Skip to main content

Thank you for visiting nature.com. 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.

  • Review Article
  • Published:

Dynamic circuit motifs underlying rhythmic gain control, gating and integration

Nature Neuroscience volume 17, pages 1031–1039 (2014)Cite this article

Subjects

Abstract

Brain circuitry processes information by rapidly and selectively engaging functional neuronal networks. The dynamic formation of networks is often evident in rhythmically synchronized neuronal activity and tightly correlates with perceptual, cognitive and motor performances. But how synchronized neuronal activity contributes to network formation and how it relates to the computation of behaviorally relevant information has remained difficult to discern. Here we structure recent empirical advances that link synchronized activity to the activation of so-called dynamic circuit motifs. These motifs explicitly relate (1) synaptic and cellular properties of circuits to (2) identified timescales of rhythmic activation and to (3) canonical circuit computations implemented by rhythmically synchronized circuits. We survey the ubiquitous evidence of specific cell and circuit properties underlying synchronized activity across theta, alpha, beta and gamma frequency bands and show that their activation likely implements gain control, context-dependent gating and state-specific integration of synaptic inputs. This evidence gives rise to the dynamic circuit motifs hypothesis of synchronized activation states, with its core assertion that activation states are linked to uniquely identifiable local circuit structures that are recruited during the formation of functional networks to perform specific computational operations.

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

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Dynamic circuit motifs and the structural basis of several motifs with identified timescales.
Figure 2: Canonical computations of cortical circuits and generic response modulations supported by specific cell types.
Figure 3: Dynamic circuit motifs activated at alpha, low beta and gamma frequencies that implement gain controls, gating and integration of inputs.
Figure 4: Gating of distal and proximal dendritic information streams through rhythmic inhibition at theta frequencies in the hippocampus and at 10–20 Hz in the neocortex.

Similar content being viewed by others

References

  1. Fell, J. & Axmacher, N. The role of phase synchronization in memory processes. Nat. Rev. Neurosci. 12, 105–118 (2011).

    CAS  PubMed  Google Scholar 

  2. Siegel, M., Donner, T.H. & Engel, A.K. Spectral fingerprints of large-scale neuronal interactions. Nat. Rev. Neurosci. 13, 121–134 (2012).

    CAS  PubMed  Google Scholar 

  3. Buzsáki, G. & Wang, X.J. Mechanisms of gamma oscillations. Annu. Rev. Neurosci. 35, 203–225 (2012).

    PubMed  PubMed Central  Google Scholar 

  4. Tiesinga, P., Fellous, J.M. & Sejnowski, T.J. Regulation of spike timing in visual cortical circuits. Nat. Rev. Neurosci. 9, 97–107 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Grillner, S., Markram, H., De Schutter, E., Silberberg, G. & LeBeau, F.E. Microcircuits in action–from CPGs to neocortex. Trends Neurosci. 28, 525–533 (2005).

    CAS  PubMed  Google Scholar 

  6. Akam, T. & Kullmann, D.M. Oscillatory multiplexing of population codes for selective communication in the mammalian brain. Nat. Rev. Neurosci. 15, 111–122 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Silver, R.A. Neuronal arithmetic. Nat. Rev. Neurosci. 11, 474–489 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

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

    Google Scholar 

  9. Wang, X.J. Neurophysiological and computational principles of cortical rhythms in cognition. Physiol. Rev. 90, 1195–1268 (2010).

    PubMed  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Bruno, R.M. Synchrony in sensation. Curr. Opin. Neurobiol. 21, 701–708 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Pouille, F., Marin-Burgin, A., Adesnik, H., Atallah, B.V. & Scanziani, M. Input normalization by global feedforward inhibition expands cortical dynamic range. Nat. Neurosci. 12, 1577–1585 (2009).

    CAS  PubMed  Google Scholar 

  13. Kremkow, J., Aertsen, A. & Kumar, A. Gating of signal propagation in spiking neural networks by balanced and correlated excitation and inhibition. J. Neurosci. 30, 15760–15768 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Kremkow, J., Perrinet, L.U., Masson, G.S. & Aertsen, A. Functional consequences of correlated excitatory and inhibitory conductances in cortical networks. J. Comput. Neurosci. 28, 579–594 (2010).

    PubMed  Google Scholar 

  15. Zemankovics, R., Veres, J.M., Oren, I. & Hajos, N. Feedforward inhibition underlies the propagation of cholinergically induced gamma oscillations from hippocampal CA3 to CA1. J. Neurosci. 33, 12337–12351 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Cruikshank, S.J., Urabe, H., Nurmikko, A.V. & Connors, B.W. Pathway-specific feedforward circuits between thalamus and neocortex revealed by selective optical stimulation of axons. Neuron 65, 230–245 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Thomson, A.M. & Bannister, A.P. Interlaminar connections in the neocortex. Cereb. Cortex 13, 5–14 (2003).

    PubMed  Google Scholar 

  18. Kumar, A., Vlachos, I., Aertsen, A. & Boucsein, C. Challenges of understanding brain function by selective modulation of neuronal subpopulations. Trends Neurosci. 36, 579–586 (2013).

    CAS  PubMed  Google Scholar 

  19. 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 

  20. Akam, T. & Kullmann, D.M. Oscillations and filtering networks support flexible routing of information. Neuron 67, 308–320 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Timofeev, I., Bazhenov, M., Seigneur, J. & Sejnowski, T. Neuronal synchronization and thalamocortical rhythms in sleep, wake and epilepsy. in Jasper's Basic Mechanisms of the Epilepsies (eds. Noebels, J.L., Avoli, M., Rogawski, M.A., Olsen, R.W. & Delgado-Escueta, A.V.) (National Center for Biotechnology Information, Bethesda, Maryland, USA, 2012).

  22. Hutcheon, B. & Yarom, Y. Resonance, oscillation and the intrinsic frequency preferences of neurons. Trends Neurosci. 23, 216–222 (2000).

    CAS  PubMed  Google Scholar 

  23. Otte, S., Hasenstaub, A. & Callaway, E.M. Cell type-specific control of neuronal responsiveness by gamma-band oscillatory inhibition. J. Neurosci. 30, 2150–2159 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Lawrence, J.J. Cholinergic control of GABA release: emerging parallels between neocortex and hippocampus. Trends Neurosci. 31, 317–327 (2008).

    CAS  PubMed  Google Scholar 

  25. Fröhlich, F. & McCormick, D.A. Endogenous electric fields may guide neocortical network activity. Neuron 67, 129–143 (2010).

    PubMed  PubMed Central  Google Scholar 

  26. Moca, V.V., Nikolic, D., Singer, W. & Muresan, R.C. Membrane resonance enables stable and robust gamma oscillations. Cereb. Cortex 24, 119–142 (2014).

    PubMed  Google Scholar 

  27. Sohal, V.S., Zhang, F., Yizhar, O. & Deisseroth, K. Parvalbumin neurons and gamma rhythms enhance cortical circuit performance. Nature 459, 698–702 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Patel, M. & Joshi, B. Decoding synchronized oscillations within the brain: phase-delayed inhibition provides a robust mechanism for creating a sharp synchrony filter. J. Theor. Biol. 334, 13–25 (2013).

    PubMed  Google Scholar 

  29. Bollimunta, A., Mo, J., Schroeder, C.E. & Ding, M. Neuronal mechanisms and attentional modulation of corticothalamic alpha oscillations. J. Neurosci. 31, 4935–4943 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Buffalo, E.A., Fries, P., Landman, R., Buschman, T.J. & Desimone, R. Laminar differences in gamma and alpha coherence in the ventral stream. Proc. Natl. Acad. Sci. USA 108, 11262–11267 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Saalmann, Y.B., Pinsk, M.A., Wang, L., Li, X. & Kastner, S. The pulvinar regulates information transmission between cortical areas based on attention demands. Science 337, 753–756 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Lorincz, M.L., Kekesi, K.A., Juhasz, G., Crunelli, V. & Hughes, S.W. Temporal framing of thalamic relay-mode firing by phasic inhibition during the alpha rhythm. Neuron 63, 683–696 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Constantinople, C.M. & Bruno, R.M. Deep cortical layers are activated directly by thalamus. Science 340, 1591–1594 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Hughes, S.W. et al. Thalamic gap junctions control local neuronal synchrony and influence macroscopic oscillation amplitude during EEG alpha rhythms. Front. Psychol. 2, 193 (2011).

    PubMed  PubMed Central  Google Scholar 

  35. Silva, L.R., Amitai, Y. & Connors, B.W. Intrinsic oscillations of neocortex generated by layer 5 pyramidal neurons. Science 251, 432–435 (1991).

    CAS  PubMed  Google Scholar 

  36. Castro-Alamancos, M.A. & Rigas, P. Synchronized oscillations caused by disinhibition in rodent neocortex are generated by recurrent synaptic activity mediated by AMPA receptors. J. Physiol. (Lond.) 542, 567–581 (2002).

    CAS  Google Scholar 

  37. Olsen, S.R., Bortone, D.S., Adesnik, H. & Scanziani, M. Gain control by layer six in cortical circuits of vision. Nature 483, 47–52 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Castro-Alamancos, M.A. & Oldford, E. Cortical sensory suppression during arousal is due to the activity-dependent depression of thalamocortical synapses. J. Physiol. (Lond.) 541, 319–331 (2002).

    CAS  Google Scholar 

  39. Florez, C.M. et al. In vitro recordings of human neocortical oscillations. Cereb. Cortex doi:10.1093/cercor/bht235 17 September (2013).

  40. Jensen, O. & Mazaheri, A. Shaping functional architecture by oscillatory alpha activity: gating by inhibition. Front. Hum. Neurosci. 4, 186 (2010).

    PubMed  PubMed Central  Google Scholar 

  41. Fischer, I. et al. Zero-lag long-range synchronization via dynamical relaying. Phys. Rev. Lett. 97, 123902 (2006).

    PubMed  Google Scholar 

  42. Helfrich, R.F. et al. Entrainment of brain oscillations by transcranial alternating current stimulation. Curr. Biol. 24, 333–339 (2014).

    CAS  PubMed  Google Scholar 

  43. Saalmann, Y.B. & Kastner, S. Cognitive and perceptual functions of the visual thalamus. Neuron 71, 209–223 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Sherman, S.M. & Guillery, R.W. Exploring the Thalamus and its Role in Cortical Function (MIT Press, 2006).

  45. Petersen, C.C. & Crochet, S. Synaptic computation and sensory processing in neocortical layer 2/3. Neuron 78, 28–48 (2013).

    CAS  PubMed  Google Scholar 

  46. Vinck, M., Womelsdorf, T., Buffalo, E.A., Desimone, R. & Fries, P. Attentional modulation of cell-class-specific gamma-band synchronization in awake monkey area v4. Neuron 80, 1077–1089 (2013).

    CAS  PubMed  Google Scholar 

  47. Gregoriou, G.G., Gotts, S.J. & Desimone, R. Cell-type-specific synchronization of neural activity in FEF with V4 during attention. Neuron 73, 581–594 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  48. Spaak, E., Bonnefond, M., Maier, A., Leopold, D.A. & Jensen, O. Layer-specific entrainment of gamma-band neural activity by the alpha rhythm in monkey visual cortex. Curr. Biol. 22, 2313–2318 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. Thut, G., Miniussi, C. & Gross, J. The functional importance of rhythmic activity in the brain. Curr. Biol. 22, R658–R663 (2012).

    CAS  PubMed  Google Scholar 

  50. de Almeida, L., Idiart, M. & Lisman, J.E. The input-output transformation of the hippocampal granule cells: from grid cells to place fields. J. Neurosci. 29, 7504–7512 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Tiesinga, P. & Sejnowski, T.J. Cortical enlightenment: are attentional gamma oscillations driven by ING or PING? Neuron 63, 727–732 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  52. Börgers, C., Epstein, S. & Kopell, N.J. Gamma oscillations mediate stimulus competition and attentional selection in a cortical network model. Proc. Natl. Acad. Sci. USA 105, 18023–18028 (2008).

    PubMed  PubMed Central  Google Scholar 

  53. Cardin, J.A. et al. Driving fast-spiking cells induces gamma rhythm and controls sensory responses. Nature 459, 663–667 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  54. Womelsdorf, T. et al. Orientation selectivity and noise correlation in awake monkey area V1 are modulated by the gamma cycle. Proc. Natl. Acad. Sci. USA 109, 4302–4307 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Vinck, M. et al. Gamma-phase shifting in awake monkey visual cortex. J. Neurosci. 30, 1250–1257 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  56. Tiesinga, P.H. & Sejnowski, T.J. Mechanisms for phase shifting in cortical networks and their role in communication through coherence. Front. Hum. Neurosci. 4, 196 (2010).

    PubMed  PubMed Central  Google Scholar 

  57. Knoblich, U., Siegle, J.H., Pritchett, D.L. & Moore, C.I. What do we gain from gamma? Local dynamic gain modulation drives enhanced efficacy and efficiency of signal transmission. Front. Hum. Neurosci. 4, 185 (2010).

    PubMed  PubMed Central  Google Scholar 

  58. Azouz, R. & Gray, C.M. Adaptive coincidence detection and dynamic gain control in visual cortical neurons in vivo. Neuron 37, 513–523 (2003).

    CAS  PubMed  Google Scholar 

  59. Bosman, C.A. et al. Attentional stimulus selection through selective synchronization between monkey visual areas. Neuron 75, 875–888 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  60. Womelsdorf, T. et al. Modulation of neuronal interactions through neuronal synchronization. Science 316, 1609–1612 (2007).

    CAS  PubMed  Google Scholar 

  61. Womelsdorf, T., Fries, P., Mitra, P.P. & Desimone, R. Gamma-band synchronization in visual cortex predicts speed of change detection. Nature 439, 733–736 (2006).

    CAS  PubMed  Google Scholar 

  62. Sippy, T. & Yuste, R. Decorrelating action of inhibition in neocortical networks. J. Neurosci. 33, 9813–9830 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  63. Tetzlaff, T., Helias, M., Einevoll, G.T. & Diesmann, M. Decorrelation of neural-network activity by inhibitory feedback. PLoS Comput. Biol. 8, e1002596 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  64. Yizhar, O. et al. Neocortical excitation/inhibition balance in information processing and social dysfunction. Nature 477, 171–178 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  65. Wilson, N.R., Runyan, C.A., Wang, F.L. & Sur, M. Division and subtraction by distinct cortical inhibitory networks in vivo. Nature 488, 343–348 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  66. Lee, S.H., Kwan, A.C. & Dan, Y. Interneuron subtypes and orientation tuning. Nature 508, E1–E2 (2014).

    CAS  PubMed  Google Scholar 

  67. Kopell, N., Whittington, M.A. & Kramer, M.A. Neuronal assembly dynamics in the beta1 frequency range permits short-term memory. Proc. Natl. Acad. Sci. USA 108, 3779–3784 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  68. Kramer, M.A. et al. Rhythm generation through period concatenation in rat somatosensory cortex. PLoS Comput. Biol. 4, e1000169 (2008).

    PubMed  PubMed Central  Google Scholar 

  69. Roopun, A.K. et al. Period concatenation underlies interactions between gamma and beta rhythms in neocortex. Front. Cell. Neurosci. 2, 1 (2008).

    PubMed  PubMed Central  Google Scholar 

  70. Salazar, R.F., Dotson, N.M., Bressler, S.L. & Gray, C.M. Content-specific fronto-parietal synchronization during visual working memory. Science 338, 1097–1100 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  71. Lipsman, N. et al. Beta coherence within human ventromedial prefrontal cortex precedes affective value choices. Neuroimage 85, 769–778 (2014).

    CAS  PubMed  Google Scholar 

  72. Larkum, M. A cellular mechanism for cortical associations: an organizing principle for the cerebral cortex. Trends Neurosci. 36, 141–151 (2013).

    CAS  PubMed  Google Scholar 

  73. Lovett-Barron, M. et al. Regulation of neuronal input transformations by tunable dendritic inhibition. Nat. Neurosci. 15, 423–430 (2012).

    CAS  PubMed  Google Scholar 

  74. Palmer, L., Murayama, M. & Larkum, M. Inhibitory regulation of dendritic activity in vivo. Front. Neural Circuits 6, 26 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  75. Wang, X.J., Tegner, J., Constantinidis, C. & Goldman-Rakic, P.S. Division of labor among distinct subtypes of inhibitory neurons in a cortical microcircuit of working memory. Proc. Natl. Acad. Sci. USA 101, 1368–1373 (2004).

    CAS  PubMed  PubMed Central  Google Scholar 

  76. Leão, R.N. et al. OLM interneurons differentially modulate CA3 and entorhinal inputs to hippocampal CA1 neurons. Nat. Neurosci. 15, 1524–1530 (2012).

    PubMed  PubMed Central  Google Scholar 

  77. Gloveli, T. et al. Differential involvement of oriens/pyramidale interneurones in hippocampal network oscillations in vitro. J. Physiol. (Lond.) 562, 131–147 (2005).

    CAS  Google Scholar 

  78. Varga, C., Golshani, P. & Soltesz, I. Frequency-invariant temporal ordering of interneuronal discharges during hippocampal oscillations in awake mice. Proc. Natl. Acad. Sci. USA 109, E2726–E2734 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  79. Colgin, L.L. et al. Frequency of gamma oscillations routes flow of information in the hippocampus. Nature 462, 353–357 (2009).

    CAS  PubMed  Google Scholar 

  80. Hasselmo, M.E., Bodelon, C. & Wyble, B.P. A proposed function for hippocampal theta rhythm: separate phases of encoding and retrieval enhance reversal of prior learning. Neural Comput. 14, 793–817 (2002).

    PubMed  Google Scholar 

  81. Li, X., Morita, K., Robinson, H.P. & Small, M. Control of layer 5 pyramidal cell spiking by oscillatory inhibition in the distal apical dendrites: a computational modeling study. J. Neurophysiol. 109, 2739–2756 (2013).

    PubMed  Google Scholar 

  82. Mancilla, J.G., Lewis, T.J., Pinto, D.J., Rinzel, J. & Connors, B.W. Synchronization of electrically coupled pairs of inhibitory interneurons in neocortex. J. Neurosci. 27, 2058–2073 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  83. Jiang, X., Wang, G., Lee, A.J., Stornetta, R.L. & Zhu, J.J. The organization of two new cortical interneuronal circuits. Nat. Neurosci. 16, 210–218 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  84. Metherate, R. & Cruikshank, S.J. Thalamocortical inputs trigger a propagating envelope of gamma-band activity in auditory cortex in vitro. Exp. Brain Res. 126, 160–174 (1999).

    CAS  PubMed  Google Scholar 

  85. Robbe, D. & Buzsaki, G. Alteration of theta timescale dynamics of hippocampal place cells by a cannabinoid is associated with memory impairment. J. Neurosci. 29, 12597–12605 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  86. Buzsáki, G., Logothetis, N. & Singer, W. Scaling brain size, keeping timing: evolutionary preservation of brain rhythms. Neuron 80, 751–764 (2013).

    PubMed  PubMed Central  Google Scholar 

  87. Drion, G., Massotte, L., Sepulchre, R. & Seutin, V. How modeling can reconcile apparently discrepant experimental results: the case of pacemaking in dopaminergic neurons. PLoS Comput. Biol. 7, e1002050 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  88. Hentschke, H. et al. Altered GABAA,slow inhibition and network oscillations in mice lacking the GABAA receptor β3 subunit. J. Neurophysiol. 102, 3643–3655 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  89. White, J.A., Banks, M.I., Pearce, R.A. & Kopell, N.J. Networks of interneurons with fast and slow gamma-aminobutyric acid type A (GABAA) kinetics provide substrate for mixed gamma-theta rhythm. Proc. Natl. Acad. Sci. USA 97, 8128–8133 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  90. Capogna, M. & Pearce, R.A. GABAA,slow: causes and consequences. Trends Neurosci. 34, 101–112 (2011).

    CAS  PubMed  Google Scholar 

  91. English, D.F. et al. GABAergic circuits mediate the reinforcement-related signals of striatal cholinergic interneurons. Nat. Neurosci. 15, 123–130 (2012).

    CAS  Google Scholar 

  92. Molyneaux, B.J. & Hasselmo, M.E. GABAB presynaptic inhibition has an in vivo time constant sufficiently rapid to allow modulation at theta frequency. J. Neurophysiol. 87, 1196–1205 (2002).

    CAS  PubMed  Google Scholar 

  93. Blatow, M. et al. A novel network of multipolar bursting interneurons generates theta frequency oscillations in neocortex. Neuron 38, 805–817 (2003).

    CAS  PubMed  Google Scholar 

  94. Chapman, C.A. & Lacaille, J.C. Intrinsic theta-frequency membrane potential oscillations in hippocampal CA1 interneurons of stratum lacunosum-moleculare. J. Neurophysiol. 81, 1296–1307 (1999).

    CAS  PubMed  Google Scholar 

  95. Glasgow, S.D. & Chapman, C.A. Conductances mediating intrinsic theta-frequency membrane potential oscillations in layer II parasubicular neurons. J. Neurophysiol. 100, 2746–2756 (2008).

    PubMed  Google Scholar 

  96. Boehlen, A., Henneberger, C., Heinemann, U. & Erchova, I. Contribution of near-threshold currents to intrinsic oscillatory activity in rat medial entorhinal cortex layer II stellate cells. J. Neurophysiol. 109, 445–463 (2013).

    PubMed  Google Scholar 

  97. Beierlein, M., Gibson, J.R. & Connors, B.W. A network of electrically coupled interneurons drives synchronized inhibition in neocortex. Nat. Neurosci. 3, 904–910 (2000).

    CAS  PubMed  Google Scholar 

  98. Stark, E. et al. Inhibition-induced theta resonance in cortical circuits. Neuron 80, 1263–1276 (2013).

    CAS  PubMed  Google Scholar 

  99. Fanselow, E.E., Richardson, K.A. & Connors, B.W. Selective, state-dependent activation of somatostatin-expressing inhibitory interneurons in mouse neocortex. J. Neurophysiol. 100, 2640–2652 (2008).

    PubMed  PubMed Central  Google Scholar 

  100. Hughes, S.W. et al. Synchronized oscillations at alpha and theta frequencies in the lateral geniculate nucleus. Neuron 42, 253–268 (2004).

    CAS  PubMed  Google Scholar 

  101. Karameh, F.N., Dahleh, M.A., Brown, E.N. & Massaquoi, S.G. Modeling the contribution of lamina 5 neuronal and network dynamics to low frequency EEG phenomena. Biol. Cybern. 95, 289–310 (2006).

    PubMed  Google Scholar 

  102. Castro-Alamancos, M.A. The motor cortex: a network tuned to 7–14 Hz. Front. Neural Circuits 7, 21 (2013).

    PubMed  PubMed Central  Google Scholar 

  103. Castro-Alamancos, M.A., Rigas, P. & Tawara-Hirata, Y. Resonance (approximately 10 Hz) of excitatory networks in motor cortex: effects of voltage-dependent ion channel blockers. J. Physiol. (Lond.) 578, 173–191 (2007).

    CAS  Google Scholar 

  104. Roopun, A.K. et al. A beta2-frequency (20–30 Hz) oscillation in nonsynaptic networks of somatosensory cortex. Proc. Natl. Acad. Sci. USA 103, 15646–15650 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  105. Brumberg, J.C., Nowak, L.G. & McCormick, D.A. Ionic mechanisms underlying repetitive high-frequency burst firing in supragranular cortical neurons. J. Neurosci. 20, 4829–4843 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  106. Cunningham, M.O. et al. A role for fast rhythmic bursting neurons in cortical gamma oscillations in vitro. Proc. Natl. Acad. Sci. USA 101, 7152–7157 (2004).

    CAS  PubMed  PubMed Central  Google Scholar 

  107. Cardin, J.A., Palmer, L.A. & Contreras, D. Stimulus-dependent gamma (30–50 Hz) oscillations in simple and complex fast rhythmic bursting cells in primary visual cortex. J. Neurosci. 25, 5339–5350 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  108. Wang, X.J. Fast burst firing and short-term synaptic plasticity: a model of neocortical chattering neurons. Neuroscience 89, 347–362 (1999).

    CAS  PubMed  Google Scholar 

  109. Hughes, S.W. et al. Novel modes of rhythmic burst firing at cognitively-relevant frequencies in thalamocortical neurons. Brain Res. 1235, 12–20 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  110. Whittington, M.A., Traub, R.D. & Jefferys, J.G. Synchronized oscillations in interneuron networks driven by metabotropic glutamate receptor activation. Nature 373, 612–615 (1995).

    CAS  PubMed  Google Scholar 

  111. Hormuzdi, S.G. et al. Impaired electrical signaling disrupts gamma frequency oscillations in connexin 36-deficient mice. Neuron 31, 487–495 (2001).

    CAS  PubMed  Google Scholar 

  112. Xu, H., Jeong, H.Y., Tremblay, R. & Rudy, B. Neocortical somatostatin-expressing GABAergic interneurons disinhibit the thalamorecipient layer 4. Neuron 77, 155–167 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  113. 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).

    CAS  PubMed  PubMed Central  Google Scholar 

  114. Gibson, J.R., Beierlein, M. & Connors, B.W. Two networks of electrically coupled inhibitory neurons in neocortex. Nature 402, 75–79 (1999).

    CAS  PubMed  Google Scholar 

  115. Swadlow, H.A. Fast-spike interneurons and feedforward inhibition in awake sensory neocortex. Cereb. Cortex 13, 25–32 (2003).

    PubMed  Google Scholar 

  116. Hu, H., Ma, Y. & Agmon, A. Submillisecond firing synchrony between different subtypes of cortical interneurons connected chemically but not electrically. J. Neurosci. 31, 3351–3361 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  117. Berger, T.K., Silberberg, G., Perin, R. & Markram, H. Brief bursts self-inhibit and correlate the pyramidal network. PLoS Biol. 8, e1000473 (2010).

    PubMed  PubMed Central  Google Scholar 

  118. Flint, A.C. & Connors, B.W. Two types of network oscillations in neocortex mediated by distinct glutamate receptor subtypes and neuronal populations. J. Neurophysiol. 75, 951–957 (1996).

    CAS  PubMed  Google Scholar 

  119. Murayama, M. et al. Dendritic encoding of sensory stimuli controlled by deep cortical interneurons. Nature 457, 1137–1141 (2009).

    CAS  PubMed  Google Scholar 

  120. Carracedo, L.M. et al. A neocortical delta rhythm facilitates reciprocal interlaminar interactions via nested theta rhythms. J. Neurosci. 33, 10750–10761 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We are grateful to the speakers of two workshops held at the Computational and Systems Neuroscience (cosyne.org) meetings on The Consequences of Brain Rhythms in the Organization of Neuronal Computation (2009) and Developing Simplified Algebras to Describe Large-Scale Brain Dynamics (2011) for numerous discussions. We thank T. Donner, C. Eliasmith, B. Hansen and M. Vinck for discussions and comments on an earlier version of the manuscript. T.W. was supported by grants from the Canadian Institutes of Health Research (CIHR), the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Ontario Ministry of Economic Development and Innovation (MEDI). T.A.V. was supported by grants from the CIHR. N.T.S. was supported by US National Institutes of Health (NIH) R01 grants NS18741, NS44623 and grant HD 18381, NIH Institutional Training Grant T32 MH070328, and the US National Center for Research Resources (P41 RR14075). P.T. was supported by a grant from the Netherlands Organization for Scientific Research (NWO) Computational Lifesciences program and by Neuroseeker (FP7 grant agreement 600925).

Author information

Authors and Affiliations

  1. Department of Biology, York University, Toronto, Ontario, Canada

    Thilo Womelsdorf

  2. Centre for Vision Research, York University, Toronto, Ontario, Canada

    Thilo Womelsdorf

  3. Division of Fundamental Neurobiology, Toronto Western Research Institute, Toronto, Ontario, Canada

    Taufik A Valiante

  4. Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada

    Taufik A Valiante

  5. Brain Power, LLC, Boston, Massachusetts, USA

    Ned T Sahin

  6. Department of Psychology, Harvard University, Cambridge, Massachusetts, USA

    Ned T Sahin

  7. Department of Physics, University of Washington, Seattle, Washington, USA

    Kai J Miller

  8. Department of Neurosurgery, Stanford University, Stanford, California, USA

    Kai J Miller

  9. Donders Institute for Brain, Behavior, and Cognition, Radboud University Nijmegen, Nijmegen, the Netherlands

    Paul Tiesinga

Authors
  1. Thilo Womelsdorf
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Taufik A Valiante
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ned T Sahin
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Kai J Miller
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Paul Tiesinga
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Thilo Womelsdorf.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Thalamo-cortical alpha rhythmic motif.

(a) The structural connectivity (top) shows that the alpha rhythmic motif depends on rhythmically bursting, high threshold (HT) cells entraining inhibitory neurons (IN), which in turn impose rhythmic suppression onto relay-mode, regular spiking projection neurons. The bursting frequency of the HT cells depends on intrinsic currents, whereas the synchrony derives from coupling by gap junctions. Depending on whether the IN cells fire single spikes or burst, the relay cells are either in-phase suppressed or anti-phase suppressed. The bottom panels shows the cross correlograms illustrating the rhythmic activation of the interneurons (Int) by bursting HT cells (left) and the alpha rhythmic inhibition of relay mode cells by an interneurons (right). (b) Example activation traces showing the relation of interneuron IPSPs (bottom) on relay mode neuron spike generation (middle) and the extracellular recorded filtered LFP (top). The phase-of-firing histogram (right) shows that during alpha rhythmic pulsed inhibition relay neuron firing is facilitated particularly in the third quarter of the oscillation cycle. Adapted from Lorincz, M.L., Kekesi, K.A., Juhasz, G., Crunelli, V. & Hughes, S.W. Temporal framing of thalamic relay-mode firing by phasic inhibition during the alpha rhythm. Neuron 63, 683-696, copyright Elsevier (2009).

Supplementary Figure 2 Selective gamma coherence during selective visual processing.

(a) The spatial coverage of ECoG electrode locations (dots) projected on the rendered cortical surface of a macaque brain. Dots indicate the 252 electrodes of a high density ECoG grid. Green and red dots indicate electrodes recording activity over V1 and V4, respectively. ‘V1a’ and ‘V1b’ denote two V1 electrode locations recording non-overlapping receptive fields. (b) Stimulus arrangement for the two attention conditions was identical. In one condition attention was directed to the stimulus that activated V4 and the V1a site (stimulus circled in red for illustration purposes). In the other condition attention was directed to the stimulus that activated V4 and the V1b site (stimulus circled in blue for illustration purposes). (c) Spectral power change relative to pre-stimulus baseline (upper panel) in V1 in the two attention conditions (red and blue). The bottom panel shows the coherence spectra of the V4 to V1a and V1b (red and blue) when the attended stimulus overlaid V1a (red) and V1b (blue). (d) Illustration of the attention condition (left). Bottom-Up Granger causal influence for the V1a to V4 (red) and the V1b to V4 (blue) connections when the attended stimulus overlaid with V4 and V1a. The rightmost panel shows the respective Top-Down Granger causal influence. (e) Same format as (d) but for the condition with attention on the stimulus that activated the V4 and the V1b recording site. Gray bars in (c,d,e) indicate the frequencies with a significant effect (p<0.05, corrected for multiple comparisons across frequencies, non-parametric randomization across site pairs). Adapted from Bosman, C.A., et al. Attentional Stimulus Selection through Selective Synchronization between Monkey Visual Areas. Neuron 75, 875-888, copyright Elsevier (2012).

Supplementary Figure 3 Visual attention and selective ‘push-pull’ gating in visual cortex at gamma band frequencies mediated by putative interneurons.

(a) Normalized action potential waveforms of single cells recorded in area V4. (b) Distribution of peak-to-trough durations of action potentials across neurons reveals a bimodal distribution that separate narrow spiking from broad spiking cells. (c) Spike-LFP phase locking (measured as pairwise phase consistency) across cells in V4 for narrow and broad spiking cells shows significant gamma band synchronization for NS and BS cells, and significant alpha band synchronization for NS cells. (d,e) Attention (attend inside, PPCin, versus outside, the visual receptive field of the cells, PPCout) decreases gamma band phase locking for NS and BS cells that show low firing rates (d), and increases phase locking for cells with higher firing rates (e). The respective gamma bands are highlighted with grey bars in the top of the panels. This finding suggests a push-pull mechanism of attention that implements the up- and down-modulation of cells’ synchronization depending on their overall rate in response to visual stimuli. Low/High firing rate cells were median split. Adapted from Vinck, M., Womelsdorf, T., Buffalo, E.A., Desimone, R. & Fries, P. Attentional modulation of cell-class-specific gamma-band synchronization in awake monkey area v4. Neuron 80, 1077-1089, copyright Elsevier (2013).

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–3 (PDF 5557 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Womelsdorf, T., Valiante, T., Sahin, N. et al. Dynamic circuit motifs underlying rhythmic gain control, gating and integration. Nat Neurosci 17, 1031–1039 (2014). https://doi.org/10.1038/nn.3764

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nn.3764

This article is cited by

Search

Advanced search

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