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Parvalbumin-expressing basket-cell network plasticity induced by experience regulates adult learning

Nature volume 504, pages 272–276 (2013)Cite this article

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Abstract

Learning and memory processes can be influenced by recent experience, but the mechanisms involved are poorly understood. Enhanced plasticity during critical periods of early life is linked to differentiating parvalbumin (PV)-interneuron networks1,2,3,4,5,6,7, suggesting that recent experience may modulate learning by targeting the differentiation state of PV neurons8,9,10,11 in the adult. Here we show that environmental enrichment and Pavlovian contextual fear conditioning induce opposite, sustained and reversible hippocampal PV-network configurations in adult mice. Specifically, enrichment promotes the emergence of large fractions of low-differentiation (low PV and GAD67 expression) basket cells with low excitatory-to-inhibitory synaptic-density ratios, whereas fear conditioning leads to large fractions of high-differentiation (high PV and GAD67 expression) basket cells with high excitatory-to-inhibitory synaptic-density ratios. Pharmacogenetic inhibition or activation of PV neurons was sufficient to induce such opposite low-PV-network or high-PV-network configurations, respectively. The low-PV-network configuration enhanced structural synaptic plasticity12,13, and memory consolidation and retrieval, whereas these were reduced by the high-PV-network configuration. We then show that maze navigation learning14 induces a hippocampal low-PV-network configuration paralleled by enhanced memory and structural synaptic plasticity throughout training, followed by a shift to a high-PV-network configuration after learning completion. The shift to a low-PV-network configuration specifically involved increased vasoactive intestinal polypeptide (VIP)-positive GABAergic boutons and synaptic transmission onto PV neurons15,16. Closely comparable low- and high-PV-network configurations involving VIP boutons were specifically induced in primary motor cortex upon rotarod motor learning17,18. These results uncover a network plasticity mechanism induced after learning through VIP–PV microcircuit modulation19, and involving large, sustained and reversible shifts in the configuration of PV basket-cell networks in the adult. This novel form of experience-related plasticity in the adult modulates memory consolidation, retrieval and learning, and might be harnessed for therapeutic strategies to promote cognitive enhancement and neuroprotection.

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Figure 1: Differentiation plasticity of hippocampal parvalbumin-expressing basket-cell networks in adult mice.
Figure 2: Configuration shifts in parvalbumin-expressing networks modulate hippocampal synaptic structural plasticity and learning in the adult.
Figure 3: Maze trial-and-error learning involves early PV-network shift to low-PV configuration, and shift to high-PV configuration upon learning completion.
Figure 4: A PV-VIP microcircuit controls PV-network configuration and behavioural performance during incremental learning.

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References

  1. Huang, Z. J. et al. BDNF regulates the maturation of inhibition and the critical period of plasticity in mouse visual cortex. Cell 98, 739–755 (1999)

    Article  CAS  Google Scholar 

  2. Fagiolini, M. et al. Specific GABAA circuits for visual cortical plasticity. Science 303, 1681–1683 (2004)

    Article  ADS  CAS  Google Scholar 

  3. Sugiyama, S. et al. Experience-dependent transfer of Otx2 homeoprotein into the visual cortex activates postnatal plasticity. Cell 134, 508–520 (2008)

    Article  CAS  Google Scholar 

  4. Maya Vetencourt, J. F. et al. The antidepressant fluoxetine restores plasticity in the adult visual cortex. Science 320, 385–388 (2008)

    Article  ADS  CAS  Google Scholar 

  5. Yazaki-Sugiyama, Y., Kang, S., Câteau, H., Fukai, T. & Hensch, T. K. Bidirectional plasticity in fast-spiking GABA circuits by visual experience. Nature 462, 218–221 (2009)

    Article  ADS  CAS  Google Scholar 

  6. Levelt, C. N. & Hübener, M. Critical-period plasticity in the visual cortex. Annu. Rev. Neurosci. 35, 309–330 (2012)

    Article  CAS  Google Scholar 

  7. Sale, A., Berardi, N., Spolidoro, M., Baroncelli, L. & Maffei, L. GABAergic inhibition in visual cortical plasticity. Front Cell. Neurosci. 4, 10 (2010)

    PubMed  PubMed Central  Google Scholar 

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

    Article  ADS  CAS  Google Scholar 

  9. Isaacson, J. S. & Scanziani, M. How inhibition shapes cortical activity. Neuron 72, 231–243 (2011)

    Article  CAS  Google Scholar 

  10. Hendry, S. H. & Jones, E. G. Activity-dependent regulation of GABA expression in the visual cortex of adult monkeys. Neuron 1, 701–712 (1988)

    Article  CAS  Google Scholar 

  11. Welker, E., Soriano, E., Dörfl, J. & Van der Loos, H. Plasticity in the barrel cortex of the adult mouse: transient increase of GAD-immunoreactivity following sensory stimulation. Exp. Brain Res. 78, 659–664 (1989)

    Article  CAS  Google Scholar 

  12. Bednarek, E. & Caroni, P. β-Adducin is required for stable assembly of new synapses and improved memory upon environmental enrichment. Neuron 69, 1132–1146 (2011)

    Article  CAS  Google Scholar 

  13. Caroni, P., Donato, F. & Muller, D. Structural plasticity upon learning: regulation and functions. Nature Rev. Neurosci. 13, 478–490 (2012)

    Article  CAS  Google Scholar 

  14. Morris, R. G. M., Garrud, P., Rawlins, J. N. P. & O’Keefe, J. Place navigation impaired in rats with hippocampal lesions. Nature 297, 681–683 (1982)

    Article  ADS  CAS  Google Scholar 

  15. Acsády, L., Arabadzisz, D. & Freund, T. F. Correlated morphological and neurochemical features identify different subsets of vasoactive intestinal polypeptide-immunoreactive interneurons in rat hippocampus. Neuroscience 73, 299–315 (1996)

    Article  Google Scholar 

  16. Dávid, C., Schleicher, A., Zuschratter, W. & Staiger, J. F. The innervation of parvalbumin-containing interneurons by VIP-immunopositive interneurons in the primary somatosensory cortex of the adult rat. Eur. J. Neurosci. 25, 2329–2340 (2007)

    Article  Google Scholar 

  17. Xu, T. et al. Rapid formation and selective stabilization of synapses for enduring motor memories. Nature 462, 915–919 (2009)

    Article  ADS  CAS  Google Scholar 

  18. Yang, G., Pan, F. & Gan, W. B. Stably maintained dendritic spines are associated with lifelong memories. Nature 462, 920–924 (2009)

    Article  ADS  CAS  Google Scholar 

  19. Pi, H.-J., Hangya, B., Kvitsiani, D., Sanders, J. I. & Huang, J. Z. &. Kepecs. A. Cortical interneurons that specialize in disinhibitory control. Nature 503, 521–524 (2013)

    Article  ADS  CAS  Google Scholar 

  20. Ruediger, S. et al. Learning-related feedforward inhibitory connectivity growth required for memory precision. Nature 473, 514–518 (2011)

    Article  ADS  CAS  Google Scholar 

  21. Chattopadhyaya, B. et al. GAD67-mediated GABA synthesis and signaling regulate inhibitory synaptic innervation in the visual cortex. Neuron 54, 889–903 (2007)

    Article  CAS  Google Scholar 

  22. Ruediger, S., Spirig, D., Donato, F. & Caroni, P. Goal-oriented searching mediated by ventral hippocampus early in trial-and-error learning. Nature Neurosci. 15, 1563–1571 (2012)

    Article  CAS  Google Scholar 

  23. Kleinlogel, S. et al. Ultra light-sensitive and fast neuronal activation with the Ca2+-permeable channelrhodopsin CatCh. Nature Neurosci. 14, 513–518 (2011)

    Article  CAS  Google Scholar 

  24. Magnus, C. J. et al. Chemical and genetic engineering of selective ion channel-ligand interactions. Science 333, 1292–1296 (2011)

    Article  ADS  CAS  Google Scholar 

  25. Keck, T. et al. Loss of sensory input causes rapid structural changes of inhibitory neurons in adult mouse visual cortex. Neuron 71, 869–882 (2011)

    Article  CAS  Google Scholar 

  26. Volman, V., Behrens, M. M. & Sejnowski, T. J. Downregulation of parvalbumin at cortical GABA synapses reduces network gamma oscillatory activity. J. Neurosci. 31, 18137–18148 (2011)

    Article  CAS  Google Scholar 

  27. Lee, S. H. et al. Activation of specific interneurons improves V1 feature selectivity and visual perception. Nature 488, 379–383 (2012)

    Article  ADS  CAS  Google Scholar 

  28. Komiyama, T. et al. Learning-related fine-scale specificity imaged in motor cortex circuits of behaving mice. Nature 464, 1182–1186 (2010)

    Article  ADS  CAS  Google Scholar 

  29. Lewis, D. A., Curley, A. A., Glausier, J. R. & Volk, D. W. Cortical parvalbumin interneurons and cognitive dysfunction in schizophrenia. Trends Neurosci. 35, 57–67 (2012)

    Article  CAS  Google Scholar 

  30. Deguchi, Y., Donato, F., Galimberti, I., Cabuy, E. & Caroni, P. Temporally matched subpopulations of selectively interconnected principal neurons in the hippocampus. Nature Neurosci. 14, 495–504 (2011)

    Article  CAS  Google Scholar 

  31. Galimberti, I. et al. Long-term rearrangements of hippocampal mossy fiber terminal connectivity in the adult regulated by experience. Neuron 50, 749–763 (2006)

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank S. Arber for valuable comments on the manuscript and S. Sternson (Janelia), S. Arber and A. Dayer for reagents. F.D. was supported by the NCCR Synapsy. The Friedrich Miescher Institut is part of and supported by the Novartis Research Foundation.

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Authors and Affiliations

  1. Friedrich Miescher Institut, Maulbeerstrasse 66, CH-4058 Basel, Switzerland,

    Flavio Donato, Santiago Belluco Rompani & Pico Caroni

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  1. Flavio Donato
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  2. Santiago Belluco Rompani
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  3. Pico Caroni
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Contributions

F.D. devised, carried out and analysed all experiments; S.B.R. provided reagents and assistance for the optogenetics experiments; P.C. helped to devise the experiments and wrote the manuscript. All authors discussed the results and commented on the manuscript.

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Correspondence to Pico Caroni.

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The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Schematic showing how PV-neuron plasticity is induced by experience to modulate learning.

Recent experience regulates local incidences of PV neurons with low-differentiation (low PV and low GAD67 expression; yellow) and high-differentiation properties (high PV and GAD67 expression; blue) in the adult, producing local PV networks of distinct configurations. A low-PV and low-GAD67 network configuration is induced early during training and upon environmental enrichment to promote synaptic plasticity, memory consolidation and retrieval, and learning. A high-PV and high-GAD67 network configuration is induced upon learning completion and restricts synaptic plasticity and new learning. A low-PV and low-GAD67 configuration might promote memory consolidation and retrieval, and learning, by lowering the threshold for neuronal recruitment and synaptic plasticity, and by preventing the emergence of dominant representations due to low synchronization of neuronal activities. A high-PV and high-GAD67 configuration might promote consolidation and exploitation of learned skills by enhancing consolidation of strong memories through more effective bundling and propagation of recruited neuron ensemble activity, and by suppression of distractor stimuli.

Extended Data Figure 2 Analysis of parvalbumin-network configuration in mouse hippocampal CA3b.

a, Illustration of how PV-labelling intensities were binned in the study. Dots represent values from individual PV neurons in dorsal CA3b, from one mouse per condition. The low threshold at the intensity value of 800 was selected based on the large subpopulation of neurons with lower PV signals in the environmentally enriched (EE) and the P15 sample. The threshold at 800 sets apart a low-PV subpopulation overrepresented in the developing and EE sample, and underrepresented in the control sample. The other three subpopulations were defined through multiples of the basal value of 800. b, Variability of PV-labelling intensity distributions among different mice. Examples shown: 15 for control conditions and 5 each for EE and contextual fear conditioning (cFC); 50 neurons per mouse. c, Closely comparable results obtained with monoclonal and polyclonal antibody against PV. The results shown in the paper were obtained with the goat anti PV antibody. The two antibodies also detected closely comparable total numbers of PV neurons (not shown). n = 8 mice each, 50 neurons per mouse. d, Calibration of PV and GAD67 immunoreactivity. The signal at a CA3 pyramidal neuron (white arrow) was set as zero. PV- and GAD67-positive cell indicated by yellow arrow. The maximal signal was set in order to maximize dynamic range and minimize signal saturation, as described in Methods. A single confocal plane is shown in the panel. Values are means ± s.e.m.

Extended Data Figure 3 Opposite parvalbumin-network configurations induced by environmental enrichment and contextual fear conditioning.

a, Time course of PV-network configuration shifts upon EE and cFC in CA3b. Persistence of PV-network shift induced by 1 week of EE: value at 2 weeks upon returning EE mice to their standard cages (indicated as 7 days and 14 days). n > 4 mice each. b, c, PV-network shifts in CA3b at 1 year (b) and in CA1 (c; 3 months mice). n = 5 mice each. *P < 0.05,**P < 0.01 and ***P < 0.001. Values are means ± s.e.m.

Extended Data Figure 4 Parvalbumin-neuron basket and chandelier connectivities in CA3b.

a, Fractions (%) of PV boutons with high (H), intermediate high (iH), intermediate low (iL) and low (L) PV-immunoreactivity values around individual pyramidal neuron somas in control, EE and cFC mice (each line represents values for one pyramidal neuron). n = 3 mice, >20 pyramidal cells per mouse, 30–70 boutons per basket. b, Example of a GFP-positive PV basket by an individual PV neuron (sparse Thy1-mGFPLsi1 transgenic line). c, Fractions (%) of PV boutons with high (H), intermediate high (iH), intermediate low (iL) and low (L) PV-immunoreactivity values along individual axon-initial segments in control, EE and cFC mice (each line represents values for one AIS). Note how experience influences PV distributions of basket-cell boutons but not of chandelier boutons. n = 3 mice, >20 AIS per mouse, 5–20 boutons per AIS. Scale bar, 5 μm.

Extended Data Figure 5 Behavioural counterpart of parvalbumin-network configuration shifts.

Left, c-Fos recruitment upon FOR. Values determined in dorsal hippocampus CA3, 90 min upon behavioural testing. Threshold for c-Fos-positive neurons includes high- and intermediate-c-Fos neurons, as described20. n = 4 mice each. Right, fear conditioning in the dark22 does not influence PV-neuron differentiation markers. n = 4 mice each. Values are means ± s.e.m.

Extended Data Figure 6 Analysis of synaptic puncta onto parvalbumin neurons in CA3b.

a, Representative triple-labelling experiments, including PV, VIP, and pre- and postsynaptic markers for inhibitory (gephyrin, VGAT) and excitatory (Bassoon, PSD95) synapses. Scale bars, 0.5 μm. b, Equal contributions by VIP-positive and VIP-negative boutons to increased inhibitory synaptic puncta densities upon EE or ChABC. Average values from 5 mice (30 PV-dendrite stretches per mouse) each. c, Relationship between excitatory–inhibitory synaptic puncta densities and PV-immunoreactivity levels. Individual neuron data from Fig. 2c, labelled according to experimental condition of origin. Values are means ± s.e.m.

Extended Data Figure 7 Genetic control of parvalbumin neurons.

a, Specific optogenetic control of PV-network configuration shift in VIP–Cre and PV–Cre slice cultures. Combination of ChR2 construct and light induces PV shift, whereas construct or light alone have no influence on PV-neuron configuration. Time point, 6 h; 3 slice cultures and 15–20 PV neurons each. b, Representative examples of CA3b PV neurons expressing PSAM activator or inhibitor for pharmacogenetic control. PSAM constructs are visualized with α-Bungarotoxin. c, Specific pharmacogenetic control of hippocampal CA3 PV network in vivo. PSAM construct or ligand (PSEM308) alone have no influence on PV-neuron configuration or FOR performance. n = 6 mice each (50 neurons per mouse). d, Left, tracing of VIP–GFP neuron in slice culture from VIP–Cre mouse, with dendrites in stratum lacunosum molecolare and axonal arborization restricted to CA3 stratum radiatum. Center, putative synaptic contacts (arrows) by VIP–GFP varicosities from a neuron as in the left panel, and PV-positive dendrites (see also Fig. 4b). Right, proposed connectivity by VIP–PV microcircuit in CA3b. e, Pharmacogenetic activation of CA3 VIP neurons at FOR enhances c-Fos recruitment. PSAM-activator was expressed in dorsal CA3 VIP neurons (VIP–Cre mice). FOR memory was retrieved 45 min after delivery of PSAM ligand, and mice were analysed 90 min later for CA3 c-Fos expression. Activation of VIP neurons enhanced contents of c-Fos-positive CA3 pyramidal neurons to an extent comparable to that of a low-PV network shift during MWM training. n = 3 mice each. Scale bars, 5 μm. Values are means ± s.e.m.

Extended Data Figure 8 Pharmacological manipulation of hippocampal CA3 parvalbumin network with ChABC or BDNF.

a, PV-network configuration, FOR performance and synapse turnover upon local CA3b treatments with ChABC (low-PV configuration) or BDNF (high-PV configuration). n = 3–6 mice each. b, Excitatory (Bassoon) and inhibitory (gephyrin) synaptic puncta densities along PV dendrites in CA3b stratum lucidum (SL), radiatum (SR) and oriens (SO) upon ChABC or BDNF. Fold changes versus values in control mice; average values from 5 mice (30 PV-dendrite stretches per mouse) each. Values are means ± s.e.m.

Extended Data Figure 9 Regulation of MWM learning by VIP signalling and previous experience.

a, VIP modulation of MWM learning. Accelerated spatial learning upon local delivery of VIP (left) and impaired spatial memory upon local inhibition of VIP receptor (right) during MWM training. n = 5 mice each. b, Influence of previous EE or cFC experience on MWM learning. Learning curves and reference memory tests. n = 10 mice each. c, Influence of previous EE or cFC experience on PV-network configuration shift during MWM training. PV-network configurations at day10 of MWM training, and at start of MWM training. n = 10 mice each. Values are means ± s.e.m.

Extended Data Figure 10 System specificity of learning-related PV-network configuration shifts.

a–c, No PV = network configuration shifts in M1 upon MWM (a) or in hippocampal CA3 upon rotarod learning (b); no shift in synaptic puncta densities onto CA3b PV neurons upon rotarod learning (c). n = 4 mice each. d, No alterations in hippocampal mossy-fibre-terminal active-zone turnover (left) or FOR performance (right) upon rotarod learning. n = 6 mice each. Values are means ± s.e.m.

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Donato, F., Rompani, S. & Caroni, P. Parvalbumin-expressing basket-cell network plasticity induced by experience regulates adult learning. Nature 504, 272–276 (2013). https://doi.org/10.1038/nature12866

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