA as well as brainstem nuclei that drive the muscles of the syrinx (nXIIts) or the respiratory system (RAm and PAm). These later two structures form part of a vocal respiratory network that also includes DM. The second division consists of projections from the diencephalon and brainstem back to HVC (shown in green). Although not shown for simplicity, all of these projections (from PAm, DM and DMP) are bilateral in nature and therefore play a likely critical role in hemispheric coordination. The third major division of the song system consists of the anterior pathway (shown in red), which is made up of Area X, DLM and LMAN. This circuit is not necessary for song production but plays an important role in song learning and maintenance. The song system receives processed auditory information from an ascending auditory pathway (shown in blue). Area NCM in the auditory forebrain (highlighted with a red circle) has been suggested as the area where the song template is stored. Anatomical names: DLM, medial part of the dorsolateral thalamic nucleus; LMAN, lateral magnocellular nucleus of the anterior nidopallium; Field L, the primary auditory forebrain structure in birds; Area X, Area X of the medial striatum; NIf, nucleus interfacialis of the nidopallium; RAm, nucleus retroambigualis; PAm, nucleus paraambigualus; DM, dorsomedial nucleus of the intercollicular complex; CMM, caudal medial mesopallium; CLM, caudal lateral mesopallium; Field L, auditory forebrain areas consisting of Fields L1, L2, L2a, L2b and L3; Ov/Ovm, nucleus ovoidalis; MLd, dorsal lateral nucleus of the mesencephalon; NCM, caudal medial nidopallium and LLV, ventral nucleus of the lateral lemniscus.
Figure 2. Songbirds can switch rapidly between sides when they sing. Many songbirds use both their left and right syrinx to produce song. In some cases, as illustrated here by the brown-headed cowbird, they can switch rapidly from producing sound in the left syrinx to produce sound in the right syrinx. In this example, a cluster of 5 short song elements is produced within a very short period of approximately 200 ms. The contribution of each syringeal side can be measured by implanting a small heated microbead thermistor in each primary bronchus. This measures the rate of airflow through each side of the syrinx and is shown at the bottom of the figure with airflow from the right side in green and from the left side in red. Note the left airflow has been flipped upside down to better compare with the right side. From these measurements, one can infer the syringeal source of each song element. As shown in the sonogram, cowbirds rapidly alternate between producing a note with the left (red) and the right (green) sides of the syrinx. (This cartoon is based on measurements recorded by Dr. Rod Suthers.) Adapted from Figure 2 in Schmidt MF (2008) PLoS Biology 6(10): 2089–2093.
Figure 3. Sparse neural representation in HVC during singing. (a) Single-unit recording in HVC of an RA-projection neuron (HVCRA) during the production of three sequential song motifs (top trace) reveals that this neuron only produces a single burst of action potentials (i, ii and iii) at precisely the same time in each song motif. The boxed inset shows an expanded view of each burst. (b) A spike raster plot is shown for eight different HVCRA neurons recorded in the same bird where each row of tick mark represents action potentials generated during one rendition of the song. Each recorded neuron is represented by a separate colour. This graph illustrates the precision with which HVCRA neurons burst at exactly the same time period in each motif. It also shows how different neurons fire preferentially at different time periods in the motif. Reproduced from Hahnloser et al. (2002), Figure 2. With permission from Macmillan Publisherd Ltd.
Figure 4. Conceptual representation of the ‘sparse code’ model for song production. During the production of song in the zebra finch (top panel: ‘SONG’), single HVCRA neurons fire only a single burst during the entire duration of the motif, which occurs at exactly the same acoustic transition from one motif to the next. It has been hypothesized that approximately 100–200 neurons will be active simultaneously (i.e. produce a single burst) during each 10 ms time window (t). The second panel (‘HVCRA neurons’) shows a schematic representation of this concept by dividing syllable ‘d’ into discrete time windows (t1, t2, t3, t4, ) where different subpopulation of HVCRA neurons (red cells during t1, blue cells during t2, etc.) are active during each time window. Each of these subpopulations of HVCRA neurons (e.g. blue cells in window t2) is thought to activate a discrete population of neurons in RA (shown in the third panel ‘RA neurons’). To represent the known myotopic map, RA is divided into three sections (RA-m1, RA-m2 and RA-m3). For simplicity, the nXIIts layer has been omitted and only three of the six muscle groups are represented (lowest panel ‘syringeal muscles’). Activation of a specific subset of neurons in RA recruits various muscle groups and results in a distinct acoustic output for that specific window in time. In the case of window t1, for example, activation of the red cell population in HVC leads to activation of a subset of neurons in RA which, in this example, activate muscle 1, a little bit of muscle 3 and not muscle 2.
Figure 5. Effect of pharmacological silencing LMAN on plastic song. (a) Sonographic representation of three different song renditions of a juvenile zebra finch (57 days posthatch) show large variability in the sequence and acoustic structure of song syllables. (b) TTX was then injected into LMAN and song output was recorded a short duration thereafter. Inactivation of LMAN with TTX produces an immediate reduction of sequence and acoustic variability, revealing a highly stereotyped song produced by the descending motor pathway. The song segments shown in (a) and (b) are from consecutive song bouts, immediately before and 1 h after TTX injection. Modified from Figure 1 in Olveczky et al. PLoS Biology 3(5): e153.
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Learning and Memory: Cellular and Molecular Mechanisms | Neural Networks and Behaviour
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Article Title: Neural Control of Birdsong
 
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Schmidt, Marc F(Dec 2009) Neural Control of Birdsong. In: eLS. John Wiley & Sons Ltd, Chichester. http://www.els.net [doi: 10.1002/9780470015902.a0021400]