Skip to main content
Log in

Contributions of distinct prefrontal neuron classes in reward processing

  • Article
  • Published:
Science China Technological Sciences Aims and scope Submit manuscript

Abstract

The prefrontal cortex (PFC) is thought to be involved in higher order cognitive functions, such as in working memory, abstract categorization, and reward processing. It has been reported that two distinct neuron classes (putative pyramidal cells and interneurons) in the PFC played different functional roles in neural circuits involved in forming working memory and abstract categories. However, it remains elusive how the two types of neurons process reward information in the PFC. To investigate this issue, the activity of single neurons was extracellularly recorded in the PFC of the monkey performing a reward predicting task. PFC neurons were classified into putative pyramidal cells and interneurons, respectively, based on the waveforms of action potentials. Both the two types of neurons encoded reward information and discriminated two reward conditions (the preferred reward condition vs. the nonpreferred reward condition). However, the putative pyramidal neurons had better and more reliable discriminability than the putative interneurons. Also, the pyramidal cells represented reward information in the preferred reward condition, but not in the nonpreferred reward condition by raising their firing rates relative to the baseline rates. In contrast, the interneurons encoded reward information in the nonpreferred reward condition, but not in the preferred reward condition by inhibiting their discharge rates relative to the baseline rates. These results suggested that the putative pyramidal cells and interneurons had complementary functions in reward processing. These findings may help to clarify individual functions of each type of neurons in PFC neuronal circuits involved in reward processing.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Contreras D. Electrophysiological classes of neocortical neurons. Neural Netw, 2004, 17: 633–646

    Article  MATH  Google Scholar 

  2. Markram H, Toledo-Rodriguez M, Wang Y, et al. Interneurons of the neocortical inhibitory system. Nat Rev Neurosci, 2004, 5: 793–907

    Article  Google Scholar 

  3. Wonders C P, Anderson S A. The origin and specification of cortical interneurons. Nat Rev Neurosci, 2006, 7: 687–696

    Article  Google Scholar 

  4. White E L. Cortical Circuits: Synaptic Organization of the Cerebral Cortex. Boston: Birkhauser, 1989

    Book  Google Scholar 

  5. Peters A, Jones E G. Cellular Components of the Cerebral Cortex. New York: Plenum, 1984

    Google Scholar 

  6. Connors B W, Gutnick M J. Intrinsic firing patterns of diverse neocortical neurons. Trends Neurosci, 1990, 13: 99–104

    Article  Google Scholar 

  7. Henze D A, Borhegyi Z, Csicsvari J, et al. Intracellular features predicted by extracellular recordings in the hippocampus in vivo. J Neurophysiol, 2000, 84: 390–400

    Google Scholar 

  8. Gold C, Henze D A, Koch C, et al. On the origin of the extracellular action potential waveform: a modeling study. J Neurophysiol, 2006, 95: 3113–3128

    Article  Google Scholar 

  9. Nowak L G, Sanchez-Vives M V, McCormick D A. Lack of orientation and direction selectivity in a subgroup of fast-spiking inhibitory interneurons: cellular and synaptic mechanisms and comparison with other electrophysiological cell types. Cereb Cortex, 2008, 18: 1058–1078

    Article  Google Scholar 

  10. Atencio C A, Schreiner C E. Spectrotemporal processing differences between auditory cortical fast-spiking and regular-spiking neurons. J Neurosci, 2008, 28: 3897–3910

    Article  Google Scholar 

  11. Swadlow H A, Gusev A G. Receptive-field construction in cortical inhibitory interneurons. Nat Neurosci, 2002, 5: 403–404

    Article  Google Scholar 

  12. Mitchell J F, Sundberg K A, Reynolds J H. Differential attention dependent response modulation across cell classes in macaque visual area V4. Neuron, 2007, 55: 131–141

    Article  Google Scholar 

  13. Kvitsiani D, Ranade S, Hangya B, et al. Distinct behavioural and network correlates of two interneuron types in prefrontal cortex. Nature, 2013, 498: 363–366

    Article  Google Scholar 

  14. Constantinidis C, Goldman-Rakic P S. Correlated discharges among putative pyramidal neurons and interneurons in the primate prefrontal cortex. J Neurophysiol, 2002, 88: 3487–3497

    Article  Google Scholar 

  15. Diester I, Nieder A. Complementary contributions of prefrontal neurons classes in abstract numerical categorization. J Neurosci, 2008, 28: 7737–7747

    Article  Google Scholar 

  16. Miller E K, Cohen J D. An integrative theory of prefrontal cortex function. Annu Rev Neurosci, 2001, 24: 167–202

    Article  Google Scholar 

  17. Rigotti M, Barak O, Warden M R, et al. The importance of mixed selectivity in complex cognitive tasks. Nature, 2013, 497: 585–590

    Article  Google Scholar 

  18. Pan X, Sakagami M. Category representation and generalization in the prefrontal cortex. Eur J Neurosci, 2012, 35: 1083–1091

    Article  Google Scholar 

  19. Bongard S, Nieder A. Basic mathematical rules are encoded by primate prefrontal cortex neurons. Proc Natl Acad Sci USA, 2010, 107: 2277–2282

    Article  Google Scholar 

  20. Rao S G, Williams G V, Goldman-Rakic P S. Isodirectional tuning of adjacent interneurons and pyramidal cells during working memory: evidence for microcolumnar organization in PFC. J Neurophysiol, 1999, 81: 1903–1916

    Google Scholar 

  21. Rao S G, Williams G V, Goldman-Rakic P S. Destruction and creation of spatial tuning by disinhibition: GABA(A) blockade of prefrontal cortical neurons engaged by working memory. J Neurosci, 2000, 20: 485–494

    Google Scholar 

  22. Constantinidis C, Williams G V, Goldman-Rakic P S. A role for inhibition in shaping the temporal flow of information in prefrontal cortex. Nat Neurosci, 2002, 5: 175–180

    Article  Google Scholar 

  23. Watanabe M. Reward expectancy in primate prefrontal neurons. Nature, 1996, 382: 629–632

    Article  Google Scholar 

  24. Leon M I, Shadlen M N. Effect of expected reward magnitude on the response of neurons in the dorsolateral prefrontal cortex of the macaque. Neuron, 1999, 24: 415–425

    Article  Google Scholar 

  25. Kobayashi S, Lauwereyns J, Koizumi M, et al. Influence of reward expectation on visuospatial processing in macaque lateral prefrontal cortex. J Neurophysiol, 2002, 87: 1488–1498

    Google Scholar 

  26. Roesch M R, Olson C R. Impact of expected reward on neuronal activity in prefrontal cortex, frontal and supplementary eye fields and premotor cortex. J Neurophysiol, 2003, 90: 1766–1789

    Article  Google Scholar 

  27. Pan X, Sawa K, Tsuda I, et al. Reward prediction based on stimulus categorization in primate lateral prefrontal cortex. Nat Neurosci, 2008, 11: 703–712

    Article  Google Scholar 

  28. Ma C F, Pan X, Wang R B, et al. Estimating causal interaction between prefrontal cortex and striatum by transfer entropy. Cogn Neurodyn, 2013, 7: 253–261

    Article  Google Scholar 

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

    Article  Google Scholar 

  30. Homayoun H, Moghaddam B. NMDA receptor hypofunction produces opposite effects on prefrontal cortex interneurons and pyramidal neurons. J Neurosci, 2007, 27: 11496–11500

    Article  Google Scholar 

  31. Kawaguchi Y. Physiological subgroups of nonpyramidal cells with specific morphological characteristics in layer II/III of rat frontal cortex. J Neurosci, 1995, 15: 2638–2655

    Google Scholar 

  32. Gabbott P L, Bacon S J. Local circuit neurons in the medial prefrontal cortex (areas 24 a,b,c, 25 and 32) in the monkey: II. Quantitative areal and laminar distributions. J Comp Neurol, 1996, 364: 609–636

    Article  Google Scholar 

  33. Mann E O, Paulsen O. Role of GABAergic inhibition in hippocampal network oscillations. Trends Neurosci, 2007, 30: 343–349

    Article  Google Scholar 

  34. Povysheva N V, Gonzalez-Burgos G, Zaitsev A V, et al. Properties of excitatory synaptic responses in fast-spiking interneurons and pyramidal cells from monkey and rat prefrontal cortex. Cereb Cortex, 2006, 16: 541–552

    Article  Google Scholar 

  35. Goldman-Rakic P S. The prefrontal landscape: Implications of functional architecture for understanding human mentation and the central executive. Philos Trans R Soc Lond B Biol Sci, 1996, 351: 1445–1453

    Article  Google Scholar 

  36. Takada K, Funahashi N. Prefrontal task-related activity representing visual cue location or saccade direction in spatial working memory tasks. J Neurophysiol, 2002, 87: 567–588

    Google Scholar 

  37. Araki O. Computer simulations of synchrony and oscillations evoked by two coherent inputs. Cogn Neurodyn, 2013, 7: 133–141

    Article  MathSciNet  Google Scholar 

  38. Li Y T, Tsuda I. Novelty-induced memory transmission between two nonequilibrium neural networks. Cogn Neurodyn, 2013, 7: 225–236

    Article  Google Scholar 

  39. Du Y, Wang R B, Han F, et al. Firing pattern and synchronization property analysis in a network model of the olfactory bulb. Cogn Neurodyn, 2012, 6: 203–209

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to XiaoChuan Pan.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pan, X., Fan, H., Wang, R. et al. Contributions of distinct prefrontal neuron classes in reward processing. Sci. China Technol. Sci. 57, 1257–1268 (2014). https://doi.org/10.1007/s11431-014-5561-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11431-014-5561-x

Keywords

Navigation