Biomedical Engineering Reference
In-Depth Information
signals have most often been used in monitoring membrane
potential and calcium concentration from tissue-cultured neu-
rons. Both fluorescence and absorption have been used in
measurements from ganglia and brain slices. Fluorescence or
reflectance has always been used in measurements from intact
brains.
3.2. Amplitude of the
Voltage or Calcium
Change
Both the signals are often presented as a fractional intensity
change (
I/I). These signals give information about the time
course of the potential or calcium concentration change but no
direct information about the absolute magnitude. However, in
some instances, approximate estimations can be obtained. For
example, the size of the optical signal in response to a sensory
stimulus can be compared to the size of the signal in response
to an epileptic event
(62)
. Another approach is the use of ratio-
metric measurements at two independent wavelengths
(63, 64)
.
However, to determine the amplitude of the voltage or calcium
change from a ratio measurement, one must know the fraction of
the fluorescence that results from dye in the expected location, i.e.
bound to active
versus
inactive membranes for voltage-sensitive
dyes, or dye free in the axoplasm
versus
dye bound to protein
or in intracellular compartments for calcium dyes. These require-
ments are only approximately met in special circumstances. For
voltage-sensitive dyes, the best calibration is an electrode mea-
surement of membrane potential. One case where this was possi-
ble was described in the first example presented above.
4. Measuring
Technology
The limit of accuracy with which light can be measured is set by
the shot noise arising from the statistical nature of photon emis-
sion and detection. Random fluctuations in the number of pho-
tons emitted (and measured) per unit time occur; the root-mean-
square (RMS) deviation in the number emitted is the square root
of the average number. In a shot noise limited measurement, the
signal-to-noise ratio is directly proportional to the square root of
the number of measured photons and inversely proportional to
the square root of the bandwidth of the photodetection system
(65, 66)
. The basis for the square root dependence on intensity is
illustrated in
Figure 3.10
. In 10A, the result of using a random
number table to distribute 20 photons into 20 time windows is
shown. In 10B, the same procedure was used to distribute 200
photons into the same 20 bins. Relative to the average light level,
there is more noise in the top trace (20 photons) than in the bot-
tom trace (200 photons). On the right side of
Fig. 3.10
,the
measured signal-to-noise ratios are listed; the improvement from
4.1. Noise
4.1.1. Shot Noise
