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When a compound is expecting to show some central nervous system (CNS) activity, its potentials
still need to be well established for the drug to be classified properly before thinking about
therapeutic effect. For that purpose pharmaco-dynamic (PDY) studies are required and currently
involve electro-encephalographic signal recording (EEG) of healthy subjects according to a
crossover design wherein each period includes repeated measures of EEG (days, times).
Spatio-temporal distributions of parameters (frequency bands of the signal) are of interest for
differences between placebo and verum doses. Links with additional variables such as
neurocognitive variables (psychometric tests) can also be explored and will be addressed briefly
in the discussion as well as a current interest on looking at pharmaco-kinetic parameters
conjointly.
The data-recording methodology and the quantification of the EEG-signal used for the dataset
analysed thereafter is fully described in [17]. A collection and quantification of
EEG-data, for each of the 28 leads (international 10/20 system is complemented to 28 leads with
B1, FC1, FC2, B2, W1, PC1, PC2, W2). At each time of measurement, EEGs are taken under 3 minutes
vigilance controlled (VC) recording condition (subjects push two knobs with their eyes closed),
followed by 3 minutes resting (R) recording condition (subjects relax with their eyes closed).
After filtering and digitisation and artefact removal procedure completed, energy spectra () is calculated, for each 2 second period over a frequency range of 0.5 to 32Hz, using the
Fast Fourier Transform (FFT), and then averaged for each subject and each recording condition.
Each mean energy spectra is averaged by standard frequency EEG bands : (0.5-3.5Hz),
(4-7.5Hz), (8-9.5Hz), (10-12.5Hz), (13-17.5Hz),
(18-20.5Hz), (21-32Hz) and Total (0.5-32Hz). Absolute energies and relative
energies (percentage of the Total band energy) are considered. The alpha slow wave index (
), the mean frequency (GMF) and the mean
complexity (GCO) of the EEG spectrum are also calculated.
The whole process will then analyse at each time of measurement(typically not regularly
spaced measures):
28 leads(2 absolute or % (7 bands)+1 total+3 synthetic variables) 2 conditions
28 locations18 parameters2 conditions
1008 variables measured say times on say subjects. In fact only parameters generated the .
This methodology was conducted for the following pharmaco-dynamic study (PDY),a
placebo-controlled, double-blind trial, with randomisation of 12 healthy male subjects into a 4
periods and 4 treatments cross-over design. Each received a single morning dose of 10, 30, 90mg of
compound or placebo and wake-EEG was performed on day 1 before administration and 0.5, 1, 1.5, 2,
2.5, 3, 4, 6, hours post-dosing and on day 2: 24 and 36 hours post-dosing. Blood was sampled for
determination of drug plasma concentration and endocrinological assessments on day 1 before
administration and then 1, 2, 4, 6 hours post-dosing and on day 2: 24 and 36 hours post-dosing.
The interest is in knowing if the compound has an effect? which dose? (dose effect?), at what
point in time does it happen? where is it located on the scalp? for which frequency band or
pattern of frequency band does this affect? To answer these questions, parametric and
non-parametric testing methods have been routinely implemented. In the first place some
weaknesses of these mainly univariate methods will be pointed out before introducing our
proposed method involving multiway data analysis methods. The main method applied here was
theoretically exposed in [16]. The purpose of this paper is show how to modify and
apply it in this context. This involves different methods which are related to existing approaches
in multidimensional analysis (two-way analysis), and thereby extending them to multiway data. An
important generalisation is about Correspondence Analysis extended from the analysis of
variables to variables enabling to break down the lack of complete independence into additive
components relating to different level of interactions between the variables.
Next: Shortcomings of current statistical
Up: tr00dl2
Previous: tr00dl2
Didier Leibovici
2001-09-04