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Excitatory cortical neurons form fine-scale functional networks

Author

Listed:
  • Yumiko Yoshimura

    (The Salk Institute for Biological Studies
    Nagoya University, Furo-cho)

  • Jami L. M. Dantzker

    (The Salk Institute for Biological Studies
    Stanford University)

  • Edward M. Callaway

    (The Salk Institute for Biological Studies)

Abstract

The specificity of cortical neuron connections creates columns of functionally similar neurons spanning from the pia to the white matter1,2,3,4,5,6. Here we investigate whether there is an additional, finer level of specificity that creates subnetworks of excitatory neurons within functional columns. We tested for fine-scale specificity of connections to cortical layer 2/3 pyramidal neurons in rat visual cortex by using cross-correlation analyses of synaptic currents evoked by photostimulation. Recording simultaneously from adjacent layer 2/3 pyramidal cells, we find that when they are connected to each other (20% of all recorded pairs) they share common input from layer 4 and within layer 2/3. When adjacent layer 2/3 neurons are not connected to each other, they share very little (if any) common excitatory input from layers 4 and 2/3. In contrast, all layer 2/3 neurons share common excitatory input from layer 5 and inhibitory input from layers 2/3 and 4, regardless of whether they are connected to each other. Thus, excitatory connections from layer 4 to layer 2/3 and within layer 2/3 form fine-scale assemblies of selectively interconnected neurons; inhibitory connections and excitatory connections from layer 5 link neurons across these fine-scale subnetworks. Relatively independent subnetworks of excitatory neurons are therefore embedded within the larger-scale functional architecture; this allows neighbouring neurons to convey information more independently than suggested by previous descriptions of cortical circuitry.

Suggested Citation

  • Yumiko Yoshimura & Jami L. M. Dantzker & Edward M. Callaway, 2005. "Excitatory cortical neurons form fine-scale functional networks," Nature, Nature, vol. 433(7028), pages 868-873, February.
  • Handle: RePEc:nat:nature:v:433:y:2005:i:7028:d:10.1038_nature03252
    DOI: 10.1038/nature03252
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    Cited by:

    1. Gabriel Koch Ocker & Krešimir Josić & Eric Shea-Brown & Michael A Buice, 2017. "Linking structure and activity in nonlinear spiking networks," PLOS Computational Biology, Public Library of Science, vol. 13(6), pages 1-47, June.
    2. Xing, Miaomiao & Song, Xinlin & Wang, Hengtong & Yang, Zhuoqin & Chen, Yong, 2022. "Frequency synchronization and excitabilities of two coupled heterogeneous Morris-Lecar neurons," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    3. Yoav Printz & Pritish Patil & Mathias Mahn & Asaf Benjamin & Anna Litvin & Rivka Levy & Max Bringmann & Ofer Yizhar, 2023. "Determinants of functional synaptic connectivity among amygdala-projecting prefrontal cortical neurons in male mice," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    4. Suchin S Gururangan & Alexander J Sadovsky & Jason N MacLean, 2014. "Analysis of Graph Invariants in Functional Neocortical Circuitry Reveals Generalized Features Common to Three Areas of Sensory Cortex," PLOS Computational Biology, Public Library of Science, vol. 10(7), pages 1-12, July.
    5. Gabriel Koch Ocker & Ashok Litwin-Kumar & Brent Doiron, 2015. "Self-Organization of Microcircuits in Networks of Spiking Neurons with Plastic Synapses," PLOS Computational Biology, Public Library of Science, vol. 11(8), pages 1-40, August.
    6. Volker Pernice & Benjamin Staude & Stefano Cardanobile & Stefan Rotter, 2011. "How Structure Determines Correlations in Neuronal Networks," PLOS Computational Biology, Public Library of Science, vol. 7(5), pages 1-14, May.
    7. Ke Chen & Ai-Min Ding & Xiao-Hua Liang & Li-Peng Zhang & Ling Wang & Xue-Mei Song, 2015. "Effect of Contrast on Visual Spatial Summation in Different Cell Categories in Cat Primary Visual Cortex," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-14, December.
    8. Erez Persi & David Hansel & Lionel Nowak & Pascal Barone & Carl van Vreeswijk, 2011. "Power-Law Input-Output Transfer Functions Explain the Contrast-Response and Tuning Properties of Neurons in Visual Cortex," PLOS Computational Biology, Public Library of Science, vol. 7(2), pages 1-21, February.
    9. Maxim Volgushev & Vladimir Ilin & Ian H Stevenson, 2015. "Identifying and Tracking Simulated Synaptic Inputs from Neuronal Firing: Insights from In Vitro Experiments," PLOS Computational Biology, Public Library of Science, vol. 11(3), pages 1-31, March.
    10. Yulin Shi & Zoran Nenadic & Xiangmin Xu, 2010. "Novel Use of Matched Filtering for Synaptic Event Detection and Extraction," PLOS ONE, Public Library of Science, vol. 5(11), pages 1-15, November.

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