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A Model of Spatial Reach in LFP Recordings

  • Henrik LindénEmail author
  • Tom Tetzlaff
  • Szymon Łeski
  • Klas H. Pettersen
  • Sonja Grün
  • Markus Diesmann
  • Gaute T. Einevoll
Chapter
Part of the Springer Series in Computational Neuroscience book series (NEUROSCI)

Abstract

The measurement of local field potentials (LFP), the low-frequency part of extracellularly recorded potentials, is one of the most commonly used methods for probing hippocampal and cortical activity in vivo. It offers the possibility to monitor the activity of many neurons close to the recording electrode simultaneously but has the limitation that it may be difficult to interpret and relate to the underlying neuronal activity. The recording electrode picks up activity from proximal neurons, but what about more distant neurons? An important piece of information for a correct interpretation of the LFP is to decide the size of the tissue that substantially contributes to the LFP, i.e., the reach of the LFP signal. In this chapter we present a simple model that describes how population geometry, spatial decay of single-cell LFP contributions, and correlation between LFP sources determine the relation between LFP amplitude and population size and use it to study the spatial reach of the LFP. The model can also be used to study different frequency bands of the LFP separately as well as the spatial decay outside the active neuronal population.

Notes

Acknowledgements

This work was done with financial support from the Danish Council for Independent Research and FP7 Marie Curie Actions – COFUND (grant id: DFF – 1330-00226), the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement 604102 (Human Brain Project, HBP) and grant agreement 269912 (BrainScaleS), the Helmholtz Association through the Helmholtz Portfolio Theme “Supercomputing and Modeling for the Human Brain” (SMHB), Jülich Aachen Research Alliance (JARA), and the Research Council of Norway (NFR, through ISP, NOTUR -NN4661K).

References

  1. Agarwal G, Stevenson IH, Berényi A, Mizuseki K, Buzsáki G, Sommer FT (2014) Spatially distributed local fields in the hippocampus encode rat position. Science 344(6184):626–630CrossRefGoogle Scholar
  2. Bédard C, Kröger H, Destexhe A (2006) Does the 1∕f frequency scaling of brain signals reflect self-organized critical states? Phys Rev Lett 97:118102CrossRefGoogle Scholar
  3. Belitski A, Gretton A, Magri C, Murayama Y, Montemurro MA, Logothetis NK, Panzeri S (2008) Low-frequency local field potentials and spikes in primary visual cortex convey independent visual information. J Neurosci 28(22):5696–5709CrossRefGoogle Scholar
  4. Belluscio MA, Mizuseki K, Schmidt R, Kempter R, Buzsáki G (2012) Cross-frequency phase-phase coupling between theta and gamma oscillations in the hippocampus. J Neurosci 32(2):423–435CrossRefGoogle Scholar
  5. Berens P, Keliris GA, Ecker AS, Logothetis NK, Tolias AS (2008) Comparing the feature selectivity of the gamma-band of the local field potential and the underlying spiking activity in primate visual cortex. Front Syst Neurosci 2:2CrossRefGoogle Scholar
  6. Bragin A, Jando G, Nadasdy Z, Hetke J, Wise K, Buzsáki G (1995) Gamma (40–100 Hz) oscillation in the hippocampus of the behaving rat. J Neurosci 15(1):47–60CrossRefGoogle Scholar
  7. Brankack J, Stewart M, Fox SE (1993) Current source density analysis of the hippocampal theta rhythm: associated sustained potentials and candidate synaptic generators. Brain Res 615:310–327CrossRefGoogle Scholar
  8. Buzsáki G (2002) Theta oscillations in the hippocampus. Neuron 33(3):325–340CrossRefGoogle Scholar
  9. Buzsáki G (2004) Large-scale recording of neuronal ensembles. Nat Neurosci 7(5):446–451CrossRefGoogle Scholar
  10. Buzsáki G, Anastassiou C, Koch C (2012) The origin of extracellular fields and currents–EEG, ECoG, LFP and spikes. Nat Rev Neurosci 13:407–420CrossRefGoogle Scholar
  11. Einevoll GT, Lindén H, Tetzlaff T, Łeski S, Pettersen KH (2012) Local field potentials: biophysical origin and analysis. In: Quiroga QR, Panzeri S (eds) Principles of neural coding. Taylor & FrancisGoogle Scholar
  12. Einevoll GT, Kayser C, Logothetis N, Panzeri, S (2013) Modelling and analysis of local field potentials for studying the function of cortical circuits. Nat Rev Neurosci 14:770–785CrossRefGoogle Scholar
  13. Fernandez-Ruiz A, Muñoz S, Sancho M, Makarova J, Makarov VA, Herreras O (2013) Cytoarchitectonic and dynamic origins of giant positive local field potentials in the dentate gyrus. J Neurosci 33(39):15518–15532CrossRefGoogle Scholar
  14. Herreras O, Makarova J, Makarov VA (2015) New uses of LFPs: pathway-specific threads obtained through spatial discrimination. Neuroscience 310:486–503CrossRefGoogle Scholar
  15. Holt GR, Koch C (1999) Electrical interactions via the extracellular potential near cell bodies. J Comp Neurol 6(2):169–184Google Scholar
  16. Kajikawa Y, Schroeder CE (2011) How local is the local field potential? Neuron 72:847–858CrossRefGoogle Scholar
  17. Katzner S, Nauhaus I, Benucci A, Bonin V, Ringach DL, Carandini M (2009) Local origin of field potentials in visual cortex. Neuron 61:35–41CrossRefGoogle Scholar
  18. Kreiman G, Hung CP, Kraskov A, Quiroga RQ, Poggio T, DiCarlo JJ (2006). Object selectivity of local field potentials and spikes in the macaque inferior temporal cortex. Neuron 49:433–445CrossRefGoogle Scholar
  19. Łeski S, Lindén H, Pettersen KH, Einevoll GT (2013) Frequency dependence of signal power and spatial reach of the local field potential. PLoS Comput Biol 9(7):e1003137CrossRefGoogle Scholar
  20. Lindén H, Pettersen KH, Einevoll GT (2010). Intrinsic dendritic filtering gives low-pass power spectra of local field potentials. J Comp Neurol 29(3):423–444Google Scholar
  21. Lindén H, Tetzlaff T, Potjans TC, Pettersen KH, Grün S, Diesmann M, Einevoll GT (2011) Modeling the spatial reach of the LFP. Neuron 72:859–872CrossRefGoogle Scholar
  22. Lindén H, Hagen E, Łeski S, Norheim ES, Pettersen KH, Einevoll GT (2014) LFPy: a tool for biophysical simulation of extracellular potentials generated by detailed model neurons. Front Neuroinform 7Google Scholar
  23. Liu J, Newsome WT (2006) Local field potential in cortical area MT: stimulus tuning and behavioral correlations. J Neurosci 26(30):7779–7790CrossRefGoogle Scholar
  24. Logothetis NK, Kayser C, Oeltermann A (2007) In vivo measurement of cortical impedance spectrum in monkeys: implications for signal propagation. Neuron 55:809–823CrossRefGoogle Scholar
  25. Maier N, Tejero-Cantero A, Dorrn AL, Winterer J, Beed PS, Morris G, Kempter R, Poulet JF, Leibold C, Schmitz D (2011) Coherent phasic excitation during hippocampal ripples. Neuron 72:137–152CrossRefGoogle Scholar
  26. Mainen ZF, Sejnowski TJ (1996) Influence of dendritic structure on firing pattern in model neocortical neurons. Nature 382(6589):363–366CrossRefGoogle Scholar
  27. Mazzoni A, Brunel N, Cavallari S, Logothetis NK, Panzeri S (2011) Cortical dynamics during naturalistic sensory stimulations: experiments and models. J Physiol Paris 105(1–3):2–15CrossRefGoogle Scholar
  28. Mitzdorf U (1985) Current source-density method and application in cat cerebral cortex: investigation of evoked potentials and EEG phenomena. Physiol Rev 65(1):37–100CrossRefGoogle Scholar
  29. Ness TV, Remme MWH, Einevoll GT (2015) Active subthreshold dendritic conductances shape the local field potential. arXiv 1512.04293Google Scholar
  30. Nunez PL, Srinivasan R (2006) Electric fields of the brain, 2nd edn. Oxford University Press, Inc., New YorkCrossRefGoogle Scholar
  31. Pettersen KH, Einevoll GT (2008) Amplitude variability and extracellular low-pass filtering of neuronal spikes. Biophys J 94(3):784–802CrossRefGoogle Scholar
  32. Pettersen KH, Lindén H, Dale AM, Einevoll GT (2012) Extracellular spikes and current-source density. In Brette R, Destexhe A (eds) Handbook of neural activity measurement. Cambridge University Press, CambridgeGoogle Scholar
  33. Schomburg EW, Anastassiou CA, Buzsáki G, Koch C (2012) The spiking component of oscillatory extracellular potentials in the rat hippocampus. J Neurosci 32:11798–11811CrossRefGoogle Scholar
  34. Siapas AG, Wilson MA (1998) Coordinated interactions between hippocampal ripples and cortical spindles during slow-wave sleep. Neuron 21:1123–1112CrossRefGoogle Scholar
  35. Sirota A, Csicsvari J, Buhl D, Buzsáki G (2003) Communication between neocortex and hippocampus during sleep in rodents. Proc Natl Acad Sci USA 100:2065–2069CrossRefGoogle Scholar
  36. Taxidis J, Anastassiou CA, Diba K, Koch C (2015) Local field potentials encode place cell ensemble activation during hippocampal sharp wave ripples. Neuron 87(3):590–604CrossRefGoogle Scholar
  37. Tetzlaff T, Rotter S, Stark E, Abeles M, Aertsen A, Diesmann M (2008) Dependence of neuronal correlations on filter characteristics and marginal spike-train statistics. Neural Comput 20(9):2133–2184CrossRefGoogle Scholar
  38. Xing D, Yeh C-I, Shapley RM (2009) Spatial spread of the local field potential and its laminar variation in visual cortex. J Neurosci 29:11540–11549CrossRefGoogle Scholar
  39. Ylinen A, Bragin A, Nádasdy Z, Jandó G, Szabó I, Sik A, Buzsáki G (1995) Sharp wave-associated high-frequency oscillation (200 Hz) in the intact hippocampus: network and intracellular mechanisms. J Neurosci 15:30–46CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Henrik Lindén
    • 1
    Email author
  • Tom Tetzlaff
    • 2
  • Szymon Łeski
    • 3
  • Klas H. Pettersen
    • 4
  • Sonja Grün
    • 2
    • 5
  • Markus Diesmann
    • 2
    • 6
  • Gaute T. Einevoll
    • 7
    • 8
  1. 1.Department of NeuroscienceUniversity of CopenhagenCopenhagenDenmark
  2. 2.Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA Institute Brain Structure-Function Relationships (INM-10), Jülich Research CentreJülichGermany
  3. 3.Department of Neurophysiology, Nencki Institute of Experimental Biology of Polish Academy of SciencesWarsawPoland
  4. 4.Letten Centre and GliaLab, Department of Molecular Medicine, Institute of Basic Medical SciencesUniversity of OsloOsloNorway
  5. 5.Theoretical Systems NeurobiologyRWTH Aachen UniversityAachenGermany
  6. 6.Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, and Department of Physics, Faculty 1RWTH Aachen UniversityAachenGermany
  7. 7.Faculty of Science and TechnologyNorwegian University of Life SciencesÅsNorway
  8. 8.Department of PhysicsUniversity of OsloOsloNorway

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