Heterogeneous firing rate response of mouse layer V pyramidal neurons in the fluctuation-driven regime

Journal of Physiology

Volumn 594, Issue 13, 2016, Pages 3791-3808

  Zerlaut, Y ^a,b   Telenczuk B ^a,b   Deleuze, C ^a   Bal, T ^a   Ouanounou, G ^a   Destexhe, A ^a,b  

^a CNRS   (France)

^b European Institute for Theoretical Neuroscience   (France)

Author keywords

[No Author keywords available]

Indexed keywords

SODIUM CHANNEL;

ADOLESCENT; ANIMAL CELL; ANIMAL TISSUE; ARTICLE; BIOPHYSICS; BRAIN NERVE CELL; CONTROLLED STUDY; CORTEX LAYER V; FEMALE; FIRING RATE; IN VITRO STUDY; IN VIVO STUDY; MALE; MATHEMATICAL MODEL; MOUSE; NEOCORTEX; NERVE CELL MEMBRANE POTENTIAL; NERVE CELL NETWORK; NERVE EXCITABILITY; NONHUMAN; PERFORATED PATCH CLAMP; PRIORITY JOURNAL; PYRAMIDAL NERVE CELL; SODIUM TRANSPORT; THEORETICAL MODEL; VISUAL CORTEX;

EID: 84977504935     PISSN: 00223751     EISSN: 14697793     Source Type: Journal    
DOI: 10.1113/JP272317     Document Type: Article

References (43)

1. Altwegg-Boussac T, Chavez M, Mahon S & Charpier S (2014). Excitability and responsiveness of rat barrel cortex neurons in the presence and absence of spontaneous synaptic activity in vivo. J Physiol 592, 3577–3595.
2. Amit DJ & Brunel N (1997). Model of global spontaneous activity and local structured activity during delay periods in the cerebral cortex. Cerebral Cortex 7, 237–252.
3. Badel L, Lefort S, Berger TK, Petersen CCH, Gerstner W & Richardson MJE (2008). Extracting non-linear integrate-and-fire models from experimental data using dynamic I-V curves. Biol Cybern 99, 361–370.
4. Baudot P, Levy M, Marre O, Monier C, Pananceau M & Frégnac Y (2013). Animation of natural scene by virtual eye-movements evokes high precision and low noise in V1 neurons. Front Neural Circuits 7, 206.
5. Brette R & Gerstner W (2005). Adaptive exponential integrate-and-fire model as an effective description of neuronal activity. J Neurophysiol 94, 3637–3642.
6. Brunel N & Sergi S (1998). Firing frequency of leaky intergrate-and-fire neurons with synaptic current dynamics. J Theor Biol 195, 87–95.
7. Chance FS, Abbott LF & Reyes AD (2002). Gain modulation from background synaptic input. Neuron 35, 773–782.
8. Contreras D, Destexhe A & Steriade M (1997). Intracellular and computational characterization of the intracortical inhibitory control of synchronized thalamic inputs in vivo. J Neurophysiol 78, 335–350.
9. Crochet S, Poulet JFA, Kremer Y & Petersen CCH (2011). Synaptic mechanisms underlying sparse coding of active touch. Neuron 69, 1160–1175.
10. Daley DJ & Vere-Jones D (2007). An Introduction to the Theory of Point Processes, vol. Ii, General Theory and Structure, vol. 2. Springer Science & Business Media.
11. Debanne D, Campanac E, Bialowas A, Carlier E & Alcaraz G (2011). Axon physiology. Physiol Rev 91, 555–602.
12. Destexhe A & Bal T (2009). Dynamic-Clamp: From Principles to Applications. Springer, New York.
13. Destexhe A & Contreras D (2006). Neuronal computations with stochastic network states. Science 989, 85–90.
14. Destexhe A & Paré D (1999). Impact of network activity on the integrative properties of neocortical pyramidal neurons in vivo. J Neurophysiol 81, 1531–1547.
15. Destexhe A, Rudolph M, Fellous JM & Sejnowski TJ (2001). Fluctuating synaptic conductances recreate in vivo-like activity in neocortical neurons. Neuroscience 107, 13–24.
16. Destexhe A, Rudolph M & Paré D (2003). The high-conductance state of neocortical neurons in vivo. Nature Reviews. Neuroscience 4, 739–751.
17. El Boustani S, Marre O, Béhuret S, Baudot P, Yger P, Bal T, Destexhe A & Frégnac Y (2009). Network-state modulation of power-law frequency-scaling in visual cortical neurons. PLoS Comput Biol 5, e1000519.
18. Fernandez FR, Broicher T, Truong A & White JA (2011). Membrane voltage fluctuations reduce spike frequency adaptation and preserve output gain in CA1 pyramidal neurons in a high-conductance state. J Neurosci 31, 3880–3893.
19. Fourcaud N, Hansel D, van Vreeswijk C & Brunel N (2003). How spike generation mechanisms determine the neuronal response to fluctuating inputs. J Neurosci 23, 11628–11640.
20. Giugliano M, La Camera G, Fusi S & Senn W (2008). The response of cortical neurons to in vivo-like input current: theory and experiment: II. Time-varying and spatially distributed inputs. Biol Cybern 99, 303–318.
21. Hille B (2001). Ion Channels of Excitable Membranes. Sinauer, Sunderland, MA, USA.
22. Hines ML & Carnevale N (1997). The NEURON simulation environment. Neu Comput 9, 1179–1209.
23. Ilin V, Malyshev A, Wolf F & Volgushev M (2013). Fast computations in cortical ensembles require rapid initiation of action potentials. J Neurosci 33, 2281–2292.
24. Köndgen H, Geisler C, Fusi S, Wang X-J, Lüscher H-R & Giugliano M (2008). The dynamical response properties of neocortical neurons to temporally modulated noisy inputs in vitro. Cereb Cortex 18, 2086–2097.
25. Kuhn A, Aertsen A & Rotter S (2004). Neuronal integration of synaptic input in the fluctuation-driven regime. J Neurosci 24, 2345–2356.
26. Kyrozis A & Reichling DB (1995). Perforated-patch recording with gramicidin avoids artifactual changes in intracellular chloride concentration. J Neurosci Methods 57, 27–35.
27. La Camera G, Giugliano M, Senn W & Fusi S (2008). The response of cortical neurons to in vivo-like input current: theory and experiment: I. Noisy inputs with stationary statistics. Biol Cybern 99, 279–301.
28. Lippiat J (2009). Whole-cell recording using the perforated patch clamp technique. In Potassium Channels, ed. Lippiat J, vol. 491, Methods in Molecular Biology, pp. 141–149. Humana Press.
29. Lundstrom BN, Famulare M, Sorensen LB, Spain WJ & Fairhall AL (2009). Sensitivity of firing rate to input fluctuations depends on time scale separation between fast and slow variables in single neurons. J Comput Neurosci 27, 277–290.
30. McCormick DA, Connors BW, Lighthall JW & Prince DA (1985). Comparative electrophysiology of pyramidal and sparsely spiny stellate neurons of the neocortex. J Neurophysiol 54, 782–806.
31. McCormick DA & Prince DA (1987). Post-natal development of electrophysiological properties of rat cerebral cortical pyramidal neurones. J Physiol 393, 743–762.
32. Mejias JF & Longtin A (2012). Optimal heterogeneity for coding in spiking neural networks. Phys Rev Lett 108, 228102.
33. Okun M, Steinmetz NA, Cossell L, Iacaruso MF, Ko H, Barthó P, Moore T, Hofer SB, Mrsic-Flogel TD, Carandini M et al. (2015). Diverse coupling of neurons to populations in sensory cortex. Nature 521, 511–515.
34. Platkiewicz J & Brette R (2010). A threshold equation for action potential initiation. PLoS Comput Biol 6, e1000850.
35. Platkiewicz J & Brette R (2011). Impact of fast sodium channel inactivation on spike threshold dynamics and synaptic integration. PLoS Comput Biol 7, e1001129.
36. Rae J, Cooper K, Gates P & Watsky M (1991). Low access resistance perforated patch recordings using amphotericin B. J Neurosci Methods 37, 15–26.
37. Rauch A, La Camera G, Lüscher H-R, Senn W, Fusi S & Luscher H-R (2003). Neocortical pyramidal cells respond as integrate-and-fire neurons to in vivo-like input currents. J Neurophysiol 90, 1598–1612.
38. Rossant C, Leijon S, Magnusson AK & Brette R (2011). Sensitivity of noisy neurons to coincident inputs. J Neurosci 31, 17193–17206.
39. Rudolph M & Destexhe A (2003). Tuning neocortical pyramidal neurons between integrators and coincidence detectors. J Comput Neurosci 14, 239–251.
40. Stuart GJ & Spruston N (2015). Dendritic integration: 60 years of progress. Nature Neurosci 18, 1713–1721.
41. Tuckwell HC, Wan FYM & Rospars J-P (2002). A spatial stochastic neuronal model with Ornstein–Uhlenbeck input current. Biol Cybern 86, 137–145.
42. Wendt DJ, Starmer CF & Grant AO (1992). Na channel kinetics remain stable during perforated-patch recordings. Am J Physiol Cell Physiol 263, C1234–C1240.
43. Yang H, Kwon SE, Severson KS & O'Connor DH (2015). Origins of choice-related activity in mouse somatosensory cortex. Nature Neurosci 19, 127–134.