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Extracellular Potentials in the Hippocampus pp 17–33Cite as

Methods

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Abstract

Chronic recordings were performed in the Langone Medical Center of the New York University and the Department of Physiology of the School of Medicine of the University of Szeged. All experiments were performed in accordance with European Union guidelines (2003/65/CE) and the National Institutes of Health Guidelines for the Care and Use of Animals for Experimental Procedures. The experimental protocols were approved by the Animal Care and Use Committee of New York University Medical Center and the Ethical Committee for Animal Research at the Albert Szent-György Medical and Pharmaceutical Center of the University of Szeged respectively.

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References

  1. Amaral DG (1978) A Golgi study of cell types in the hilar region of the hippocampus in the rat. J Comp Neurol 182:851–914

    Google Scholar 

  2. Bartho P, Hirase H, Monconduit L, Zugaro M, Harris KD, Buzsàki G (2004) Characterization of neocortical principal cells and Interneurons by network interactions and extracellular features. J Neurophysiol 92:600–608

    Google Scholar 

  3. Bédard C, Destexhe A (2011) Generalized theory for current-source-density analysis in brain tissue. Phys Rev E 84:041909

    Google Scholar 

  4. Bell AJ, Sejnowski TJ (1995) An information-maximization approach to blind separation and blind deconvolution. Neural Comput 7:1129–1159

    Article  Google Scholar 

  5. Benito N, Fernandez-Ruiz A, Makarov VA, Makarova J, Korovaichuk A, Herreras O (2014) Spatial modules of coherent activity in pathway-specific LFPs in the hippocampus reflect topology and different modes of presynaptic synchronization. Cereb Cortex 24:1738–1752

    Article  Google Scholar 

  6. Berens P (2009) CircStat: a MATLAB toolbox for circular statistics. J Stat Softw 31

    Google Scholar 

  7. Brown GD, Yamada S, Sejnowski TJ (2001) Independent component analysis at the neural cocktail party. Trends Neurosci 24:54–56

    Article  Google Scholar 

  8. Buzsáki G, Mizuseki K (2014) The log-dynamic brain: how skewed distributions affect network operations. Nat Rev Neurosci 15:264–278

    Article  Google Scholar 

  9. Buzsáki G, Wang X-J (2012) Mechanisms of gamma oscillations. Annu Rev Neurosci 35:203–225

    Article  Google Scholar 

  10. Buzsáki G, Anastassiou CA, Koch C (2012) The origin of extracellular fields and currents—EEG, ECoG, LFP and spikes. Nat Rev Neurosci 13:407–420

    Google Scholar 

  11. Canolty RT, Edwards E, Dalal SS, Soltani M, Nagarajan SS, Kirsch HE, Berger MS, Barbaro NM, Knight RT (2006) High gamma power is phase-locked to theta oscillations in human neocortex. Science 313:1626–1628

    Article  ADS  Google Scholar 

  12. Chen A, Bickel PJ (2005) Consistent independent component analysis and prewhitening. IEEE Trans Sig Proc 53:3625–3632

    Google Scholar 

  13. Chen A (2006) Fast kernel density independent component analysis. Lect Notes Comput Sci 3889:24–31

    Google Scholar 

  14. Chen M, Mogul DJ (2009) A structurally detailed finite element human head model for simulation of transcranial magnetic stimulation. J Neurosci Meth 179:11–120

    Google Scholar 

  15. Choi S, Cichocki A, Park HM, Lee SY (2005) Blind source separation and independent component analysis: a review. Neur Inf Process Lett Rev 6:1–57

    Article  Google Scholar 

  16. Comon P (1994) Independent component analysis, a new concept? Sig Process 36:287–314

    Google Scholar 

  17. Csicsvari J, Hirase H, Czurko A, Buzsáki G (1998) Reliability and state dependence of pyramidal cell-interneuron synapses in the hippocampus: an ensemble approach in the behaving rat. Neuron 21:179–189

    Google Scholar 

  18. Delorme A, Makeig S (2004) EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J Neurosci Methods 134:9–21

    Article  Google Scholar 

  19. Einevoll GT, Kayser C, Logothetis NK, Panzeri S (2013) Modelling and analysis of local field potentials for studying the function of cortical circuits. Nat Rev Neurosci 14:770–785

    Article  Google Scholar 

  20. Fernández-Ruiz A, Herreras O (2013) Identifying the synaptic origin of ongoing neuronal oscillations through spatial discrimination of electric fields. Front Comput Neurosci 7:5

    Article  Google Scholar 

  21. Fernández-Ruiz A, Makarov VA, Benito N, Herreras O (2012) Schaffer-specific local field potentials reflect discrete excitatory events at gamma frequency that may fire postsynaptic hippocampal CA1 units. J Neurosci 32:5165–5176

    Article  Google Scholar 

  22. Fernández-Ruiz A, Makarov VA, Herreras O (2012) Sustained increase of spontaneous input and spike transfer in the CA3-CA1 pathway following long-term potentiation in vivo. Front Neural Circuits 6:71

    Article  Google Scholar 

  23. Fernández-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 33:15518–15532

    Article  Google Scholar 

  24. Freeman JA, Nicholson C (1975) Theory of current source-density analysis and determination of conductivity tensor for anuran cerebellum. J Neurophysiol 38:356–368

    Google Scholar 

  25. Hyvärinen A, Oja E (2000) Independent component analysis: algorithms and applications. Neural Netw 13:411–430

    Article  Google Scholar 

  26. Hyvärinen A, Karhunen J, Oja E (2004) Independent component analysis. Wiley, New York

    Google Scholar 

  27. Kadir SN, Goodman DFM, Harris KD (2014) High-dimensional cluster analysis with the masked EM algorithm. Neural Comput 26:11

    Article  Google Scholar 

  28. Lindén H, Tetzlaff T, Potjans TC, Pettersen KH, Gru S, Diesmann M, Einevoll G (2011) Modeling the spatial reach of the LFP. Neuron 5:859–872

    Google Scholar 

  29. Logothetis NK, Kayser C, Oeltermann A (2007) In vivo measurement of cortical impedance spectrum in monkeys: implications for signal propagation. Neuron 55:809–823

    Google Scholar 

  30. Mitra PP, Pesaran B (1999) Analysis of dynamic brain imaging data. Biophys J 76:691–708

    Article  Google Scholar 

  31. Mitzdorf U (1985) Current source-density method and application in cat cerebral cortex: investigation of evoked potentials and EEG phenomena. Physiol Rev 65:37–100

    Google Scholar 

  32. Mizuseki K, Diba K, Pastalkova E, Teeters J, Sirota A, Buzsáki G (2014) Neurosharing: large-scale data sets (spike, LFP) recorded from the hippocampal-entorhinal system in behaving rats. F1000 Research 3

    Google Scholar 

  33. Mizuseki K, Sirota A, Pastalkova E, Buzsáki G (2009) Theta oscillations provide temporal windows for local circuit computation in the entorhinal-hippocampal loop. Neuron 64:267–280

    Article  Google Scholar 

  34. Nunez PL, Srinivasan R (2006) Electric fields of the brain: the neurophysics of EEG, 2nd edn. Oxford University Press, New York

    Book  Google Scholar 

  35. Pettersen KH, Devor A, Ulbert I, Dale AM, Einevoll GT (2006) Current-source density estimation based on inversion of electrostatic forward solution: effects of finite extent of neuronal activity and conductivity discontinuities. J Neurosci Methods 154:116–133

    Article  Google Scholar 

  36. Plonsey R, Heppner DB (1967) Considerations of quasi-stationarity in electrophysiological systems. Bull Math Biophys 29:657–664

    Article  Google Scholar 

  37. Rossant C, Kadir SN, Goodman DF, Schulman J, Hunter ML, Saleem AB, Grosmark A, Belluscio M, Denfield GH, Ecker AS, Tolias AS, Solomon S, Buzsáki G, Carandini M, Harris KD (2016) Spike sorting for large, dense electrode arrays. Nat Neurosci 19:634-41

    Google Scholar 

  38. Salvador R, Silva S, Basser PJ, Miranda PC (2011) Determining which mechanisms lead to activation in the motor cortex: a modeling study of transcranial magnetic stimulation using realistic stimulus waveforms and sulcal geometry. Clin Neurophysiol 122:748–758

    Article  Google Scholar 

  39. Schomburg EW, Fernández-Ruiz A, Berényi A, Mizuseki K, Anastassiou CA, Koch C, Buzsáki G (2014) Theta phase segregation of input-specific gamma patterns in entorhinal-hippocampal networks. Neuron 84:470–485

    Article  Google Scholar 

  40. Stark E, Roux L, Eichler R, Senzai Y, Royer S, Buzsáki G (2014) Pyramidal cell-interneuron interactions underlie hippocampal ripple oscillations. Neuron 83:467–8

    Google Scholar 

  41. Thielscher A, Opitz A, Windhoff M (2011) Impact of the gyral geometry on the electric field induced by transcranial magnetic stimulation. Neuroimage 54:234–243

    Article  Google Scholar 

  42. Torrence C, Compo G (1998) A practical guide to wavelet analysis. B Am Meteorol Soc 79:61–78

    Google Scholar 

  43. Tort ABL, Komorowski R, Eichenbaum H, Kopell N (2010) Measuring phase-amplitude coupling between neuronal oscillations of different frequencies. J Neurophysiol 2:1195–1210

    Article  Google Scholar 

  44. Tort ABL, Kramer MA, Thorn C, Gibson DJ, Kubota Y, Graybiel AM, Kopell NJ (2008) Dynamic cross-frequency couplings of local field potential oscillations in rat striatum and hippocampus during performance of a T-maze task. Proc Natl Acad Sci USA 105:20517–20522

    Article  ADS  Google Scholar 

  45. Vandecasteele M, M S, Royer S, Belluscio M, Berényi A, Diba K, Fujisawa S, Grosmark A, Mao D, Mizuseki K, Patel J, Stark E, Sullivan D, Watson B, Buzsáki G (2012) Large-scale recording of neurons by movable silicon probes in behaving rodents. J Vis Exp 4:e3568

    Google Scholar 

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Authors and Affiliations

  1. Department of Applied Physics III, Faculty of Physics, Complutense University, Ciudad Universitaria, Plaza Ciencias, 1, 28040, Madrid, Spain

    Antonio Fernández-Ruiz

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  1. Antonio Fernández-Ruiz
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Correspondence to Antonio Fernández-Ruiz .

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Fernández-Ruiz, A. (2016). Methods. In: Extracellular Potentials in the Hippocampus. Springer Theses. Springer, Cham. https://doi.org/10.1007/978-3-319-41039-5_2

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