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Cholinergic Behavior State-Dependent Mechanisms of Neocortical Gain Control: a Neurocomputational Study

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Abstract

The embodied mammalian brain evolved to adapt to an only partially known and knowable world. The adaptive labeling of the world is critically dependent on the neocortex which in turn is modulated by a range of subcortical systems such as the thalamus, ventral striatum, and the amygdala. A particular case in point is the learning paradigm of classical conditioning where acquired representations of states of the world such as sounds and visual features are associated with predefined discrete behavioral responses such as eye blinks and freezing. Learning progresses in a very specific order, where the animal first identifies the features of the task that are predictive of a motivational state and then forms the association of the current sensory state with a particular action and shapes this action to the specific contingency. This adaptive feature selection has both attentional and memory components, i.e., a behaviorally relevant state must be detected while its representation must be stabilized to allow its interfacing to output systems. Here, we present a computational model of the neocortical systems that underlie this feature detection process and its state-dependent modulation mediated by the amygdala and its downstream target the nucleus basalis of Meynert. In particular, we analyze the role of different populations of inhibitory interneurons in the regulation of cortical activity and their state-dependent gating of sensory signals. In our model, we show that the neuromodulator acetylcholine (ACh), which is in turn under control of the amygdala, plays a distinct role in the dynamics of each population and their associated gating function serving the detection of novel sensory features not captured in the state of the network, facilitating the adjustment of cortical sensory representations and regulating the switching between modes of attention and learning.

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References

  1. Turchi J, Sarter M (1997) Cortical acetylcholine and processing capacity: effects of cortical cholinergic deafferentation on crossmodal divided attention in rats. Cogn Brain Res 6:147–158

    Article  CAS  Google Scholar 

  2. Himmelheber AM, Sarter M, Bruno JP (2000) Increases in cortical acetylcholine release during sustained attention performance in rats. Cogn Brain Res 9:313–325

    Article  CAS  Google Scholar 

  3. Klinkenberg I, Sambeth A, Blokland A (2011) Acetylcholine and attention. Behav Brain Res 221:430–442

    Article  CAS  PubMed  Google Scholar 

  4. Phillis JW (1968) Acetylcholine release from the cerebral cortex: its role in cortical arousal. Brain Res 7:378–389

    Article  CAS  PubMed  Google Scholar 

  5. Gould R, Nedelcovych M, Dencker D et al (2014) Influence of M1 muscarinic acetylcholine receptor activation on arousal and cognitive performance using electroencephalography and novel touchscreen cognition assessment (845.5). FASEB J 28:845

    Google Scholar 

  6. Jones BE, Cuello AC (1989) Afferents to the basal forebrain cholinergic cell area from pontomesencephalic—catecholamine, serotonin, and acetylcholine—neurons. Neuroscience 31:37–61. doi:10.1016/0306-4522(89)90029-8

    Article  CAS  PubMed  Google Scholar 

  7. Smiley JF, Subramanian M, Mesulam M-M (1999) Monoaminergic–cholinergic interactions in the primate basal forebrain. Neuroscience 93:817–829. doi:10.1016/S0306-4522(99)00116-5

    Article  CAS  PubMed  Google Scholar 

  8. Zaborszky L (1989) Afferent connections of the forebrain cholinergic projection neurons, with special reference to monoaminergic and peptidergic fibers. In: Central cholinergic synaptic transmission. Birkhäuser Basel, pp 12–32. doi:10.1007/978-3-0348-9138-7_2

  9. Carnes KM, Fuller TA, Price JL (1990) Sources of presumptive glutamatergic/aspartatergic afferents to the magnocellular basal forebrain in the rat. J Comp Neurol 302:824–852. doi:10.1002/cne.903020413

    Article  CAS  PubMed  Google Scholar 

  10. Zaborszky L, Gaykema R, Swanson D, Cullinan W (1997) Cortical input to the basal forebrain. Neuroscience 79:1051–1078. doi:10.1016/S0306-4522(97)00049-3

    Article  CAS  PubMed  Google Scholar 

  11. Gastard M, Jensen SL, Martin JR III et al (2002) The caudal sublenticular region/anterior amygdaloid area is the only part of the rat forebrain and mesopontine tegmentum occupied by magnocellular cholinergic neurons that receives outputs from the central division of extended amygdala. Brain Res 957:207–222. doi:10.1016/S0006-8993(02)03513-8

    Article  CAS  PubMed  Google Scholar 

  12. Grove EA (1988) Neural associations of the substantia innominata in the rat: afferent connections. J Comp Neurol 277:315–346. doi:10.1002/cne.902770302

    Article  CAS  PubMed  Google Scholar 

  13. Liu AKL, Chang RC-C, Pearce RKB, Gentleman SM (2015) Nucleus basalis of Meynert revisited: anatomy, history and differential involvement in Alzheimer’s and Parkinson’s disease. Acta Neuropathol 129:527–540. doi:10.1007/s00401-015-1392-5

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Kawaguchi Y (1997) Selective cholinergic modulation of cortical GABAergic cell subtypes. J Neurophysiol 78:1743–1747. doi:10.1016/0006-8993(82)90067-1

    Article  CAS  PubMed  Google Scholar 

  15. Yi F, Ball J, Stoll KE et al (2014) Direct excitation of parvalbumin-positive interneurons by M1 muscarinic acetylcholine receptors: roles in cellular excitability, inhibitory transmission and cognition. J Physiol 592:3463–3494. doi:10.1113/jphysiol.2014.275453

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Lawrence JJ (2008) Cholinergic control of GABA release: emerging parallels between neocortex and hippocampus. Trends Neurosci 31:317–327. doi:10.1016/j.tins.2008.03.008

    Article  CAS  PubMed  Google Scholar 

  17. Markram H, Toledo-Rodriguez M, Wang Y et al (2004) Interneurons of the neocortical inhibitory system. Nat Rev Neurosci 5:793–807. doi:10.1038/nrn1519

    Article  CAS  PubMed  Google Scholar 

  18. Connors BW, Gutnick MJ (1990) Intrinsic firing patterns of diverse neocortical neurons. Trends Neurosci 13:99–104

    Article  CAS  PubMed  Google Scholar 

  19. Kawaguchi Y, Kubota Y (1997) GABAergic cell subtypes and their synaptic connections in rat frontal cortex. Cereb Cortex 7:476–486. doi:10.1093/cercor/7.6.476

    Article  CAS  PubMed  Google Scholar 

  20. Kawaguchi Y (1993) Groupings of nonpyramidal and pyramidal cells with specific physiological and morphological characteristics in rat frontal cortex. J Neurophysiol 69:416–431

    Article  CAS  PubMed  Google Scholar 

  21. Kubota Y, Hattori R, Yui Y (1994) Three distinct subpopulations of GABAergic neurons in rat frontal agranular cortex. Brain Res 649:159–173

    Article  CAS  PubMed  Google Scholar 

  22. Shepherd GM (2003) The synaptic organization of the brain. Oxford University Press, New York

  23. Rudy B, Fishell G, Lee S, Hjerling-leffler J (2010) Three groups of interneurons account for nearly 100% of neocortical GABAergic neurons. Dev Neurobiol 71(1):45–61. doi:10.1002/dneu.20853

  24. Disney AA, Aoki C, Hawken MJ (2007) Gain modulation by nicotine in macaque V1. Neuron 56:701–713. doi:10.1016/j.neuron.2007.09.034

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Disney AA, Aoki C (2008) Muscarinic acetylcholine receptors in macaque V1 are most frequently expressed by parvalbumin-immunoreactive neurons. J Comp Neurol 507:1748–1762

    Article  PubMed  PubMed Central  Google Scholar 

  26. Disney AA, Alasady HA, Reynolds JH (2014) Muscarinic acetylcholine receptors are expressed by most parvalbumin-immunoreactive neurons in area MT of the macaque. Brain Behav 4:431–445. doi:10.1002/brb3.225

    Article  PubMed  PubMed Central  Google Scholar 

  27. Demars MP, Morishita H (2014) Cortical parvalbumin and somatostatin GABA neurons express distinct endogenous modulators of nicotinic acetylcholine receptors. Mol Brain 7:75. doi:10.1186/s13041-014-0075-9

    Article  PubMed  PubMed Central  Google Scholar 

  28. Markov NT, Misery P, Falchier A et al (2011) Weight consistency specifies regularities of macaque cortical networks. Cereb Cortex 21:1254–1272. doi:10.1093/cercor/bhq201

    Article  CAS  PubMed  Google Scholar 

  29. Benucci A, Verschure PFMJ, König P (2007) Dynamical features of higher-order correlation events: Impact on cortical cells. Cogn Neurodyn. doi:10.1007/s11571-006-9000-y

  30. Markov NT, Ercsey-Ravasz MM, Gomes ARR et al (2012) A weighted and directed interareal connectivity matrix for macaque cerebral cortex. Cereb Cortex bhs270

  31. Puigbò J-Y, van Wijngaarden J, Low SC, Verschure PFMJ (2016) Synaptogenesis: constraining synaptic plasticity based on a distance rule. In: Proc. of the Int. Conf. Artif. Neural Networks in LNCS 9886:28–35. doi:10.1007/978-3-319-44778-0_4

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Adesnik H, Bruns W, Taniguchi H (2012) A neural circuit for spatial summation in visual cortex. Nature 490:226–231. doi:10.1038/nature11526

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Gulledge AT (2005) Cholinergic inhibition of neocortical pyramidal neurons. J Neurosci 25:10308–10320. doi:10.1523/JNEUROSCI.2697-05.2005

    Article  CAS  PubMed  Google Scholar 

  35. Douglas RJ, Martin K a C (2007) Mapping the matrix: the ways of neocortex. Neuron 56:226–238. doi:10.1016/j.neuron.2007.10.017

  36. Yang X, Wang K, Shamma SA (1992) Auditory representations of acoustic signals. IEEE Trans Inf Theory 38:824–839

    Article  Google Scholar 

  37. Carandini M, Heeger DJ, Movshon JA (1997) Linearity and normalization in simple cells of the macaque primary visual cortex. J Neurosci 17:8621–8644

    CAS  PubMed  Google Scholar 

  38. Hasselmo ME (2006) The role of acetylcholine in learning and memory. Curr Opin Neurobiol 16:710–715. doi:10.1016/j.conb.2006.09.002

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Metherate R, Cox CL, Ashe JH (1992) Cellular bases of neocortical activation: modulation of neural oscillations by the nucleus basalis and endogenous acetylcholine. J Neurosci 12:4701–4711

    CAS  PubMed  Google Scholar 

  40. Lee JH, Whittington MA, Kopell NJ (2015) Potential mechanisms underlying intercortical signal regulation via cholinergic neuromodulators. J Neurosci 35:15000–15014. doi:10.1523/JNEUROSCI.0629-15.2015

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Callaway EM (2004) Feedforward, feedback and inhibitory connections in primate visual cortex. Neural Netw 17:625–632. doi:10.1016/j.neunet.2004.04.004

    Article  PubMed  Google Scholar 

  42. Bastos AM, Vezoli J, Bosman CA et al (2015) Visual areas exert feedforward and feedback influences through distinct frequency channels. Neuron 85:390–401. doi:10.1016/j.neuron.2014.12.018

    Article  CAS  PubMed  Google Scholar 

  43. Michalareas G, Vezoli J, Van Pelt S et al (2016) Alpha-beta and gamma rhythms subserve feedback and feedforward influences among human visual cortical areas. Neuron 89:384–397. doi:10.1016/j.neuron.2015.12.018

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Gross J (2016) Let the rhythm guide you: non-invasive tracking of cortical communication channels. Neuron 89:247. doi:10.1016/j.neuron.2016.01.001

    Article  Google Scholar 

  45. Froemke RC, Carcea I, Barker AJ et al (2013) Long-term modification of cortical synapses improves sensory perception. Nat Neurosci 16:79–88. doi:10.1038/nn.3274

    Article  CAS  PubMed  Google Scholar 

  46. Weinberger NM (2004) Specific long-term memory traces in primary auditory cortex. Nat Rev Neurosci 5:279–290. doi:10.1038/nrn1366

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Yu AJ, Dayan P (2005) Uncertainty, neuromodulation, and attention. Neuron 46:681–692. doi:10.1016/j.neuron.2005.04.026

    Article  CAS  PubMed  Google Scholar 

  48. Roopun AK, Lebeau FEN, Rammell J et al (2010) Cholinergic neuromodulation controls directed temporal communication in neocortex in vitro. Front Neural Circuits 4:8. doi:10.3389/fncir.2010.00008

    PubMed  PubMed Central  Google Scholar 

  49. Benna MK, Fusi S (2016) Computational principles of synaptic memory consolidation. Nat Neurosci 19:1697–1706. doi:10.1038/nn.4401

    Article  CAS  PubMed  Google Scholar 

  50. Aosaki T, Miura M, Suzuki T et al (2010) Acetylcholine-dopamine balance hypothesis in the striatum: an update. Geriatr Gerontol Int. doi:10.1111/j.1447-0594.2010.00588.x

  51. Lalumiere RT, Mcgaugh JL (2005) Memory enhancement induced by post-training intrabasolateral amygdala infusions of β-adrenergic or muscarinic agonists requires activation of dopamine receptors: involvement of right, but not left, basolateral amygdala. Learn Mem 12:527–532. doi:10.1101/lm.97405

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Acknowledgments

This work has been supported by the European Research Council’s CDAC project: “The Role of Consciousness in Adaptive Behavior: A Combined Empirical, Computational and Robot based Approach” (ERC-2013- ADG 341196); as well as the European Project What You Say Is What You Did WYSIWYD (FP7 ICT 612139).

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Correspondence to P. F. M. J. Verschure.

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Puigbò, JY., Maffei, G., Herreros, I. et al. Cholinergic Behavior State-Dependent Mechanisms of Neocortical Gain Control: a Neurocomputational Study. Mol Neurobiol 55, 249–257 (2018). https://doi.org/10.1007/s12035-017-0737-6

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