  Extracellular electrical potentials (EEP) recorded from the brain are an
active manifestation of all cellular processes that propagate within a volume
of brain tissue. A standard approach for their quantification are power
spectral analyses methods that reflect the global distribution of signal power
over frequency. However, these methods incorporate analysis windows to achieve
locality and therefore, are limited by the inherent trade - off between time
and frequency resolutions. In this paper, we present a novel approach to
estimate local power more precisely at a resolution as high as the sampling
frequency. Our methods are well grounded on established neurophysiology of the
bio-signals where we model EEPs as comprising of two components:
neuromodulations and background activity. A local measure of power, we call
Marked Point Process (MPP) spectrogram, is then derived as a power - weighted
intensity function of the point process for neuromodulations. We demonstrate
our results on two datasets: 1) local field potentials recorded from the
prefrontal cortex of 3 rats performing a working memory task and 2) EEPs
recorded via electroencephalography from the visual cortex of human subjects
performing a conditioned stimulus task. A detailed analysis of the power -
specific marked features of neuromodulations confirm high correlation between
power spectral density and power in neuromodulations establishing the aptness
of MPP spectrogram as a finer measure of power where it is able to track local
variations in power while preserving the global structure of signal power
distribution.
