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Reflexive startle electromyography


What Does This Channel Measure?

People exhibit in response to a sudden threatening event a whole body startle response, including increased heart rate, contraction of the neck muscles, and an eyeblink, among others. Measuring the startle response is important in the context of emotion research, as its magnitude is modulated by affective valence. Roughly, the more negative someone feels the larger the magnitude of the startle response. Typically, startle responses are provoked using loud (95 dB), sudden (50 ms) bursts of white noise – so-called startle probes. As an indicator of startle magnitude we use the strength of the eyeblink response, which is measured with electromyographic (EMG) activation of the lower eyelid. ANSLAB preprocesses and displays this EMG activation and allows to edit it for individual startle probes.




Editing of Startle Data:


The raw data file needs to contain a marker channel that indicates when the startle probe was given. The marker needs to go up when the noise burst starts and down when the noise burst ends. ANSLAB will first analyze this marker channel and then, probe-by-probe, load in the raw EMG data surrounding this probe.
A window will pop open showing you the first startle probe (=trial) within this file. You go from trial to trial by just hitting “enter.”
Here’s how to read the startle data display windows:


Upper graph, yellow line = filtered and rectified EMG signal (this is what you should focus on)

Lower graph, yellow line = raw EMG signal

Upper graph:
First vertical blue line
= start of baseline

Second vertical blue line = probe onset and end of baseline

Lower horizontal blue line = startle response baseline (average of the baseline window)

Higher horizontal blue line = indicator for 1 standard deviation above the average baseline

Red area = startle scoring area (ANSLAB only looks for a response in the window between 20 and 120 ms after the tone as this is physiologically the time window we expect a startle response to occur. Sometimes there will be a second, partially voluntary response, after this time window which we do not want to include - see Example 1 below).


The three main variables extracted by ANSLAB are startle response magnitude (=peak minus baseline value), startle response latency (from tone onset to peak response as evident in the EMG average upper window), and startle onset latency (from tone onset to onset of EMG response as evident in the lower raw EMG window). The highest peak within the red window should be automatically marked, which will usually be the correct decision. If not, you can reset a response by simply clicking with the left mouse button. If there are two equally plausible peaks pick the one closer to the normal response time for that subject and above the 1 SD line [see Example 2 below --> the first response is closer to this subject’s normal response latency].  If there is no clear response, click on a clearly identifiable peak that is approximately at the normal response time for that subject in order not to distort response latency. Do this only if the standard deviation is low. [See example 3 below --> this response might justifiably be set a little later on the second discernible peak if it reflects the subject’s normal response latency; or alternatively, set to 0 response.]  If the standard deviation is higher (i.e., much higher than any of the responses in that trial), consider excluding this response by hitting “i” for invalid, as this response measurement is probably not reliable due to an instable baseline.      
After you have gone through one file trial-by-trial, a window appears that displays startle magnitude and latencies for each response. They appear as step functions, because ANSLAB is set to extrapolate from each response for the whole intertrial interval.







Some Other Functions:

r: adjust range. You can use this function if you want to have a closer look at one response. Sometimes a response might be displayed as very small, because the range is contingent on the largest response in the whole file. In such cases, you can decrease the y-axis upper limit in the upper window in order to see better what is going on.

w: adjust response scoring window. You should use this function very rarely, e.g., when a technical failure for event marking occurred, and only when responses clearly lie outside the “normal time window” but not so far away as to be physiologically impossible. This will let you reset the start time for the 100 ms red area within which ANSLAB looks for a response. The selected value will remain active for the entire file.

b: adjust the baseline definition window. You can use this function carefully sometimes if there is a short and small EMG burst during the baseline window, but not during other times.  This baseline noise would result in an overestimation of the baseline mean and thus an underestimation of the response magnitude. You can reset the baseline window by clicking on the area in the upper plot where a normal baseline EMG activity is present. This can be repeated until pressing <Enter> exits this function. This resetting of the baseline should be used only in special cases where it is clearly justified. The typical guideline for dealing with an elevated baseline is to exclude this trial using option <i> (invalid), since most baseline "noise" stems from a pre-startle probe involuntary eye-blink. There is a refractory period after it that makes the startle blink response less pronounced and thus confounded.

o: adjust the onset latency. This function should be used when the onset latency estimated in the lower raw EMG window is incorrect (as e.g., in Figure 2 above). You can reset the lower graph onset line by clicking at the desired time in the upper graph. This can be repeated until the placement of the lower graph line is correct. The function can be exited with <Enter>.

l: adjust the response latency. This function should be used extremely rarely, if at all, when the response latency estimation based on the peak is incorrect, but resetting the peak would result in a misestimation of the response magnitude. You can reset the response latency time by clicking at the desired time in the upper graph. This can be repeated until the placement is correct. The function can be exited with <Enter>.

0: set the response magnitude to zero and the latencies to missing value. This option should be used if no clear startle response is discernible. Zero responses can occur within subjects after many startle tones have been presented in short succession, or in some subjects that do not have a pronounced eye-blink startle response. Caution is advised if there is generally no or a weak startle response in a subject: this might also indicate a problem with the electrode placement or amplifiers.

i: set all response parameters to invalid (set trial to missing data). This option should be used if there is so much baseline noise that the startle response is clearly below the baseline + standard deviation line. This option also should be used if there was clearly a non-startle blink right before or during the startle tone, which would dampen the response to the noise burst because of a refractory period in the eye-lid muscles. There are other possible reasons for excluding a trial which have to be weighed cautiously in each case.

Output of Startle Data:

Here’s what the variable names mean:
laa  startle magnitude (time averaged, using the step function)
la_  startle magnitude (response averaged)
lll  startle response latency (time averaged, using the step function)
ll_  startle response latency (response averaged)
lb_  baseline amplitude
ls_  number of presented tone stimuli
lv_  number of valid startle responses
lz_  number of zero startle responses
las  within subject SD of la_
lls  within subject SD of ll_
lsb  within subject SD of lB_
(SDs are normalized for number of trials)
The variables you will want to use in general are la_ and ll_.

The startle matrix is saved on disk and contains the columns startle time, startle magnitude, startle latency, startle onset, and startle baseline.


Ratio adjustment for reactivity scores (task minus baseline) may be more appropriate than change scores with EMG data. The startle response magnitude for a given individual depends on many factors: exact placement of the electrodes, muscle size, innervation density, skin thickness, etc. All these are probably multiplicative rather than additive factors for the response estimation. However, often additive change scores are used in publications.


Editing Examples: