NeuroMatic analysis software for detecting spontaneous events, such as EPSCs. The search algorithm can be either a simple level detector, a threshold-above-baseline detector similar to that described by Kudoh and Taguchi 2002, or a template-matching detector as described by Clements and Bekkers 1997.
>> Event Waves are now created inside Subfolders by default.
Event Criteria Controls
Negative/Positive Events Toggle. Click this checkbox to specify whether to detect events with a negative deflection from the baseline, or a positive deflection from the baseline. This will determine what algorithms are listed in the top drop-down menu.
Search Time Limits. Click this checkbox to set the begin and end search time limits. By default the limits are set to search the entire length of the data wave (-inf to inf).
Event Search Algorithm Select (negative events)
Threshold < Baseline. A level-detection search where the level is a threshold value below a sliding baseline window. The threshold value is entered in the top-right SetVariable control (enter absolute value). The size of the sliding baseline window is set by clicking bsln xwin. This algorithm is similar to that of Kudoh and Taguchi 2002 except the sliding baseline is a window rather than a sliding data point. See Event Detection Details.
Nstdv < Baseline. Same as (Threshold < Baseline) except the detection level equals a number of standard deviations (Nstdv) below the sliding baseline window. The standard deviation is computed within the sliding average window, so the sliding average window should be set large enough (bsln xwin) to obtain a good measure of the baseline standard deviation. Nstdv is entered in the top-right SetVariable control.
Level Detection (-slope). A simple level-detection search restricted to level crossings within a stretch of data with negative slope. The level is entered in the top-right SetVariable control. There is no sliding baseline window computation. See Igor’s FindLevels function (/EDGE=2).
Event Search Algorithm Select (positive events)
Threshold > Baseline. Same as (Threshold < Baseline) except the level is a threshold value above the sliding baseline window.
Nstdv > Baseline. Same as (Nstdv < Baseline) except the level equals Nstdv above the sliding baseline window.
Level Detection (+slope). Same as Level Detection (-slope) except the search is restricted to level crossings within a stretch of data with positive slope (/EDGE=1).
Event Onset Search. This is an optional search creteria for the “onset” of an event once the event has been detected (via one of the algorithms defined above). If no onset is found, the event is ignored and the search for events continues. If you do not wish to use this onset criteria for limiting what is considered an acceptable event, uncheck the onset checkbox. The onset search algorithm is similar to that of Kudoh and Taguchi 2002. See Event Detection Details.
Event Peak Search. Same as the onset search except the search is for the “peak” of an event. See Event Detection Details.
Template Matching Algorithm. In this algorithm, a waveform template with time-course typical of a synaptic event is first “matched” to the current data set as described by Clements and Bekkers 1997. This produces a “detection criterion” wave which NeuroMatic calls EV_MatchTmplt (displayed as a blue wave on top of your original data). An event is detected when EV_MatchTmplt crosses a defined level Clements and Bekkers suggest a level of 4 (or -4 for negative events).
To use the template matching algorithm for event detection, you need to download the appropriate MatchTemplate XOP file ( PC | PC 64-bit | Mac | Mac 64-bit ), Unzip the downloaded file and place it in the Igor Extensions folder before starting Igor.
To use the MatchTemplate XOP, click the template matching checkbox. You will be asked to provide parameters for a template, such as rise and decay time constants, or to provide the name of your predefined template wave. You have the option of specifying an initial onset of zero baseline before your waveform; this helps in detecting only those events with a relatively flat baseline. Next, click the “Match” button. NeuroMatic will compute the detection-criterion wave EV_MatchTmplt. Note, depending on the speed of your computer and length of your data waves, computing EV_MatchTmplt can take some time.
Event Search Controls
>> Successes and Rejections – event detection results are now saved to two Event Tables, one for successful event detections, the other for failed event detections. A failed event detection occurs if either the onset or peak of the event is not detected. Note, the onset and peak detection criteria are optional and can be turned off. Failures are most likely due to a failure in peak detection.
Table Menu – use the top drop-down menu to Clear or Delete the current event detection results. To delete, you need to close all graphs and tables containing the event detection waves. To the right of the menu is the number of saved events in the Event Success Table.
[>] – search for next event.
[>] – set search time and cursors to next saved event if one exists (when reviewing).
[<] – set search time and cursors to previous saved event if one exists.
[>>] – jump to end of wave.
[<<] – jump to beginning of wave.
Save current detected event to the Event Success Table. If you are reviewing rejections, this function will move the rejected event to the Event Success Table.
Reject current detected event. The event will be saved to the Event Rejection Table. If you are reviewing rejections, this function will permanently delete the event from the Event Rejection Table.
All Waves – compute spike detection on all currently selected channels and waves (7). Results are saved to an Event Success Table and Event Rejection Table.
>> Review the event detection results. If there were rejected events, you will be asked whether to review successes or rejections.
Search Time (x=) – the time displayed in this SetVariable control is the beginning time for the next event search. This is automatically set to the time of the current detected event, but can be changed manually here. This time can also be changed via the Event x slider control on the active Channel Graph.
Event x – slider control on the active Channel Graph that sets the search time (see above).
X-zoom – slider control on the active Channel Graph that sets the x-axis event-search window size.
Square Marquee Functions – to fine-tune event detection, draw a square marquee around the stretch of data that is of interest and click inside the square. A drop-down menu will appear with the following options:
NM reject events inside marquee
NM find event inside marquee
NM save cursors as an event – use this function to force NeuroMatic to search for an event. Place the circle and square cursors where you think the event onset and peak are located. Select this function and NeuroMatic will search for an event threshold crossing between the cursors. Alternatively, you can use this function to adjust the onset and/or peak location of an event that NeuroMatic has already detected.
Click this button to compute an event interval histogram, or a time histogram across data waves.
Events 2 Waves
Click this button to copy each event to a new wave, beginning with the prefix “Event”, which will automatically be added to NeuroMatic’s Wave-Prefix Select menu. Select the event prefix. You can now analyze all of the events. For example, compute averages of your events via the Main Tab, or rise/decay times using the Stats Tab.