Abstract
Recordings of brain electrophysiological activity provide the most direct reflect of neural function. Information contained in these signals varies as a function of the spatial scale at which recordings are done: from single cell recording to large scale macroscopic fields, e.g., scalp EEG. Microscopic and macroscopic measurements and models in Neuroscience are often in conflict. Solving this conflict might require the developments of a sort of bio-statistical physics, a framework for relating the microscopic properties of individual cells to the macroscopic or bulk properties of neural circuits. Such a framework can only emerge in Neuroscience from the systematic analysis and modeling of the diverse recording scales from simultaneous measurements. In this article we briefly review the different measurement scales and models in modern neuroscience to try to identify the sources of conflict that might ultimately help to create a unified theory of brain electromagnetic fields. We argue that seen the different recording scales, from the single cell to the large scale fields measured by the scalp electroencephalogram, as derived from a unique physical magnitude—the electric potential that is measured in all cases—might help to conciliate microscopic and macroscopic models of neural function as well as the animal and human neuroscience literature.
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs11517-011-0769-4/MediaObjects/11517_2011_769_Fig1_HTML.gif)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs11517-011-0769-4/MediaObjects/11517_2011_769_Fig2_HTML.gif)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs11517-011-0769-4/MediaObjects/11517_2011_769_Fig3_HTML.gif)
Similar content being viewed by others
References
Adrian ED, Matthews BHC (1934) The interpretation of potential waves in the cortex. J Physiol 81:440–471
Anastassiou CA, Montgomery SM, Barahona M, Buzsaki G, Koch C (2010) The effect of spatially inhomogeneous extracellular electric fields on neurons. J Neurosci 30:1925–1936. doi:10.1523/JNEUROSCI.3635-09.2010
Arieli A, Sterkin A, Grinvald A, Aertsen A (1996) Dynamics of ongoing activity: explanation of the large variability in evoked cortical responses. Science 273:1868–1871
Averbeck BB, Lee D (2004) Coding and transmission of information by neural ensembles. Trends Neurosci 27:225–230
Barth DS (2003) Submillisecond synchronization of fast electrical oscillations in neocortex. J Neurosci 23:2502–2510
Bedard C, Destexhe A (2009) Macroscopic models of local field potentials the apparent 1/f noise in brain activity. Biophys J 96:2589–2603
Bedard C, Kroger H, Destexhe A (2004) Modeling extracellular field potentials and the frequency-filtering properties of extracellular space. Biophys J 86:1829–1842
Bedard C, Kröger H, Destexhe A (2006) Model of low-pass filtering of local field potentials in brain tissue. Phys Rev E 73:051911
Benucci A, Frazor RA, Carandini M (2007) Standing waves and traveling waves distinguish two circuits in visual cortex. 55:103–117
Blum RA, Ross JD, Brown EA, DeWeerth SP (2007) An integrated system for simultaneous, multichannel neuronal stimulation and recording. IEEE Trans Circuits Syst 54:2608–2618
Brovelli A, Lachaux LJ, Kahane P, Boussaoud D (2005) High gamma frequency oscillatory activity dissociates attention from intention in the human premotor cortex. Neuroimage 28:154–164
Buhl DL, Buzsaki G (2005) Developmental emergence of hippocampal fast-field “ripple” oscillations in the behaving rat pups. Neuroscience 134:1423–1430
Burns SP, Xing D, Shapley RM (2010) Comparisons of the dynamics of local field potential and multiunit activity signals in macaque visual cortex. J Neurosci 30:13739–13749. doi:10.1523/JNEUROSCI.0743-10.2010
Buzsáki G (2002) Theta oscillations in the hippocampus. Neuron 33:325–340
Buzsáki G (2006) Rhythms of the brain. University Press, Oxford
Buzsaki G, Draguhn A (2004) Neuronal oscillations in cortical networks. Science 304:1926–1929
Buzsaki G, Horvath Z, Urioste R, Hetke J, Wise K (1992) High-frequency network oscillation in the hippocampus. Science 256:1025–1027. doi:10.1126/science.1589772
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. doi:10.1126/science.1128115
Cohen I, Miles R (2000) Contributions of intrinsic and synaptic activities to the generation of neuronal discharges in in vitro hippocampus. J Physiol 524(2):485–502
Curio G (2000) Linking 600-Hz “spikelike” EEG/MEG wavelets (“sigma-bursts”) to cellular substrates: concepts and caveats. J Clin Neurophysiol 17:377–396
Curio G, Mackert BM, Burghoff M, Koetitz R, Abraham-Fuchs K, Harer W (1994) Localization of evoked neuromagnetic 600 Hz activity in the cerebral somatosensory system. Electroencephalogr Clin Neurophysiol 91:483–487
Deco G, Jirsa VK, Robinson PA, Breakspear M, Friston K (2008) The dynamic brain: from spiking neurons to neural masses and cortical fields. PLoS Comput Biol 4:e1000092
Draguhn A, Traub RD, Schmitz D, Jefferys JG (1998) Electrical coupling underlies high-frequency oscillations in the hippocampus in vitro. Nature 394:189–192
Edwards E, Soltani M, Deouell LY, Berger MS, Knight RT (2005) High gamma activity in response to deviant auditory stimuli recorded directly from human cortex. J Neurophysiol 94:4269–4280. doi:10.1152/jn.00324.2005
Engel AK, Fries P, Singer W (2001) Dynamic predictions: oscillations and synchrony in top-down processing. Nat Rev Neurosci 2:704–716
Freeman WJ (2007) Definitions of state variables and state space for brain-computer interface—part 1: multiple hierarchical levels of brain function. Cogn Neurodyn 1:3–14
Fröhlich F, McCormick DA (2010) Endogenous electric fields may guide neocortical network activity. Neuron 67:129–143
Gervasoni D, Lin SC, Ribeiro S, Soares ES, Pantoja J, Nicolelis MA (2004) Global forebrain dynamics predict rat behavioral states and their transitions. J Neurosci 24:11137–11147
Gonzalez Andino SL, Grave de Peralta Menendez R, Lantz CM, Blank O, Michel CM, Landis T (2001) Non-stationary distributed source approximation: an alternative to improve localization procedures. Hum Brain Mapp 14:81–95
Gonzalez Andino SL, Michel CM, Thut G, Landis T, Grave de Peralta R (2005) Prediction of response speed by anticipatory high-frequency (gamma band) oscillations in the human brain. Hum Brain Mapp 24:50–58
Gonzalez Andino SL, Grave de Peralta R, Khateb A, Pegna AJ, Thut G, Landis T (2007) A glimpse into your vision. Hum Brain Mapp 28:614–624
Gonzalez Andino SL, Grave de Peralta Menendez R, Khateb A, Landis T, Pegna AJ (2009) Electrophysiological correlates of affective blindsight. NeuroImage 44:581–589
Gonzalez SL, Grave de Peralta R, Thut G, Millan Jdel R, Morier P, Landis T (2006) Very high frequency oscillations (VHFO) as a predictor of movement intentions. Neuroimage 32:170–179
Grave de Peralta Menendez R, Gonzalez Andino SL (2000) Two new alternatives to compute smooth solutions. NeuroImage 11:S486
Grave de Peralta Menendez R, Gonzalez Andino SL, Morand S, Michel CM, Landis T (2000) Imaging the electrical activity of the brain: ELECTRA. Hum Brain Mapp 9:1–12
Haider B, Duque A, Hasenstaub AR, McCormick DA (2006) Neocortical network activity in vivo is generated through a dynamic balance of excitation and inhibition. J Neurosci 26:4535–4545
Han F, Caporale N, Dan Y (2008) Reverberation of recent visual experience in spontaneous cortical waves. Neuron 60:321–327
Hari R, Parkkonen L, Nangini C (2010) The brain in time: insights from neuromagnetic recordings. Ann N Y Acad Sci 1191:89–109
Hastings SP (1976) On travelling wave solutions of the Hodgkin-Huxley equations. Arch Ration Mech Anal 60:229–257
Hille B (1970) Ionic channels in nerve membranes. Prog Biophys Mol Biol 21:1–32
Hoffman KL, Battaglia FP, Harris K, MacLean JN, Marshall L, Mehta MR (2007) The upshot of up states in the neocortex: from slow oscillations to memory formation. J Neurosci 27:11838–11841
Hutcheon B, Yarom Y (2000) Resonance, oscillation and the intrinsic frequency preferences of neurons. Trends Neurosci 23:216–222
Ingber L (1994) Statistical mechanics of neocortical interactions: path-integral evolution of short-term memory. Phys Rev E 49:4652–4664
Jackson JD (1998) Classical electrodynamics. Wiley, New York
Jefferys JG (1995) Nonsynaptic modulation of neuronal activity in the brain: electric currents and extracellular ions. Physiol Rev 75:689–723
Jirsa VK, Haken H (1996) Field theory of electromagnetic brain activity. Phys Rev Lett 77:960–963
Jirsa V, Jantzen K, Fuchs A, Kelso J (2002) Spatiotemporal forward solution of the EEG and MEG using network modeling. IEEE Trans Med Imag 21:493–504
Johnson KO (2000) Neural coding. Neuron 26:563–566
Katzner S, Nauhaus I, Benucci A, Bonin V, Ringach DL, Carandini M (2009) Local origin of field potentials in visual cortex. Neuron 61:35–41
Kenet T, Bibitchkov D, Tsodyks M, Grinvald A, Arieli A (2003) Spontaneously emerging cortical representations of visual attributes. Nature 425:954–956
Kerschensteiner D, Wong ROL (2008) A precisely timed asynchronous pattern of ON and OFF retinal ganglion cell activity during propagation of retinal waves. Neuron 58:851–858
Klimesch W (1999) EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis. Brain Res Brain Res Rev 2–3:169–195
Kreiman G, Hung C, Quian Quiroga R, Kraskov A, Poggio T, DiCarlo JJ (2006) Object selectivity of local field potentials and spikes in the macaque inferior temporal cortex. Neuron 49:1–13
Kruse W, Eckhorn R (1996) Inhibition of sustained gamma oscillations (35–80 Hz) by fast transient responses in cat visual cortex. Proc Natl Acad Sci USA 93:6112–6117
Lachaux JP, Rudrauf D, Kahane P (2003) Intracranial EEG and human brain mapping. J Physiol Paris 97:613–628
Le Van Quyen M, Khalilov I, Ben-Ari Y (2006) The dark side of high-frequency oscillations in the developing brain. Trends Neurosci 29:419–427
Logothetis NK, Wandell BA (2004) Interpreting the BOLD Signal. Annu Rev Physiol 66:735–769
Logothetis NK, Pauls J, Augath M, Trinath T, Oeltermann A (2001) Neurophysiological investigation of the basis of the fMRI signal. Nature 412:150–157
Mann EO, Paulsen O (2010) Local field potential oscillations as a cortical soliloquy. Neuron 67:3–5
Mehring C, Rickert J, Vaadia E, Cardosa de Oliveira S, Aertsen A, Rotter S (2003) Inference of hand movements from local field potentials in monkey motor cortex. Nat Neurosci 6:1253–1254
Niedermeyer E, Lopes da Silva F (2004) Electroencephalography: basic principles, clinical applications, and related fields. Lippincott Williams & Wilkins, New York
Nunez PL, Srinivasan R (2005) Electric fields of the brain: the neurophysics of EEG. Oxford University Press, New York
Nunez PL, Srinivasan R (2006) A theoretical basis for standing and traveling brain waves measured with human EEG with implications for an integrated consciousness. Clin Neurophysiol 117:2424–2435
Pesaran B, Pezaris JS, Sahani M, Mitra PP, Andersen RA (2002) Temporal structure in neuronal activity during working memory in macaque parietal cortex. Nat Neurosci 5:805–811
Plonsey R, Heppner DB (1967) Considerations of quasistationarity in electrophysiological systems. Bull Math Biophys 29:657–664
Saleem AB, Chadderton P, Apergis-Schoute J, Harris KD, Schultz SR (2010) Methods for predicting cortical UP and DOWN states from the phase of deep layer local field potentials. J Comput Neurosci 29:49–62. doi:10.1007/s10827-010-0228-5
Sanchez-Vives MV, McCormick DA (2000) Cellular and network mechanisms of rhythmic recurrent activity in neocortex. Nat Neurosci 3:1027–1034
Schultz W (2010) Dopamine signals for reward value and risk: basic and recent data. Behav Brain Funct 6:24
Sirota A, Csicsvari J, Buhl D, Buzsaki G (2003) Communication between neocortex and hippocampus during sleep in rodents. PNAS 100:2065–2069. doi:10.1073/pnas.0437938100
Somjen GG (2001) Mechanisms of spreading depression and hypoxic spreading depression-like depolarization. Physiol Rev 81:1065–1096
Syková E, Nicholson C (2008) Diffusion in brain extracellular space. Physiol Rev 88:1277–1340
Taylor RE, Fernândez JM, Bezanilla F (1982) Squid axon membrane low frequency dielectric properties. In: Adelman WJ, Goldman DE (eds) The biophysical approach to excitable systems. Proceedings of symposium honoring Kenneth S. Cole on his 80th birthday. Plenum Press, New York, pp 97–106
Teplan M (2002) Fundamentals of EEG measurement. Measurement Sci Rev 2:1–11
Uhlhaas PJ, Singer W (2010) Abnormal neural oscillations and synchrony in schizophrenia. Nat Rev Neurosci 11:100–113
Weiss SA, Faber DS (2010) Field effects in the CNS play functional roles. Front Neural Circuits 18:4–15
Xu W, Huang X, Takagaki K, Wu J-y (2007) Compression and reflection of visually evoked cortical waves. Neuron 55:119–129
Acknowledgments
We thank Prof. Fivos Panetsos, Laboratory of Neurocomputing and Neurorobotics, Complutense University of Madrid, Spain for graciously providing the data shown in Fig. 2. This study has been supported by the 3R Research Foundation, Switzerland, under Grant number 119-10. We thank two anonymous reviewers for their detailed comments that contributed to improve earlier versions of this manuscript.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Gonzalez Andino, S.L., Perrig, S. & Grave de Peralta Menendez, R. Spatiotemporal scales and links between electrical neuroimaging modalities. Med Biol Eng Comput 49, 511–520 (2011). https://doi.org/10.1007/s11517-011-0769-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11517-011-0769-4