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Highly Nonrandom Features of Synaptic Connectivity in Local Cortical Circuits

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  • Sen Song
  • Per Jesper Sjöström
  • Markus Reigl
  • Sacha Nelson
  • Dmitri B Chklovskii

Abstract

How different is local cortical circuitry from a random network? To answer this question, we probed synaptic connections with several hundred simultaneous quadruple whole-cell recordings from layer 5 pyramidal neurons in the rat visual cortex. Analysis of this dataset revealed several nonrandom features in synaptic connectivity. We confirmed previous reports that bidirectional connections are more common than expected in a random network. We found that several highly clustered three-neuron connectivity patterns are overrepresented, suggesting that connections tend to cluster together. We also analyzed synaptic connection strength as defined by the peak excitatory postsynaptic potential amplitude. We found that the distribution of synaptic connection strength differs significantly from the Poisson distribution and can be fitted by a lognormal distribution. Such a distribution has a heavier tail and implies that synaptic weight is concentrated among few synaptic connections. In addition, the strengths of synaptic connections sharing pre- or postsynaptic neurons are correlated, implying that strong connections are even more clustered than the weak ones. Therefore, the local cortical network structure can be viewed as a skeleton of stronger connections in a sea of weaker ones. Such a skeleton is likely to play an important role in network dynamics and should be investigated further. A dataset of hundreds of recordings in which four neurons were simultaneously monitored reveals clustered connectivity patterns among cortical neurons.

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  • Sen Song & Per Jesper Sjöström & Markus Reigl & Sacha Nelson & Dmitri B Chklovskii, 2005. "Highly Nonrandom Features of Synaptic Connectivity in Local Cortical Circuits," PLOS Biology, Public Library of Science, vol. 3(3), pages 1-1, March.
    • Handle: RePEc:plo:pbio00:0030068
    DOI: 10.1371/journal.pbio.0030068
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    1. Rosa Cossart & Dmitriy Aronov & Rafael Yuste, 2003. "Attractor dynamics of network UP states in the neocortex," Nature, Nature, vol. 423(6937), pages 283-288, May.
    2. Youngchao Ge & Sandrine Dudoit & Terence Speed, 2003. "Resampling-based multiple testing for microarray data analysis," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 12(1), pages 1-77, June.
    3. Farkas, I. & Jeong, H. & Vicsek, T. & Barabási, A.-L. & Oltvai, Z.N., 2003. "The topology of the transcription regulatory network in the yeast, Saccharomyces cerevisiae," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 318(3), pages 601-612.
    4. Winfried Denk & Heinz Horstmann, 2004. "Serial Block-Face Scanning Electron Microscopy to Reconstruct Three-Dimensional Tissue Nanostructure," PLOS Biology, Public Library of Science, vol. 2(11), pages 1-1, October.
    5. Duncan J. Watts & Steven H. Strogatz, 1998. "Collective dynamics of ‘small-world’ networks," Nature, Nature, vol. 393(6684), pages 440-442, June.
    6. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
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    1. Mengchen Zhu & Christopher J Rozell, 2015. "Modeling Inhibitory Interneurons in Efficient Sensory Coding Models," PLOS Computational Biology, Public Library of Science, vol. 11(7), pages 1-22, July.
    2. Christoph Hartmann & Andreea Lazar & Bernhard Nessler & Jochen Triesch, 2015. "Where’s the Noise? Key Features of Spontaneous Activity and Neural Variability Arise through Learning in a Deterministic Network," PLOS Computational Biology, Public Library of Science, vol. 11(12), pages 1-35, December.
    3. Leo Kozachkov & Mikael Lundqvist & Jean-Jacques Slotine & Earl K Miller, 2020. "Achieving stable dynamics in neural circuits," PLOS Computational Biology, Public Library of Science, vol. 16(8), pages 1-15, August.
    4. Robert J Prill & Pablo A Iglesias & Andre Levchenko, 2005. "Dynamic Properties of Network Motifs Contribute to Biological Network Organization," PLOS Biology, Public Library of Science, vol. 3(11), pages 1-1, October.
    5. Jimok Kim & Richard W Tsien & Bradley E Alger, 2012. "An Improved Test for Detecting Multiplicative Homeostatic Synaptic Scaling," PLOS ONE, Public Library of Science, vol. 7(5), pages 1-9, May.
    6. Vladimir V Klinshov & Jun-nosuke Teramae & Vladimir I Nekorkin & Tomoki Fukai, 2014. "Dense Neuron Clustering Explains Connectivity Statistics in Cortical Microcircuits," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-12, April.
    7. Mihai A Petrovici & Bernhard Vogginger & Paul Müller & Oliver Breitwieser & Mikael Lundqvist & Lyle Muller & Matthias Ehrlich & Alain Destexhe & Anders Lansner & René Schüffny & Johannes Schemmel & Ka, 2014. "Characterization and Compensation of Network-Level Anomalies in Mixed-Signal Neuromorphic Modeling Platforms," PLOS ONE, Public Library of Science, vol. 9(10), pages 1-30, October.
    8. Naoki Hiratani & Tomoki Fukai, 2015. "Mixed Signal Learning by Spike Correlation Propagation in Feedback Inhibitory Circuits," PLOS Computational Biology, Public Library of Science, vol. 11(4), pages 1-36, April.
    9. Jian K Liu & Zhen-Su She, 2009. "A Spike-Timing Pattern Based Neural Network Model for the Study of Memory Dynamics," PLOS ONE, Public Library of Science, vol. 4(7), pages 1-8, July.
    10. Brendan Chambers & Jason N MacLean, 2016. "Higher-Order Synaptic Interactions Coordinate Dynamics in Recurrent Networks," PLOS Computational Biology, Public Library of Science, vol. 12(8), pages 1-23, August.
    11. Fereshteh Lagzi & Stefan Rotter, 2015. "Dynamics of Competition between Subnetworks of Spiking Neuronal Networks in the Balanced State," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-28, September.
    12. Fabiano Baroni & Joaquín J Torres & Pablo Varona, 2010. "History-Dependent Excitability as a Single-Cell Substrate of Transient Memory for Information Discrimination," PLOS ONE, Public Library of Science, vol. 5(12), pages 1-19, December.
    13. Baktash Babadi & L F Abbott, 2016. "Stability and Competition in Multi-spike Models of Spike-Timing Dependent Plasticity," PLOS Computational Biology, Public Library of Science, vol. 12(3), pages 1-26, March.

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