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Small modulation of ongoing cortical dynamics by sensory input during natural vision

Author

Listed:
  • József Fiser

    (Center for Visual Science, University of Rochester
    University of Rochester)

  • Chiayu Chiu

    (University of Rochester)

  • Michael Weliky

    (Center for Visual Science, University of Rochester
    University of Rochester)

Abstract

During vision, it is believed that neural activity in the primary visual cortex is predominantly driven by sensory input from the environment. However, visual cortical neurons respond to repeated presentations of the same stimulus with a high degree of variability1,2,3,4. Although this variability has been considered to be noise owing to random spontaneous activity within the cortex5,6,7, recent studies show that spontaneous activity has a highly coherent spatio-temporal structure8,9,10,11,12,13. This raises the possibility that the pattern of this spontaneous activity may shape neural responses during natural viewing conditions to a larger extent than previously thought. Here, we examine the relationship between spontaneous activity and the response of primary visual cortical neurons to dynamic natural-scene and random-noise film images in awake, freely viewing ferrets from the time of eye opening to maturity. The correspondence between evoked neural activity and the structure of the input signal was weak in young animals, but systematically improved with age. This improvement was linked to a shift in the dynamics of spontaneous activity. At all ages including the mature animal, correlations in spontaneous neural firing were only slightly modified by visual stimulation, irrespective of the sensory input. These results suggest that in both the developing and mature visual cortex, sensory evoked neural activity represents the modulation and triggering of ongoing circuit dynamics by input signals, rather than directly reflecting the structure of the input signal itself.

Suggested Citation

  • József Fiser & Chiayu Chiu & Michael Weliky, 2004. "Small modulation of ongoing cortical dynamics by sensory input during natural vision," Nature, Nature, vol. 431(7008), pages 573-578, September.
    • Handle: RePEc:nat:nature:v:431:y:2004:i:7008:d:10.1038_nature02907
    DOI: 10.1038/nature02907
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    Citations

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    Cited by:

    1. Lars Buesing & Johannes Bill & Bernhard Nessler & Wolfgang Maass, 2011. "Neural Dynamics as Sampling: A Model for Stochastic Computation in Recurrent Networks of Spiking Neurons," PLOS Computational Biology, Public Library of Science, vol. 7(11), pages 1-22, November.
    2. Gabriel D Puccini & Albert Compte & Miguel Maravall, 2006. "Stimulus Dependence of Barrel Cortex Directional Selectivity," PLOS ONE, Public Library of Science, vol. 1(1), pages 1-6, December.
    3. 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.
    4. Miguel Maravall & Rasmus S Petersen & Adrienne L Fairhall & Ehsan Arabzadeh & Mathew E Diamond, 2007. "Shifts in Coding Properties and Maintenance of Information Transmission during Adaptation in Barrel Cortex," PLOS Biology, Public Library of Science, vol. 5(2), pages 1-12, January.
    5. Márton Albert Hajnal & Duy Tran & Michael Einstein & Mauricio Vallejo Martelo & Karen Safaryan & Pierre-Olivier Polack & Peyman Golshani & Gergő Orbán, 2023. "Continuous multiplexed population representations of task context in the mouse primary visual cortex," Nature Communications, Nature, vol. 14(1), pages 1-20, December.
    6. Anthony Randal McIntosh & Natasa Kovacevic & Roxane J Itier, 2008. "Increased Brain Signal Variability Accompanies Lower Behavioral Variability in Development," PLOS Computational Biology, Public Library of Science, vol. 4(7), pages 1-9, July.
    7. Rong J. B. Zhu & Xue-Xin Wei, 2023. "Unsupervised approach to decomposing neural tuning variability," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    8. Rava Azeredo da Silveira & Michael J Berry II, 2014. "High-Fidelity Coding with Correlated Neurons," PLOS Computational Biology, Public Library of Science, vol. 10(11), pages 1-25, November.
    9. Benjamin R Cowley & Matthew A Smith & Adam Kohn & Byron M Yu, 2016. "Stimulus-Driven Population Activity Patterns in Macaque Primary Visual Cortex," PLOS Computational Biology, Public Library of Science, vol. 12(12), pages 1-31, December.
    10. Disheng Tang & Joel Zylberberg & Xiaoxuan Jia & Hannah Choi, 2024. "Stimulus type shapes the topology of cellular functional networks in mouse visual cortex," Nature Communications, Nature, vol. 15(1), pages 1-17, December.

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