Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Selective inhibitory control of pyramidal neuron ensembles and cortical subnetworks by chandelier cells


The neocortex comprises multiple information processing streams mediated by subsets of glutamatergic pyramidal cells (PCs) that receive diverse inputs and project to distinct targets. How GABAergic interneurons regulate the segregation and communication among intermingled PC subsets that contribute to separate brain networks remains unclear. Here we demonstrate that a subset of GABAergic chandelier cells (ChCs) in the prelimbic cortex, which innervate PCs at spike initiation site, selectively control PCs projecting to the basolateral amygdala (BLAPC) compared to those projecting to contralateral cortex (CCPC). These ChCs in turn receive preferential input from local and contralateral CCPCs as opposed to BLAPCs and BLA neurons (the prelimbic cortex–BLA network). Accordingly, optogenetic activation of ChCs rapidly suppresses BLAPCs and BLA activity in freely behaving mice. Thus, the exquisite connectivity of ChCs not only mediates directional inhibition between local PC ensembles but may also shape communication hierarchies between global networks.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Figure 1: L2 ChCs preferentially innervate BLAPCs over CCPCs in prelimbic cortex.
Figure 2: L2 ChCs receive strong input from CCPCs and weak input from BLAPCs.
Figure 3: Distinct local circuit connectivity of PVBCs and ChCs in PL upper layers.
Figure 4: Systematic tracing of local and long-range inputs reveal that L2 ChCs are preferentially recruited by bilateral CCPC input as opposed to BLA input.
Figure 5: Optogenetic activation of L2 ChCs in PL inhibits PL firing, including BLAPC firing, in freely behaving mice.


  1. Harris, K.D. & Shepherd, G.M. The neocortical circuit: themes and variations. Nat. Neurosci. 18, 170–181 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  2. Somogyi, P., Katona, L., Klausberger, T., Lasztóczi, B. & Viney, T.J. Temporal redistribution of inhibition over neuronal subcellular domains underlies state-dependent rhythmic change of excitability in the hippocampus. Phil. Trans. R. Soc. Lond. B 369, 20120518 (2013).

    Google Scholar 

  3. Huang, Z.J. Toward a genetic dissection of cortical circuits in the mouse. Neuron 83, 1284–1302 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Roux, L. & Buzsáki, G. Tasks for inhibitory interneurons in intact brain circuits. Neuropharmacology 88, 10–23 (2015).

    CAS  PubMed  Google Scholar 

  5. Somogyi, P. A specific 'axo-axonal' interneuron in the visual cortex of the rat. Brain Res. 136, 345–350 (1977).

    CAS  PubMed  Google Scholar 

  6. DeFelipe, J., Hendry, S.H., Jones, E.G. & Schmechel, D. Variability in the terminations of GABAergic chandelier cell axons on initial segments of pyramidal cell axons in the monkey sensory-motor cortex. J. Comp. Neurol. 231, 364–384 (1985).

    CAS  PubMed  Google Scholar 

  7. Somogyi, P. et al. Identified axo-axonic cells are immunoreactive for GABA in the hippocampus and visual cortex of the cat. Brain Res. 332, 143–149 (1985).

    CAS  PubMed  Google Scholar 

  8. Tamás, G. & Szabadics, J. Summation of unitary IPSPs elicited by identified axo-axonic interneurons. Cereb. Cortex 14, 823–826 (2004).

    PubMed  Google Scholar 

  9. Inan, M. et al. Dense and overlapping innervation of pyramidal neurons by chandelier cells. J. Neurosci. 33, 1907–1914 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Crick, F. & Asanuma, C. Certain aspects of the anatomy and physiology of cerebral cortex. in Parallel Distributed Processing: Exploration in the Microstructures of Cognition. Vol. 2: Psychology and Biological Models (eds. Rumelhart, D.E. & McClelland, J.L.) 333–371 (MIT Press, 1986).

  11. Woodruff, A.R., Anderson, S.A. & Yuste, R. The enigmatic function of chandelier cells. Front. Neurosci. 4, 201 (2010).

    PubMed  PubMed Central  Google Scholar 

  12. Glickfeld, L.L., Roberts, J.D., Somogyi, P. & Scanziani, M. Interneurons hyperpolarize pyramidal cells along their entire somatodendritic axis. Nat. Neurosci. 12, 21–23 (2009).

    CAS  PubMed  Google Scholar 

  13. Szabadics, J. et al. Excitatory effect of GABAergic axo-axonic cells in cortical microcircuits. Science 311, 233–235 (2006).

    CAS  PubMed  Google Scholar 

  14. Woodruff, A.R. et al. State-dependent function of neocortical chandelier cells. J. Neurosci. 31, 17872–17886 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Gabbott, P.L., Warner, T.A., Jays, P.R., Salway, P. & Busby, S.J. Prefrontal cortex in the rat: projections to subcortical autonomic, motor, and limbic centers. J. Comp. Neurol. 492, 145–177 (2005).

    PubMed  Google Scholar 

  16. Hoover, W.B. & Vertes, R.P. Anatomical analysis of afferent projections to the medial prefrontal cortex in the rat. Brain Struct. Funct. 212, 149–179 (2007).

    PubMed  Google Scholar 

  17. Delevich, K., Tucciarone, J., Huang, Z.J. & Li, B. The mediodorsal thalamus drives feedforward inhibition in the anterior cingulate cortex via parvalbumin interneurons. J. Neurosci. 35, 5743–5753 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Cruikshank, S.J. et al. Thalamic control of layer 1 circuits in prefrontal cortex. J. Neurosci. 32, 17813–17823 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Gilmartin, M.R., Balderston, N.L. & Helmstetter, F.J. Prefrontal cortical regulation of fear learning. Trends Neurosci. 37, 455–464 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Little, J.P. & Carter, A.G. Synaptic mechanisms underlying strong reciprocal connectivity between the medial prefrontal cortex and basolateral amygdala. J. Neurosci. 33, 15333–15342 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Taniguchi, H., Lu, J. & Huang, Z.J. The spatial and temporal origin of chandelier cells in mouse neocortex. Science 339, 70–74 (2013).

    CAS  PubMed  Google Scholar 

  22. Hu, H., Gan, J. & Jonas, P. Fast-spiking, parvalbumin+ GABAergic interneurons: from cellular design to microcircuit function. Science 345, 1255263 (2014).

    PubMed  Google Scholar 

  23. Lee, S.H. et al. Parvalbumin-positive basket cells differentiate among hippocampal pyramidal cells. Neuron 82, 1129–1144 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Lu, J., Tucciarone, J., Lin, Y. & Huang, Z.J. Input-specific maturation of synaptic dynamics of parvalbumin interneurons in primary visual cortex. Proc. Natl. Acad. Sci. USA 111, 16895–16900 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Yoshimura, Y. & Callaway, E.M. Fine-scale specificity of cortical networks depends on inhibitory cell type and connectivity. Nat. Neurosci. 8, 1552–1559 (2005).

    CAS  PubMed  Google Scholar 

  26. He, M. et al. Strategies and tools for combinatorial targeting of GABAergic neurons in mouse cerebral cortex. Neuron 91, 1228–1243 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Karalis, N. et al. 4-Hz oscillations synchronize prefrontal-amygdala circuits during fear behavior. Nat. Neurosci. 19, 605–612 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Likhtik, E., Stujenske, J.M., Topiwala, M.A., Harris, A.Z. & Gordon, J.A. Prefrontal entrainment of amygdala activity signals safety in learned fear and innate anxiety. Nat. Neurosci. 17, 106–113 (2014).

    CAS  PubMed  Google Scholar 

  29. Siapas, A.G., Lubenov, E.V. & Wilson, M.A. Prefrontal phase locking to hippocampal theta oscillations. Neuron 46, 141–151 (2005).

    CAS  PubMed  Google Scholar 

  30. Karnani, M.M., Agetsuma, M. & Yuste, R. A blanket of inhibition: functional inferences from dense inhibitory connectivity. Curr. Opin. Neurobiol. 26, 96–102 (2014).

    CAS  PubMed  Google Scholar 

  31. Krook-Magnuson, E., Varga, C., Lee, S.H. & Soltesz, I. New dimensions of interneuronal specialization unmasked by principal cell heterogeneity. Trends Neurosci. 35, 175–184 (2012).

    CAS  PubMed  Google Scholar 

  32. Fino, E. & Yuste, R. Dense inhibitory connectivity in neocortex. Neuron 69, 1188–1203 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Packer, A.M. & Yuste, R. Dense, unspecific connectivity of neocortical parvalbumin-positive interneurons: a canonical microcircuit for inhibition? J. Neurosci. 31, 13260–13271 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Jiang, X. et al. Principles of connectivity among morphologically defined cell types in adult neocortex. Science 350, aac9462 (2015).

    PubMed  PubMed Central  Google Scholar 

  35. Oláh, S. et al. Regulation of cortical microcircuits by unitary GABA-mediated volume transmission. Nature 461, 1278–1281 (2009).

    PubMed  PubMed Central  Google Scholar 

  36. Lee, A.T. et al. Pyramidal neurons in prefrontal cortex receive subtype-specific forms of excitation and inhibition. Neuron 81, 61–68 (2014).

    CAS  PubMed  Google Scholar 

  37. Otsuka, T. & Kawaguchi, Y. Cortical inhibitory cell types differentially form intralaminar and interlaminar subnetworks with excitatory neurons. J. Neurosci. 29, 10533–10540 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Varga, C., Lee, S.Y. & Soltesz, I. Target-selective GABAergic control of entorhinal cortex output. Nat. Neurosci. 13, 822–824 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Caroni, P. Inhibitory microcircuit modules in hippocampal learning. Curr. Opin. Neurobiol. 35, 66–73 (2015).

    CAS  PubMed  Google Scholar 

  40. Donato, F., Chowdhury, A., Lahr, M. & Caroni, P. Early- and late-born parvalbumin basket cell subpopulations exhibiting distinct regulation and roles in learning. Neuron 85, 770–786 (2015).

    CAS  PubMed  Google Scholar 

  41. Donato, F., Rompani, S.B. & Caroni, P. Parvalbumin-expressing basket-cell network plasticity induced by experience regulates adult learning. Nature 504, 272–276 (2013).

    CAS  PubMed  Google Scholar 

  42. Armstrong, C. & Soltesz, I. Basket cell dichotomy in microcircuit function. J. Physiol. (Lond.) 590, 683–694 (2012).

    CAS  Google Scholar 

  43. Massi, L. et al. Temporal dynamics of parvalbumin-expressing axo-axonic and basket cells in the rat medial prefrontal cortex in vivo. J. Neurosci. 32, 16496–16502 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Viney, T.J. et al. Network state-dependent inhibition of identified hippocampal CA3 axo-axonic cells in vivo. Nat. Neurosci. 16, 1802–1811 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Courtin, J. et al. Prefrontal parvalbumin interneurons shape neuronal activity to drive fear expression. Nature 505, 92–96 (2014).

    PubMed  Google Scholar 

  46. Dejean, C. et al. Prefrontal neuronal assemblies temporally control fear behaviour. Nature 535, 420–424 (2016).

    CAS  PubMed  Google Scholar 

  47. Mátyás, F., Lee, J., Shin, H.S. & Acsády, L. The fear circuit of the mouse forebrain: connections between the mediodorsal thalamus, frontal cortices and basolateral amygdala. Eur. J. Neurosci. 39, 1810–1823 (2014).

    PubMed  Google Scholar 

  48. Parnaudeau, S. et al. Inhibition of mediodorsal thalamus disrupts thalamofrontal connectivity and cognition. Neuron 77, 1151–1162 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. Fenno, L.E. et al. Targeting cells with single vectors using multiple-feature Boolean logic. Nat. Methods 11, 763–772 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  50. Kuhlman, S.J. & Huang, Z.J. High-resolution labeling and functional manipulation of specific neuron types in mouse brain by Cre-activated viral gene expression. PLoS One 3, e2005 (2008).

    PubMed  PubMed Central  Google Scholar 

  51. Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012).

    CAS  PubMed  Google Scholar 

  52. Arganda-Carreras, I. et al. Consistent and elastic registration of histological sections using vector-spline regularization. in Computer Vision Approaches to Medical Image Analysis 85–95 (Springer, 2006).

  53. Andrey, P. & Maurin, Y. Free-D: an integrated environment for three-dimensional reconstruction from serial sections. J. Neurosci. Methods 145, 233–244 (2005).

    PubMed  Google Scholar 

  54. Tai, Y., Janas, J.A., Wang, C.L. & Van Aelst, L. Regulation of chandelier cell cartridge and bouton development via DOCK7-mediated ErbB4 activation. Cell Rep. 6, 254–263 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Wang, X. & Sun, Q.Q. Characterization of axo-axonic synapses in the piriform cortex of Mus musculus. J. Comp. Neurol. 520, 832–847 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  56. Schmitzer-Torbert, N., Jackson, J., Henze, D., Harris, K. & Redish, A.D. Quantitative measures of cluster quality for use in extracellular recordings. Neuroscience 131, 1–11 (2005).

    CAS  PubMed  Google Scholar 

  57. Vinck, M., van Wingerden, M., Womelsdorf, T., Fries, P. & Pennartz, C.M. The pairwise phase consistency: a bias-free measure of rhythmic neuronal synchronization. Neuroimage 51, 112–122 (2010).

    PubMed  Google Scholar 

Download references


We thank S. Schamiloglu for help with retrograde labeling of PL pyramidal neurons, B. Li, A. Kepecs and G. Buzsáki for comments on the manuscript. This work was supported in part by NIH R01 MH094705-05 and CSHL Robertson Neuroscience Fund to Z.J.H. and by NIH R01 MH081968 and the Hope for Depression Research Foundation to J.A.G. J.T. was supported by NRSA F30 Medical Scientist Predoctoral Fellowships. J.L. was supported by a NARSAD Postdoctoral Fellowship. N.P.C. was supported by the National Science Foundation. J.A.G. contributed to this article while at Columbia University, before joining the National Institute of Mental Health. The views expressed are the author's own and do not represent the views of the National Institutes of Health, the Department of Health and Human Services, or the United States government.

Author information

Authors and Affiliations



J.L. carried out electrophysiological and optogenetic studies of synaptic connectivity; J.T. performed anatomical and rabies synaptic tracing studies and contributed to in vivo and in vitro physiology studies and analyses; N.P.-C. performed in vivo electrophysiological recordings and data analysis; J.A.G. supervised in vivo electrophysiological recordings and data analysis; M.H. generated the LSL-Flp mouse line; Z.J.H. conceived and organized the study, and wrote the manuscript with contributions from all authors.

Corresponding author

Correspondence to Z Josh Huang.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Spatial distribution of L2 ChCs in frontal cortex.

(a-b) ChCs were labeled by tomaxifen induction at E17.5 in a Nkx2.1-CreER;Ai14 mouse. Images were taken from 100 um coronal sections, and stereologically reconstructed across 1 mm thickness of cortical tissue. Green dots are in infralimbic cortex (IL), red dots in prelimbic cortex (PL), blue dots in anterior cingulate cortex and secondary motor cortex (AC/M2), and purple dots in orbitofrontal cortex (Orb). (c) Quantification of ChCs labeled in several subregions of frontal cortex in a single animal.

Supplementary Figure 2 Counting of axon cartridge number of individual L2 ChCs in PL.

(a) Left: a RFP (+) L2 ChC from sparse labeling with lose dose TM induction in Nkx2.1-CreER;Ai14 (arrowhead: soma, small arrow: dendrite, larger arrow: axon arbor). Middle: staining of PC AIS with phosphor-IkappB. Right: overlay. Arrows indicate soma and dendrite position. (b) The Cartridges revealed as string ChC axon buttons (arrowheads) along the AIS. Images are magnified from boxes in (a). (c) Example of counting cartridge number of a ChC.

Supplementary Figure 3 Spatial relationship between ChCs and PCs in PL and in paired patch recording experiments.

(a) RFP(+) L2 ChCs in PL were positioned alongside to CTB-488 labeled BLAPCs. Dendrites (short arrow), soma (arrowhead) and axons (long arrow) of ChCs are indicated. (b) An example of whole-cell patch recordings of a L2 ChC and an adjacent CTB labeled BLAPC in brain slice. Right panel of pseudocolored cells taken from boxed area of the left under fluorescent imaging. (c) Position of all recorded ChCs in brain slice with dimension axis as indicated in b. In the distance from their somata to pia (201±7 μm vs 196±5 μm, p=0.33, Mann-Whitney test). In the depth in the slice (z axis) (67±7 μm vs 72±5 μm, p=0.46, Mann-Whitney test). (d) Position of all recorded BLAPCs and CCPCs in the brain slice. In the depth (z axis) (62±3 μm vs 73±7 μm, p=0.33, Mann-Whitney test). Mann-Whitney test found a significant difference (p<0.01) in the distance from their somata to pia (238±9 μm vs 265±5 μm).

Supplementary Figure 4 CTB injection spread.

(a) (Left panel) Injection site of medial prefrontal cortex indicates spatial extent of CTB-488 spread. (right panel) Overlay of injection spread of individual animals (n=5) onto paxinos mouse atlas. A/P coordinates indicated. (b) (Top, bottom left figures) Injection site of individual BLA injections indicates spatial extent of CTB-488 spread. (lower right) Overlay of injection spread of individual animals (n=5) onto paxinos mouse atlas. A/P coordinates indicated.

Supplementary Figure 5 Intrinsic properties of 3 subsets of PCs in the upper layer of PL.

(a) An example of membrane resistance (Rm) measurement by a 5 mV hyperpolarization under voltage-clamp; summary in right panel. No significant difference (p=0.81, Mann-Whitney test) between BLAPCs (140±66 MΩ, n=13) and CCPCs (135±53 MΩ, n=16). (b) Examples of firing properties showing regular spiking (RS) and burst spiking (BS) in two PCs under current-clamp. Step-wise ramp depolarization currents were injected into the soma through the glass pipettes. BS was recognized as an interval (<10 ms) between initial two spikes. (c) The percentage of RS and BS in each subset of PCs. (d-h) Summaries of resting membrane potential, AP threshold, AP amplitude, AP half-width and after-hyperpolarization potential of 3 subsets of PCs. BLAPCs (n=13), CCPCs (n=16) and STPCs (n=18). Comparison of BLAPC vs CCPC by Mann-Whitney test showed no significant difference in resting membrane potential (-78.2±5.2 vs -78.7±3.9 mV, p=0.88), AP threshold (-34.7±3.6 vs -33.7±3.9 mV, p=0.74), AP amplitude (76.1±9.2 vs 74.6±6.7 mV, p=0.67), AP half-width (1.04±0.15 vs 0.97±0.17 ms, p=0.42), and after-hyperpolarization potential (7.9±3.0 vs 7.8±2.3 mV, p=0.71). Values are presented as mean±s.d.. Plots display median, mean, quartiles and range.

Supplementary Figure 6 Quantification of spatial relationship between L2 ChCs and PCs in paired recording experiments.

(a) 3D plots of all recorded PCs aligned to the recorded ChCs as origin (the red dot). Innervated (I) BLAPCs: green circle, n=20; innervated CCPCs: blue circle, n=7; non-innervated (N) BLAPCs: green diamond, n=3; non-innervated CCPCs: blue diamond, n=33. (b) Summarizes of soma distance to ChC for the four categories of PCs in (a). No significant difference was detected in distance to ChCs between I-BLAPCs vs N-BLAPCs (73±26 vs 92±24 μm, p=0.19), or between I-CCPCs vs N-CCPCs (85±20 vs 82±19 μm, p=0.70), or between I-BLAPC vs I-CCPC (p=0.19). (c) Summarizes of laminar distance to ChC for the four categories of PCs. There was no significant difference detected between I-BLAPCs vs N-BLAPCs (35±30 vs 54±26 μm, p=0.49) or between I-CCPCs vs N-CCPCs (69±22 vs 72±21 μm, p=0.72). In the laminar distance to ChCs, I-BLAPCs are significantly closer than I-CCPCs (p<0.01). Values are presented as mean±s.d. and Mann-Whitney test employed. (d-e) Summary showing that the connection probability (numbers in bars indicate connected / tested pairs) from ChCs to BLAPCs (d) and CCPCs (e) were the same whether PCs were located 0-60 μm (R1) or 60-120 μm (R2) from ChCs. Although the majority of BLAPCs were located in the upper L2 close to ChCs (R1: n=17 out of 19 pairs, 89.5 %), the more sparse BLAPCs in deeper L2/3 were innervated by L2 ChCs with similar probability (R2: n=3 out of 4 pairs, 75.0 %; Fisher exact test, p=0.45). L2 ChCs had similarly low innervation probability (Fisher exact test, p = 0.99) for CCPCs located in the upper (R1: n=2 out of 10 pairs, 20.0 %) or deeper (R2: n=5 out of 30 pairs, 16.7 %) L2/3. Plots display median, mean, quartiles and the range.

Supplementary Figure 7 Detection and quantification of PC to ChC connection by loose patch stimulation of PCs.

Loose patch was achieved by the tight seal (> 100 MΩ resistance) to the targeted PCs through the same pipette for the whole-cell patch recordings. Stimulation ranged from 0.1-1 V in 200 μs at 0.1Hz. Stimulation intensity was determined by the persistence of spikes in PCs after the stimulation artifact. (a) Example of lack of synaptic responses in ChCs (red) following loose patch stimulation of a BLAPC (green). Upper: schematic of loose patch stimulation in BLAPC and whole-cell patch recording in ChC. Lower: representative traces from paired recordings in ChCs; thick trace was averaged from 20 trials. (b) Summary of BLAPC to ChC connection probability (numbers in bar graph indicate connected / tested pairs). Fisher exact test revealed no significant difference (p=0.38) in the connection probability by loose patch stimulation of BLAPCs (n=0 out of 37 pairs, 0.0 %) compared to that by whole cell patch stimulation of BLAPCs (n=1 out of 23 pairs, 4.3 %). Thus, we pooled two sets of data for the analysis in Fig. 2c. (c) Same arrangement as in a showing example of synaptic responses in ChCs (red) following loose patch stimulation in CCPC (blue). (d) Same arrangement as in b showing summaries of CCPC to ChC connection probability (numbers in bar graph indicate connected / tested pairs). Fisher exact test revealed no significant difference (p=0.72) in the connection probability by loose patch stimulation of CCPCs (n=4 out of 31 pairs, 12.6 %) compared to that by whole cell patch stimulation (n = 4 out of 40 pairs, 10.0 %). Thus, we pooled two sets of data for the analysis in Fig. 2c. Mann-Whitney test revealed no significant difference (p=0.49) in the synaptic strength evoked by loose patch stimulation (83.9±31.7 pA, n=4) and by whole cell patch stimulation (42.5±16.3 pA, n= 4). Thus, we pooled two sets of experiments together for the analysis in Fig. 2c. Plots display median, mean, quartiles and the range.

Supplementary Figure 8 Reliable light-induced spiking in ChR2(+) CCPCs and postsynaptic responses in adjacent ChR2(-) PCs.

(a) Schematic CCPCs infection by dual viral injections first with HSV-Flp in cPL and then with AAV-FD-ChR2-YFP into PL. (b) Example paired recording of YFP(+) PC and adjacent YFP(-) PC in cortical slice under fluorescent microscope. Red: RFP(+) L2 ChCs; Green: ChR2(+) CCPCs in PL. (c) Example spikes in a ChR2(+) evoked by step-wise increase of blue laser intensity (2 ms duration) and postsynaptic potentials in a ChR2(-) PC. (d) Example of high fidelity of spiking in a ChR2(+) PC and synaptic potential in a ChR2(-) PC (black trace averaged from 15 trials of gray traces) evoked by laser flash of 2 ms duration at 10 Hz with a saturation intensity based on step-wise measurement in c. (e) and (f) were magnified from the corresponding events indicated in d.

Supplementary Figure 9 Identification of GABAergic inputs to L2 ChCs revealed by rabies tracing.

(a) Left: local EnvA-dG-GFP infected cells. Middle: GAD67 immunohistochemistry. Right: overlay. (b) Incidence of colocalized inputs with GAD67. Indicated by the arrow as in a. (c) Left: local EnvA-dG-GFP infection RFP+ starter ChCs are designated by white arrow head. Middle: PV immunohistochemistry. Right: overlay. (d) Incidence of colocalized inputs with PV as indicated by arrows. (e, f) Same as in (c, d) instead stained for somastain (SOM), note absence of colocalized input. (g, h) Same as in (c, d) instead stained for vasoactive intestinal peptide (VIP). Scale bar: 100 μm.

Supplementary Figure 10 Identification of diagonal band (DB) input to L2 ChCs revealed by rabies tracing.

(a) Left: 3D reconstruction for total basal forebrain inputs from a single animal color-coded by individual nuclei. Right: 45 degree rotation zoomed image of that basal forebrain. (b) Basal forebrain immunostained for PV (blue) and ChAT (red), overlaid with EnvA-dG-GFP rabies labeled inputs to L2 ChCs in PL. (c) Incidence of inputs colocalized with ChAT (arrowheads) but negative for PV.

Supplementary Figure 11 The Specificity of mPFC ChCs labeling by injection of AAV-FD-ChR2-YFP in Nkx2.1CreER;LSL-Flp mice induced at E17.5.

(a) Injection site following injection with AAV-FD-ChR2-YFP into mPFC, amplified and co-stained with antibodies against YFP tag (dash line indicates midline pia surface; arrow indicates L2 ChCs). (b) Zoomed in injection site reveals several morphologically identified ChCs (indicated by arrows). (c) Morphologically distinct and homogenous population ChCs can be identified via dendritic trees in L1, somata on the L1/2 border (large white arrows) and extensive axonal cartridge plexus in L2/3 (small white arrows). Of total virally labeled cells, 88.6±5.6% cells were ChCs and in L2/3 specifically 94.8±3.6% of cells were ChCs (n=5 mice). No incidences of virally labeled pyramidal cells were seen.

Supplementary Figure 12 Waveform and baseline firing of single units in in vivo recordings.

(a) Plot showing hyperpolarization, spike width and baseline firing for all recorded units identified by their effects in firing by ChC activation. The subpopulation of units indicated by colors as showing in b-d. Differences in spike width (b), average waveform (c) and baseline firing (d) for the different subpopulations of single units recorded. (excited n=3; inhibited n=13; unchanged n=63; Mann Whitney test inhibited vs unchanged: ***p<.001; z-score: 4.2626). (e) Example trial-by-trial correlation between baseline firing and ChC activation induced changes in firing in one single unit. (f-g) Across the inhibited, excited and unchanged populations at different time windows post laser: 0-5 ms (f), and 0-15 ms (g) on the left, the percent of cells with a significant correlation between the baseline firing rate and the firing rate effect of ChC activation (no proportion is statistically different from eYFP group) and on the right, the correlation coefficients for the inhibited and unchange subpopulations are not different than those for control group (inhibited n=13; no change n=63; eYFP n=65; Mann Whitney test, inhibited vs eYFP p=0.32; unchange vs eYFP p=0.85, in 0-15 ms window).

Supplementary Figure 13 Assessing the identity of inhibited units by phase locking analysis.

(a) Phase-locking between PL single units and BLA LFP, depicted in the left schematic. Top: An example of phases locking: spikes from a PL unit appeared to occur at or near the peaks of the raw (gray) and filtered (black) BLA LFP (top); bottom: PSTH and phase distributions of the representative PL single units. Bin size in all PSTHs is 2 ms. (b) Summary of the percentage of phase-locked units separated into light-inhibited and unchanged groups (numbers in bars indicate phase-locked / total units in the group). Significance of phase-locking was determined by Rayleigh’s test. The dashed lines indicated the amount of phase locking with shuffled data. The probability of obtaining as many phase-locked units as were seen in the actual dataset were p<0.01 for the inhibited units, and p=0.17 for the non-inhibited units (p values were obtained with bootstrapping methods). Light-inhibited units were preferentially synchronized to BLA LFP. (c-d) Assessing PL-BLA directionality with a lag analysis. Top, phase-locking strength to BLA LFP 3-6 Hz measured as normalized mean resultant length (MRL) as a function of lag for inhibited units (c) and other L2/3 units (d) aligned by peak lag. Bottom, distributions of lags at which peak phase-locking occurred, for inhibited units (c) and for other L2/3 units (d). Inset pie charts show in gray units with negative peak lags, in red units with positive peak lags, and in white units with a lag of zero. Units had to have at least 50 spikes to be included in these analyses.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–13 and Supplementary Table 1. (PDF 2903 kb)

Life Sciences Reporting Summary (PDF 130 kb)

Supplementary Software

Supplementary Software. (ZIP 3 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Lu, J., Tucciarone, J., Padilla-Coreano, N. et al. Selective inhibitory control of pyramidal neuron ensembles and cortical subnetworks by chandelier cells. Nat Neurosci 20, 1377–1383 (2017).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:

This article is cited by


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing