Abstract
Pump activity is a homeostatic mechanism that maintains ionic gradients. Here we examined whether the slow reduction in excitability induced by sodium-pump activity that has been seen in many neuronal types is also involved in neuronal coding. We took intracellular recordings from a spike-bursting sensory neuron in the leech Hirudo medicinalis in response to naturalistic tactile stimuli with different statistical distributions. We show that regulation of excitability by sodium pumps is necessary for the neuron to make different responses depending on the statistical context of the stimuli. In particular, sodium-pump activity allowed spike-burst sizes and rates to code not for stimulus values per se, but for their ratio with the standard deviation of the stimulus distribution. Modeling further showed that sodium pumps can be a general mechanism of adaptation to statistics on the time scale of 1 min. These results implicate the ubiquitous pump activity in the adaptation of neural codes to statistics.
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References
Barlow, H.B. & Mollon, J.D. The Senses (Cambridge University Press, Cambridge, UK, 1982).
Walraven, J., Enroth-Cugell, C., Hood, D.C., MacLeod, D.I.A. & Schnapf, J.L. The control of visual sensitivity. in Visual Perception: The Neurophysiological Foundations (eds. Spillmann, L., Werner, J.S.) 53–101 (Academic Press, New York, 1990).
Shapley, R. Retinal physiology: adapting to the changing scene. Curr. Biol. 7, R421–R423 (1997).
Meister, M. & Berry, M.J., II The neural code of the retina. Neuron 22, 435–450 (1999).
Smirnakis, S.M., Berry, M.J., Warland, D.K., Bialek, W. & Meister, M. Adaptation of retinal processing to image contrast and spatial scale. Nature 386, 69–73 (1997).
DeWeese, M. & Zador, A. Asymmetric dynamics in optimal variance adaptation. Neural Comput. 10, 1179–1202 (1998).
Brenner, N., Bialek, W. & de Ruyter van Steveninck, R.R. Adaptive rescaling maximizes information transmission. Neuron 26, 695–702 (2000).
Fairhall, A.L., Lewen, G., Bialek, W. & de Ruyter van Steveninck, R.R. Efficiency and ambiguity in an adaptive neural code. Nature 412, 787–792 (2001).
Maravall, M., Petersen, R.S., Fairhall, A.L., Arabzadeh, E. & Diamond, M.E. Shifts in coding properties and maintenance of information transmission during adaptation in barrel cortex. PLoS Biol. 5, e19 (2007).
Kvale, M.N. & Schreiner, C.E. Adaptation of auditory receptive fields to dynamic stimuli. J. Neurophysiol. 91, 604–612 (2004).
Sharpee, T.O. et al. Adaptive filtering enhances information transmission in the visual cortex. Nature 439, 936–942 (2006).
Abbott, L.F., Sen, K., Varela, J.A. & Nelson, S.B. Synaptic depression and cortical gain control. Science 275, 220–224 (1997).
Tsodyks, M.V. & Markram, H. The neural code between neocortical pyramidal neurons depends on neurotransmitter release probability. Proc. Natl. Acad. Sci. USA 94, 719–723 (1997).
Markram, H., Wang, Y. & Tsodyks, M. Differential signaling via the same axon of neocortical pyramidal neurons. Proc. Natl. Acad. Sci. USA 95, 5323–5328 (1998).
Stemmler, M. & Koch, C. How voltage-dependent conductances can adapt to maximize the information encoded by neuronal firing rate. Nat. Neurosci. 2, 521–527 (1999).
Fairhall, A. & Bialek, W. Adaptive spike coding. in The Handbook of Brain Theory and Neural Networks 2nd edn. (ed. Arbib, M.A.) 90–94 (MIT Press, Cambridge, 2002).
Gilboa, G., Chen, R. & Brenner, N. History-dependent multiple–time scale dynamics in a single-neuron model. J. Neurosci. 25, 6479–6489 (2005).
Rieke, F. Temporal contrast adaptation in salamander bipolar cells. J. Neurosci. 21, 9445–9454 (2001).
Sanchez-Vives, M.V., Nowak, L.G. & McCormick, D.A. Cellular mechanisms of long-lasting adaptation in visual cortical neurons in vitro. J. Neurosci. 20, 4286–4299 (2000).
Sanchez-Vives, M.V., Nowak, L.G. & McCormick, D.A. Membrane mechanisms underlying contrast adaptation in cat area 17 in vivo. J. Neurosci. 20, 4267–4285 (2000).
Kim, K.J. & Rieke, F. Slow Na+ inactivation and variance adaptation in salamander retinal ganglion cells. J. Neurosci. 23, 1506–1516 (2003).
Shen, K.Z. & Johnson, S.W. Sodium pump evokes high-density pump current in rat midbrain dopamine neurons. J. Physiol. (Lond.) 512, 449–457 (1998).
Darbon, P., Tscherter, A., Yvon, C. & Streit, J. Role of the electrogenic Na/K pump in deinhibition-induced bursting in cultured spinal networks. J. Neurophysiol. 90, 3119–3129 (2003).
Gustafsson, B. & Wigstom, H. Hyperpolarization following long-lasting tetanus activation of pyramidal hippocampal cells. Brain Res. 275, 159–163 (1983).
Vaillend, C., Mason, S.E., Cuttle, M.F. & Alger, B.E. Mechanisms of neuronal hyperexcitability caused by partial inhibition of Na+-K+–ATPases in the rat CA1 hippocampal region. J. Neurophysiol. 88, 2963–2978 (2002).
Kobayashi, J., Ohta, M. & Terada, Y. Evidence for the involvement of Na+-K+ pump and K+ conductance in the posttetanic hyperpolarization of the tetrodoxin-resistant C-fibers in the islated bullfrog sciatic nerve. Neurosci. Lett. 236, 171–174 (1997).
French, A.S. Two components of rapid sensory adaptation in a cockroach mechanoreceptor neuron. J. Neurophysiol. 62, 768–777 (1989).
Kiernan, M.C., Lin, C.S. & Burke, D. Differences in activity-dependent hyperpolarization in human sensory and motor axons. J. Physiol. (Lond.) 558, 341–349 (2004).
Baylor, D.A. & Nicholls, J.G. After-effects of nerve impulses on signalling in the central nervous system of the leech. J. Physiol. (Lond.) 203, 571–589 (1969).
Jansen, J.K. & Nicholls, J.G. Conductance changes, an electrogenic pump and the hyperpolarization of leech neurons following impulses. J. Physiol. (Lond.) 229, 635–655 (1973).
Van Essen, D.C. The contribution of membrane hyperpolarization to adaptation and conduction block in sensory neurones of the leech. J. Physiol. (Lond.) 230, 509–534 (1973).
Scuri, R., Mozzachiodi, R. & Brunelli, M. Activity-dependent increase of the AHP amplitude in T sensory neurons of the leech. J. Neurophysiol. 88, 2490–2500 (2002).
Scuri, R., Mozzachiodi, R. & Brunelli, M. Role for calcium signaling and arachidonic acid metabolites in the activity-dependent increase of AHP amplitude in leech T sensory neurons. J. Neurophysiol. 94, 1066–1073 (2005).
Mar, A. & Drapeau, P. Modulation of conduction block in leech mechanosensory neurons. J. Neurosci. 16, 4335–4343 (1996).
Catarsi, S. & Brunelli, M. Serotonin depresses the after-hyperpolarization through the inhibition of the Na+/K+ ATPase in the sensory neurones of the leech. J. Exp. Biol. 155, 261–273 (1991).
Catarsi, S., Garcia-Gil, M., Traina, G. & Brunelli, M. Seasonal variation of serotonin content and non-associative learning of swim induction in the leech Hirudo medicinalis. J. Comp. Physiol. A 167, 469–474 (1990).
Schlue, W.R. Effects of ouabain on intracellular ion activities of sensory neurons of the leech central nervous system. J. Neurophysiol. 65, 736–746 (1991).
Krahe, R. & Gabbiani, F. Burst firing in sensory systems. Nat. Rev. Neurosci. 5, 13–23 (2004).
Gabbiani, F., Metzner, W., Wessel, R. & Koch, C. From stimulus encoding to feature extraction in weakly electric fish. Nature 384, 564–567 (1996).
Izhikevich, E.M., Desai, N.S., Walcott, E.C. & Hoppensteadt, F.C. Bursts as a unit of neural information: selective communication via resonance. Trends Neurosci. 26, 161–167 (2003).
Lisman, J.E. Bursts as a unit of neural information: making unreliable synapses reliable. Trends Neurosci. 20, 38–43 (1997).
DeBusk, B.C., DeBruyn, E.J., Snider, R.K., Kabara, J.F. & Bonds, A.B. Stimulus-dependent modulation of spike burst length in cat striate cortical cells. J. Neurophysiol. 78, 199–213 (1997).
Middlebrooks, J.C., Clock, A.E., Xu, L. & Green, D.M. A panoramic code for sound location by cortical neurons. Science 264, 842–844 (1994).
Kepecs, A., Wang, X.J. & Lisman, J. Bursting neurons signal input slope. J. Neurosci. 22, 9053–9062 (2002).
Mozzachiodi, R., Scuri, R., Roberto, M. & Brunelli, M. Caulerpenyne, a toxin from the seaweed Caulerpa taxifolia, depresses afterhyperpolarization in invertebrate neurons. Neuroscience 107, 519–526 (2001).
Cataldo, E. et al. Computational model of touch sensory cells (T cells) of the leech: role of the afterhyperpolarization (AHP) in activity-dependent conduction failure. J. Comput. Neurosci. 18, 5–24 (2005).
Livingstone, M.S., Freeman, D.C. & Hubel, D.H. Visual responses in V1 of freely viewing monkeys. Cold Spring Harb. Symp. Quant. Biol. 61, 27–37 (1996).
Chubbuck, J.G. Small-motion biological stimulator. Johns Hopkins APL Technical Digest 5, 18–23 (1966).
Juusola, M. & French, A. The efficiency of sensory information coding in mechanical receptors. Neuron 18, 959–968 (1997).
Wang, X.J. Calcium coding and adaptive temporal computation in cortical pyramidal neurons. J. Neurophysiol. 79, 1549–1566 (1998).
Acknowledgements
W. Kristan is gratefully acknowledged for support in the initial stages and M. Juusola for lending the mechanical stimulators and the MatLab-based BIOSYST program for data acquisition. F. Gabbiani is acknowledged for critical comments. Discussions with B. Burton, M. Fuenlazida, R. Harris, S. Laughlin, P. Lombardo and R. Scuri were also appreciated. We thank Ministerio de Educación y Ciencia, Spain (R.G., G.G.d.P.), Comunidad de Madrid-Universidad Autonoma de Madrid (G.G.d.P.), Comunidad de Madrid (BIOCIENCIA program) (G.G.d.P.), and a Comunidad de Madrid fellowship (S.A.) for financial support.
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S.A. conducted experiments and performed significance tests, R.G. analyzed data, performed modeling and was responsible for writing parts of the supplementary information and G.G.d.P. conceived and directed the project, procured funding and wrote the paper.
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Arganda, S., Guantes, R. & de Polavieja, G. Sodium pumps adapt spike bursting to stimulus statistics. Nat Neurosci 10, 1467–1473 (2007). https://doi.org/10.1038/nn1982
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DOI: https://doi.org/10.1038/nn1982
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