Abstract
The spontaneous activity of working neurons yields synaptic currents that mix up in the volume conductor. This activity is picked up by intracerebral recording electrodes as local field potentials (LFPs), but their separation into original informative sources is an unresolved problem. Assuming that synaptic currents have stationary placing we implemented independent component model for blind source separation of LFPs in the hippocampal CA1 region. After suppressing contaminating sources from adjacent regions we obtained three main local LFP generators. The specificity of the information contained in isolated generators is much higher than in raw potentials as revealed by stronger phase-spike correlation with local putative interneurons. The spatial distribution of the population synaptic input corresponding to each isolated generator was disclosed by current-source density analysis of spatial weights. The found generators match with axonal terminal fields from subtypes of local interneurons and associational fibers from nearby subfields. The found distributions of synaptic currents were employed in a computational model to reconstruct spontaneous LFPs. The phase-spike correlations of simulated units and LFPs show laminar dependency that reflects the nature and magnitude of the synaptic currents in the targeted pyramidal cells. We propose that each isolated generator captures the synaptic activity driven by a different neuron subpopulation. This offers experimentally justified model of local circuits creating extracellular potential, which involves distinct neuron subtypes.
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References
Bédard, C., Kröger, H., & Destexhe, A. (2004). Modeling extracellular field potentials and the frequency-filtering properties of extracellular space. Biophysical Journal, 86(3), 1829–1842.
Bell, A., & Sejnowski, T. (1995). An information-maximization approach to blind separation and blind deconvolution. Neural Computation, 7, 1129–1159.
Boss, B. D., Turlejski, K., Stanfield, B. B., & Cowan, W. M. (1987). On the numbers of neurons in fields CA1 and CA3 of the hippocampus of Sprague–Dawley and Wistar rats. Brain Research, 406, 280–287.
Bragin, A., Jandó, G., Nádasdy, Z., Hetke, J., Wise, K., & Buzsáki, G. G. (1995). Gamma (40–100 Hz) oscillation in the hippocampus of the behaving rat. Journal of Neuroscience, 15(1), 47–60.
Buzsaki, G. G. (1984). Feed forward inhibition in the hippocampal formation. Progress in Neurobiology, 22, 131–153.
Canals, S., López-Aguado, L., & Herreras, O. (2005). Synaptically-recruited apical currents are required to initiate axonal and apical spikes in hippocampal pyramidal cells: modulation by inhibition. Journal of Neurophysiology, 93, 909–918.
Castellanos, N. P., & Makarov, V. A. (2006). Recovering EEG brain signals: Artifact suppression with wavelet enhanced independent component analysis. Journal of Neuroscience Methods, 158, 300–312.
Choi, S., Cichocki, A., Park, H. M., & Lee, S. Y. (2005). Blind source separation and independent component analysis: a review. Neural Information Processing - Letters and Reviews, 6, 1–57.
Delorme, A., & Makeig, S. (2004). EEGLAB: an open source toolbox for analysis of single trial EEG dynamics including independent component analysis. Journal of Neuroscience Methods, 134, 9–21.
Einevoll, G. T., Pettersen, K. H., Devor, A., Ulbert, I., Halgren, E., & Dale, A. M. (2007). Laminar population analysis: estimating firing rates and evoked synaptic activity from multielectrode recordings in rat barrel cortex. Journal of Neurophysiology, 97(3), 2174–2190.
Fisher, N. I. (1996). Statistical analysis of circular data. Cambridge University Press.
Gävert, H., Hurri, J., Särelä, J., & Hyvärinen A. (2005). Matlab implementation of fastica is available at http://www.cis.hut.fi/projects/ica/fastica/.
Glasgow, S. D., & Chapman, C. A. (2008). Conductances mediating intrinsic theta-frequency membrane potential oscillations in layer II parasubicular neurons. Journal of Neurophysiology, 100(5), 2746–2756.
Herreras, O. (1990). Propagating dendritic action potential mediates synaptic transmission in CA1 pyramidal cells in situ. Journal of Neurophysiology, 64, 1429–1441.
Herreras, O., Solís, J. M., Martín del Río, R., & Lerma, J. (1987). Characteristics of CA1 activation through the hippocampal trisynaptic pathway in the unanaesthetized rat. Brain Research, 413, 75–86.
Herreras, O., Solís, J. M., Muñoz, M. D., Martín del Río, R., & Lerma, J. (1988). Sensory modulation of hippocampal transmission. I. Opposite effects on CA1 and dentate gyrus synapsis. Brain Research, 451, 290–302.
Hyvärinen, A., & Oja, E. (2000). Independent component analysis: algorithms and applications. Neural Networks, 13(4–5), 411–430.
Ibarz, J. M., Makarova, I., & Herreras, O. (2006). Relation of apical dendritic spikes to output decision in CA1 pyramidal cells during synchronous activation: a computational study. European Journal of Neuroscience, 23, 1219–1233.
Jung, K. Y., Kim, J. M., Kim, D. W., & Chung, C. S. (2005). Independent component analysis of generalized spike-and-wave discharges: primary versus secondary bilateral synchrony. Clinical Neurophysiology, 116, 913–919.
Kocsis, B., Bragin, A., & Buzsáki, G. G. (1999). Interdependence of multiple theta generators in the hippocampus: a partial coherence analysis. Journal of Neuroscience, 19(14), 6200–6212.
Leung, L. S., Roth, L., & Canning, K. J. (1995). Entorhinal inputs to hippocampal CA1 and dentate gyrus in the rat: a current-source-density study. Journal of Neurophysiology, 73(6), 2392–2403.
López-Aguado, L., Ibarz, J. M., & Herreras, O. (2001). Activity-dependent changes of tissue resistivity in the CA1 region in vivo are layer-specific: modulation of evoked potentials. Neuroscience, 108(2), 249–262.
Lorente de Nó, R. (1934). Studies of the structure of the cerebral cortex. II. Continuation of the study of the ammonic system. Journal of Psychology and Neurology, 46, 113–177.
Makarova, I., Gómez-Galán, M., & Herreras, O. (2008). Layer specific changes in tissue resistivity and spatial cancellation of transmembrane currents shape the voltage signal during spreading depression in the CA1 in vivo. European Journal of Neuroscience, 27, 444–456.
Makarova, J., Makarov, V. A., & Herreras, O. (2010). A model of sustained field potentials based on polarization gradients within single neurons. (to appear in the Journal of Neurophysiology).
Makeig, S., Debener, S., Onton, J., & Delorme, A. (2004). Mining event-related brain dynamics. Trends in Cognitive Science, 8, 204–210.
Mitzdorf, U. (1985). Current source-density method and application in cat cerebral cortex: investigation of evoked potentials and EEG phenomena. Physiological Reviews, 65, 37–100.
Montgomery, S. M., Betancur, M. I., & Buzsáki, G. G. (2009). Behavior-dependent coordination of multiple theta dipoles in the hippocampus. Journal of Neuroscience, 29, 1381–1394.
Mouraux, A., & Iannetti, G. D. (2008). Across-trial averaging of event-related EEG responses and beyond. Magnetic Resonance Imaging, 26(7), 1041–1054.
Murakami, S., Hirose, A., & Okada, Y. C. (2003). Contribution of ionic currents to magnetoencephalography (MEG) and electroencephalography (EEG) signals generated by guinea-pig CA3 slices. Journal of Physiology, 553(3), 975–985.
Nicholson, C., & Freeman, J. A. (1975). Theory of current source-density analysis and determination of conductivity tensor for anuran cerebellum. Journal of Neurophysiology, 38(2), 356–368.
Nunez, P. L., & Srinivasan, R. (2006). Electric fields of the brain: the neurophysics of EEG. 2. New York: Oxford University Press.
Pavlov, A., Makarov, V. A., Makarova, J., & Panetsos, F. (2007). Sorting of neural spikes: when wavelet based methods outperform principal component analysis. Natural Computing, 6, 269–281.
Pettersen, K. H., & Einevoll, G. T. (2008). Amplitude variability and extracellular low-pass filtering of neuronal spikes. Biophysical Journal, 94, 784–802.
Ranck, J. B., Jr. (1973). Studies on single neurons in dorsal hippocampal formation and septum in unrestrained rats. I. Behavioral correlates and firing repertoires. Experimental Neurology, 41(2), 461–531.
Rudolph, M., Pelletier, J. G., Paré, D., & Destexhe, A. (2005). Characterization of synaptic conductances and integrative properties during electrically induced EEG-activated states in neocortical neurons in vivo. Journal of Neurophysiology, 94, 2805–2821.
Somogyi, P., & Klausberger, T. (2005). Defined types of cortical interneurone structure space and spike timing in the hippocampus. Journal of Physiology, 562, 9–26.
Spruston, N., & Johnston, D. (1992). Perforated patch-clamp analysis of the passive membrane properties of three classes of hippocampal neurons. Journal of Neurophysiology, 67, 508–529.
Tanskanen, J. M., Mikkonen, J. E., & Penttonen, M. (2005). Independent component analysis of neural populations from multielectrode field potential measurements. Journal of Neuroscience Methods, 145(1–2), 213–232.
Varona, P., Ibarz, J. M., López-Aguado, L., & Herreras, O. (2000). Macroscopic and subcellular factors shaping CA1 population spikes. Journal of Neurophysiology, 83, 2192–2208.
Acknowledgements
We thank J. Lerma and M. Maravall for the critical reading of a previous version of the manuscript. This work was supported by grants: BFU2007-66621, FIS2007-65173, S-SEM-0255-2006, and PR41/06-15058.
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Makarov, V.A., Makarova, J. & Herreras, O. Disentanglement of local field potential sources by independent component analysis. J Comput Neurosci 29, 445–457 (2010). https://doi.org/10.1007/s10827-009-0206-y
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DOI: https://doi.org/10.1007/s10827-009-0206-y