Skip to main content
Log in

The Influence of Spike Rate and Stimulus Duration on Noradrenergic Neurons

  • Published:
Journal of Computational Neuroscience Aims and scope Submit manuscript

Abstract

We model spiking neurons in locus coeruleus (LC), a brain nucleus involved in modulating cognitive performance, and compare with recent experimental data. Extracellular recordings from LC of monkeys performing target detection and selective attention tasks show varying responses dependent on stimuli and performance accuracy. From membrane voltage and ion channel equations, we derive a phase oscillator model for LC neurons. Average spiking probabilities of a pool of cells over many trials are then computed via a probability density formulation. These show that: (1) Post-stimulus response is elevated in populations with lower spike rates; (2) Responses decay exponentially due to noise and variable pre-stimulus spike rates; and (3) Shorter stimuli preferentially cause depressed post-activation spiking. These results allow us to propose mechanisms for the different LC responses observed across behavioral and task conditions, and to make explicit the role of baseline firing rates and the duration of task-related inputs in determining LC response.

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.

Institutional subscriptions

Similar content being viewed by others

References

  • Alvarez V, Chow C, van Bockstaele E, Williams J (2002) Frequency dependent synchrony in locus coeruleus: Role of electronic coupling. Proc. Nat. Acad. Sci. USA 99: 4032-4036.

    Google Scholar 

  • Arnold L (1974) Stochastic Differential Equations. John Wiley, New York.

    Google Scholar 

  • Aston-Jones G, Akaoka H, Charlety P, Chouvet G (1991) Serotonin selectively attenuates glutamate-evoked activation of locus coeruleus neurons in vivo. J. Neurosci. 11: 760-769.

    Google Scholar 

  • Aston-Jones G, Chen S, Zhu Y, Oshinsky ML (2001a) A neural circuit for circadian regulation of arousal. Nature Neurosci. 4: 732-738.

    Google Scholar 

  • Aston-Jones G, Rajkowski J, Cohen J (2000) Locus coeruleus and regulation of behavioral flexibility and attention. Prog. Brain Res. 126: 165-182.

    Google Scholar 

  • Aston-Jones G, Rajkowski J, Kubiak P, Alexinsky T (1994) Locus coeruleus neurons in the monkey are selectively activated by attended stimuli in a vigilance task. J. Neurosci. 14: 4467-4480.

    Google Scholar 

  • Aston-Jones G, Zhu Y, Card P (2001b) Gabaergic afferents to locus coeruleus (LC) from the peri-lc region: Possible LC interneurons. Soc. Neurosci. Abst. 27: 373.8.

    Google Scholar 

  • Brown E, Moehlis J, Holmes P (2004) On the phase reduction and response dynamics of neural oscillator populations. Neural Comp. 16(4): 673-715.

    Google Scholar 

  • Chow C, Kopell N (2000) Dynamics of spiking neurons with electrotonic coupling. Neural Comp. 12: 1643-1678.

    Google Scholar 

  • Clayton E, Rajkowski J, Cohen JD, Aston-Jones G (2004) Decisionrelated activation of monkey locus coeruleus neurons in a forced choice task. In preparation.

  • Connor J, Walter D, McKown R (1977) Neural repetitive firing: Modifications of the Hodgkin-Huxley axon suggested by experimental results from crustacean axons. Biophys. J. 18: 81-102.

    Google Scholar 

  • Eriksen BA, Eriksen CW (1974) Effects of noise letters upon the identification of target letters in a non-search task. Perception and Psychophysics 16: 143-149.

    Google Scholar 

  • Ermentrout B (1996) Type I membranes, phase resetting curves, and synchrony. Neural Comp. 8: 979-1001.

    Google Scholar 

  • Evans L (1998) Partial Differential Equations. American Mathematical Society, Providence.

  • Fetz E, Gustaffson B (1983) Relation between shapes of postsynaptic potentials and changes in firing probability of cat motoneurones. J. Physiol. 341: 387-410.

    Google Scholar 

  • Foote SL, Bloom FE, Aston-Jones G(1983) Nucleus locus coeruleus: New evidence of anatomical and physiological specificity. Physiol. Rev. 63(3): 844-914.

    Google Scholar 

  • Freidlin M, Wentzell A (1998) Random Perturbations of Dynamical Systems. Springer, New York.

    Google Scholar 

  • Gardiner C (1985) Handbook of Stochastic Methods. Springer, New York.

    Google Scholar 

  • Gilzenrat MG, Holmes BD, Rajkowski J, Aston-Jones G, Cohen JD (2002) Simplified dynamics in a model of noradrenergic modulation of cognitive performance. Neural Networks 15: 647-663.

    Google Scholar 

  • Grant SJ, Aston-Jones G, Redmond DE (1988) Responses of primate locus coeruleus neurons to simple and complex sensory stimuli. Brain Res. Bull. 21(3): 401-410.

    Google Scholar 

  • Guckenheimer J, Holmes PJ (1983) Nonlinear Oscillations, Dynamical Systems and Bifurcations of Vector Fields. Springer-Verlag, New York.

    Google Scholar 

  • Herrmann A, Gerstner W (2001) Noise and the PSTH response to current transients: I. General theory and application to the integrate and-fire neuron. J. Comp. Neurosci. 11: 135-151.

    Google Scholar 

  • Jodo E, Aston-Jones, G (1997) Activation of locus coeruleus by prefrontal cortex is mediated by excitatory amino acid inputs. Brain Res. 768: 327-332.

    Google Scholar 

  • Jodo E, Chiang C, Aston-Jones G (1998) Potent excitatory influence of prefrontal cortex activity on noradrenergic locus coeruleus neurons. Neuroscience 83: 63-80.

    Google Scholar 

  • Moore RY, Bloom FE (1979) Central catecholamine neuron systems: Anatomy and physiology of the norepinephrine and epinephrine systems. Ann. Rev. Neurosci. 2: 113-168.

    Google Scholar 

  • Nykamp D, Tranchina D (2000) A population density approach that facilitates large-scale modeling of neural networks: Analysis and application to orientation tuning. J. Comp. Neurosci. 8: 19-50.

    Google Scholar 

  • Omurtag A, Knight BW, Sirovich L (2000) On the simulation of large populations of neurons. J. Comp. Neurosci. 8: 51-63.

    Google Scholar 

  • Rajkowski J, Lu W, Zhu Y, Cohen J, Aston-Jones G (2000) Prominent projections from the anterior cingulate cortex to the locus coeruleus (LC) in rhesus monkey. Soc. Neurosci. Abst. 26: 838.15.

    Google Scholar 

  • Ritt J (2003) A Probabilistic Analysis of Forced Oscillators, with Application to Neuronal Response Reliability. PhD thesis, Boston University.

  • Rose R, Hindmarsh J (1989) The assembly of ionic currents in a thalamic neuron I. The three-dimensional model. Proc. R. Soc. Lond. B 237: 267-288.

    Google Scholar 

  • Rush M, Rinzel J (1995) The potassium A-current, low firing rates and rebound excitation in Hodgkin-Huxley models. Bull. Math. Biol. 57: 899-929.

    Google Scholar 

  • Servan-Schreiber D, Printz H, Cohen JD (1990) A network model of catecholamine effects: Gain, signal-to-noise ratio, and behavior. Science 249: 892-895.

    Google Scholar 

  • Stein R (1965) Atheoretical analysis of neuronal variability. Biophys. J. 5: 173-194.

    Google Scholar 

  • Tass P (1999) Phase Resetting in Medicine and Biology. Springer, New York.

    Google Scholar 

  • Usher M, Cohen JD, Servan-Schreiber D, Rajkowsky J, Aston-Jones G (1999) The role of locus coeruleus in the regulation of cognitive performance. Science 283: 549-554.

    Google Scholar 

  • Usher M, Davelaar EJ (2002) Neuromodulation of decision and response selection. Neural Networks 15: 635-645.

    Google Scholar 

  • Valentino RJ, Foote SL (1987) Corticotropin-releasing factor disrupts sensory responses of brain noradrenergic neurons. Neuroendocrinology 45(1): 28-36.

    Google Scholar 

  • Whitham GB (1974) Linear and Nonlinear Waves. Wiley, New York.

    Google Scholar 

  • Williams J, North R, Shefner A, Nishi S, Egan T (1984) Membrane properties of rat locus coeruleus neurons. Neuroscience 13: 137-156.

    Google Scholar 

  • Williams JT, Bobker DH, Harris GC (1991) Synaptic potentials in locus coeruleus neurons in brain slices. Prog. Brain Res. 88: 167-172.

    Google Scholar 

  • Winfree AT (2001) The Geometry of Biological Time. 2nd edition. Springer, New York.

    Google Scholar 

  • Zhu WQ (1988) Stochastic averaging methods in random vibration. Appl. Mech. Rev. 41: 189-199.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Brown, E., Moehlis, J., Holmes, P. et al. The Influence of Spike Rate and Stimulus Duration on Noradrenergic Neurons. J Comput Neurosci 17, 13–29 (2004). https://doi.org/10.1023/B:JCNS.0000023867.25863.a4

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/B:JCNS.0000023867.25863.a4

Navigation