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Distinct synchronization, cortical coupling and behavioral function of two basal forebrain cholinergic neuron types

A Publisher Correction to this article was published on 14 August 2020

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Abstract

Basal forebrain cholinergic neurons (BFCNs) modulate synaptic plasticity, cortical processing, brain states and oscillations. However, whether distinct types of BFCNs support different functions remains unclear. Therefore, we recorded BFCNs in vivo, to examine their behavioral functions, and in vitro, to study their intrinsic properties. We identified two distinct types of BFCNs that differ in their firing modes, synchronization properties and behavioral correlates. Bursting cholinergic neurons (Burst-BFCNs) fired synchronously, phase-locked to cortical theta activity and fired precisely timed bursts after reward and punishment. Regular-firing cholinergic neurons (Reg-BFCNs) were found predominantly in the posterior basal forebrain, displayed strong theta rhythmicity and responded with precise single spikes after behavioral outcomes. In an auditory detection task, synchronization of Burst-BFCNs to the auditory cortex predicted the timing of behavioral responses, whereas tone-evoked cortical coupling of Reg-BFCNs predicted correct detections. We propose that differential recruitment of two basal forebrain cholinergic neuron types generates behavior-specific cortical activation.

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Fig. 1: In vivo recordings revealed two types of central cholinergic neurons, Burst-BFCNs and Reg-BFCNs.
Fig. 2: In vitro recordings confirmed two types of central cholinergic neurons.
Fig. 3: Cholinergic bursts transmit phasic information about reinforcers.
Fig. 4: Bursting cholinergic neurons show synchronous activity.
Fig. 5: Cholinergic bursts are coupled to cortical activity.
Fig. 6: Cortex–BFCN synchrony predicts behavior in an auditory detection task.
Fig. 7: The horizontal diagonal band contains few regular firing cholinergic neurons.
Fig. 8: Tonic and phasic cholinergic effects.

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Data availability

Statistics source data underlying the figures are provided in Excel format. The datasets analyzed during the current study are available from the corresponding author on reasonable request.

Code availability

Data analysis was performed by built-in and custom written Matlab code (Mathworks) available at: https://github.com/hangyabalazs/nb_sync_subimtted.

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References

  1. Everitt, B. J. & Robbins, T. W. Central cholinergic systems and cognition. Annu. Rev. Psychol. 48, 649–84 (1997).

    CAS  PubMed  Google Scholar 

  2. Hasselmo, M. E. & Sarter, M. Modes and models of forebrain cholinergic neuromodulation of cognition. Neuropsychopharmacology 36, 52–73 (2011).

    CAS  PubMed  Google Scholar 

  3. Herman, aM., Huang, L., Murphey, D. K., Garcia, I. & Arenkiel, B. R. Cell type-specific and time-dependent light exposure contribute to silencing in neurons expressing Channelrhodopsin-2. eLife 3, e01481–e01481 (2014).

    PubMed  PubMed Central  Google Scholar 

  4. Froemke, R. C., Merzenich, M. M. & Schreiner, C. E. A synaptic memory trace for cortical receptive field plasticity. Nature 450, 425–9 (2007).

    CAS  PubMed  Google Scholar 

  5. Chubykin, A. A., Roach, E. B., Bear, M. F. & Shuler, M. G. H. A cholinergic mechanism for reward timing within primary visual cortex. Neuron 77, 723–35 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Gu, Z. & Yakel, J. L. Timing-dependent septal cholinergic induction of dynamic hippocampal synaptic plasticity. Neuron 71, 155–65 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Yang, C., Thankachan, S., McCarley, R. W. & Brown, R. E. The menagerie of the basal forebrain: how many (neural) species are there, what do they look like, how do they behave and who talks to whom? Curr. Opin. Neurobiol. 44, 159–166 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  8. Parikh, V., Kozak, R., Martinez, V. & Sarter, M. Prefrontal acetylcholine release controls cue detection on multiple timescales. Neuron 56, 141–54 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  9. Teles-Grilo Ruivo, L. M. et al. Coordinated acetylcholine release in prefrontal cortex and hippocampus Is associated with arousal and reward on distinct timescales. Cell Rep. 18, 905–917 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Palacios-Filardo, J. & Mellor, J. R. Neuromodulation of hippocampal long-term synaptic plasticity. Curr. Opin. Neurobiol. 54, 37–43 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Unal, C. T., Golowasch, J. P. & Zaborszky, L. Adult mouse basal forebrain harbors two distinct cholinergic populations defined by their electrophysiology. Front. Behav. Neurosci. 6, 21 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. López-Hernández, G. Y. et al. Electrophysiological properties of basal forebrain cholinergic neurons identified by genetic and optogenetic tagging. J. Neurochem. 142, 103–110 (2017).

    PubMed  PubMed Central  Google Scholar 

  13. Khateb, A. et al. Cholinergic nucleus basalis neurons display the capacity for rhythmic bursting activity mediated by low-threshold calcium spikes. Neuroscience 51, 489–94 (1992).

    CAS  PubMed  Google Scholar 

  14. Nyíri, G. et al. GABA B and CB 1 cannabinoid receptor expression identifies two types of septal cholinergic neurons. Eur. J. Neurosci. 21, 3034–3042 (2005).

    PubMed  Google Scholar 

  15. Harrison, T. C., Pinto, L., Brock, J. R. & Dan, Y. Calcium imaging of basal forebrain activity during innate and learned behaviors. Front. Neural Circuits 10, 1–12 (2016).

    Google Scholar 

  16. Lovett-Barron, M. et al. Dendritic inhibition in the hippocampus supports fear learning. Science 343, 857–63 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Hangya, B., Ranade, S. P., Lorenc, M. & Kepecs, A. Central cholinergic neurons are rapidly recruited by reinforcement feedback. Cell 162, 1155–1168 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Fries, P. et al. Rhythms for cognition: communication through coherence. Neuron 88, 220–35 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Somogyi, P., Katona, L., Klausberger, T., Lasztóczi, B. & Viney, T. J. Temporal redistribution of inhibition over neuronal subcellular domains underlies state-dependent rhythmic change of excitability in the hippocampus. Phil. Trans. R. Soc. B Biol. Sci. 369, 20120518 (2014).

    Google Scholar 

  20. van Dijk, H., Schoffelen, J.-M., Oostenveld, R. & Jensen, O. Prestimulus oscillatory activity in the alpha band predicts visual discrimination ability. J. Neurosci. 28, 1816–23 (2008).

    PubMed  PubMed Central  Google Scholar 

  21. Landau, A. N. & Fries, P. Attention samples stimuli rhythmically. Curr. Biol. 22, 1000–1004 (2012).

    CAS  PubMed  Google Scholar 

  22. Simon, A. P., Poindessous-Jazat, F., Dutar, P., Epelbaum, J. & Bassant, M. H. Firing properties of anatomically identified neurons in the medial septum of anesthetized and unanesthetized restrained rats. J. Neurosci. 26, 9038–9046 (2006).

    CAS  PubMed  Google Scholar 

  23. Duque, A., Balatoni, B., Detari, L. & Zaborszky, L. EEG correlation of the discharge properties of identified neurons in the basal forebrain. J. Neurophysiol. 84, 1627–35 (2000).

    CAS  PubMed  Google Scholar 

  24. Lee, M. G., Hassani, O. K., Alonso, A. & Jones, B. E. Cholinergic basal forebrain neurons burst with theta during waking and paradoxical sleep. J. Neurosci. 25, 4365–9 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Zaborszky, L., van den Pol, A. & Gyengesi, E. in The Mouse Nervous System (eds Watson, C. et al.) 684–718 (Elsevier, 2012).

  26. Royer, S. et al. Control of timing, rate and bursts of hippocampal place cells by dendritic and somatic inhibition. Nat. Neurosci. 15, 769–75 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Buzsáki, G. & Mizuseki, K. The log-dynamic brain: how skewed distributions affect network operations. Nat. Rev. Neurosci. 15, 264–278 (2014).

    PubMed  PubMed Central  Google Scholar 

  28. Lin, S.-C. & Nicolelis, Ma. L. Neuronal ensemble bursting in the basal forebrain encodes salience irrespective of valence. Neuron 59, 138–49 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Sarter, M., Parikh, V. & Howe, W. M. Phasic acetylcholine release and the volume transmission hypothesis: time to move on. Nat. Rev. Neurosci. 10, 383–90 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Saper, C. B. Organization of cerebral cortical afferent systems in the rat. II. Magnocellular basal nucleus. J. Comp. Neurol. 222, 313–42 (1984).

    CAS  PubMed  Google Scholar 

  31. Buzsaki, G. et al. Nucleus basalis and thalamic control of neocortical activity in the freely moving rat. J. Neurosci. 8, 4007–26 (1988).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Pinto, L. et al. Fast modulation of visual perception by basal forebrain cholinergic neurons. Nat. Neurosci. 16, 1857–63 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Gielow, M. R. & Zaborszky, L. The input–output relationship of the cholinergic basal forebrain. Cell Rep. 18, 1817–1830 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Do, J. P. et al. Cell type-specific long-range connections of basal forebrain circuit. eLife 5, 1–17 (2016).

    Google Scholar 

  35. Tingley, D., Alexander, A. S., Quinn, L. K., Chiba, A. A. & Nitz, D. A. Cell assemblies of the basal forebrain. J. Neurosci. 35, 2992–3000 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Rye, D. B., Wainer, B. H., Mesulam, M. M., Mufson, E. J. & Saper, C. B. Cortical projections arising from the basal forebrain: a study of cholinergic and noncholinergic components employing combined retrograde tracing and immunohistochemical localization of choline acetyltransferase. Neuroscience 13, 627–43 (1984).

    CAS  PubMed  Google Scholar 

  37. Kepecs, A., Wang, X.-J. & Lisman, J. Bursting neurons signal input slope. J. Neurosci. 22, 9053–62 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Arroyo, S., Bennett, C. & Hestrin, S. Nicotinic modulation of cortical circuits. Front. Neural Circuits 8, 1–6 (2014).

    Google Scholar 

  39. Urban-Ciecko, J., Jouhanneau, J. S., Myal, S. E., Poulet, J. F. A. & Barth, A. L. Precisely timed nicotinic activation drives SST inhibition in neocortical circuits. Neuron 97, 611–625.e5 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. Tanimura, A. et al. Striatal cholinergic interneurons and Parkinson’s disease. Eur. J. Neurosci. 47, 1148–1158 (2018).

    PubMed  Google Scholar 

  41. Schiemann, J. et al. K-ATP channels in dopamine substantia nigra neurons control bursting and novelty-induced exploration. Nat. Neurosci. 15, 1272–80 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Moore, J. D. et al. Hierarchy of orofacial rhythms revealed through whisking and breathing. Nature 497, 205–210 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Hires, S. A., Gutnisky, D. A., Yu, J., O’Connor, D. H. & Svoboda, K. Low-noise encoding of active touch by layer 4 in the somatosensory cortex. eLife 4, 1–18 (2015).

    Google Scholar 

  44. Bali, Z. K., Nagy, L. V. & Hernádi, I. Alpha7 nicotinic acetylcholine receptors play a predominant role in the cholinergic potentiation of N-methyl-d-aspartate evoked firing responses of hippocampal CA1 pyramidal cells. Front. Cell. Neurosci. 11, 1–13 (2017).

    Google Scholar 

  45. Pesti, K., Szabo, A. K., Mike, A. & Vizi, E. S. Neuropharmacology kinetic properties and open probability of α7 nicotinic acetylcholine receptors. Neuropharmacology 81, 101–115 (2014).

    CAS  PubMed  Google Scholar 

  46. Guo, W., Robert, B. & Polley, D. B. The cholinergic basal forebrain links auditory stimuli with delayed reinforcement to support learning. Neuron 103, 1164–1177 (2019).

  47. Letzkus, J. J. et al. A disinhibitory microcircuit for associative fear learning in the auditory cortex. Nature 480, 331–335 (2011).

    CAS  PubMed  Google Scholar 

  48. Li, X. et al. Generation of a whole-brain atlas for the cholinergic system and mesoscopic projectome analysis of basal forebrain cholinergic neurons. Proc. Natl Acad. Sci. USA 115, 415–420 (2018).

    CAS  PubMed  Google Scholar 

  49. Otto, T., Eichenbaum, H., Wiener, S. I. & Wible, C. G. Learning-related patterns of CA1 spike trains parallel stimulation parameters optimal for inducing hippocampal long-term potentiation. Hippocampus 1, 181–92 (1991).

    CAS  PubMed  Google Scholar 

  50. Reinagel, P., Godwin, D., Sherman, S. M. & Koch, C. Encoding of visual information by LGN bursts. J. Neurophysiol. 81, 2558–2569 (1999).

    CAS  PubMed  Google Scholar 

  51. Higley, M. J. et al. Cholinergic interneurons mediate fast vGluT3-dependent glutamatergic transmission in the striatum. PLoS ONE 6, e19155 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  52. Zhao, S. et al. Cell type–specific channelrhodopsin-2 transgenic mice for optogenetic dissection of neural circuitry function. Nat. Methods 8, 745–752 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Solari, N., Sviatkó, K., Laszlovszky, T., Hegedüs, P. & Hangya, B. Open source tools for temporally controlled rodent behavior suitable for electrophysiology and optogenetic manipulations. Front. Syst. Neurosci. 12, 18 (2018).

    PubMed  PubMed Central  Google Scholar 

  54. Schmitzer-Torbert, N. et al. Quantitative measures of cluster quality for use in extracellular recordings. Neuroscience 131, 1–11 (2005).

  55. Endres, D. M. & Schindelin, J. E. A new metric for probability distributions. IEEE Trans. Inf. Theory 49, 1858–1860 (2003).

    Google Scholar 

  56. Kvitsiani, D. et al. Distinct behavioural and network correlates of two interneuron types in prefrontal cortex. Nature 498, 363–366 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank J. Szabadics, V. Varga, L. Acsády, N. Hádinger and G. Buzsáki for insightful discussions and comments on the manuscript and K. Sviatkó for help with graphics in Fig. 8. This work was supported by the ‘Lendület’ Program of the Hungarian Academy of Sciences (LP2015-2/2015), NKFIH KH125294 and the European Research Council Starting (grant no. 715043) to B.H., NKFIH K115441 and KH124345 to A.G., NINDS R01NS088661, R01NS075531 and McKnight Cognitive Disorders Award to A.K., ÚNKP-19-3 New National Excellence Program of the Ministry for Innovation and Technology to P.H., and EFOP-3.6.3-VEKOP-16-2017-00009 to D.S. and T.L. B.H. is a member of the FENS-Kavli Network of Excellence.

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Authors and Affiliations

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Contributions

B.H. conceived the project, B.H. recorded in vivo data under the supervision of A.K. P.H. recorded in vivo data under the supervision of B.H. D.S. recorded and analyzed in vitro data under the supervision of A.G. and T.F.F. T.L., P.H. and B.H. analyzed in vivo data. B.H., T.L. and D.S. wrote the manuscript, with comments from all authors.

Corresponding author

Correspondence to Balázs Hangya.

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The authors declare no competing interests.

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Peer review information Nature Neuroscience thanks Anita Disney, Shih-Chieh Lin and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Optogenetically identified and putative cholinergic neurons behave similarly.

a, Average auto-correlogram of Burst-BFCN-SBs (red), Burst-BFCN-PLs (orange) and Reg-BFCNs (green). Left, optogenetically identified; right, putative. While nominal normalized magnitudes may differ due to varying noise levels and moderate sample sizes, the auto-correlation curves are qualitatively similar. Solid lines, mean; shading, s.e.m. b, Response to punishment of identified cholinergic neurons (left, identified NB; right, identified HDB). Solid lines, mean; shading, s.e.m. c, Response to punishment of putative cholinergic neurons. HDB neurons showed somewhat slower and more variable responses. Note also the longer response latencies of two regular pChAT neurons. Solid lines, mean; shading, s.e.m. d, Burst index vs. relative refractory period for identified (circle; red, n = 26 Burst-BFCN-SBs; orange, n = 17 Burst-BFCN-PLs; green, n = 13 Reg-BFCNs) and putative (triangle; red, n = 12 Burst-BFCN-SBs; orange, n = 8 Burst-BFCN-PLs; green, n = 2 Reg-BFCNs) cholinergic neurons. e, Pearson’s correlation between theta index and relative refractory period. No systematic difference between identified (circle; red, n = 26 Burst-BFCN-SBs; orange, n = 17 Burst-BFCN-PLs; green, n = 13 Reg-BFCNs) and putative (triangle; red, n = 12 Burst-BFCN-SBs; orange, n = 8 Burst-BFCN-PLs; green, n = 2 Reg- BFCNs) cholinergic neurons were detected (p = 0.0007 for n = 15 Reg-BFCNs, one-sided F-test, F(1,13) = 19.67). f, Baseline firing rate did not show systematic differences between identified (circle; red, n = 26 Burst-BFCN-SBs; orange, n = 17 Burst-BFCN-PLs; green, n = 13 Reg-BFCNs) and putative (triangle; red, n = 12 Burst-BFCN-SBs; orange, n = 8 Burst-BFCN-PLs; green, n = 2 Reg-BFCNs) cholinergic neurons.

Source data

Extended Data Fig. 2 Burst selectivity and model fitting.

a, Identified (left, p = 0.00021, two-sided Wilcoxon signed rank test) and putative (right, p = 0.0005, two-sided Wilcoxon signed rank test) Burst-BFCN-SBs exhibited similar burst selectivity. Solid lines, mean; shading, s.e.m.; bars, median. b, The same for Burst-BFCN-PLs (left, identified, p = 0.0084, two-sided Wilcoxon signed rank test; right, putative, p = 0.0078, two-sided Wilcoxon signed rank test). Solid lines, mean; shading, s.e.m.; bars, median. c, A mixture of Gaussian distributions from 1 to 5 modes were fitted on the logarithm of refractory period distribution. Refractory period of BFCNs (n = 78) showed bimodal distribution, confirmed by AIC (red) and BIC (blue) model selection measures (lowest value corresponds to best fit model).

Source data

Extended Data Fig. 3 Many regular rhythmic basal forebrain neurons are cholinergic.

a-c, Auto-correlations of untagged bursting (a), Poisson-like (b), and regular rhythmic (c) NB neurons. d, Average auto-correlations (red, n = 559 untagged strongly bursting; orange, n = 692 Poisson-like; green, n = 17 regular rhythmic basal forebrain neurons). Solid lines, mean; shading, s.e.m. e, Scatter plot showing burst index and refractory period of the same neurons. f, Pearson’s correlation between refractory period and theta index (p = 6.36 × 10-6 for n = 17 regular rhythmic basal forebrain neurons (green), one-sided F-test, F(1,15) = 45.77; red, n = 559 untagged strongly bursting; orange, n = 692 Poisson-like basal forebrain neurons). g, Median theta index (red, n = 559 untagged strongly bursting; orange, n = 692 Poisson-like; green, n = 17 regular rhythmic basal forebrain neurons; ***, p < 0.001; strongly bursting vs. Poisson-like, p = 1.99 × 10-24; strongly bursting vs. regular rhythmic, p = 4.41 × 10-8; Poisson-like vs. regular rhythmic, 6.04 × 10-11; two-sided Mann-Whitney U-test). Bars, median. h, Predictive value of regular rhythmic firing pattern for cholinergic identity as a function of relative refractory period. Black line and right y-axis correspond to the ratio of (identified or putative) cholinergic neurons to all neurons in the bin.

Source data

Extended Data Fig. 4 Similar testing conditions resulted in robust spike delay difference between Burst-BFCNs and Reg-BFCNs, while spike delays were comparable at depolarized membrane potentials.

a, Statistical comparison of spike delay as function of pre-polarization membrane potential. To confirm that late spiking property of Reg-BFCNs was not due to different testing conditions, we compared pre-polarization membrane potentials between groups (n = 31 late-firing and n = 29 early firing cholinergic cells, two-sample, two-sided Kolmogorov-Smirnov test). Bars show median. b, Example traces of a Reg-BFCN (left) and Burst-BFCN (right) spike response at hyperpolarized and depolarized membrane potentials. Note that the late-firing property of Reg-BFCNs is characteristic to hyperpolarized membrane potentials. c, Minimum spike delay of each recorded cell vs. burst index (green, Reg-BFCNs; red, Burst-BFCNs). d, Minimum spike delay group statistics (n = 31 late-firing and n = 29 early firing cholinergic cells). Box-whisker plots show median, interquartile range, non-outlier range and outliers.

Source data

Extended Data Fig. 5 Cholinergic bursts transmit phasic information about reinforcers.

a, Raster plots (left) and corresponding peri-event time histograms (PETH, right) aligned to reward (blue) and punishment (brown) of a Reg-BFCN. After the precise phasic response, the intrinsic theta oscillation resumes. b, Raster plots (left) and corresponding PETHs (right) aligned to reward (blue) and punishment (brown) of an optogenetically identified tonically active cholinergic interneuron (TAN) recorded from the nucleus accumbens. Note the lack of precisely timed action potentials after reinforcement. Instead, TANs show well-characterized so-called ‘pause-burst’ responses after reward. c, Average PETH aligned to reward (blue) and punishment (brown) at two different time scales of n = 5 optogenetically identified TANs from caudate putamen (n = 3) and nucleus accumbens (n = 2) Solid lines, mean; shading, s.e.m. d, PETHs aligned to punishment (left) and reward (right) for all recorder TANs. e, Burst-BFCN-PLs showed similar burst selectivity after punishment as Burst-BFCN-SBs (p = 0.0004, two-sided Wilcoxon signed rank test). Solid lines, mean; shading, s.e.m.; bars, median. f, BFCNs responded phasically to reward (red, n = 38 Burst-BFCN-SBs; orange, n = 25 Burst-BFCN-PLs; green, n = 15 Reg-BFCNs). Solid lines, mean; shading, s.e.m. g, Bursts of Burst-BFCN-SBs (n = 33) appeared selectively after reward (p = 0.0093, two-sided Wilcoxon signed rank test). Solid lines, mean; shading, s.e.m.; bars, median.

Source data

Extended Data Fig. 6 Individual cross-correlations for all BFCN pairs.

a, Pairs of Burst-BFCN-SBs. b, Pairs containing Burst-BFCN-PLs and Burst-BFCN-SBs. c, Pairs containing Reg-BFCNs. Grey lines indicate 95% bootstrap confidence intervals calculated with the shift predictor method.

Extended Data Fig. 7 Bursting and regular rhythmic cholinergic neurons respond differently to hyperpolarization in vitro.

a, Peak latency statistics of auditory LFP average triggered on BF spikes in vivo (see Fig. 5b-c; red, n = 16 Burst-BFCN-SBs; orange, n = 12 Burst-BFCN-PLs; green, n = 9 Reg-BFCNs; *, p < 0.05; Burst-BFCN-SBs vs. Burst- BFCN-PLs, p = 0.546; Burst-BFCN-SBs vs. Reg-BFCNs, p = 0.014; Burst-BFCN-PLs vs. Reg-BFCNs, p = 0.017; two-sided Mann-Whitney U-test). Bars, median. b, Representative responses of a Burst-BFCN (top, red) and Reg-BFCN (bottom, green) upon short (20 ms) hyperpolarizing somatic current injection in vitro. Spike rasters of 30 consecutive current injection sessions are displayed below. c, Distribution of the first spike latencies following hyperpolarization. Individual cells (horizontal bar plots) are shown above summary histogram (red, n = 4 Burst-BFCNs, green, n = 6 Reg-BFCNs, p = 6.47 × 10-44, two-sided Mann-Whitney U-test; box plots show median, interquartile range and non-outlier range).

Source data

Extended Data Fig. 8 Some auditory cortical neurons are synchronous with local LFP.

a-d, Example cortical neurons that show synchrony with local LFP. Left, STA; middle, STS power; right, STS phase (a, n = 50000 spikes; b, n = 21765 spikes; c, n = 4083 spikes; d, n = 7834 spikes). Solid line, mean; shading, s.e.m.

Extended Data Fig. 9 HDB contains few regular rhythmic neurons.

Auto-correlograms of all unidentified HDB neurons (left, bursting, n = 274; middle, Poisson-like, n = 274; right, regular rhythmic, n = 12). HDB had only 12/560 regular rhythmic neurons.

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Laszlovszky, T., Schlingloff, D., Hegedüs, P. et al. Distinct synchronization, cortical coupling and behavioral function of two basal forebrain cholinergic neuron types. Nat Neurosci 23, 992–1003 (2020). https://doi.org/10.1038/s41593-020-0648-0

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