Temperature Manipulation in Songbird Brain Implicates the Premotor Nucleus HVC in Birdsong Syntax.

Variable motor sequences of animals are often structured and can be described by probabilistic transition rules between action elements. Examples include the songs of many songbird species such as the Bengalese finch, which consist of stereotypical syllables sequenced according to probabilistic rules (song syntax). The neural mechanisms behind such rules are poorly understood.

Finding motifs in birdsong data in the presence of acoustic noise and temporal jitter.

Here we present a novel approach to quickly and reliably find long (200 ms - 2 s) stereotyped sequences of sounds ("motifs") in acoustic recordings of birdsong. Robust and time-efficient identification of such sequences is a crucial first step in many studies ranging from development to neuronal basis of motor behavior. Accurately identifying motifs is usually hindered by the presence of animal-intrinsic variability in execution and tempo, and by extrinsic acoustic noise (e.

Real-time system for studies of the effects of acoustic feedback on animal vocalizations.

Studies of behavioral and neural responses to distorted auditory feedback (DAF) can help shed light on the neural mechanisms of animal vocalizations. We describe an apparatus for generating real-time acoustic feedback. The system can very rapidly detect acoustic features in a song and output acoustic signals if the detected features match the desired acoustic template.

A simple miniature device for wireless stimulation of neural circuits in small behaving animals.

The use of wireless neural stimulation devices offers significant advantages for neural stimulation experiments in behaving animals. We demonstrate a simple, low-cost and extremely lightweight wireless neural stimulation device which is made from off-the-shelf components. The device has low power consumption and does not require a high-power RF preamplifier.

A compact statistical model of the song syntax in Bengalese finch.

Songs of many songbird species consist of variable sequences of a finite number of syllables. A common approach for characterizing the syntax of these complex syllable sequences is to use transition probabilities between the syllables. This is equivalent to the Markov model, in which each syllable is associated with one state, and the transition probabilities between the states do not depend on the state transition history.

Singing-related activity of identified HVC neurons in the zebra finch.

High vocal center (HVC) is part of the premotor pathway necessary for song production and is also a primary source of input to the anterior forebrain pathway (AFP), a basal ganglia-related circuit essential for vocal learning. We have examined the activity of identified HVC neurons of zebra finches during singing. Antidromic activation was used to identify three classes of HVC cells: neurons projecting to the premotor nucleus RA, neurons projecting to area X in the AFP, and putative HVC interneurons.

Sleep-related neural activity in a premotor and a basal-ganglia pathway of the songbird.

During singing, neurons in premotor nucleus RA (robust nucleus of the arcopallium) of the zebra finch produce complex temporal sequences of bursts that are recapitulated during sleep. RA receives input from nucleus HVC via the premotor pathway, and also from the lateral magnocellular nucleus of the anterior nidopallium (LMAN), part of a basal ganglia-related circuit essential for vocal learning. We explore the propagation of sleep-related spike patterns in these two pathways and their influences on RA activity.

Neural mechanisms of vocal sequence generation in the songbird.

Little is known about the biophysical and neuronal circuit mechanisms underlying the generation and learning of behavioral sequences. Songbirds provide a marvelous animal model in which to study these phenomena. By use of a motorized microdrive to record the activity of single neurons in the singing bird, we are beginning to understand the circuits that generate complex vocal sequences.

An ultra-sparse code underlies the generation of neural sequences in a songbird.

Sequences of motor activity are encoded in many vertebrate brains by complex spatio-temporal patterns of neural activity; however, the neural circuit mechanisms underlying the generation of these pre-motor patterns are poorly understood. In songbirds, one prominent site of pre-motor activity is the forebrain robust nucleus of the archistriatum (RA), which generates stereotyped sequences of spike bursts during song and recapitulates these sequences during sleep. We show that the stereotyped sequences in RA are driven from nucleus HVC (high vocal centre), the principal pre-motor input to RA.