In general, signal amplitude in optical imaging is normalized using the
well-established ΔF/F method, where functional activity is divided by
the total fluorescent light flux. This measure is used both directly, as a
measure of population activity, and indirectly, to quantify spatial and
spatiotemporal activity patterns. Despite its ubiquitous use, the stability and
accuracy of this measure has not been validated for voltage-sensitive dye
imaging of mammalian neocortex in vivo. In this report, we find
that this normalization can introduce dynamic biases. In particular, the
ΔF/F is influenced by dye staining quality, and the ratio is also
unstable over the course of experiments. As methods to record and analyze
optical imaging signals become more precise, such biases can have an
increasingly pernicious impact on the accuracy of findings, especially in the
comparison of cytoarchitechtonic areas, in area-of-activation measurements, and
in plasticity or developmental experiments. These dynamic biases of the
ΔF/F method may, to an extent, be mitigated by a novel method of
normalization, ΔF/ΔFepileptiform. This normalization
uses as a reference the measured activity of epileptiform spikes elicited by
global disinhibition with bicuculline methiodide. Since this normalization is
based on a functional measure, i.e. the signal amplitude of
“hypersynchronized” bursts of activity in the cortical
network, it is less influenced by staining of non-functional elements. We
demonstrate that such a functional measure can better represent the amplitude of
population mass action, and discuss alternative functional normalizations based
on the amplitude of synchronized spontaneous sleep-like activity. These findings
demonstrate that the traditional ΔF/F normalization of voltage-sensitive
dye signals can introduce pernicious inaccuracies in the quantification of
neural population activity. They further suggest that normalization-independent
metrics such as waveform propagation patterns, oscillations in single detectors,
and phase relationships between detector pairs may better capture the biological
information which is obtained by high-sensitivity imaging.