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Turning on and off recurrent balanced cortical activity

Author

Listed:
  • Yousheng Shu

    (Yale University School of Medicine)

  • Andrea Hasenstaub

    (Yale University School of Medicine)

  • David A. McCormick

    (Yale University School of Medicine)

Abstract

The vast majority of synaptic connections onto neurons in the cerebral cortex arise from other cortical neurons, both excitatory and inhibitory, forming local and distant ‘recurrent’ networks. Although this is a basic theme of cortical organization, its study has been limited largely to theoretical investigations, which predict that local recurrent networks show a proportionality or balance between recurrent excitation and inhibition, allowing the generation of stable periods of activity1,2,3,4,5. This recurrent activity might underlie such diverse operations as short-term memory4,6,7, the modulation of neuronal excitability with attention8,9, and the generation of spontaneous activity during sleep5,10,11,12,13,14. Here we show that local cortical circuits do indeed operate through a proportional balance of excitation and inhibition generated through local recurrent connections, and that the operation of such circuits can generate self-sustaining activity that can be turned on and off by synaptic inputs. These results confirm the long-hypothesized role of recurrent activity as a basic operation of the cerebral cortex.

Suggested Citation

  • Yousheng Shu & Andrea Hasenstaub & David A. McCormick, 2003. "Turning on and off recurrent balanced cortical activity," Nature, Nature, vol. 423(6937), pages 288-293, May.
  • Handle: RePEc:nat:nature:v:423:y:2003:i:6937:d:10.1038_nature01616
    DOI: 10.1038/nature01616
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    Citations

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    Cited by:

    1. Ashok Litwin-Kumar & Anne-Marie M Oswald & Nathaniel N Urban & Brent Doiron, 2011. "Balanced Synaptic Input Shapes the Correlation between Neural Spike Trains," PLOS Computational Biology, Public Library of Science, vol. 7(12), pages 1-14, December.
    2. Borges, F.S. & Protachevicz, P.R. & Pena, R.F.O. & Lameu, E.L. & Higa, G.S.V. & Kihara, A.H. & Matias, F.S. & Antonopoulos, C.G. & de Pasquale, R. & Roque, A.C. & Iarosz, K.C. & Ji, P. & Batista, A.M., 2020. "Self-sustained activity of low firing rate in balanced networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    3. Gustavo Deco & Daniel Martí & Anders Ledberg & Ramon Reig & Maria V Sanchez Vives, 2009. "Effective Reduced Diffusion-Models: A Data Driven Approach to the Analysis of Neuronal Dynamics," PLOS Computational Biology, Public Library of Science, vol. 5(12), pages 1-10, December.
    4. Matteo Farinella & Daniel T Ruedt & Padraig Gleeson & Frederic Lanore & R Angus Silver, 2014. "Glutamate-Bound NMDARs Arising from In Vivo-like Network Activity Extend Spatio-temporal Integration in a L5 Cortical Pyramidal Cell Model," PLOS Computational Biology, Public Library of Science, vol. 10(4), pages 1-21, April.
    5. Robert R Kerr & Anthony N Burkitt & Doreen A Thomas & Matthieu Gilson & David B Grayden, 2013. "Delay Selection by Spike-Timing-Dependent Plasticity in Recurrent Networks of Spiking Neurons Receiving Oscillatory Inputs," PLOS Computational Biology, Public Library of Science, vol. 9(2), pages 1-19, February.
    6. Krishna Choudhary & Sven Berberich & Thomas T. G. Hahn & James M. McFarland & Mayank R. Mehta, 2024. "Spontaneous persistent activity and inactivity in vivo reveals differential cortico-entorhinal functional connectivity," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    7. Ghanim Ullah & Steven J Schiff, 2010. "Assimilating Seizure Dynamics," PLOS Computational Biology, Public Library of Science, vol. 6(5), pages 1-12, May.
    8. Christian Meisel & Andreas Klaus & Christian Kuehn & Dietmar Plenz, 2015. "Critical Slowing Down Governs the Transition to Neuron Spiking," PLOS Computational Biology, Public Library of Science, vol. 11(2), pages 1-20, February.
    9. Shrey Dutta & Kartik K. Iyer & Sampsa Vanhatalo & Michael Breakspear & James A. Roberts, 2023. "Mechanisms underlying pathological cortical bursts during metabolic depletion," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    10. Kyriaki Sidiropoulou & Panayiota Poirazi, 2012. "Predictive Features of Persistent Activity Emergence in Regular Spiking and Intrinsic Bursting Model Neurons," PLOS Computational Biology, Public Library of Science, vol. 8(4), pages 1-15, April.
    11. Andreas Steimer & Kaspar Schindler, 2015. "Random Sampling with Interspike-Intervals of the Exponential Integrate and Fire Neuron: A Computational Interpretation of UP-States," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-26, July.
    12. Nariman Valizadeh & Majid Mirzaei & Mohammed Falah Allawi & Haitham Abdulmohsin Afan & Nuruol Syuhadaa Mohd & Aini Hussain & Ahmed El-Shafie, 2017. "Artificial intelligence and geo-statistical models for stream-flow forecasting in ungauged stations: state of the art," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 86(3), pages 1377-1392, April.
    13. Balázs Ujfalussy & Tamás Kiss & Péter Érdi, 2009. "Parallel Computational Subunits in Dentate Granule Cells Generate Multiple Place Fields," PLOS Computational Biology, Public Library of Science, vol. 5(9), pages 1-16, September.
    14. Sreedhar S Kumar & Jan Wülfing & Samora Okujeni & Joschka Boedecker & Martin Riedmiller & Ulrich Egert, 2016. "Autonomous Optimization of Targeted Stimulation of Neuronal Networks," PLOS Computational Biology, Public Library of Science, vol. 12(8), pages 1-22, August.
    15. Vanessa F Descalzo & Roberto Gallego & Maria V Sanchez-Vives, 2014. "Adaptation in the Visual Cortex: Influence of Membrane Trajectory and Neuronal Firing Pattern on Slow Afterpotentials," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-10, November.
    16. Weijie Ye & Xiaoying Chen, 2023. "Effects of NMDA Receptor Hypofunction on Inhibitory Control in a Two-Layer Neural Circuit Model," Mathematics, MDPI, vol. 11(19), pages 1-12, September.

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