Electrophysiology · reads
Conventional wet scalp EEG is a non-invasive recording of the brain's electrical activity through gel-coupled electrodes on the scalp. What it reads is the electric potential at the scalp, which arises from currents crossing nerve cell membranes, mainly synchronized currents at the synapses of aligned cortical cells. That potential is a smoothed electrical trace of the neural currents themselves, blurred over several square centimetres of cortex by the skull and tissue in between. Timing is in principle milliseconds, but the spread of current through the head can distort it.
Conventional wet scalp electroencephalography (EEG) is a non-invasive recording of the brain's oscillating electric potentials from electrodes on the scalp, with conductive gel between skin and electrode to carry the charge. The recorded quantity is the extracellular electric potential at the scalp: a local field potential smoothed in space and time. It arises from transmembrane currents, mainly synaptic and postsynaptic activity, with contributions from calcium spikes, other intrinsic events, action potentials and afterpotentials. Its generators are attributed to synchronous postsynaptic currents in aligned pyramidal cells. In space the scalp signal is a volume-conducted, blurred superposition of synchronous cortical activity over extended cortical patches. Tissue, especially the skull, attenuates it, and the attenuation depends on the source extent: with at least 10 cm² of active cortex, the predicted cortical-to-scalp potential ratio is about 2 to 6 because many source contributions superpose. Low-density montages resolve roughly 5 to 9 cm; simulations with 64 or more electrodes achieve about 1–3 cm, depending on electrode density; dense sampling alone is insufficient, and source modelling or surface-Laplacian (current source density) processing can improve the resolution. In time the resolution is in principle milliseconds, but volume conduction and reference effects can distort scalp-potential time courses and misestimate latencies; surface-Laplacian processing can substantially improve the recovered timing.
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