Local field potential

A local field potential (LFP) is a particular class of electrophysiological signals, which is related to the sum of all dendritic synaptic activity within a volume of tissue.

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Background

A signal is recorded using a low impedance extracellular microelectrode, placed sufficiently far from individual local neurons to prevent any particular cell from dominating the electrophysiological signal. This signal is then low-pass filtered, cut off at ~300 Hz, to obtain the local field potential (LFP). The low impedance and positioning of the electrode allows the activity of a large number of neurons to contribute to the signal. The unfiltered signal reflects the sum of action potentials from cells within approximately 50-350 μm from the tip of the electrode (Legatt 1980; Gray 1995)^[1] and slower ionic events from within 0.5-3 mm from the tip of the electrode (Juergens 1999). The low-pass filter removes the spike component of the signal and passes the lower frequency signal, the LFP.

The voltmeter or analog-to-digital converter to which the microelectrode is connected measures the electrical potential difference (measured in volts) between the microelectrode and a reference electrode. One end of the reference electrode is also connected to the voltmeter while the other end is placed in a medium which is continuous with, and compositionally identical to the extracellular medium. In a simple fluid, with no biological component present, there would be slight fluctuations in the measured potential difference around an equilibrium point, this is known as the thermal noise. This is due to the random movement of ions in the medium and electrons in the electrode. However, in neural tissue the opening of an ion channel results in the net flow of ions into the cell from the extracellular medium, or out of the cell into the extracellular medium. These local currents result in larger changes in the electrical potential between the local extracellular medium and the interior of the recording electrode. The overall recorded signal thus represents the potential caused by the sum of all local currents on the surface of the electrode.

Synchronised Input

The local field potential is believed to represent the synchronised input into the observed area, as opposed to the spike data, which represents the output from the area. In the LFP, quick fluctuations in the potential difference are filtered out, leaving only the slower fluctuations. The quick fluctuations are caused by the short inward and outward currents of the action potential. Therefore the action potential plays no part in the LFP. The LFP is thus composed of the more sustained currents in the tissue, typical of the somato-dendritic currents. The major slow current is the postsynaptic potential (PSP). It was thought until recently that EPSPs and IPSPs were the exclusive constituents of LFPs. However, phenomena unrelated to synaptic events have been found to contribute to the signal (Kobayashi 1997; Kamondi 1998). These phenomena will not be explored here.

Geometrical Arrangement

Cells which contribute to the slow field variations are determined by the geometric configuration of the cells themselves. In some cells the dendrites face one direction and the soma another, such as the pyramidal cells. This is known as an open field geometrical arrangement. When there is simultaneous activation of the dendrites a strong dipole is produced. In cells where the dendrites are arranged more radially, the potential difference between individual dendrites and the soma tend to cancel with diametrically opposite dendrites. As a result the net potential difference over the whole cell when the dendrites are simultaneously activated tends to be very small. Thus changes in the local field potential represent simultaneous dendritic events in cells in the open field configuration.

References

1. ^ Legatt, A. D., Arezzo, J., & Vaughan, H. G. (1980). Averaged multiple unit activity as an estimate of phasic changes in local neuronal activity: effects of volume-conducted potentials. Journal of Neuroscience Methods, 2(2), 203-217.