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

Author

Listed:
  • Richard H. R. Hahnloser

    (Lucent Technologies
    Massachusetts Institute of Technology)

  • Alexay A. Kozhevnikov

    (Lucent Technologies)

  • Michale S. Fee

    (Lucent Technologies)

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.

Suggested Citation

  • Richard H. R. Hahnloser & Alexay A. Kozhevnikov & Michale S. Fee, 2002. "An ultra-sparse code underliesthe generation of neural sequences in a songbird," Nature, Nature, vol. 419(6902), pages 65-70, September.
  • Handle: RePEc:nat:nature:v:419:y:2002:i:6902:d:10.1038_nature00974
    DOI: 10.1038/nature00974
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    Citations

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    Cited by:

    1. Alpha Renner & Forrest Sheldon & Anatoly Zlotnik & Louis Tao & Andrew Sornborger, 2024. "The backpropagation algorithm implemented on spiking neuromorphic hardware," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    2. Yang Yiling & Katharine Shapcott & Alina Peter & Johanna Klon-Lipok & Huang Xuhui & Andreea Lazar & Wolf Singer, 2023. "Robust encoding of natural stimuli by neuronal response sequences in monkey visual cortex," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    3. David Kappel & Bernhard Nessler & Wolfgang Maass, 2014. "STDP Installs in Winner-Take-All Circuits an Online Approximation to Hidden Markov Model Learning," PLOS Computational Biology, Public Library of Science, vol. 10(3), pages 1-22, March.
    4. Benjamin M. Zemel & Alexander A. Nevue & Andre Dagostin & Peter V. Lovell & Claudio V. Mello & Henrique Gersdorff, 2021. "Resurgent Na+ currents promote ultrafast spiking in projection neurons that drive fine motor control," Nature Communications, Nature, vol. 12(1), pages 1-23, December.
    5. John Palmer & Adam Keane & Pulin Gong, 2017. "Learning and executing goal-directed choices by internally generated sequences in spiking neural circuits," PLOS Computational Biology, Public Library of Science, vol. 13(7), pages 1-23, July.
    6. Chong Guo & Vincent Huson & Evan Z. Macosko & Wade G. Regehr, 2021. "Graded heterogeneity of metabotropic signaling underlies a continuum of cell-intrinsic temporal responses in unipolar brush cells," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    7. Linda Bistere & Carlos M. Gomez-Guzman & Yirong Xiong & Daniela Vallentin, 2024. "Female calls promote song learning in male juvenile zebra finches," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    8. Fabian Heim & Ezequiel Mendoza & Avani Koparkar & Daniela Vallentin, 2024. "Disinhibition enables vocal repertoire expansion after a critical period," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    9. Morgan A. Brown & Kara M. Zappitelli & Loveprit Singh & Rachel C. Yuan & Melissa Bemrose & Valerie Brogden & David J. Miller & Matthew C. Smear & Stuart F. Cogan & Timothy J. Gardner, 2023. "Direct laser writing of 3D electrodes on flexible substrates," Nature Communications, Nature, vol. 14(1), pages 1-11, December.

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