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An ultra-sparse code underliesthe generation of neural sequences in a songbird

An Erratum to this article was published on 16 January 2003

Abstract

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 song1 and recapitulates these sequences during sleep2. We show that the stereotyped sequences in RA are driven from nucleus HVC (high vocal centre), the principal pre-motor input to RA3,4. Recordings of identified HVC neurons in sleeping and singing birds show that individual HVC neurons projecting onto RA neurons produce bursts sparsely, at a single, precise time during the RA sequence. These HVC neurons burst sequentially with respect to one another. We suggest that at each time in the RA sequence, the ensemble of active RA neurons is driven by a subpopulation of RA-projecting HVC neurons that is active only at that time. As a population, these HVC neurons may form an explicit representation of time in the sequence. Such a sparse representation, a temporal analogue of the ‘grandmother cell’5 concept for object recognition, eliminates the problem of temporal interference during sequence generation and learning attributed to more distributed representations6,7.

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Figure 1: RA sequences and identification of HVC neurons.
Figure 2: Spiking activity of identified HVC neurons during singing.
Figure 3: Relationship between burst patterns in a sleeping bird of RA neurons and HVC(RA) neurons.
Figure 4: Global synchrony of HVC interneurons.

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Acknowledgements

We acknowledge discussions with W. Denk, D. Lee, I. Nebel and S. Seung. We also thank F. Nottelbohm for comments on the manuscript. Recordings of RA neurons in the singing bird were carried out in collaboration with A. Leonardo. This work was supported in part by the National Science Foundation.

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Correspondence to Michale S. Fee.

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Hahnloser, R., Kozhevnikov, A. & Fee, M. An ultra-sparse code underliesthe generation of neural sequences in a songbird. Nature 419, 65–70 (2002). https://doi.org/10.1038/nature00974

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