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The plasticitome of cortical interneurons

Abstract

Hebb postulated that, to store information in the brain, assemblies of excitatory neurons coding for a percept are bound together via associative long-term synaptic plasticity. In this view, it is unclear what role, if any, is carried out by inhibitory interneurons. Indeed, some have argued that inhibitory interneurons are not plastic. Yet numerous recent studies have demonstrated that, similar to excitatory neurons, inhibitory interneurons also undergo long-term plasticity. Here, we discuss the many diverse forms of long-term plasticity that are found at inputs to and outputs from several types of cortical inhibitory interneuron, including their plasticity of intrinsic excitability and their homeostatic plasticity. We explain key plasticity terminology, highlight key interneuron plasticity mechanisms, extract overarching principles and point out implications for healthy brain functionality as well as for neuropathology. We introduce the concept of the plasticitome — the synaptic plasticity counterpart to the genome or the connectome — as well as nomenclature and definitions for dealing with this rich diversity of plasticity. We argue that the great diversity of interneuron plasticity rules is best understood at the circuit level, for example as a way of elucidating how the credit-assignment problem is solved in deep biological neural networks.

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Fig. 1: Cellular learning while normalizing synaptic weights by combining homosynaptic and heterosynaptic plasticity.
Fig. 2: One, two or more factors can determine IN plasticity.
Fig. 3: Opposing forms of IN intrinsic plasticity.
Fig. 4: The plasticitome.

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References

  1. Bliss, T. V. & Collingridge, G. L. A synaptic model of memory: long-term potentiation in the hippocampus. Nature 361, 31–39 (1993).

    Article  CAS  Google Scholar 

  2. Malenka, R. C. & Bear, M. F. LTP and LTD: an embarrassment of riches. Neuron 44, 5–21 (2004).

    Article  CAS  Google Scholar 

  3. Markram, H., Gerstner, W. & Sjöström, P. J. Spike-timing-dependent plasticity: a comprehensive overview. Front. Synaptic Neurosci. 4, 2 (2012).

    Article  CAS  Google Scholar 

  4. Katz, L. C. & Shatz, C. J. Synaptic activity and the construction of cortical circuits. Science 274, 1133–1138 (1996).

    Article  CAS  Google Scholar 

  5. Hensch, T. K. Critical period plasticity in local cortical circuits. Nat. Rev. Neurosci. 6, 877–888 (2005).

    Article  CAS  Google Scholar 

  6. Cline, H. T. Topographic maps: developing roles of synaptic plasticity. Curr. Biol. 8, R836–R839 (1998).

    Article  CAS  Google Scholar 

  7. Markram, H., Gerstner, W. & Sjöström, P. J. A history of spike-timing-dependent plasticity. Front. Synaptic Neurosci. 3, 4 (2011).

    Article  Google Scholar 

  8. Hebb, D. O. The Organization of Behaviour (Wiley, 1949).

  9. Shatz, C. J. The developing brain. Sci. Am. 267, 60–67 (1992).

    Article  CAS  Google Scholar 

  10. Löwel, S. & Singer, W. Selection of intrinsic horizontal connections in the visual cortex by correlated neuronal activity. Science 255, 209–212 (1992).

    Article  Google Scholar 

  11. Hebb, D. O. A Textbook of Psychology (W. B. Saunders, 1972).

  12. Hopfield, J. J. & Tank, D. W. Computing with neural circuits: a model. Science 233, 625–633 (1986).

    Article  CAS  Google Scholar 

  13. McBain, C. J., Freund, T. F. & Mody, I. Glutamatergic synapses onto hippocampal interneurons: precision timing without lasting plasticity. Trends Neurosci. 22, 228–235 (1999).

    Article  CAS  Google Scholar 

  14. Sjöström, P. J., Rancz, E. A., Roth, A. & Häusser, M. Dendritic excitability and synaptic plasticity. Physiol. Rev. 88, 769–840 (2008).

    Article  Google Scholar 

  15. Maheux, J., Froemke, R. C. & Sjöström, P. J. in Dendrites Ch. 18 (eds Stuart, G., Spruston, N. & Häusser, M.) 465–498 (Oxford Univ. Press, 2016).

  16. Yazaki-Sugiyama, Y., Kang, S., Cateau, H., Fukai, T. & Hensch, T. K. Bidirectional plasticity in fast-spiking GABA circuits by visual experience. Nature 462, 218–221 (2009). In this work, in vivo visual cortex recordings following monocular deprivation reveal that BCs have an unexpected initial preference for the occluded eye before a late preference for the open eye, in keeping with temporally symmetric STDP at excitatory inputs to BCs.

    Article  CAS  Google Scholar 

  17. Udakis, M., Pedrosa, V., Chamberlain, S. E. L., Clopath, C. & Mellor, J. R. Interneuron-specific plasticity at parvalbumin and somatostatin inhibitory synapses onto CA1 pyramidal neurons shapes hippocampal output. Nat. Commun. 11, 4395 (2020). Using computer modelling, this study demonstrates that timing-dependent LTP at SST+ IN inputs onto CA1 PCs stabilizes hippocampal place cells and prevents interference in new environments, whereas timing-dependent LTD at PV+ IN inputs maintains place cell spike output.

    Article  CAS  Google Scholar 

  18. Vogels, T. P., Sprekeler, H., Zenke, F., Clopath, C. & Gerstner, W. Inhibitory plasticity balances excitation and inhibition in sensory pathways and memory networks. Science 334, 1569–1573 (2011).

    Article  CAS  Google Scholar 

  19. Kullmann, D. M. & Lamsa, K. P. LTP and LTD in cortical GABAergic interneurons: emerging rules and roles. Neuropharmacology 60, 712–719 (2011).

    Article  CAS  Google Scholar 

  20. Lamsa, K. P., Heeroma, J. H., Somogyi, P., Rusakov, D. A. & Kullmann, D. M. Anti-Hebbian long-term potentiation in the hippocampal feedback inhibitory circuit. Science 315, 1262–1266 (2007).

    Article  CAS  Google Scholar 

  21. Markram, H. et al. Interneurons of the neocortical inhibitory system. Nat. Rev. Neurosci. 5, 793–807 (2004).

    Article  CAS  Google Scholar 

  22. Ascoli, G. A. et al. Petilla terminology: nomenclature of features of GABAergic interneurons of the cerebral cortex. Nat. Rev. Neurosci. 9, 557–568 (2008).

    Article  CAS  Google Scholar 

  23. Gouwens, N. W. et al. Integrated morphoelectric and transcriptomic classification of cortical GABAergic cells. Cell 183, 935–953.e19 (2020).

    Article  CAS  Google Scholar 

  24. Larsen, R. S. & Sjöström, P. J. Synapse-type-specific plasticity in local circuits. CONB 35, 127–135 (2015). This review defines the research field of synapse type-specific plasticity in local circuits.

    CAS  Google Scholar 

  25. Sjöström, P. J. Grand challenge at the frontiers of synaptic neuroscience. Front. Synaptic Neurosci. 13, 748937 (2021).

    Article  Google Scholar 

  26. Abbott, L. F. et al. The mind of a mouse. Cell 182, 1372–1376 (2020).

    Article  CAS  Google Scholar 

  27. Gregory, S. G. et al. A physical map of the mouse genome. Nature 418, 743–750 (2002).

    Article  CAS  Google Scholar 

  28. Kepecs, A. & Fishell, G. Interneuron cell types are fit to function. Nature 505, 318–326 (2014).

    Article  CAS  Google Scholar 

  29. Rudy, B., Fishell, G., Lee, S. & Hjerling-Leffler, J. Three groups of interneurons account for nearly 100% of neocortical GABAergic neurons. Dev. Neurobiol. 71, 45–61 (2011).

    Article  Google Scholar 

  30. Tremblay, R., Lee, S. & Rudy, B. GABAergic interneurons in the neocortex: from cellular properties to circuits. Neuron 91, 260–292 (2016).

    Article  CAS  Google Scholar 

  31. Pfeffer, C. K., Xue, M., He, M., Huang, Z. J. & Scanziani, M. Inhibition of inhibition in visual cortex: the logic of connections between molecularly distinct interneurons. Nat. Neurosci. 16, 1068–1076 (2013).

    Article  CAS  Google Scholar 

  32. Kawaguchi, Y. & Kubota, Y. Correlation of physiological subgroupings of nonpyramidal cells with parvalbumin- and calbindinD28k-immunoreactive neurons in layer V of rat frontal cortex. J. Neurophysiol. 70, 387–396 (1993).

    Article  CAS  Google Scholar 

  33. Mele, M., Leal, G. & Duarte, C. B. Role of GABAA R trafficking in the plasticity of inhibitory synapses. J. Neurochem. 139, 997–1018 (2016).

    Article  CAS  Google Scholar 

  34. Kullmann, D. M., Moreau, A. W., Bakiri, Y. & Nicholson, E. Plasticity of inhibition. Neuron 75, 951–962 (2012).

    Article  CAS  Google Scholar 

  35. Chiu, C. Q., Barberis, A. & Higley, M. J. Preserving the balance: diverse forms of long-term GABAergic synaptic plasticity. Nat. Rev. Neurosci. 20, 272–281 (2019).

    Article  CAS  Google Scholar 

  36. Capogna, M., Castillo, P. E. & Maffei, A. The ins and outs of inhibitory synaptic plasticity: neuron types, molecular mechanisms and functional roles. Eur. J. Neurosci. 54, 6882–6901 (2021).

    Article  CAS  Google Scholar 

  37. Wu, Y. K., Miehl, C. & Gjorgjieva, J. Regulation of circuit organization and function through inhibitory synaptic plasticity. Trends Neurosci. https://doi.org/10.1016/j.tins.2022.10.006 (2022).

    Article  Google Scholar 

  38. Sprekeler, H. Functional consequences of inhibitory plasticity: homeostasis, the excitation–inhibition balance and beyond. Curr. Opin. Neurobiol. 43, 198–203 (2017).

    Article  CAS  Google Scholar 

  39. Topolnik, L. & Tamboli, S. The role of inhibitory circuits in hippocampal memory processing. Nat. Rev. Neurosci. https://doi.org/10.1038/s41583-022-00599-0 (2022).

    Article  Google Scholar 

  40. Hensch, T. K. et al. Local GABA circuit control of experience-dependent plasticity in developing visual cortex. Science 282, 1504–1508 (1998).

    Article  CAS  Google Scholar 

  41. Maffei, A., Nataraj, K., Nelson, S. B. & Turrigiano, G. G. Potentiation of cortical inhibition by visual deprivation. Nature 443, 81–84 (2006). This work shows that visual deprivation leaves excitatory connections in L4 unaffected but potentiates BC inhibition of PCs, which shifts the E/I balance in PCs to favour inhibition and may, thus, underlie deprivation-induced degradation of visual function.

    Article  CAS  Google Scholar 

  42. Sjöström, P. J. & Gerstner, W. Spike-timing dependent plasticity. Scholarpedia 5, 1362 (2010).

    Article  Google Scholar 

  43. Song, S., Miller, K. D. & Abbott, L. F. Competitive Hebbian learning through spike-timing-dependent synaptic plasticity. Nat. Neurosci. 3, 919–926 (2000).

    Article  CAS  Google Scholar 

  44. Vickers, E. D. et al. Parvalbumin-interneuron output synapses show spike-timing-dependent plasticity that contributes to auditory map remodeling. Neuron 99, 720–735.e6 (2018). Using paired recordings in L4 of auditory cortex, this work shows how critical period sound exposure transforms the sign of plasticity from LTD to LTP at PV+ IN to PC synapses, which may provide disinhibition during critical period plasticity.

    Article  CAS  Google Scholar 

  45. Field, R. E. et al. Heterosynaptic plasticity determines the set point for cortical excitatory–inhibitory balance. Neuron https://doi.org/10.1016/j.neuron.2020.03.002 (2020). Using electrode stimulation arrays, this work finds that, in developing auditory cortex, homosynaptic and heterosynaptic excitatory and inhibitory inputs to L5 PCs all exhibit STDP; however, compared with homosynaptic inputs, heterosynaptic inputs have a stronger influence on the set point for overall E/I balance.

    Article  Google Scholar 

  46. Wang, L. & Maffei, A. Inhibitory plasticity dictates the sign of plasticity at excitatory synapses. J. Neurosci. 34, 1083–1093 (2014).

    Article  CAS  Google Scholar 

  47. D’Amour, J. A. & Froemke, R. C. Inhibitory and excitatory spike-timing-dependent plasticity in the auditory cortex. Neuron https://doi.org/10.1016/j.neuron.2015.03.014 (2015). This work shows how both inhibitory and excitatory neocortical synapses are modified by STDP and how inhibitory plasticity depends on the initial E/I ratio, which helps maintain E/I balance.

    Article  Google Scholar 

  48. Lourenço, J. et al. Non-associative potentiation of perisomatic inhibition alters the temporal coding of neocortical layer 5 pyramidal neurons. PLoS Biol. 12, e1001903 (2014). This work shows that, in L5 PCs, the selective potentiation of perisomatic inhibition via nitric oxide retrograde signalling alters the ability to integrate excitatory inputs and improves spiking precision.

    Article  Google Scholar 

  49. Wiesel, T. N. & Hubel, D. H. Comparison of the effects of unilateral and bilateral eye closure on cortical unit responses in kittens. J. Neurophysiol. 28, 1029–1040 (1965).

    Article  CAS  Google Scholar 

  50. Kuhlman, S. J. et al. A disinhibitory microcircuit initiates critical-period plasticity in the visual cortex. Nature 501, 543–546 (2013).

    Article  CAS  Google Scholar 

  51. Lu, J. T., Li, C. Y., Zhao, J. P., Poo, M. M. & Zhang, X. H. Spike-timing-dependent plasticity of neocortical excitatory synapses on inhibitory interneurons depends on target cell type. J. Neurosci. 27, 9711–9720 (2007). This work shows that PC–MC synapses exhibit the classical temporally asymmetric STDP also found at PC–PC connections, although plasticity at these two synapse types relies on different mechanisms, whereas PC–BC synapses connections depress irrespective of relative timing.

    Article  CAS  Google Scholar 

  52. Xue, M., Atallah, B. V. & Scanziani, M. Equalizing excitation–inhibition ratios across visual cortical neurons. Nature 511, 596–600 (2014).

    Article  CAS  Google Scholar 

  53. Hennequin, G., Agnes, E. J. & Vogels, T. P. Inhibitory plasticity: balance, control, and codependence. Annu. Rev. Neurosci. 40, 557–579 (2017).

    Article  CAS  Google Scholar 

  54. Blackman, A. V., Abrahamsson, T., Costa, R. P., Lalanne, T. & Sjöström, P. J. Target cell-specific short-term plasticity in local circuits. Front. Synaptic Neurosci. 5, 1–13 (2013).

    Article  Google Scholar 

  55. Costa, R. P., Froemke, R. C., Sjöström, P. J. & van Rossum, M. C. W. Unified pre- and postsynaptic long-term plasticity enables reliable and flexible learning. eLife https://doi.org/10.7554/eLife.09457 (2015).

    Article  Google Scholar 

  56. Chistiakova, M. et al. Distinct heterosynaptic plasticity in fast spiking and non-fast-spiking inhibitory neurons in rat visual cortex. J. Neurosci. 39, 6865–6878 (2019).

    Article  CAS  Google Scholar 

  57. Zenke, F., Agnes, E. J. & Gerstner, W. Diverse synaptic plasticity mechanisms orchestrated to form and retrieve memories in spiking neural networks. Nat. Commun. 6, 6922 (2015).

    Article  CAS  Google Scholar 

  58. Chen, H. X., Jiang, M., Akakin, D. & Roper, S. N. Long-term potentiation of excitatory synapses on neocortical somatostatin-expressing interneurons. J. Neurophysiol. 102, 3251–3259 (2009).

    Article  CAS  Google Scholar 

  59. Castillo, P. E., Weisskopf, M. G. & Nicoll, R. A. The role of Ca2+ channels in hippocampal mossy fiber synaptic transmission and long-term potentiation. Neuron 12, 261–269 (1994).

    Article  CAS  Google Scholar 

  60. Seol, G. H. et al. Neuromodulators control the polarity of spike-timing-dependent synaptic plasticity. Neuron 55, 919–929 (2007).

    Article  CAS  Google Scholar 

  61. Sjöström, P. J. & Häusser, M. A cooperative switch determines the sign of synaptic plasticity in distal dendrites of neocortical pyramidal neurons. Neuron 51, 227–238 (2006).

    Article  Google Scholar 

  62. Huang, S., Huganir, R. L. & Kirkwood, A. Adrenergic gating of Hebbian spike-timing-dependent plasticity in cortical interneurons. J. Neurosci. 33, 13171–13178 (2013). This study is a prime example of a three-factor plasticity learning rule, showing how neuromodulation controls the polarity of STDP at PC synapses onto BCs and MCs in mouse visual cortex.

    Article  CAS  Google Scholar 

  63. Sarihi, A. et al. Metabotropic glutamate receptor type 5-dependent long-term potentiation of excitatory synapses on fast-spiking GABAergic neurons in mouse visual cortex. J. Neurosci. 28, 1224–1235 (2008).

    Article  CAS  Google Scholar 

  64. Ho, O. H., Delgado, J. Y. & O’Dell, T. J. Phosphorylation of proteins involved in activity-dependent forms of synaptic plasticity is altered in hippocampal slices maintained in vitro. J. Neurochem. 91, 1344–1357 (2004).

    Article  CAS  Google Scholar 

  65. Edelmann, E. & Lessmann, V. Dopamine modulates spike timing-dependent plasticity and action potential properties in CA1 pyramidal neurons of acute rat hippocampal slices. Front. Synaptic Neurosci. 3, 6 (2011).

    Article  CAS  Google Scholar 

  66. Lourenço, J. et al. Modulation of coordinated activity across cortical layers by plasticity of inhibitory synapses. Cell Rep. 30, 630–641 e635 (2020). This work shows that potentiation of perisomatic inhibition by L5 PC bursting affects information transfer across cortical layers and determines PC phase locking to cognition-relevant oscillations.

    Article  Google Scholar 

  67. Kullander, K. & Topolnik, L. Cortical disinhibitory circuits: cell types, connectivity and function. Trends Neurosci. 44, 643–657 (2021).

    Article  CAS  Google Scholar 

  68. Artinian, J. & Lacaille, J. C. Disinhibition in learning and memory circuits: new vistas for somatostatin interneurons and long-term synaptic plasticity. Brain Res. Bull. 141, 20–26 (2018).

    Article  CAS  Google Scholar 

  69. Cunha-Reis, D. & Caulino-Rocha, A. VIP modulation of hippocampal synaptic plasticity: a role for VIP receptors as therapeutic targets in cognitive decline and mesial temporal lobe epilepsy. Front. Cell. Neurosci. https://doi.org/10.3389/fncel.2020.00153 (2020).

    Article  Google Scholar 

  70. Khoshkhoo, S., Vogt, D. & Sohal, V. S. Dynamic, cell-type-specific roles for GABAergic interneurons in a mouse model of optogenetically inducible seizures. Neuron 93, 291–298 (2017).

    Article  CAS  Google Scholar 

  71. Froemke, R. C., Merzenich, M. M. & Schreiner, C. E. A synaptic memory trace for cortical receptive field plasticity. Nature 450, 425–429 (2007).

    Article  CAS  Google Scholar 

  72. Letzkus, J. J. et al. A disinhibitory microcircuit for associative fear learning in the auditory cortex. Nature 480, 331–335 (2011). This work shows that associative fear learning in auditory cortex relies on the activation of L1 INs, which in turn inhibit L2/3 PV+ INs for an overall disinhibitory effect in cortical circuits.

    Article  CAS  Google Scholar 

  73. Gentet, L. J., Avermann, M., Matyas, F., Staiger, J. F. & Petersen, C. C. Membrane potential dynamics of GABAergic neurons in the barrel cortex of behaving mice. Neuron 65, 422–435 (2010).

    Article  CAS  Google Scholar 

  74. Niell, C. M. & Stryker, M. P. Modulation of visual responses by behavioral state in mouse visual cortex. Neuron 65, 472–479 (2010).

    Article  CAS  Google Scholar 

  75. Kaneko, M. & Stryker, M. P. Sensory experience during locomotion promotes recovery of function in adult visual cortex. eLife 3, e02798 (2014).

    Article  Google Scholar 

  76. Fu, Y. et al. A cortical circuit for gain control by behavioral state. Cell 156, 1139–1152 (2014).

    Article  CAS  Google Scholar 

  77. Fu, Y., Kaneko, M., Tang, Y., Alvarez-Buylla, A. & Stryker, M. P. A cortical disinhibitory circuit for enhancing adult plasticity. eLife 4, e05558 (2015).

    Article  Google Scholar 

  78. Adler, A., Zhao, R., Shin, M. E., Yasuda, R. & Gan, W. B. Somatostatin-expressing interneurons enable and maintain learning-dependent sequential activation of pyramidal neurons. Neuron https://doi.org/10.1016/j.neuron.2019.01.036 (2019).

    Article  Google Scholar 

  79. Letzkus, J. J., Wolff, S. B. & Luthi, A. Disinhibition, a circuit mechanism for associative learning and memory. Neuron 88, 264–276 (2015).

    Article  CAS  Google Scholar 

  80. Leroy, F. et al. Enkephalin release from VIP interneurons in the hippocampal CA2/3a region mediates heterosynaptic plasticity and social memory. Mol. Psychiatry 27, 2879–2900 (2022).

    Article  CAS  Google Scholar 

  81. Woodin, M. A., Ganguly, K. & Poo, M. M. Coincident pre- and postsynaptic activity modifies GABAergic synapses by postsynaptic changes in Cl- transporter activity. Neuron 39, 807–820 (2003). Using both hippocampal cultures and acute slices, this influential study shows that coincident presynaptic and postsynaptic activity modifies GABA reversal potential locally by decreasing chloride co-transporter activity.

    Article  CAS  Google Scholar 

  82. Ormond, J. & Woodin, M. A. Disinhibition mediates a form of hippocampal long-term potentiation in area CA1. PLoS ONE 4, e7224 (2009).

    Article  Google Scholar 

  83. Ormond, J. & Woodin, M. A. Disinhibition-mediated LTP in the hippocampus is synapse specific. Front. Cell Neurosci. 5, 17 (2011).

    Article  CAS  Google Scholar 

  84. Diering, G. H. & Huganir, R. L. The AMPA receptor code of synaptic plasticity. Neuron 100, 314–329 (2018).

    Article  CAS  Google Scholar 

  85. Diaz-Alonso, J. & Nicoll, R. A. AMPA receptor trafficking and LTP: carboxy-termini, amino-termini and TARPs. Neuropharmacology 197, 108710 (2021).

    Article  CAS  Google Scholar 

  86. Kurotani, T., Yamada, K., Yoshimura, Y., Crair, M. C. & Komatsu, Y. State-dependent bidirectional modification of somatic inhibition in neocortical pyramidal cells. Neuron 57, 905–916 (2008).

    Article  CAS  Google Scholar 

  87. Komatsu, Y. GABAB receptors, monoamine receptors, and postsynaptic inositol trisphosphate-induced Ca2+ release are involved in the induction of long-term potentiation at visual cortical inhibitory synapses. J. Neurosci. 16, 6342–6352 (1996).

    Article  CAS  Google Scholar 

  88. Sjöström, P. J. & Nelson, S. B. Spike timing, calcium signals and synaptic plasticity. Curr. Opin. Neurobiol. 12, 305–314 (2002).

    Article  Google Scholar 

  89. Marsden, K. C., Shemesh, A., Bayer, K. U. & Carroll, R. C. Selective translocation of Ca2+/calmodulin protein kinase IIα (CaMKIIα) to inhibitory synapses. Proc. Natl Acad. Sci. USA 107, 20559–20564 (2010).

    Article  CAS  Google Scholar 

  90. Marsden, K. C., Beattie, J. B., Friedenthal, J. & Carroll, R. C. NMDA receptor activation potentiates inhibitory transmission through GABA receptor-associated protein-dependent exocytosis of GABAA receptors. J. Neurosci. 27, 14326–14337 (2007).

    Article  CAS  Google Scholar 

  91. Petrini, E. M. et al. Synaptic recruitment of gephyrin regulates surface GABAA receptor dynamics for the expression of inhibitory LTP. Nat. Commun. 5, 3921 (2014).

    Article  CAS  Google Scholar 

  92. Chiu, C. Q. et al. Input-specific NMDAR-dependent potentiation of dendritic GABAergic inhibition. Neuron 97, 368–377 e363 (2018). By combining optogenetics with electrophysiology, this work demonstrates how activation of NMDARs selectively potentiates inhibition from SST+ INs onto neocortical PCs, revealing a candidate mechanism for regulating the E/I balance specifically in PC dendrites.

    Article  CAS  Google Scholar 

  93. Pafundo, D. E., Miyamae, T., Lewis, D. A. & Gonzalez-Burgos, G. Presynaptic effects of N-methyl-d-aspartate receptors enhance parvalbumin cell-mediated inhibition of pyramidal cells in mouse prefrontal cortex. Biol. Psychiatry 84, 460–470 (2018).

    Article  CAS  Google Scholar 

  94. Wong, H. H., Rannio, S., Jones, V., Thomazeau, A. & Sjöström, P. J. NMDA receptors in axons: there’s no coincidence. J. Physiol. 599, 367–387 (2021).

    Article  CAS  Google Scholar 

  95. Bouvier, G., Larsen, R. S., Rodriguez-Moreno, A., Paulsen, O. & Sjöström, P. J. Towards resolving the presynaptic NMDA receptor debate. Curr. Opin. Neurobiol. 51, 1–7 (2018).

    Article  CAS  Google Scholar 

  96. Dore, K. et al. Unconventional NMDA receptor signaling. J. Neurosci. 37, 10800–10807 (2017).

    Article  CAS  Google Scholar 

  97. Buchanan, K. A. et al. Target-specific expression of presynaptic NMDA receptors in neocortical microcircuits. Neuron 75, 451–466 (2012).

    Article  CAS  Google Scholar 

  98. Kullmann, D. M. & Lamsa, K. P. Long-term synaptic plasticity in hippocampal interneurons. Nat. Rev. Neurosci. 8, 687–699 (2007).

    Article  CAS  Google Scholar 

  99. Szabo, A. et al. Calcium-permeable AMPA receptors provide a common mechanism for LTP in glutamatergic synapses of distinct hippocampal interneuron types. J. Neurosci. 32, 6511–6516 (2012).

    Article  CAS  Google Scholar 

  100. Oren, I., Nissen, W., Kullmann, D. M., Somogyi, P. & Lamsa, K. P. Role of ionotropic glutamate receptors in long-term potentiation in rat hippocampal CA1 oriens-lacunosum moleculare interneurons. J. Neurosci. 29, 939–950 (2009).

    Article  CAS  Google Scholar 

  101. Nissen, W., Szabo, A., Somogyi, J., Somogyi, P. & Lamsa, K. P. Cell type-specific long-term plasticity at glutamatergic synapses onto hippocampal interneurons expressing either parvalbumin or CB1 cannabinoid receptor. J. Neurosci. 30, 1337–1347 (2010).

    Article  CAS  Google Scholar 

  102. Camiré, O. & Topolnik, L. Dendritic calcium nonlinearities switch the direction of synaptic plasticity in fast-spiking interneurons. J. Neurosci. 34, 3864–3877 (2014). This ground-breaking study shows how, in the mouse hippocampal CA1 region, TBS of PC–BC connections elicits LTP when paired with subthreshold BC activation but evokes LTD when paired with BC spiking.

    Article  Google Scholar 

  103. Toth, K. & McBain, C. J. Target-specific expression of pre- and postsynaptic mechanisms. J. Physiol. 525, 41–51 (2000).

    Article  CAS  Google Scholar 

  104. Maccaferri, G., Toth, K. & McBain, C. J. Target-specific expression of presynaptic mossy fiber plasticity. Science 279, 1368–1370 (1998).

    Article  CAS  Google Scholar 

  105. Lalanne, T., Oyrer, J., Farrant, M. & Sjöström, P. J. Synapse type-dependent expression of calcium-permeable AMPA receptors. Front. Synaptic Neurosci. 10, 34 (2018).

    Article  CAS  Google Scholar 

  106. Lalanne, T. et al. Synapse-specific expression of calcium-permeable AMPA receptors in neocortical layer 5. J. Physiol. 594, 837–861 (2016).

    Article  CAS  Google Scholar 

  107. Vasuta, C. et al. Metaplastic regulation of CA1 schaffer collateral pathway plasticity by hebbian MGluR1a-mediated plasticity at excitatory synapses onto somatostatin-expressing interneurons. eNeuro https://doi.org/10.1523/ENEURO.0051-15.2015 (2015).

    Article  Google Scholar 

  108. Perez, Y., Morin, F. & Lacaille, J. C. A Hebbian form of long-term potentiation dependent on mGluR1a in hippocampal inhibitory interneurons. Proc. Natl Acad. Sci. USA 98, 9401–9406 (2001).

    Article  CAS  Google Scholar 

  109. Lapointe, V. et al. Synapse-specific mGluR1-dependent long-term potentiation in interneurones regulates mouse hippocampal inhibition. J. Physiol. 555, 125–135 (2004).

    Article  CAS  Google Scholar 

  110. Topolnik, L., Azzi, M., Morin, F., Kougioumoutzakis, A. & Lacaille, J. C. mGluR1/5 subtype-specific calcium signalling and induction of long-term potentiation in rat hippocampal oriens/alveus interneurones. J. Physiol. 575, 115–131 (2006).

    Article  CAS  Google Scholar 

  111. Hasselmo, M. E. The role of acetylcholine in learning and memory. Curr. Opin. Neurobiol. 16, 710–715 (2006).

    Article  CAS  Google Scholar 

  112. Bear, M. F. & Singer, W. Modulation of visual cortical plasticity by acetylcholine and noradrenaline. Nature 320, 172–176 (1986).

    Article  CAS  Google Scholar 

  113. Takkala, P. & Woodin, M. A. Muscarinic acetylcholine receptor activation prevents disinhibition-mediated LTP in the hippocampus. Front. Cell Neurosci. 7, 16 (2013).

    Article  CAS  Google Scholar 

  114. Mitsushima, D., Sano, A. & Takahashi, T. A cholinergic trigger drives learning-induced plasticity at hippocampal synapses. Nat. Commun. 4, 2760 (2013). This work shows that contextual fear learning enhances the strength of inhibitory inputs onto hippocampal PCs through nAChR activation but not mAChR activation.

    Article  Google Scholar 

  115. Morales-Weil, K. et al. Priming of GABAergic long-term potentiation by muscarinic receptors. Neuroscience 428, 242–251 (2020).

    Article  CAS  Google Scholar 

  116. Griguoli, M. & Cherubini, E. Regulation of hippocampal inhibitory circuits by nicotinic acetylcholine receptors. J. Physiol. 590, 655–666 (2012).

    Article  CAS  Google Scholar 

  117. Castillo, P. E., Younts, T. J., Chavez, A. E. & Hashimotodani, Y. Endocannabinoid signaling and synaptic function. Neuron 76, 70–81 (2012).

    Article  CAS  Google Scholar 

  118. Castillo, P. E., Chiu, C. Q. & Carroll, R. C. Long-term plasticity at inhibitory synapses. Curr. Opin. Neurobiol. 21, 328–338 (2011).

    Article  CAS  Google Scholar 

  119. Piette, C., Cui, Y., Gervasi, N. & Venance, L. Lights on endocannabinoid-mediated synaptic potentiation. Front. Mol. Neurosci. 13, 132 (2020).

    Article  CAS  Google Scholar 

  120. Sjöström, P. J., Turrigiano, G. G. & Nelson, S. B. Neocortical LTD via coincident activation of presynaptic NMDA and cannabinoid receptors. Neuron 39, 641–654 (2003).

    Article  Google Scholar 

  121. Chevaleyre, V. & Castillo, P. E. Heterosynaptic LTD of hippocampal GABAergic synapses: a novel role of endocannabinoids in regulating excitability. Neuron 38, 461–472 (2003).

    Article  CAS  Google Scholar 

  122. Jiang, B. et al. The maturation of GABAergic transmission in visual cortex requires endocannabinoid-mediated LTD of inhibitory inputs during a critical period. Neuron 66, 248–259 (2010).

    Article  CAS  Google Scholar 

  123. Gibson, J. R., Bartley, A. F. & Huber, K. M. Role for the subthreshold currents ILeak and IH in the homeostatic control of excitability in neocortical somatostatin-positive inhibitory neurons. J. Neurophysiol. 96, 420–432 (2006). This work shows that an increase in excitability of SST+ INs in somatosensory cortex following a 2.5-day pharmacological blockade of spiking, which ultimately increases inhibitory drive, is an example of a non-homeostatic response to reduced circuit activity.

    Article  CAS  Google Scholar 

  124. Vogels, T. P., Rajan, K. & Abbott, L. F. Neural network dynamics. Annu. Rev. Neurosci. 28, 357–376 (2005).

    Article  CAS  Google Scholar 

  125. Turrigiano, G. G. & Nelson, S. B. Homeostatic plasticity in the developing nervous system. Nat. Rev. Neurosci. 5, 97–107 (2004).

    Article  CAS  Google Scholar 

  126. Mongillo, G., Curti, E., Romani, S. & Amit, D. J. Learning in realistic networks of spiking neurons and spike-driven plastic synapses. Eur. J. Neurosci. 21, 3143–3160 (2005).

    Article  Google Scholar 

  127. Royer, S. & Paré, D. Conservation of total synaptic weight through balanced synaptic depression and potentiation. Nature 422, 518–522 (2003).

    Article  CAS  Google Scholar 

  128. Turrigiano, G., Abbott, L. F. & Marder, E. Activity-dependent changes in the intrinsic properties of cultured neurons. Science 264, 974–977 (1994).

    Article  CAS  Google Scholar 

  129. Turrigiano, G. G., Leslie, K. R., Desai, N. S., Rutherford, L. C. & Nelson, S. B. Activity-dependent scaling of quantal amplitude in neocortical neurons. Nature 391, 892–896 (1998).

    Article  CAS  Google Scholar 

  130. Kilman, V., van Rossum, M. C. & Turrigiano, G. G. Activity deprivation reduces miniature IPSC amplitude by decreasing the number of postsynaptic GABAA receptors clustered at neocortical synapses. J. Neurosci. 22, 1328–1337 (2002).

    Article  CAS  Google Scholar 

  131. Echegoyen, J., Neu, A., Graber, K. D. & Soltesz, I. Homeostatic plasticity studied using in vivo hippocampal activity-blockade: synaptic scaling, intrinsic plasticity and age-dependence. PLoS ONE 2, e700 (2007).

    Article  Google Scholar 

  132. Wetmore, C., Olson, L. & Bean, A. J. Regulation of brain-derived neurotrophic factor (BDNF) expression and release from hippocampal neurons is mediated by non-NMDA type glutamate receptors. J. Neurosci. 14, 1688–1700 (1994).

    Article  CAS  Google Scholar 

  133. Rutherford, L. C., Nelson, S. B. & Turrigiano, G. G. BDNF has opposite effects on the quantal amplitude of pyramidal neuron and interneuron excitatory synapses. Neuron 21, 521–530 (1998).

    Article  CAS  Google Scholar 

  134. Hengen, K. B., Lambo, M. E., Van Hooser, S. D., Katz, D. B. & Turrigiano, G. G. Firing rate homeostasis in visual cortex of freely behaving rodents. Neuron 80, 335–342 (2013).

    Article  CAS  Google Scholar 

  135. Keck, T., Hubener, M. & Bonhoeffer, T. Interactions between synaptic homeostatic mechanisms: an attempt to reconcile BCM theory, synaptic scaling, and changing excitation/inhibition balance. Curr. Opin. Neurobiol. 43, 87–93 (2017).

    Article  CAS  Google Scholar 

  136. Chen, J. L. et al. Structural basis for the role of inhibition in facilitating adult brain plasticity. Nat. Neurosci. 14, 587–594 (2011).

    Article  CAS  Google Scholar 

  137. Chen, J. L. et al. Clustered dynamics of inhibitory synapses and dendritic spines in the adult neocortex. Neuron 74, 361–373 (2012).

    Article  CAS  Google Scholar 

  138. van Versendaal, D. et al. Elimination of inhibitory synapses is a major component of adult ocular dominance plasticity. Neuron 74, 374–383 (2012).

    Article  Google Scholar 

  139. Debanne, D., Inglebert, Y. & Russier, M. Plasticity of intrinsic neuronal excitability. Curr. Opin. Neurobiol. 54, 73–82 (2019).

    Article  CAS  Google Scholar 

  140. Desai, N. S., Rutherford, L. C. & Turrigiano, G. G. Plasticity in the intrinsic excitability of cortical pyramidal neurons. Nat. Neurosci. 2, 515–520 (1999).

    Article  CAS  Google Scholar 

  141. MacLean, J. N., Zhang, Y., Johnson, B. R. & Harris-Warrick, R. M. Activity-independent homeostasis in rhythmically active neurons. Neuron 37, 109–120 (2003).

    Article  CAS  Google Scholar 

  142. Marder, E. & Prinz, A. A. Current compensation in neuronal homeostasis. Neuron 37, 2–4 (2003).

    Article  CAS  Google Scholar 

  143. Ross, S. T. & Soltesz, I. Long-term plasticity in interneurons of the dentate gyrus. Proc. Natl Acad. Sci. USA 98, 8874 (2001).

    Article  CAS  Google Scholar 

  144. Dasgupta, D. & Sikdar, S. K. Calcium permeable AMPA receptor-dependent long lasting plasticity of intrinsic excitability in fast spiking interneurons of the dentate gyrus decreases inhibition in the granule cell layer. Hippocampus 25, 269–285 (2015).

    Article  CAS  Google Scholar 

  145. Dasgupta, D. & Sikdar, S. K. Heterogeneous network dynamics in an excitatory–inhibitory network model by distinct intrinsic mechanisms in the fast spiking interneurons. Brain Res. 1714, 27–44 (2019).

    Article  CAS  Google Scholar 

  146. Campanac, E. et al. Enhanced intrinsic excitability in basket cells maintains excitatory–inhibitory balance in hippocampal circuits. Neuron 77, 712–722 (2013).

    Article  CAS  Google Scholar 

  147. Mansvelder, H. D., Verhoog, M. B. & Goriounova, N. A. Synaptic plasticity in human cortical circuits: cellular mechanisms of learning and memory in the human brain? Curr. Opin. Neurobiol. 54, 186–193 (2019).

    Article  CAS  Google Scholar 

  148. Chittajallu, R. et al. Activity-dependent tuning of intrinsic excitability in mouse and human neurogliaform cells. eLife https://doi.org/10.7554/eLife.57571 (2020).

    Article  Google Scholar 

  149. Suzuki, N., Tang, C. & Bekkers, J. Persistent barrage firing in cortical interneurons can be induced in vivo and may be important for the suppression of epileptiform activity. Front. Cell. Neurosci. https://doi.org/10.3389/fncel.2014.00076 (2014).

    Article  Google Scholar 

  150. Desai, N. S., Nelson, S. B. & Turrigiano, G. G. Activity-dependent regulation of excitability in rat visual cortical neurons. Neurocomputing 26–27, 101–106 (1999).

    Article  Google Scholar 

  151. Desai, N. S., Rutherford, L. C. & Turrigiano, G. G. BDNF regulates the intrinsic excitability of cortical neurons. Learn. Mem. 6, 284–291 (1999).

    Article  CAS  Google Scholar 

  152. Lee, S.-H., Land, P. W. & Simons, D. J. Layer- and cell-type-specific effects of neonatal whisker-trimming in adult rat barrel cortex. J. Neurophysiol. 97, 4380–4385 (2007).

    Article  Google Scholar 

  153. Bartley, A. F., Huang, Z. J., Huber, K. M. & Gibson, J. R. Differential activity-dependent, homeostatic plasticity of two neocortical inhibitory circuits. J. Neurophysiol. 100, 1983–1994 (2008).

    Article  Google Scholar 

  154. Sun, Q.-Q. Experience-dependent intrinsic plasticity in interneurons of barrel cortex layer IV. J. Neurophysiol. 102, 2955–2973 (2009).

    Article  Google Scholar 

  155. Dehorter, N. et al. Tuning of fast-spiking interneuron properties by an activity-dependent transcriptional switch. Science 349, 1216 (2015).

    Article  CAS  Google Scholar 

  156. Gainey, M. A., Aman, J. W. & Feldman, D. E. Rapid disinhibition by adjustment of PV intrinsic excitability during whisker map plasticity in mouse S1. J. Neurosci. 38, 4749 (2018). This work shows that whisker deprivation reduces the intrinsic excitability of mouse barrel cortex PV+ INs, which leads to disinhibition and to homeostatic stabilization of feedforward E/I balance in PCs.

    Article  CAS  Google Scholar 

  157. Miller, M. N., Okaty, B. W., Kato, S. & Nelson, S. B. Activity-dependent changes in the firing properties of neocortical fast-spiking interneurons in the absence of large changes in gene expression. Dev. Neurobiol. 71, 62–70 (2011).

    Article  Google Scholar 

  158. Zhong, P. & Yan, Z. Differential regulation of the excitability of prefrontal cortical fast-spiking interneurons and pyramidal neurons by serotonin and fluoxetine. PLoS ONE 6, e16970 (2011).

    Article  CAS  Google Scholar 

  159. Takesian, A. E., Kotak, V. C. & Sanes, D. H. Age-dependent effect of hearing loss on cortical inhibitory synapse function. J. Neurophysiol. 107, 937–947 (2012).

    Article  CAS  Google Scholar 

  160. Turrigiano, G. G. & Nelson, S. B. Hebb and homeostasis in neuronal plasticity. Curr. Opin. Neurobiol. 10, 358–364 (2000).

    Article  CAS  Google Scholar 

  161. Itami, C., Kimura, F. & Nakamura, S. Brain-derived neurotrophic factor regulates the maturation of layer 4 fast-spiking cells after the second postnatal week in the developing barrel cortex. J. Neurosci. 27, 2241–2252 (2007).

    Article  CAS  Google Scholar 

  162. Okaty, B. W., Miller, M. N., Sugino, K., Hempel, C. M. & Nelson, S. B. Transcriptional and electrophysiological maturation of neocortical fast-spiking GABAergic interneurons. J. Neurosci. 29, 7040–7052 (2009).

    Article  CAS  Google Scholar 

  163. Doischer, D. et al. Postnatal differentiation of basket cells from slow to fast signaling devices. J. Neurosci. 28, 12956–12968 (2008).

    Article  CAS  Google Scholar 

  164. Chattopadhyaya, B. et al. Experience and activity-dependent maturation of perisomatic GABAergic innervation in primary visual cortex during a postnatal critical period. J. Neurosci. 24, 9598–9611 (2004).

    Article  CAS  Google Scholar 

  165. Takesian, A. E., Kotak, V. C., Sharma, N. & Sanes, D. H. Hearing loss differentially affects thalamic drive to two cortical interneuron subtypes. J. Neurophysiol. 110, 999–1008 (2013).

    Article  Google Scholar 

  166. Goldberg, E. M. et al. K+ channels at the axon initial segment dampen near-threshold excitability of neocortical fast-spiking GABAergic interneurons. Neuron 58, 387–400 (2008).

    Article  CAS  Google Scholar 

  167. Wonders, C. P. & Anderson, S. A. The origin and specification of cortical interneurons. Nat. Rev. Neurosci. 7, 687–696 (2006).

    Article  CAS  Google Scholar 

  168. Flames, N. et al. Delineation of multiple subpallial progenitor domains by the combinatorial expression of transcriptional codes. J. Neurosci. 27, 9682–9695 (2007).

    Article  CAS  Google Scholar 

  169. Vullhorst, D. et al. Selective expression of ErbB4 in interneurons, but not pyramidal cells, of the rodent hippocampus. J. Neurosci. 29, 12255 (2009).

    Article  CAS  Google Scholar 

  170. Wen, L. et al. Neuregulin 1 regulates pyramidal neuron activity via ErbB4 in parvalbumin-positive interneurons. Proc. Natl Acad. Sci. USA 107, 1211 (2010).

    Article  CAS  Google Scholar 

  171. Li, K.-X. et al. Neuregulin 1 regulates excitability of fast-spiking neurons through Kv1.1 and acts in epilepsy. Nat. Neurosci. 15, 267–273 (2012).

    Article  CAS  Google Scholar 

  172. Zhang, W. & Linden, D. J. The other side of the engram: experience-driven changes in neuronal intrinsic excitability. Nat. Rev. Neurosci. 4, 885–900 (2003).

    Article  CAS  Google Scholar 

  173. Wang, Z., Xu, N. L., Wu, C. P., Duan, S. & Poo, M. M. Bidirectional changes in spatial dendritic integration accompanying long-term synaptic modifications. Neuron 37, 463–472 (2003).

    Article  CAS  Google Scholar 

  174. Frick, A., Magee, J. & Johnston, D. LTP is accompanied by an enhanced local excitability of pyramidal neuron dendrites. Nat. Neurosci. 7, 126–135 (2004).

    Article  CAS  Google Scholar 

  175. Campanac, E., Daoudal, G., Ankri, N. & Debanne, D. Downregulation of dendritic Ih in CA1 pyramidal neurons after LTP. J. Neurosci. 28, 8635–8643 (2008).

    Article  CAS  Google Scholar 

  176. Daoudal, G. & Debanne, D. Long-term plasticity of intrinsic excitability: learning rules and mechanisms. Learn. Mem. 10, 456–465 (2003).

    Article  Google Scholar 

  177. Hensch, T. K. & Quinlan, E. M. Critical periods in amblyopia. Vis. Neurosci. 35, E014 (2018).

    Article  Google Scholar 

  178. Sjöström, P. J., Turrigiano, G. G. & Nelson, S. B. Rate, timing, and cooperativity jointly determine cortical synaptic plasticity. Neuron 32, 1149–1164 (2001).

    Article  Google Scholar 

  179. Pawlak, V., Wickens, J. R., Kirkwood, A. & Kerr, J. N. D. Timing is not everything: neuromodulation opens the STDP gate. Front. Synaptic Neurosci. 2, 146 (2010).

    Article  Google Scholar 

  180. Larsen, R. S., Rao, D., Manis, P. B. & Philpot, B. D. STDP in the developing sensory neocortex. Front. Synaptic Neurosci. 2, 9 (2010).

    Google Scholar 

  181. Larsen, R. S. et al. Synapse-specific control of experience-dependent plasticity by presynaptic NMDA receptors. Neuron 83, 879–893 (2014).

    Article  CAS  Google Scholar 

  182. Stent, G. S. A physiological mechanism for Hebb’s postulate of learning. Proc. Natl Acad. Sci. Usa. 70, 997–1001 (1973).

    Article  CAS  Google Scholar 

  183. Kilb, W. When are depolarizing GABAergic responses excitatory? Front. Mol. Neurosci. https://doi.org/10.3389/fnmol.2021.747835 (2021).

    Article  Google Scholar 

  184. Ben-Ari, Y., Gaiarsa, J. L., Tyzio, R. & Khazipov, R. GABA: a pioneer transmitter that excites immature neurons and generates primitive oscillations. Physiol. Rev. 87, 1215–1284 (2007).

    Article  CAS  Google Scholar 

  185. Bonifazi, P. et al. GABAergic hub neurons orchestrate synchrony in developing hippocampal networks. Science 326, 1419–1424 (2009).

    Article  CAS  Google Scholar 

  186. van Welie, I., Smith, I. T. & Watt, A. J. The metamorphosis of the developing cerebellar microcircuit. Curr. Opin. Neurobiol. 21, 245–253 (2011).

    Article  Google Scholar 

  187. Zilberter, M. Reality of inhibitory GABA in neonatal brain: time to rewrite the textbooks? J. Neurosci. 36, 10242–10244 (2016).

    Article  Google Scholar 

  188. Haam, J. et al. GABA is excitatory in adult vasopressinergic neuroendocrine cells. J. Neurosci. 32, 572–582 (2012).

    Article  CAS  Google Scholar 

  189. Mongillo, G., Rumpel, S. & Loewenstein, Y. Inhibitory connectivity defines the realm of excitatory plasticity. Nat. Neurosci. 21, 1463–1470 (2018).

    Article  CAS  Google Scholar 

  190. Minsky, M. L. in Computers and Thought (eds E. A. Feigenbaum & J. Feldman) 406-450 (McGraw-Hill, 1963).

  191. Sacramento, J., Costa, R. P., Bengio, Y. & Senn, W. in Advances in Neural Information Processing Systems 31 (eds Bengio, S., et al.) 8721–8732 (Curran Associates, Inc., 2018).

  192. Greedy, W., Zhu, H. W., Pemberton, J., Mellor, J. & Costa, R. P. Single-phase deep learning in cortico-cortical networks. Preprint at arXiv arXiv:2206.11769 (2022).

  193. Sejnowski, T. J. & Rosenberg, C. R. in Neurocomputing: Foundations of Research 661–672 (Bradford Books, 1988).

  194. Lecun, Y. et al. Handwritten digit recognition with a back-propagation network. In Advances in Neural Information Processing Systems 1989 (1990).

  195. Rumelhart, D. E., Hinton, G. E. & Williams, R. J. Learning representations by back-propagating errors. Nature 323, 533 (1986).

    Article  Google Scholar 

  196. Roelfsema, P. R. & Holtmaat, A. Control of synaptic plasticity in deep cortical networks. Nat. Rev. Neurosci. 19, 166–180 (2018).

    Article  CAS  Google Scholar 

  197. Halvagal, M. S. & Zenke, F. The combination of Hebbian and predictive plasticity learns invariant object representations in deep sensory networks. Preprint at bioRxiv https://doi.org/10.1101/2022.03.17.484712 (2022).

  198. Journé, A., Rodriguez, H. G., Guo, Q. & Moraitis, T. Hebbian deep learning without feedback. Preprint at arXiv arXiv:2209.11883 (2022).

  199. Illing, B., Ventura, J., Bellec, G. & Gerstner, W. Local plasticity rules can learn deep representations using self-supervised contrastive predictions. In Advances in Neural Information Processing Systems 34, 30365–30379 (2021).

    Google Scholar 

  200. Whittington, J. C. R. & Bogacz, R. An approximation of the error backpropagation algorithm in a predictive coding network with local Hebbian synaptic plasticity. Neural Comput. 29, 1229–1262 (2017).

    Article  Google Scholar 

  201. Crick, F. The recent excitement about neural networks. Nature 337, 129–132 (1989).

    Article  CAS  Google Scholar 

  202. Grossberg, S. Competitive learning: from interactive activation to adaptive resonance. Cogn. Sci. 11, 23–63 (1987).

    Article  Google Scholar 

  203. Whittington, J. C. R. & Bogacz, R. Theories of error back-propagation in the brain. Trends Cogn. Sci. 23, 235–250 (2019).

    Article  Google Scholar 

  204. Richards, B. A. & Lillicrap, T. P. Dendritic solutions to the credit assignment problem. Curr. Opin. Neurobiol. 54, 28–36 (2018).

    Article  Google Scholar 

  205. Richards, B. A. et al. A deep learning framework for neuroscience. Nat. Neurosci. 22, 1761–1770 (2019).

    Article  CAS  Google Scholar 

  206. Marblestone, A. H., Wayne, G. & Kording, K. P. Toward an integration of deep learning and neuroscience. Front. Comput. Neurosci. 10, 94 (2016).

    Article  Google Scholar 

  207. Tripp, B. & Eliasmith, C. Function approximation in inhibitory networks. Neural Netw. 77, 95–106 (2016).

    Article  Google Scholar 

  208. Payeur, A., Guerguiev, J., Zenke, F., Richards, B. A. & Naud, R. Burst-dependent synaptic plasticity can coordinate learning in hierarchical circuits. Nat. Neurosci. 24, 1010–1019 (2021).

    Article  CAS  Google Scholar 

  209. Mercier, M. S., Magloire, V., Cornford, J. H. & Kullmann, D. M. Long-term potentiation in neurogliaform interneurons modulates excitation-inhibition balance in the temporoammonic pathway. J. Physiol. https://doi.org/10.1113/JP282753 (2022).

    Article  Google Scholar 

  210. Khan, A. G. et al. Distinct learning-induced changes in stimulus selectivity and interactions of GABAergic interneuron classes in visual cortex. Nat. Neurosci. 21, 851–859 (2018).

    Article  CAS  Google Scholar 

  211. Williams, L. E. & Holtmaat, A. Higher-order thalamocortical inputs gate synaptic long-term potentiation via disinhibition. Neuron 101, 91–102.e4 (2019).

    Article  CAS  Google Scholar 

  212. Jasper, P. et al. Learning and attention increase visual response selectivity through distinct mechanisms. Neuron 110, 686–697.e6 (2022).

    Article  Google Scholar 

  213. Markram, H., Wang, Y. & Tsodyks, M. Differential signaling via the same axon of neocortical pyramidal neurons. Proc. Natl Acad. Sci. USA 95, 5323–5328 (1998).

    Article  CAS  Google Scholar 

  214. Campagnola, L. et al. Local connectivity and synaptic dynamics in mouse and human neocortex. Science 375, eabj5861 (2022).

    Article  CAS  Google Scholar 

  215. Kodandaramaiah, S. B., Franzesi, G. T., Chow, B. Y., Boyden, E. S. & Forest, C. R. Automated whole-cell patch-clamp electrophysiology of neurons in vivo. Nat. Methods 9, 585–587 (2012).

    Article  CAS  Google Scholar 

  216. Annecchino, L. A. & Schultz, S. R. Progress in automating patch clamp cellular physiology. Brain Neurosci. Adv. 2, 2398212818776561 (2018).

    Article  Google Scholar 

  217. Perin, R. & Markram, H. A computer-assisted multi-electrode patch-clamp system. JoVE https://doi.org/10.3791/50630 (2013).

    Article  Google Scholar 

  218. Lalanne, T., Abrahamsson, T. & Sjöström, P. J. Using multiple whole-cell recordings to study spike-timing-dependent plasticity in acute neocortical slices. CSH Protoc. 6, 573–583 (2016).

    Google Scholar 

  219. Song, S., Sjöström, P. J., Reigl, M., Nelson, S. & Chklovskii, D. B. Highly nonrandom features of synaptic connectivity in local cortical circuits. PLoS Biol. 3, e68 (2005).

    Article  Google Scholar 

  220. Zhang, Y. P. & Oertner, T. G. Optical induction of synaptic plasticity using a light-sensitive channel. Nat. Methods 4, 139–141 (2007).

    Article  CAS  Google Scholar 

  221. Emiliani, V., Cohen, A. E., Deisseroth, K. & Häusser, M. All-optical interrogation of neural circuits. J. Neurosci. 35, 13917–13926 (2015).

    Article  CAS  Google Scholar 

  222. Cela, E. & Sjöström, P. J. Novel optogenetic approaches in epilepsy research. Front. Neurosci. https://doi.org/10.3389/fnins.2019.00947 (2019).

    Article  Google Scholar 

  223. Cela, E. et al. An optogenetic kindling model of neocortical epilepsy. Sci. Rep. 9, 5236 (2019).

    Article  Google Scholar 

  224. Marin, O. Interneuron dysfunction in psychiatric disorders. Nat. Rev. Neurosci. 13, 107–120 (2012).

    Article  CAS  Google Scholar 

  225. Cao, W. et al. Gamma oscillation dysfunction in mPFC leads to social deficits in neuroligin 3 R451C knockin mice. Neuron 98, 670 (2018).

    Article  CAS  Google Scholar 

  226. Chao, H. T. et al. Dysfunction in GABA signalling mediates autism-like stereotypies and Rett syndrome phenotypes. Nature 468, 263–269 (2010).

    Article  CAS  Google Scholar 

  227. Tabuchi, K. et al. A neuroligin-3 mutation implicated in autism increases inhibitory synaptic transmission in mice. Science 318, 71–76 (2007).

    Article  CAS  Google Scholar 

  228. Lewis, D. A., Hashimoto, T. & Volk, D. W. Cortical inhibitory neurons and schizophrenia. Nat. Rev. Neurosci. 6, 312–324 (2005).

    Article  CAS  Google Scholar 

  229. Del Pino, I. et al. Erbb4 deletion from fast-spiking interneurons causes schizophrenia-like phenotypes. Neuron 79, 1152–1168 (2013).

    Article  Google Scholar 

  230. Mukherjee, A., Carvalho, F., Eliez, S. & Caroni, P. Long-lasting rescue of network and cognitive dysfunction in a genetic Schizophrenia model. Cell 178, 1387–1402.e14 (2019).

    Article  CAS  Google Scholar 

  231. Kempter, R., Gerstner, W. & van Hemmen, J. L. Hebbian learning and spiking neurons. Phys. Rev. E 59, 4498–4514 (1999).

    Article  CAS  Google Scholar 

  232. Gerstner, W., Kempter, R., van Hemmen, J. L. & Wagner, H. A neuronal learning rule for sub-millisecond temporal coding. Nature 383, 76–81 (1996).

    Article  CAS  Google Scholar 

  233. Barack, D. L. et al. A call for more clarity around causality in neuroscience. Trends Neurosci. https://doi.org/10.1016/j.tins.2022.06.003 (2022).

    Article  Google Scholar 

  234. Chistiakova, M., Bannon, N. M., Bazhenov, M. & Volgushev, M. Heterosynaptic plasticity: multiple mechanisms and multiple roles. Neuroscientist 20, 483–498 (2014).

    Article  Google Scholar 

  235. Andersen, P., Sundberg, S. H., Sveen, O. & Wigstrom, H. Specific long-lasting potentiation of synaptic transmission in hippocampal slices. Nature 266, 736–737 (1977).

    Article  CAS  Google Scholar 

  236. Schuman, E. M. Synapse specificity and long-term information storage. Neuron 18, 339–342 (1997).

    Article  CAS  Google Scholar 

  237. Alemi, A., Baldassi, C., Brunel, N. & Zecchina, R. A three-threshold learning rule approaches the maximal capacity of recurrent neural networks. PLoS Comput. Biol. 11, e1004439 (2015).

    Article  Google Scholar 

  238. Engert, F. & Bonhoeffer, T. Synapse specificity of long-term potentiation breaks down at short distances. Nature 388, 279–284 (1997).

    Article  CAS  Google Scholar 

  239. Harvey, C. D. & Svoboda, K. Locally dynamic synaptic learning rules in pyramidal neuron dendrites. Nature 450, 1195–1200 (2007).

    Article  CAS  Google Scholar 

  240. Schuman, E. M. & Madison, D. V. Locally distributed synaptic potentiation in the hippocampus. Science 263, 532–536 (1994).

    Article  CAS  Google Scholar 

  241. Lynch, G. S., Dunwiddie, T. & Gribkoff, V. Heterosynaptic depression: a postsynaptic correlate of long-term potentiation. Nature 266, 737–739 (1977).

    Article  CAS  Google Scholar 

  242. Bramham, C. R. & Srebro, B. Induction of long-term depression and potentiation by low- and high-frequency stimulation in the dentate area of the anesthetized rat: magnitude, time course and EEG. Brain Res. 405, 100–107 (1987).

    Article  CAS  Google Scholar 

  243. Dudek, S. M. & Bear, M. F. Homosynaptic long-term depression in area CA1 of hippocampus and effects of N-methyl-d-aspartate receptor blockade. Proc. Natl Acad. Sci. Usa. 89, 4363–4367 (1992).

    Article  CAS  Google Scholar 

  244. Mulkey, R. M. & Malenka, R. C. Mechanisms underlying induction of homosynaptic long-term depression in area CA1 of the hippocampus. Neuron 9, 967–975 (1992).

    Article  CAS  Google Scholar 

  245. Naraghi, M. & Neher, E. Linearized buffered Ca2+ diffusion in microdomains and its implications for calculation of [Ca2+] at the mouth of a calcium channel. J. Neurosci. 17, 6961–6973 (1997).

    Article  CAS  Google Scholar 

  246. Kaiser, K. M., Lübke, J., Zilberter, Y. & Sakmann, B. Postsynaptic calcium influx at single synaptic contacts between pyramidal neurons and bitufted interneurons in layer 2/3 of rat neocortex is enhanced by backpropagating action potentials. J. Neurosci. 24, 1319–1329 (2004).

    Article  CAS  Google Scholar 

  247. Nicoll, R. A. & Schmitz, D. Synaptic plasticity at hippocampal mossy fibre synapses. Nat. Rev. Neurosci. 6, 863–876 (2005).

    Article  CAS  Google Scholar 

  248. Foncelle, A. et al. Modulation of spike-timing dependent plasticity: towards the inclusion of a third factor in computational models. Front. Comput. Neurosci. https://doi.org/10.3389/fncom.2018.00049 (2018).

    Article  Google Scholar 

  249. Sjöström, P. J., Turrigiano, G. G. & Nelson, S. B. Endocannabinoid-dependent neocortical layer-5 LTD in the absence of postsynaptic spiking. J. Neurophysiol. 92, 3338–3343 (2004).

    Article  Google Scholar 

  250. Gambino, F. et al. Sensory-evoked LTP driven by dendritic plateau potentials in vivo. Nature 515, 116–119 (2014).

    Article  CAS  Google Scholar 

  251. Lisman, J., Grace, A. A. & Duzel, E. A neoHebbian framework for episodic memory; role of dopamine-dependent late LTP. Trends Neurosci. 34, 536–547 (2011).

    Article  CAS  Google Scholar 

  252. Kuśmierz, L., Isomura, T. & Toyoizumi, T. Learning with three factors: modulating Hebbian plasticity with errors. Curr. Opin. Neurobiol. 46, 170–177 (2017).

    Article  Google Scholar 

  253. Frémaux, N. & Gerstner, W. Neuromodulated spike-timing-dependent plasticity, and theory of three-factor learning rules. Front. Neural Circuits 9, 85 (2015).

    Google Scholar 

  254. Destexhe, A., Rudolph, M. & Pare, D. The high-conductance state of neocortical neurons in vivo. Nat. Rev. Neurosci. 4, 739–751 (2003).

    Article  CAS  Google Scholar 

  255. Ganguly, K., Kiss, L. & Poo, M. Enhancement of presynaptic neuronal excitability by correlated presynaptic and postsynaptic spiking. Nat. Neurosci. 3, 1018–1026 (2000).

    Article  CAS  Google Scholar 

  256. Cudmore, R. H. & Turrigiano, G. G. Long-term potentiation of intrinsic excitability in LV visual cortical neurons. J. Neurophysiol. 92, 341–348 (2004).

    Article  Google Scholar 

  257. Losonczy, A., Makara, J. K. & Magee, J. C. Compartmentalized dendritic plasticity and input feature storage in neurons. Nature 452, 436–441 (2008).

    Article  CAS  Google Scholar 

  258. Grubb, M. S. & Burrone, J. Activity-dependent relocation of the axon initial segment fine-tunes neuronal excitability. Nature 465, 1070–1074 (2010).

    Article  CAS  Google Scholar 

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Acknowledgements

The authors thank A. Watt, W. Gerstner, R. P. Costa, A. Suvrathan, C. Bourque, H. Wong, O. Camiré, S. Rannio and Sjöström laboratory members for help and useful discussions. P.J.S. was supported by Fonds de Recherche du Québec - Santé (FRQS) CB 254033 and Natural Sciences and Engineering Research Council of Canada (NSERC) DG 2017-04730. A.R.M. was supported by doctoral awards from FRQS (287520) and Healthy Brains for Healthy Lives (HBHL). C.Y.C.C. was in receipt of doctoral awards NSERC D3-534171-2019 and Fonds de Recherche du Québec - Nature et technologies (FRQNT) 275075. A.W. was a recipient of HBHL, Integrated Program in Neuroscience(IPN) and Quebec Bio-Imaging Network (QBIN) fellowships. N.C. is an NSERC USRA (552184-2020) and FRQNT BRPC Supplement (298265) recipient. M.H. was funded by Canada Summer Jobs (CSJ).

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All authors researched data for the article, contributed substantially to discussion of the content and wrote the article. A.R.M, C.Y.C.C, A.W. and P.J.S. reviewed and edited the manuscript before submission.

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Correspondence to P. Jesper Sjöström.

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Glossary

Anti-Hebbian

A rule that disobeys Hebb’s postulate, such as synaptic strengthening resulting from asynchronous firing in connected cells or, conversely, coincident firing eliciting synaptic weakening.

Coincidence detection

A process by which a neuron or a neuronal circuit can detect the occurrence of temporally close but spatially distributed input signals to form associations between distinct events.

Disinhibition

Reduction of inhibitory drive onto an excitatory neuron.

E → I plasticity

Plasticity at synapses from excitatory to inhibitory cells.

E/I balance

The relative contributions of excitatory and inhibitory synaptic input to an individual neuron or in a local circuit.

Excitatory postsynaptic potential (EPSP)-spike potentiation

The ability of long-term potentiation (LTP) to additionally increase the potentiated input’s capacity to drive postsynaptic spiking by altering postsynaptic excitability.

Expression of plasticity

The mechanisms that alter the strength of a synaptic connection, such as the addition or removal of neurotransmitter receptor channels postsynaptically, or changes of release probability presynaptically.

Homeostatic plasticity

The capacity of neurons to regulate their own excitability and synaptic drive slowly over many hours in the face of changes in network structure and activity.

I → E plasticity

Plasticity at synapses from inhibitory to excitatory cells, which has often been called inhibitory long-term potentiation (LTP) or inhibitory long-term depression (LTD).

Induction of plasticity

The processes that trigger the expression of long-term plasticity; typically a repeated activity pattern, but could also be chemical or pharmacological.

Miniature excitatory postsynaptic current

A depolarizing current elicited by excitatory neurotransmitters such as glutamate that promotes spiking in the postsynaptic neuron.

Miniature inhibitory postsynaptic current

A hyperpolarizing current elicited by inhibitory neurotransmitters such as GABA that reduces spiking in the postsynaptic neuron.

Negative feedback

A mechanism that acts similar to a thermostat to keep a parameter such as temperature or activity within reasonable bounds by reducing it if too high and increasing it if too low.

Positive feedback

A mechanism that achieves run-away regenerative events, such as voltage-dependent sodium channels driving action potential rise; the more they depolarize, the more they open and promote further depolarization.

Quantal amplitude

The release of one synaptic vesicle containing a stereotyped amount of neurotransmitter — a quantum — elicits a postsynaptic response of one quantal amplitude.

Reversal potential

The membrane potential at which an ion channel current reverses its sign.

Rheobase

The minimal current amplitude needed to be injected into a cell to elicit an action potential. It is a measure of membrane potential excitability.

Synapse type-specific plasticity

The activity requirements that determine plasticity depend on the synapse type, which in turn is related to the presynaptic and the postsynaptic cell types.

Theta burst stimulation

(TBS). Short bursts of stimulation at high frequency, typically 100 Hz, with the bursts themselves applied at 5–8 Hz, to mimic hippocampal theta rhythm and to achieve pre-priming disinhibition, which yields more long-term potentiation (LTP) while improving biological realism.

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McFarlan, A.R., Chou, C.Y.C., Watanabe, A. et al. The plasticitome of cortical interneurons. Nat Rev Neurosci 24, 80–97 (2023). https://doi.org/10.1038/s41583-022-00663-9

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