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Module 2: Introduction to neural data types, file formats and preprocessing


  • Consider the common structure in diverse (neural) data sets
  • Understand how such data can be intuitively and efficiently represented in three custom MATLAB data types (ts, tsd, and iv)
  • Learn where to find commonly used utility functions that perform basic operations on these data types
  • Obtain a basic overview of the different file formats saved by a Neuralynx system (as an example)
  • Become aware of the pre-processing steps typically applied to raw data
  • Get to know the different files in a pre-processed (“promoted”) vandermeerlab data set, and their relationship to the raw data
  • Use the low-level and wrapped loading functions for all these files


Introductory remarks

Careful analysis of neural data begins with a thorough understanding of the raw data that is saved by your data acquisition system(s). However, raw data is only rarely suitable for analysis beyond a few quick checks. At a minimum, freshly acquired data sets typically must be annotated, and/or the files systematically renamed – for instance, with the ID of the experimental subject and some information about recording locations – so that the analyst can select which files to analyze, and combine results across sessions and subjects. More complex pre-processing steps include spike sorting (the process of assigning spike waveforms to putative single neurons to obtain their spike times), artefact removal, and many others.

Pre-processed data can be loaded into MATLAB, typically using code provided by the vendor, or perhaps by something created by the community. Either way, how you represent the data – what data types you use – has a major bearing on how effectively you can accomplish multiple principles of careful data analysis. Therefore, we will begin with a consideration of the general structure of neural data sets.

A word of warning and encouragement: this module is probably the least exciting of the tutorial, but it's important to get the fundamentals in place before we get to the more interesting parts.

Structure of (describing) neural data

Sampled signals

In general, data acquisition systems work by sampling (i.e. periodically taking a measurement of) some quantity of interest, such as the potential difference (voltage) between an electrode placed in a brain area of interest and a reference. That is, measurements of a signal are repeatedly taken, at some finite sampling rate, as the signal evolves over time. This kind of data is often referred to as time series data, and may look like this:

Time is shown on the horizontal axis (“abscissa”), and the value of this particular quantity (on the vertical axis, “ordinate”) is changing over time. At regular intervals – the inverse of the sampling rate (1 / Fs), to be precise – we obtain a measurement, indicated by the black dots. We are blind to any changes in between the samples, illustrated by the unbroken line. Obviously, this illustration shows a single signal, but many systems will record multiple signals simultaneously, such as an EEG system that records voltages from 256 scalp electrodes, or a rodent electrophysiology system that in addition to neural data also records the position of the animal, a video camera records a signal in each of many pixels, and so on.

The fact that we are dealing with sampled signals has some important consequences for data analysis, broadly captured by the term sampling theory, of which we will introduce a few in Module 5. The “Nyquist limit” and the “Moiré effect” (aliasing) are two well-known examples.

Point processes (timestamps)

Neuroscience attributes particular significance to action potentials, or “spikes”, which are typically understood as all-or-none events that occur at a specific point in time (hence the technical term, point process). To describe a train of spikes, it is not necessary to state all the times at which there was no spike: it suffices to maintain a list of those times (sometimes called timestamps) at which a spike train was emitted.

The same description works well for other quantities of interest which are essentially punctate events, such as delivery of a reward pellet, initiation of a key press, and so on.


Although uncommon in raw neural data, time intervals (epochs with a certain duration, rather than a point in time) commonly arise in some aspect of experimental procedures and analyses. Intervals describe occurrences that have start and end times, such as a trial of an experiment, the presence of a cue (e.g. a light or a tone), et cetera.

Together, these three types of data can describe most data sets encountered in neuroscience. Putting all three together in a simple visualization might look something like this:

At the top of the figure, you can see several rows containing point process data: the dots indicate spikes, one row per neuron. At the bottom, you see time series data (a local field potential), and the colored blocks show intervals with two different labels, indicated by the color.

☛ Now, think about one of your own experiments. How would you describe the data you collect? What quantities (signals) of interest are time series data, what are point processes, and what is best described as intervals?

Introduction to vandermeerlab data types

A data type is the computer science term for a standardized format of representing data. Classical data types include things like integers and floating-point numbers, but our data types of interest are essentially all MATLAB structs with particular constraints on field names and formats.

(Note for the connoisseurs: the choice to not implement these data types as MATLAB objects is deliberate.)

The three main data types are (1) timestamped data (TSD), (2) timestamps (TS), (3) and intervals (IV), discussed in turn below. Standardizing how we represent these data makes it possible for commonly used functions to be used on any data set – good for readability and robustness!

Timestamped data (TSD) data-type

As introduced above, a sampled signal is essentially a list of data points (values), taken at specific times. Thus, what we need to fully describe such a signal is two arrays of the same length: one with the timestamps and the other with the corresponding values. This is exactly what the timestamped data (TSD) data type is, as illustrated by the LoadCSC() function:

%% load data
cd('D:\Data\R016\R016-2012-10-08'); % same session as Module 1
cfg = [];
cfg.fc = {'R016-2012-10-08-CSC02d.ncs'}; % cell array with filenames to load
csc = LoadCSC(cfg);
>> csc
csc = 
     type: 'tsd'
     tvec: [5498360x1 double]
     data: [1x5498360 double]
    label: {'R016-2012-10-08-CSC02d.ncs'}
      cfg: [1x1 struct]

The TSD data type has the following fields:

  • type: string indicating data type, 'tsd'
  • tvec: nSamples x 1 double, timestamps (in seconds)
  • data: nSignals x nSamples double, values (units can be specified in cfg if needed)
  • label: nSignals x 1 cell array, filenames
  • cfg: content depends on specific data, but always has a history field. For CSC data, there is also hdr, ExpKeys, and SessionID.

Thus, the tvec field and the data field together define the sampled signal.

In the above example, we only loaded one .ncs file (a single local field potential, recorded from a specific electrode in the brain) and therefore there is only one label, containing the filename. To plot this data you can simply do plot(csc.tvec,

☛ Consider the tvec field in the struct above. If the sampling rate for a given signal is constant, is this field strictly necessary? Can you think of a way to describe such an idealized signal more efficiently (i.e. by taking up less memory)?

☛ How does LoadCSC() represent multiple, simultaneously acquired, signals? A nice way to do so is to use a config field like cfg.fc = FindFiles('*CSC01*.ncs');.

If at some point you want to construct a tsd variable yourself, you can do help tsd to see how. The tsd() function is a constructor for variables of type tsd. LoadCSC() calls this function to create an empty tsd template, and then fills it with data loaded from .ncs files; you can check if the result meets the specification by calling CheckTSD().

There are a number of functions that work with tsd data: some of these can be found in the tsd folder in the GitHub repository. Two other important ones you will meet in this module are restrict() and getd() (which also work on other data types, below).

Timestamp (TS) data-type

A different data type is needed to describe sets of punctate events (a point process in statistics), such as times of action potentials (spikes) or task events such as reward delivery times. For this we use the TS (timestamp) data type, defined as follows:

  • type: string indicating data type: 'ts'
  • t: nSignals x 1 cell array, timestamps (in seconds)
  • label: nSignals x 1 cell array, labels
  • usr: nSignals x nUsr double, optional additional data corresponding to intervals
  • cfg: content depends on specific data, but always has a history field.

An example is provided by the function LoadEvents(), which loads the timestamps of events used in this particular experiment (such as the delivery of reward pellets):

%% remember to use Cell Mode in the editor to run this code! 
cfg = [];
evt = LoadEvents(cfg);

>> evt

evt = 

     type: 'ts'
        t: {1x109 cell}
    label: {1x109 cell}
      cfg: [1x1 struct]

Note how several of the fields of the resulting evt struct are cell arrays.

Because we provided LoadEvents() with an empty config input, it by default loads the times of all events it can find. As you can see by the size of the cell arrays, there are 109 labels here. Let's look at some of them:

>> evt.label(1:3) % display first three labels
ans = 
    '1 or 5 pellet cue'    '1 pellet cue'    '1 pellet dispensed'

Taking the second label as an example, it describes an experimental event: the onset of a cue (tone in this case). The corresponding timestamps (in seconds) can be found in the second .t field:

>> evt.t{2}
ans =
   1.0e+03 *
  Columns 1 through 8
    1.1475    1.1533    1.1706    1.1798    1.2190    1.2255    1.2380    1.2435

These timestamps completely describe a point process (timestamp data).

☛ Why do you think the event times (in the .t field) are stored in a cell array, rather than in a matrix?

A way to address timestamps by label is provided by the getd() function:

plot(getd(evt,'1 pellet cue'),0,'.k') % retrieve times associated with 1 pellet cue and plot each time against zero

getd() also works for tsd data. Try plotting a specific channel this way.

A different function that loads data into a ts data type is LoadSpikes(). Try it:

S = LoadSpikes([])

Notice how instead of creating an empty config variable and passing it as an input, I now just passed an empty array [] as an input directly. This instructs LoadSpikes() to load all spike files it can find. As you can see from the labels, two different files were loaded: as will be explained below. *.t indicates a file containing spike times from one neuron.

☛ How many spikes did the second neuron emit in this session?

As with tsd data above, you can call the ts constructor ts() to start with a template that you can then fill with data if you want to build your own. The ts folder on GitHub contains some other utility functions that work with timestamp data.

Interval (IV) data-type

Interval data – matched sets of start and end times – is typically not loaded directly from data files. However, it commonly comes up during analysis, for instance when defining trials, running vs. resting epochs, sharp wave-ripple complexes, et cetera.

Interval data is defined as follows:

  • type: string to indicate data type, 'iv'
  • tstart: nIntervals x 1 double, interval start times (in seconds)
  • tend: nIntervals x 1 double, end times (in seconds)
  • usr: nIntervals x nUsr double, optional additional data corresponding to intervals
  • cfg: content depends on specific data, but always has a history field.

Some common ways of creating an iv object from scratch are the following:

>> a = iv([1 2]) % define a single interval from 1 to 2
a = 
      type: 'iv'
    tstart: 1
      tend: 2
       usr: []
       cfg: [1x1 struct]
>> b = iv([1 2],[3 3]) % define two intervals, 1 to 3 and 2 to 3
b = 
      type: 'iv'
    tstart: [2x1 double]
      tend: [2x1 double]
       usr: []
       cfg: [1x1 struct]

There are a number of useful functions available that work with interval data. One of the most useful ones is TSDtoIV() which will be demonstrated below. The iv folder on the codebase has a number of functions whose functions you can guess from their names, for instance, IntersectIV() computes the intersection between two sets of intervals (i.e. output only those intervals in A which overlap with intervals in B).

Data files overview

Our next goal is to learn about the different kinds of data and associated information that make up a typical neural recording session (as an example, we will use Neuralynx data; obviously the details will be different for other systems), and to meet the various loading functions that will enable you to access them in the data type formats introduced above.

Make sure you have the data session R042-2013-08-18 from the shared drive, and that this is placed in a sensible location (NOT in a GitHub or project folder! See Module 1 if this is not obvious). This folder contains data from a single recording session that has been pre-processed so that it is ready for analysis. Such a pre-processed data set is referred to as “promoted”; raw data that has just been recorded is “incoming”, data being pre-processed is “inProcess”. The schematic below (drawn using the dot tool in GraphViz) gives an overview of the major data files and their transformation during pre-processing:

The files you find in a promoted folder such as R042-2013-08-18 are those enclosed in the gray box. They are:

  • Each .ncs file (“Neuralynx Continuously Sampled”) contains a single channel of continuously sampled voltage data. The sampling rate and filters for these channels can be configured in the Cheetah data acquisition software. Typically, as in this data set, the sampling rate and filters are set so that these files are local field potentials (LFPs) sampled at 2kHz and filtered between 1 and 475 Hz. It is also possible to have wide-band, 32kHz .ncs files suitable for spike extraction, but these are not included in the current dataset. (We will discuss filtering in a subsequent module.)
  • Each .t file contains a set of times – a spike train from a putative neuron. The qualifier “putative” is used because this is extracellular data and spike-sorting is not perfect, so it's likely there will be some spikes missing and some spikes included that are not from this neuron. Always remember this even if I will omit the “putative” from now on for short! *.t files are generated by MClust, a spike sorting tool developed by A. David Redish, from the raw *.ntt (“Neuralynx TeTrode”) files saved by Neuralynx. *.ntt files do not contain continuously sampled data; instead, a one-millisecond snapshot across the channels of a tetrode is stored whenever any of the four channels exceeds a threshold set in Cheetah by the experimenter.
  • The *.nvt file (“Neuralynx Video Tracking”) contains the location of the rat as tracked by an overhead camera. For Neuralynx systems, this is typically sampled at 30 Hz. Because the raw files are large, they are usually stored in compressed (zip) format. The .nvt files are in units of camera pixels (typically 640×480).
  • The *.Nev file (“Neuralynx EVents”) contains timestamps and labels of events, such as those input by the user during recording, received from experimental components connected to Neuralynx's digital I/O (Input/Output) port, and system messages such as recording start, data loss, et cetera.

A critical part of any promoted data set is the following:

  • The *keys.m file, referred to as “ExpKeys” or “keys”. This file contains experimenter-provided information that describes this data set. This information is stored as a .m file so that it can be edited and read by standard text editors (rather than having to be loaded into MATLAB to view, as would be the case for a .mat file). This file and the correct format for ExpKeys is explained in more detail here.
  • The *metadata.m file, which like the ExpKeys contains descriptive information about the data set, such as start and end times of individual trials, but that is not desirable or practical to include in the ExpKeys file. See here for guidelines on what should go in ExpKeys versus metadata.

Next, we have:

  • *wv.mat files. There is one file for each *.t file, containing the average waveforms for that cell.
  • *ClusterQual.mat files. Also, one file for each *.t file, containing some cluster quality statistics.

Both of these files are generated by a MATLAB script (CreateCQFile.m) or directly from MClust version 4.1 or higher.

Finally, there is also:

  • the *vt.mat file. This contains the position data in tsd format (see above for a description of data types), after potential position artifacts have been removed, and the raw camera pixel units have been converted to centimeters.

:!: NOTE: Some older data sessions may not have this conversion to centimeters done. What units the video data are in is not crucial for this tutorial, but in general it is a good idea to be aware of what these units are!

☛ Look at the contents of the R042-2013-08-18 folder.

Notice how each file is named: all start with R042-2013-08-18 followed by a suffix indicating the file type and (if necessary) an identifier. Applying this naming scheme consistently is a key part of good data management because it enables provenance tracking – which cells from what animal, what session, and what condition are contributing to each plot, et cetera. The rename steps in the above schematic are an important first step.

Using the low-level data loading functions

Neuralynx supplies a set of functions that load the raw data into MATLAB (included in your GitHub clone). We will use these one by one in the following subsections. A common theme is that all of these functions will output a Timestamps variable, indicating when each data sample or event occurred. Data acquisition systems need to solve the engineering challenge of aligning many different kinds of signals (video, neural activity, events) on a common timebase, so that relationships between them can be analyzed. These Timestamps are what ties the different data files together. By default, Neuralynx data loaders return timestamps in microseconds (us).

Before getting started, create a folder with today's date in your project folder, and create a new file in it named sandbox.m. These sandbox files are not meant to be re-used or committed to GitHub – as the name indicates, they are just a temporary file that is easier to work with compared to typing everything directly into the MATLAB Command Window.

Next, make sure that your path is set correctly using a Shortcut button. Also, set MATLAB's current directory to the data folder (R042-2013-08-18); you can do this either using the MATLAB GUI (I often paste from Explorer into MATLAB) or by using the cd command.

All instructions that follow should be pasted into a cell in this sandbox file and executed from there (Ctrl-Enter when a cell is selected), unless they are prefaced with » to indicate the Command Prompt.

Position data (*.nvt) loading

The low-level loading function for video data is Nlx2MatVT. Deploy it as follows:

%% load video data (make sure the file is unzipped first and now present in MATLAB's working folder!)
[Timestamps, X, Y, Angles, Targets, Points, Header] = Nlx2MatVT('VT1.nvt', [1 1 1 1 1 1], 1, 1, [] );

The abundance of ones in the function call are basically saying, “load everything” (type help Nlx2MatVT for the gory details). Notice that the output arguments (with the exception of the Header) share a common dimension:

>> whos
  Name              Size                    Bytes  Class     Attributes
  Angles            1x131898              1055184  double              
  Header           28x1                      4262  cell                
  Points          400x131898            422073600  double              
  Targets          50x131898             52759200  double              
  Timestamps        1x131898              1055184  double              
  X                 1x131898              1055184  double              
  Y                 1x131898              1055184  double              

We appear to have 131898 samples of “X” and “Y”, the main variables of interest, with corresponding timestamps. We can plot X against Y:

>> plot(X,Y);

to get:

You can see the outline of a modified T-maze used for this recording session (rotated 90 degrees). Notice that this way of plotting the position data reveals something strange going on: there are many abrupt jumps to the (0,0) position! As it turns out, these are Neuralynx's way of indicating missing data (samples on which no position data could be acquired).

☛ Plot X against Y again, but this time without the missing data. A good way of doing this is to first define a variable keep_idx that contains the indices of those samples which you want to keep (i.e. that are not (0,0)).

Inspect the resulting plot. The shape of the T-maze is now more clear; also visible are two roughly circular areas. These are the “pedestals” on which the rat can relax at the beginning and end of the recording session, as well as in between trials (if you want more details about what is going on this task, see here).

I plotted my version as follows:

%% plot video data -- use a new cell so that you can rerun this without also reloading the data
fh = figure; set(fh,'Color',[0 0 0]);
plot(X(keep_idx),Y(keep_idx),'.','Color',[0.7 0.7 0.7],'MarkerSize',1); axis off;

The first line opens a new figure, and uses its handle to set the background to black. The second line uses additional arguments for plot() to plot the X and Y data points not as a connected line, but as individual points of size 1 in a gray color. The result:

It is useful to know how to save figures to a format that is easy to view:

set(gcf, 'InvertHardCopy', 'off');

The first line is necessary to preserve the black background. The second line saves a 75dpi PNG image. PNG is a good choice for saving MATLAB images, because it uses lossless compression and therefore will not cause ugly artifacts the way JPEG will.

Let's look at the Timestamps next, by plotting the X data as a function of time:

box off;

Note the use of some different plotting options here, to give:

The horizontal axis is still in Neuralynx's raw data units (us).

☛ Convert the Timestamps to seconds, and replot.

If you look closely, you can spot some gaps in the data (times when no position data is plotted).

☛ (Optional exercise to test your MATLAB skills) Are these gaps because of (0,0) samples that have been removed? Or because there are no records in the data for those times?

As you should have ascertained, there are in fact two short gaps in the data. These occur on purpose to separate behavior on the T-maze (when you can see the X coordinate changing as the rat runs) from the times when the rat is resting on the pedestal. In the Cheetah software this can be done by simply turning off Recording and then turning it back on. (Sneak preview: although doing this is helpful for some applications, it can be problematic for analyses that assume your data is continuous. We will encounter this when we start using the FieldTrip toolbox later.)

☛ Determine the video tracker sampling rate from the Timestamps variable. Watch out for gaps in the data! (Hint: the diff() function is useful here!)

This concludes the introduction to Neuralynx video data. The other outputs of Nlx2MatVT are not used for typical analyses.

LFP data file (*.Ncs) loading

The Neuralynx loader for Ncs files is Nlx2MatCSC. Use it thusly:

clear all;
fname = 'R042-2013-08-18-CSC05a.ncs';
[Timestamps, ~, SampleFrequencies, NumberOfValidSamples, Samples, Header] = Nlx2MatCSC(fname, [1 1 1 1 1], 1, 1, []);

..and inspect the result:

>> whos
  Name                        Size                  Bytes  Class     Attributes
  Header                     33x1                    5182  cell                
  NumberOfValidSamples        1x17193              137544  double              
  SampleFrequencies           1x17193              137544  double              
  Samples                   512x17193            70422528  double              
  Timestamps                  1x17193              137544  double              
  fname                       1x9                      18  char           

Now we get only 17193 Timestamps, a surprising number because it is substantially less than the number of video tracking timestamps we got (on the order of 10 times less), even though the video tracking data was only sampled at about 30 Hz, and this LFP data is supposed to be sampled at something like 2kHz! As it turns out, Neuralynx Ncs data is stored in blocks of 512 samples, with only the first sample of each block timestamped. Hence the [512 x 17193] size of Samples, which contains the actual time-varying voltage signal. This is not a very convenient format for plotting timestamps against voltage, the way we typically would like to do. This is one reason why we generally don't use these low-level loading functions, but instead wrap them in a function that is more user-friendly. These loading functions are discussed in the next section.

For now, one more point about this data: Samples is not in units of volts, but on a scale internal to the Neuralynx system. To know how these “A-D bits” (analog-to-digital) correspond to real voltages, we need to look in the Header:

>> Header
Header = 
    '######## Neuralynx Data File Header'
    '## File Name C:\CheetahData\2013-08-18_09-06-16\CSC49.ncs'
    '## Time Opened (m/d/y): 8/18/2013  ( 9:6:36.546'
    '## Time Closed (m/d/y): 8/18/2013  ( 10:26:2.875'
    '-FileType CSC'
    '-FileVersion 3.3.0'
    '-RecordSize 1044'
    '-CheetahRev 5.6.3 '
    '-HardwareSubSystemName AcqSystem1'
    '-HardwareSubSystemType DigitalLynxSX'
    '-SamplingFrequency 2000'
    '-ADMaxValue 32767'
    '-ADBitVolts 0.000000061037020770982053'
    '-AcqEntName CSC49'
    '-NumADChannels 1'
    '-ADChannel 80'
    '-InputRange 2000'
    '-InputInverted True'
    '-DSPLowCutFilterEnabled True'
    '-DspLowCutFrequency 1'
    '-DspLowCutNumTaps 0'
    '-DspLowCutFilterType DCO'
    '-DSPHighCutFilterEnabled True'
    '-DspHighCutFrequency 475'
    '-DspHighCutNumTaps 128'
    '-DspHighCutFilterType FIR'
    '-DspDelayCompensation Disabled'
    '-DspFilterDelay_µs 1984'

Aha, the -ADBitVolts entry gives us the conversion from the raw data to volts. Another reason to wrap this lowlevel function into something that does the conversion for us! As you can see, the header contains some other information, which will be discussed in more detail in later modules.

Event file (*.Nev) loading

*.Nev (Neuralynx Event) files contain timestamps of various task events. Use as follows:

fn = FindFile('*Events.nev');
[EVTimeStamps, EventIDs, TTLs, EVExtras, EventStrings, EVHeader] = Nlx2MatEV(fn,[1 1 1 1 1],1,1,[]);

As before, all the ones in the function call make sure we load everything. In return, we get:

>> whos
  Name                Size              Bytes  Class     Attributes
  EVExtras            8x462             29568  double              
  EVHeader           12x1                1924  cell                
  EVTimeStamps        1x462              3696  double              
  EventIDs            1x462              3696  double              
  EventStrings      462x1              103104  cell                
  TTLs                1x462              3696  double              
  fn                  1x44                 88  char  

Each of the 462 events in this file has a timestamp (EVTimeStamps) and a description (EventStrings) as well as some other information we generally don't need. Let's inspect some of the EventStrings:

>> EventStrings(1:13)
ans = 
    'Starting Recording'
    'Stopping Recording'
    'Starting Recording'
    'TTL Input on AcqSystem1_0 board 0 port 1 value (0x0020).'
    'TTL Input on AcqSystem1_0 board 0 port 1 value (0x0000).'
    'TTL Input on AcqSystem1_0 board 0 port 1 value (0x0020).'
    'TTL Input on AcqSystem1_0 board 0 port 1 value (0x0000).'
    'TTL Input on AcqSystem1_0 board 0 port 1 value (0x0080).'
    'TTL Input on AcqSystem1_0 board 0 port 1 value (0x0000).'
    'TTL Output on AcqSystem1_0 board 0 port 0 value (0x0004).'
    'TTL Input on AcqSystem1_0 board 0 port 1 value (0x0080).'
    'TTL Output on AcqSystem1_0 board 0 port 0 value (0x0000).'
    'TTL Input on AcqSystem1_0 board 0 port 1 value (0x0000).'

The meaning of these cryptic strings depends on the specific experimental setup. “AcqSystem1_0 board 0 port 0” and “1” refer to connectors on the Neuralynx data acquisition mainbox, which can be hooked up to various experimental peripherals such as photobeams, levers, and pellet dispensers.

In this session, Input/Output (I/O) Port 0 was configured as Output, controlling a pellet dispenser and a valve (for sucrose solution delivery). Port 1 was set to be an Input, receiving inputs from three photobeams (one on the central stem of the maze, and one each for each reward site on either end of the maze arms). The EventStrings above refer to the status of an I/O port, represented as a hexadecimal number (indicated by the prefix “0x”). The activation of each peripheral is associated with a unique number.

As with the previous low-level loading functions, the Neuralynx loader does not provide us directly with what we want. We'd like a loader that just gives us the times for the events we are interested in, without us having to figure out what hexadecimal number they correspond to and then pull out the matching times. These wrapped loaders will be introduced below.

☛ (Optional exercise to test your MATLAB skills) Find out which EventString corresponds to which input or output (food pellet reward on left arm, sucrose water reward on right arm, left reward photobeam, right reward photobeam, central stem photobeam) by plotting the location of the animal at the time of each event.

Hint: example pseudocode for a nice approach to find this out would look like the following:

get list of unique event strings to process -- unique()

for each event string
  find indices of events that match current event string -- strncmp()
  get timestamps for matched events
  find indices of position timestamps that are closest in time -- nearest_idx()
  get x and y coordinates of closest timestamps
  plot x and y coordinates on top of position plot


Using the wrapped data loaders

You have already seen examples of TSD and TS data types returned by some loading functions. The full set used for Neuralynx data in this course follows below. You will notice that each loading function takes in a cfg (“configuration”) variable, which is used to specify parameters and options such as the filenames to be loaded. This use of cfg variables is shared by many other vandermeerlab data analysis functions (as well as those in the FieldTrip toolbox), and is highly encouraged when you start writing your own code: it encourages well-organized code and enables provenance tracking, two principles of good programming practice.

To find out what cfg options are used by a given function, use the help (or doc) function on each data loader, e.g. doc LoadCSC. Some functions will run using default options when you pass an empty cfg ([]), whereas others will require you to input something.


This loads raw Neuralynx position data (*.nvt). If no filename is specified in the input cfg, LoadPos() checks if a single .Nvt file is found in the current directory and loads that one:

>> posdata = LoadPos([]); % note empty config
LoadPos.m: 100.00% of samples tracked.
>> posdata
posdata = 
     type: 'tsd'
     tvec: [1x131898 double]
     data: [2x131898 double]
    label: {'x'  'y'}
      cfg: [1x1 struct]

Note that LoadPos() provides some basic information on the quality of the data (percentage of samples tracked) – consistent with the "garbage in, garbage out" principle, this helps ensure that you are aware of any potential issues at the raw data stage.

Because the .Nvt files are large, it is often convenient to save this posdata variable as a .mat file. This should be named Rxxx-yyyy-mm-dd-vt.mat (for mice, remember to replace R with M).

Note that the data field now has dimensionality [2 x nSamples]; this is because there is both x and y data as indicated by the label field. So, if you wanted to plot x against y, you could do plot(,:),,:),'.');, but a more general approach that doesn't require knowing which variable is which dimension is plot(getd(posdata,'x'),getd(posdata,'y'),'.');.


To load a .Ncs file, containing sampled data (a hippocampal local field potential in this case):

cfg = []; % starting with an empty config is good practice -- that way you avoid carryover of previous values!
cfg.fc = {'R042-2013-08-18-CSC05a.ncs'};
csc = LoadCSC(cfg);

This gives the following struct of type tsd:

>> csc
csc = 
     type: 'tsd'
     tvec: [8802816x1 double]
     data: [1x8802816 double]
    label: {'R042-2013-08-18-CSC05a.ncs'}
      cfg: [1x1 struct]

Note that the format is the same as for the position data above; this is because both LoadPos() and LoadCSC() return TSDs.

LoadCSC() outputs some information about the files being loaded; in particular the number of “bad blocks”. These will be explored in Module 3 (short version: bad blocks indicate a problem with the recording system and should be fixed).

Finally, the cfg field has the ExpKeys, the SessionID (R042-2013-08-18), the headers (.hdr) for each .Ncs file, and the history.


By default, LoadEvents() returns a TS with the labels and timestamps of all unique strings found in the EventStrings:

>> evt = LoadEvents([])
evt = 
     type: 'ts'
        t: {1x9 cell}
    label: {1x9 cell}
      cfg: [1x1 struct]

evt.label(:) will reveal the familiar list of events introduced above. However, by using the cfg file, we can get something more specific:

cfg = [];
cfg.eventList = {'TTL Output on AcqSystem1_0 board 0 port 0 value (0x0004).','TTL Output on AcqSystem1_0 board 0 port 0 value (0x0040).'};
cfg.eventLabel = {'FoodDelivery','WaterDelivery'};
evt = LoadEvents(cfg)
evt = 
     type: 'ts'
        t: {[1x9 double]  [1x9 double]}
    label: {'FoodDelivery'  'WaterDelivery'}
      cfg: [1x1 struct]

By specifying which EventString is associated with which human-readable event ('FoodDelivery','WaterDelivery') we now have a more user-friendly events variable. Of course, this requires knowing how these events map onto the event codes (given here in cfg.eventList) generated by the system. Make sure that you know what the event codes generated by your system mean!


LoadSpikes() loads spike trains (times of action potentials) in *.t files. By default, it loads all such files:

>> S = LoadSpikes([])
S = 
     type: 'ts'
        t: {1x67 cell}
    label: {1x67 cell}
      cfg: [1x1 struct]
      usr: [1x1 struct]

As you can see, this loaded spike data from 67 neurons. The usr field by default contains the tetrode number from which each spike train was recorded; this behavior can be disabled by setting cfg.getTTnumbers = 0. If you wish to load *._t files (containing spikes from neurons of questionable cluster quality), do cfg.load_questionable_cells = 1;. See the function documentation for further options.


The other files of interest are all MATLAB .mat files which can be loaded directly using the load() function.

Putting it all together

Here are two examples that illustrate some simple operations you are now equipped to do. You should run them and make sure you understand what is happening – how raw data is transformed by some simple steps:

%% example 1: use of restrict()
pos = LoadPos([]);
left_pos = restrict(pos,metadata.taskvars.trial_iv_L); % left trials only
plot(getd(left_pos,'x'),getd(left_pos,'y'),'.'); % looks like right trials! camera reverses image, can fix with set(gca,'YDir','reverse')
%% example 2: interplay between tsd and iv data
please = []; please.fc = ExpKeys.goodSWR(1); % local field potential with good "sharp wave-ripple" events
lfp = LoadCSC(please); % aacarey is Canadian and asks nicely; cfg name is just arbitrary
% detect possible artifacts
cfg = [];
cfg.method = 'zscore'; % first normalize the data
cfg.threshold = -8;
cfg.minlen = 0; % no minimum length on events to detect
cfg.dcn = '<'; % detect intervals with z-score lower than threshold
artifact_iv = TSDtoIV(cfg,lfp); % creates iv with start and end times of possible artifacts
% plot detected intervals
cfg = []; cfg.display = 'tsd'; % also try 'iv' mode!

☛ (Optional exercise to test your understanding) Use the function IntersectIV() to only keep potential artifacts that occur when the rat's x-position is larger than 300.

NOTE: if you are on a Mac, you might get an error related to the nearest_idx3 function; you can fix that for now by changing this to nearest_idx in the PlotTSDfromIV function.


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Garnet and Ludongling Bracelet 本物と同じプラダサングラスコピー

スーパーコピーブランドサイト, 2021/01/03 00:02

China Wood Burning Stove N級品ブルガリサングラスコピー

サンローラン靴コピー販売店, 2021/01/03 03:00

Prefab Container House オーデマピゲ時計スーパーコピー

ディオールブレスレットコピー店舗, 2021/01/03 04:42

China Astro Turf For Gardens Prices ディオールブレスレットスーパーコピー販売店

フェラガモ靴スーパーコピー, 2021/01/03 06:20

Oblique Photogrammetry ブランドコピー激安通販

Finger Vibrator Sex Toy, 2021/01/03 08:02

ルイヴィトン帽子コピー通販店 Finger Vibrator Sex Toy

Foam Case Inserts, 2021/01/03 09:03

シャネルバッグコピー優良サイト Foam Case Inserts

Industrial Tyre Factory, 2021/01/03 14:14

N級品クロムハーツブレスレットコピー Industrial Tyre Factory

ブランドネックレスコピーサイト, 2021/01/03 16:13

Leather Stationery Factory クロムハーツ指輪スーパーコピー激安

Extension Socket Price, 2021/01/03 18:12

バーバリー靴コピー通販店 Extension Socket Price

Ginseng Extract Price, 2021/01/03 18:54

ブレゲ時計コピー Ginseng Extract Price

Hengda New Materials (Fujian) Co., Ltd., 2021/01/03 22:34

ルイヴィトン帽子スーパーコピー Hengda New Materials (Fujian) Co., Ltd.

N級品ボッテガヴェネタ靴コピー, 2021/01/04 12:14

贝博足彩 シャネル時計コピー

エルメスバッグコピー代引き, 2021/01/04 18:13

欧美性爱视频 ブランドコピーn級とは

アレキサンダーマックィーン靴スーパーコピー激安, 2021/01/04 18:57

Colorful Pillowcase ジバンシィバッグコピー国内発送

ジャガールクルトレベルソコピー, 2021/01/05 02:23

5211 Bearing ジャガールクルトレベルソスーパーコピー

Din Rail Mount Ethernet Switch, 2021/01/05 12:22

ルイヴィトン長財布偽物 Din Rail Mount Ethernet Switch

ブランドピアスコピー代引き, 2021/01/05 14:20

Air-Cooled Indirect Cooling ディオールベルトコピー

70mm Diameter Tube, 2021/01/05 16:14

IWCパイロットウォッチコピー 70mm Diameter Tube

スーパーコピーブランドn級, 2021/01/05 18:09

Ferrite Ring Magnet Or Ndfeb Ring Magnet シャネル指輪コピー品

ウブロクラシックフュージョンコピー, 2021/01/05 18:55

Copper Tube Terminal Cable Lug ウブロクラシックフュージョンコピー

ブランドディオール靴コピー, 2021/01/06 08:11

1/2 driver socket set スーパーコピー時計防水

iphonexrケースブランドコピー, 2021/01/06 14:13

Electronic Hotel Safe Deposit Box With Digital Lock カルティエネックレスブラントコピー代引き

Enjo Sports Inc., 2021/01/07 08:25

Q13210 Enjo Sports Inc.

Geared Transmission Price, 2021/01/07 10:26

シャネルケースコピー激安 Geared Transmission Price

ブランドブライトリング時計コピー, 2021/01/07 14:29

Home Display Equipment Price ブランド指輪コピー通販店

Lady Fashion Apparel Price, 2021/01/07 16:19

タグホイヤーアクアレーサーコピー Lady Fashion Apparel Price

China Pipe Equipment Manufacture, 2021/01/07 18:09

クロエサングラスコピー通販店 China Pipe Equipment Manufacture

オメガコンステレーションレプリカ, 2021/01/07 18:53

Air Suspension Shock オメガコンステレーション偽物

フランクミュラートノウカーベックススーパーコピー, 2021/01/08 12:45

Face Coin Bank フランクミュラートノウカーベックス偽物

トッズ靴コピー店舗, 2021/01/08 14:49

13676-91-0 ブランド帽子スーパーコピーN級品

301CT130RX, 2021/01/08 16:56

4 Pvc Gate Valves 301CT130RX

CAR2013FC6313, 2021/01/09 06:34

Assembly Line Reflow Soldering Oven タグホイヤーカレラ偽物

Aluminum Screen Printing Frame, 2021/01/09 08:28

N級品ルイヴィトン時計コピー Aluminum Screen Printing Frame

Ethyl-2 Anthraquinone, 2021/01/09 14:11

本物と同じロジェヴィヴィエ靴コピー Ethyl-2 Anthraquinone

Fuel Pump And Heating Control Relay, 2021/01/09 18:17

本物と同じセリーヌバッグコピー Fuel Pump And Heating Control Relay

Sintered Filter For Filtration, 2021/01/09 20:06

ロレックスデイトジャストコピー Sintered Filter For Filtration

グッチベルトコピー, 2021/01/09 20:49

Car Wash Equipment フェンディサングラススーパーコピー

China Ion Exchange Resin, 2021/01/10 00:02

N級品カルティエ指輪コピー China Ion Exchange Resin

Badminton Training Equipment, 2021/01/10 02:21

プラダバッグコピー Badminton Training Equipment

KT Other Brand Diesel Generator Supplier, 2021/01/10 04:40

プラダベルト偽物 KT Other Brand Diesel Generator

116231G, 2021/01/10 06:25

China Washable Wipes ロレックスデイトジャスト偽物

Small Lazy Susan Bearing, 2021/01/10 08:09

ブルガリネックレススーパーコピー代引き Small Lazy Susan Bearing Supplier

ウブロビッグバンスーパーコピー, 2021/01/10 10:13

China Boxes For Sweets ウブロビッグバン偽物

China 22060 Ac Fan, 2021/01/10 12:32

スーパーコピー時計専門店口コミ 22060 Ac Fan

332/LQWLMD/D31, 2021/01/10 14:36

Stainless Steel Glass Balustrade 332/LQWLMD/D31

1 Inch Tubing Baja, 2021/01/11 18:19

オメガコンステレーションレプリカ 1 Inch Tubing Baja

在线赌场游戏, 2021/01/11 22:35

iphone11ケースブランドコピー楽天 赌厅网投

シャネル財布スーパーコピー, 2021/01/12 04:57

日本性爱直播 カルティエネックレスコピー

Shipping Warmer, 2021/01/12 08:04

セリーヌ靴コピー Shipping Warmer

Hard Plastic Shredder, 2021/01/12 18:26

ロレックスデイトジャスト偽物 Hard Plastic Shredder

クロエサングラススーパーコピー販売店, 2021/01/12 20:12

Glass Cutting Table Machine クロエサングラススーパーコピー販売店

ステラマッカートニーバッグコピー店舗, 2021/01/13 00:30

Custom Silicone Rubber Strip スーパーコピーブランドyamada

高品質シャネルストールコピー, 2021/01/13 05:00

12 Oz Coffee Bags With Valve ディオールストールコピー優良サイト

カルティエバロンブルーコピー, 2021/01/13 12:02

Dmx Rgb Led Wall Washer WE900151

Natural Face Cleanser, 2021/01/13 14:11

スーパーコピーブランド専門店口コミ Natural Face Cleanser

Cosmetic Makeup Brushes, 2021/01/13 16:13

シャネルJ12コピー Cosmetic Makeup Brushes

パネライ時計スーパーコピー, 2021/01/13 20:56

5.0 Inch Ips Tft コピーブランド口コミ

ピアジェ偽物, 2021/01/14 12:52

Ankle Brace Packaging Supplier ピアジェ時計コピー

Angle Bar With Holes, 2021/01/15 04:51

WF9006Y7 Angle Bar With Holes

Pallet Box, 2021/01/15 12:52

オメガシーマスター最高品質時計 Pallet Box

Hollow Pc Price, 2021/01/15 18:18

カルティエコピー Hollow Pc Price

カルティエブレスレット偽物, 2021/01/16 08:32

澳门博狗 グッチベルトコピー国内発送

欧美性爱视频, 2021/01/16 14:16

12315246005003 日本AV性爱电影 http://www.ascentet.comsex/1382/

Micro Switch 12v, 2021/01/16 18:29

509103 Micro Switch 12v

ガガミラノ偽物, 2021/01/16 20:59

Poly Mailers 603603

ブランドコピーtシャツ, 2021/01/17 02:09

Floor Protect Sheets タグホイヤー時計スーパーコピー通販店

ディオールブレスレットブラントコピー代引き, 2021/01/17 04:41

Insulating Glass Production Machine エルメスピアススーパーコピー激安

ブライトリング時計ブラントコピー代引き, 2021/01/17 08:31

Seismic Support For Cable Tray エルメスブレスレットスーパーコピー

Fcc Dl-Methionine, 2021/01/17 16:23

オーデマピゲロイヤルオークコピー Fcc Dl-Methionine

シャネルバッグ偽物, 2021/01/18 16:01

Ductile Iron Gate Valves Chanelバッグコピー

セイコープロスペックスレプリカ, 2021/01/19 04:52

Ac Condenser Fan Blowing Cold Air セイコープロスペックス偽物

Herb Grinder Amazon, 2021/01/19 18:37

タグホイヤーカレラコピー Herb Grinder Amazon

グッチ財布偽物, 2021/01/20 07:00

15m3/h Mobile Concrete Mixer With Pump 402724KU2IN8693

シャネル財布スーパーコピー, 2021/01/20 12:51

Explosives Detector A48980

赌厅网投, 2021/01/20 15:00

IWC最高品質時計 欧美牲交AⅤ

日本AV性爱电影, 2021/01/20 18:54

YA101505 欧美牲交AⅤ

セイコーグランドセイコーコピー, 2021/01/20 20:35

欧美牲交AⅤ SBGV009

Recycle Girl Down Jacket, 2021/01/21 01:22

ロレックスETA2824-2搭載 Recycle Girl Down Jacket

Eva Outsole Automatic Machine, 2021/01/21 02:28

セリーヌ財布コピー Eva Outsole Automatic Machine

CHLOE財布コピー, 2021/01/21 06:33

90 Ball Valve CHLOE財布コピー

ジラールペルゴ偽物, 2021/01/22 06:48

Suede Fabric Lining Leather For Shoes Lining ジラールペルゴコピー

Tumblers Cups Mugs, 2021/01/22 18:57

116523NR Tumblers Cups Mugs

Angle Steel Flange Production Line, 2021/01/23 00:36

CBG2A1ZBA0658 Angle Steel Flange Production Line

China Autism Awareness Lapel Pin, 2021/01/23 06:39

フランクミュラーロングアイランドスーパーコピー China Autism Awareness Lapel Pin

ジャガールクルトレベルソコピー, 2021/01/23 08:47

Hotel Collection Bedding Duvet Covers ジャガールクルトレベルソコピー

グッチマフラーコピー, 2021/01/23 12:10

China 15kw 1000v Acdc Charging Power Module グッチマフラーコピー

ユリスナルダンマリーンクロノメーター偽物, 2021/01/23 14:36

China Amazon To Shopify Dropshipping 1183-126/42

PFC528-1010302-HA1442, 2021/01/23 16:49

Cosmetic Lotion Pump パルミジャーニフルーリエ偽物

IWCポルトギーゼ最高品質時計, 2021/01/23 20:42

China Modern Medical Bed For Hospital IWCポルトギーゼコピー

エルメス財布?小物, 2021/01/23 22:23

Essential Amino Energy スーパーコピーエルメス

Machinery Engine, 2021/01/24 06:15

ハミルトン時計コピー Machinery Engine

スーパーコピープラダ, 2021/01/24 14:21

Glass Candle プラダ財布?小物

Hotel Adult Toothbrush Price, 2021/01/24 16:26

スーパーコピープラダ Hotel Adult Toothbrush Price

409154-5, 2021/01/25 04:57

贝博足彩 グッチバッグ

欧美牲交AⅤ, 2021/01/25 08:49

スーパーコピーロレックス 欧美牲交AⅤ

日本AV性爱电影, 2021/01/25 12:21

スーパーコピーカルティエ 日本AV性爱电影

Professional Video Lighting Kits, 2021/01/25 14:35

ティファニー偽物 Professional Video Lighting Kits

75 Kva 3 Phase Generator, 2021/01/25 16:48

スーパーコピージュエリー 75 Kva 3 Phase Generator

Electrolysis Of Salt Water, 2021/01/25 18:47

M60002 Electrolysis Of Salt Water

プラダ財布コピー, 2021/01/26 00:37

Corten Steel Price Per Kg PRADA財布コピー

スーパーコピープラダ, 2021/01/26 06:12

Extruder スーパーコピープラダ

10 Ton Rough Terrain Crane, 2021/01/26 20:56

スーパーコピールイ?ヴィトン 10 Ton Rough Terrain Crane

Cavitation Rf Slimming, 2021/01/27 06:15

PRADAバッグコピー Cavitation Rf Slimming

High Pressure Brass Car Wash Water Spray Gun, 2021/01/27 12:22

バレンシアガ財布?小物 High Pressure Brass Car Wash Water Spray Gun

カルティエ時計, 2021/01/27 18:28

Glass To Glass Hinge スーパーコピーカルティエ

Flush Mounted Floor Power Outlets Supplier, 2021/01/28 08:46

スーパーコピーグッチ China Flush Mounted Floor Power Outlets

Cost Of Led Sign Boards, 2021/01/28 12:01

プラダサングラスコピー Cost Of Led Sign Boards

3in Pipe Clamp, 2021/01/28 16:26

プラダバッグ偽物 3in Pipe Clamp

Plastic Circuit Board, 2021/01/28 18:31

ルイ?ヴィトン財布?小物 Plastic Circuit Board

High Speed Handpiece Price, 2021/01/29 04:04

スーパーコピーエルメス High Speed Handpiece Price

Collapsible Wheelchairs For Sale, 2021/01/29 16:08

ブルガリブルガリブルガリレプリカ Collapsible Wheelchairs For Sale

Laser Engraving Machine For Plastic, 2021/01/29 18:13

A222G17NP Laser Engraving Machine For Plastic

Sand Dredge Pump, 2021/01/30 06:26

パネライラジオミール偽物 Sand Dredge Pump

5ton Slurry Ice Machine, 2021/01/30 06:59

プラダ財布スーパーコピー 5ton Slurry Ice Machine

Filter, 2021/01/30 18:37

フェンディバッグコピー Filter

Gfrc Admix, 2021/01/30 22:03

ブライトリングクロノマットコピー Gfrc Admix

パネライ時計, 2021/01/31 02:15

Children Disposable Face Masks PAM00632

A362B24SP, 2021/01/31 04:02

43 Series Fittings ブライトリング偽物

ブライトリングクロノマットレプリカ, 2021/02/01 04:19

25 Micron Stainless Steel Mesh Rosin Filter Bags ブライトリングクロノマットコピー

5207BB/12/9V6, 2021/02/01 08:50

Gluten Free Lemon Slice ブレゲクラシックレプリカ

スーパーコピーカルティエ, 2021/02/01 16:47

Calcium Hypochlorite Swimming Pool カルティエ時計

ジバンシィ靴偽物, 2021/02/02 16:17

Aluminium Sliding Doors カルティエネックレスコピー

Material, 2021/02/02 18:16

スーパーコピーブランド通販専門店 Material

欧美性爱视频, 2021/02/03 06:56

ティファニー指輪偽物 快车足彩

Bike Pump, 2021/02/03 08:53

ピアジェ時計スーパーコピー販売店 Bike Pump

エルメス靴スーパーコピー通販店, 2021/02/03 16:15

Emulsifier And Homogenizer IWC時計スーパーコピー代引き

Plastic Bottle Recycling Machine, 2021/02/03 20:44

ディオールサングラススーパーコピー Plastic Bottle Recycling Machine

韓国コピーブランド税関, 2021/02/04 18:55

Finned Heat Exchanger ロレックス時計スーパーコピー

2 Pipe Fittings, 2021/02/05 02:51

スーパーコピーブランドn級品 2 Pipe Fittings

Adjustable Ac Voltage Regulator, 2021/02/05 14:29

カルティエネックレスコピー国内発送 Adjustable Ac Voltage Regulator Supplier

ジバンシーサングラススーパーコピー販売店, 2021/02/05 16:32

Denim Backpack 高品質ブルガリ時計コピー

スーパーコピー時計専門店, 2021/02/05 21:03

3 Inch Ball Bearing Supplier ジバンシーサングラスコピー国内発送

ドルチェガッバーナ靴コピー, 2021/02/06 02:47

Kitchen Spoon Set Price ボッテガヴェネタベルトブラントコピー代引き

Metal Toy Factory, 2021/02/06 04:22

トリーバーチバッグ偽物 Metal Toy Factory

Golf Set Price, 2021/02/06 06:07

スーパーコピーブランド激安高品質 Golf Set Price

赌厅网投, 2021/02/07 00:30

ルイヴィトン時計ブラントコピー代引き 澳门博狗

オメガ時計スーパーコピー, 2021/02/07 02:12

在线赌场游戏 ディオールネックレススーパーコピー販売店

トリーバーチ財布偽物, 2021/02/07 08:13

UV flatbed printer トリーバーチ財布偽物

ロジェヴィヴィエ靴コピー, 2021/02/07 10:37

Cnc Cutting Machine Plasma グッチブレスレットコピー

ボッテガヴェネタバッグコピー店舗, 2021/02/07 16:23

Camera Clean クロエサングラスコピー品

Clear Folding Box, 2021/02/07 19:48

ロエベバッグスーパーコピー販売店 Clear Folding Box

パテックフィリップ時計偽物, 2021/02/07 21:40

insulating glass machine ディオールストールスーパーコピー激安

セリーヌピアスコピー販売店, 2021/02/08 02:37

Carbon Fiber Twill Fabric クロムハーツ帽子スーパーコピー通販店

Civil Mask Without Box, 2021/02/08 04:18

パネライ時計コピー激安 Civil Mask Without Box

Face Mask Loop Welding Machine, 2021/02/08 06:53

楽天市場スーパーコピーブランドメール Face Mask Loop Welding Machine

セリーヌ財布コピー販売店, 2021/02/08 08:55

Conductive Proximity Switch ブルガリピアスコピー店舗

3 Stages Kitchen Knife Sharpener, 2021/02/08 14:39

韓国コピーブランド税関 3 Stages Kitchen Knife Sharpener

SPC FLOOR, 2021/02/08 17:07

グッチピアスコピー優良サイト SPC FLOOR

Apple Cellular, 2021/02/08 22:15

フェラガモベルトコピー Apple Cellular

3m Aura 9322 Ffp2, 2021/02/09 00:36

シャネル帽子コピー国内発送 3m Aura 9322 Ffp2

250 Mig Welder For Sale, 2021/02/09 02:17

ブランドボッテガヴェネタベルトコピー 250 Mig Welder For Sale

コーチ財布スーパーコピー激安, 2021/02/09 04:41

Package ヴィトンケース偽物

Conduit Saddle Clamp Supplier, 2021/02/09 06:26

本物と同じステラマッカートニーバッグコピー Conduit Saddle Clamp Supplier

Adjustable Aquarium Pump Supplier, 2021/02/09 14:14

エルメスベルトコピー国内発送 Adjustable Aquarium Pump

China Boys Wearing Briefs, 2021/02/09 16:33

高品質セリーヌ靴コピー China Boys Wearing Briefs

プラダサングラススーパーコピー代引き, 2021/02/09 20:26

China Luxury Cosmetic Jars コーチ帽子スーパーコピー販売店

Disposable Face Mask, 2021/02/09 22:06

ルイヴィトンネックレスコピー品 Disposable Face Mask Supplier

Excavator Parts Online, 2021/02/09 23:27

ブランドストール/スカーフスーパーコピー販売店 Excavator Parts Online

フェンディブレスレットコピー品, 2021/02/10 06:22

Mobile Phone Headphone Factory コンスタンタン時計スーパーコピー激安

Guangdong Shunde Seko Machinery Technology Co., Ltd., 2021/02/10 08:22

ブランドブルガリバッグコピー Guangdong Shunde Seko Machinery Technology Co., Ltd.

ブランドコピー激安財布, 2021/02/10 14:33

Guangzhou XuFengEn Technology Co., Ltd. ブランド財布スーパーコピー専門店

block machine made in china alibaba, 2021/02/10 20:59

スーパーコピーブランドメガネ block machine made in china alibaba

ヴェトモンコピーブランド, 2021/02/11 00:47

3 Phase Electric Meter エルメス時計コピー激安

Airline Single Package Sanitizing Hand Wet Napkins, 2021/02/11 03:17

シャネル指輪コピー代引き Airline Single Package Sanitizing Hand Wet Napkins

快车足彩, 2021/02/11 08:16

バーバリー靴コピー店舗 欧美性爱视频

ミュウミュウバッグコピー激安, 2021/02/11 14:27

在线赌场游戏 ブランドコピーおすすめサイト

ブルガリ財布コピー国内発送, 2021/02/11 18:05

澳门博狗 トッズ靴コピー国内発送

高品質ディオール財布コピー, 2021/02/11 22:45

Self Heating Hand Warmers N級品シャネルブレスレットコピー

Dengue Nsi Antigen Positive, 2021/02/12 00:50

シャネルピアスコピー Dengue Nsi Antigen Positive

1.5"Pvc Fitting, 2021/02/12 12:55

ルイヴィトンサングラスコピー 1.5“Pvc Fitting

Gel Nails Products, 2021/02/12 16:36

ディオールネックレススーパーコピー激安 Gel Nails Products

エムシーエム財布スーパーコピー, 2021/02/12 22:08

Concrete Additives Australia エムシーエムバッグコピー

ユンハンス時計ブラントコピー代引き, 2021/02/13 00:07

Bc203m Magnetic Scale Dro バーバリー帽子コピー激安

シャネル指輪コピー販売店, 2021/02/13 06:26

air gun cylinderhigh pressure air cylinder カルティエ時計スーパーコピー

ブランド財布スーパーコピー販売店, 2021/02/13 12:38

50tr Water Chiller ドルチェガッバーナ靴コピー優良サイト

スーパーコピーブランド靴, 2021/02/13 16:25

Arch Tungsten Coil Wire バーバリーバッグコピー

Bathroom Wash Sink, 2021/02/13 20:03

シャネル時計スーパーコピー代引き Bathroom Wash Sink

Membrane Switch Keyboard, 2021/02/14 02:03

クロムハーツ指輪コピー Membrane Switch Keyboard

Electrical Power Cable, 2021/02/14 06:09

Electrical Power Cable

Garden Led Solar Light, 2021/02/14 08:23

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N級品グッチベルトコピー, 2021/04/03 15:53

Acrylic Serving Platters エムシーエム財布コピー国内発送

Magnesium Powder Canada, 2021/04/03 23:41

スーパーコピーブランド専門店知恵袋 Magnesium Powder Canada

Grooved Ball Bearing, 2021/04/04 01:17

オメガ時計コピー代引き Grooved Ball Bearing

シャネルベルトスーパーコピー激安, 2021/04/04 01:57

Instant Noodles ルイヴィトンサングラスコピー品

China Heavy Duty Strimmer, 2021/04/04 03:40

グッチピアススーパーコピー代引き Heavy Duty Strimmer Supplier

Hammer Test Digital, 2021/04/04 05:26

ブランドジバンシィ靴コピー Hammer Test Digital

Fiberglass Brick Mold, 2021/04/04 09:34

プラダ靴コピー店舗 Fiberglass Brick Mold

ブランド帽子スーパーコピーN級品, 2021/04/04 11:21

Temperature Measurement And Calibration エルメス指輪スーパーコピー通販店

Jet Chisel Pneumatic Model Jex-2800a, 2021/04/04 13:56

プラダ帽子ブラントコピー代引き Jet Chisel Pneumatic Model Jex-2800a

Cultured White Freshwater Pearl, 2021/04/04 15:56

トリーバーチ財布コピー代引き Cultured White Freshwater Pearl

ジャガールクルト時計ブラントコピー代引き, 2021/04/05 15:01

Dome Head Blind Rivet Stainless Steel スーパーコピーブランド買ってみた

Blank Black Cap, 2021/04/05 17:55

本物と同じクロムハーツブレスレットコピー Blank Black Cap

Cheese Making Machine, 2021/04/05 21:37

N級品フェラガモ靴コピー Cheese Making Machine

Glass Bottle Washing Machine, 2021/04/06 05:24

VACHERONCONSTANTIN時計コピー Glass Bottle Washing Machine

30# Brown Fused Alumina, 2021/04/06 09:12

エムシーエム財布コピー優良サイト 30# Brown Fused Alumina

Dental Lamp, 2021/04/06 10:00

ジバンシィ靴コピー店舗 Dental Lamp

Electric Power Reactor, 2021/04/06 11:46

ルイヴィトンサングラスコピー代引き Electric Power Reactor

Gas Ball Valve Price, 2021/04/06 15:25

ブランドブレスレットスーパーコピー専門店 Gas Ball Valve Price

Hangzhou Lichang Tools Co., Ltd., 2021/04/06 17:49

サンローラン財布コピー品 Hangzhou Lichang Tools Co., Ltd.

DW25CNC-3A-2S, 2021/04/07 07:13

シャネルサングラスコピー代引き DW25CNC-3A-2S

バレンシアガバッグコピー品, 2021/04/07 12:00

5v Car Air Purifier カルティエ指輪コピー激安

エルメスバッグ偽物, 2021/04/07 13:54

Aluminium Sheet Metal Parts ロジェデュブイ時計スーパーコピー

ルイヴィトンサングラスコピー国内発送, 2021/04/07 15:49

3-5mm Activated Alumina Desiccant ヴィトンケースコピー

Laser Cutting Machine, 2021/04/07 17:44

ブランドバッグコピー商品 Laser Cutting Machine

高品質エルメス財布コピー, 2021/04/07 19:38

During Production Inspection トリーバーチ財布スーパーコピー通販店

カルティエ時計ブラントコピー代引き, 2021/04/07 23:01

Digital Facial Steamer バーバリーストールコピー代引き

Comb Set, 2021/04/08 01:52

ブランドブレスレット最高级コピー Comb Set

Drip Irrigation Pipe, 2021/04/08 07:57

グッチ時計偽物 Drip Irrigation Pipe

Automatic Punching Machine For Wheel Barrow, 2021/04/08 13:39

高品質ボッテガヴェネタ財布コピー Automatic Punching Machine For Wheel Barrow

D-Alpha Tocopherol 1300iu With 190kg Iron Drum China, 2021/04/08 15:59

本物と同じプラダベルトコピー D-Alpha Tocopherol 1300iu With 190kg Iron Drum China

150lb Super Duplex 2507 Wafer Dual Plate Check Valve, 2021/04/08 17:50

ベル&ロス時計スーパーコピー 150lb Super Duplex 2507 Wafer Dual Plate Check Valve

ブランドスーパーコピーn級品, 2021/04/09 09:07

Ford Mustang Floor Mats ブランドピアススーパーコピー

ブランド時計スーパーコピー専門店, 2021/04/09 09:52

Christmas Ornaments Sets シャネルピアスコピー品

コーチ帽子スーパーコピー通販店, 2021/04/09 13:38

Automatic Pipe Cutting Machine トッズ靴コピー

China Ch350c Lightning Cylinder Heads, 2021/04/09 17:17

エルメスブレスレット偽物 Ch350c Lightning Cylinder Heads Supplier

ブランドフェンディ財布コピー, 2021/04/09 20:00

N95 Filtration Test Machine バーバリーストールスーパーコピー

フェンディバッグスーパーコピー, 2021/04/10 07:20

China Basketball Score Board バーバリーサングラススーパーコピー

クロエバッグコピー, 2021/04/10 13:32

Color E Ink Screen シャネル時計コピー激安

Countersunk Head Rivet Nut Insert, 2021/04/10 15:26

フェンディ帽子コピー国内発送 Countersunk Head Rivet Nut Insert

Foot And Ankle Ice Pack, 2021/04/10 17:17

コピーブランドヤフオク Foot And Ankle Ice Pack

0681621, 2021/04/10 20:00

フェンディサングラススーパーコピー販売店 0681621

luxury mink eyelashes, 2021/04/10 23:42

バーバリーストールスーパーコピー luxury mink eyelashes

N級品エルメス時計コピー, 2021/04/11 11:10

Industrial water softener コピーブランド意見書

Gasifier For Heating Rotary Dryer, 2021/04/11 13:47

ジバンシィ靴スーパーコピー通販店 Gasifier For Heating Rotary Dryer

バーバリー財布コピー, 2021/04/12 07:58

Suc20412 Insert Bearings Food Grad エルメス靴コピー国内発送

ディオール靴コピー激安, 2021/04/12 13:01

Table Top Heat Sealer コーチ帽子スーパーコピー激安

シャネル帽子コピー通販店, 2021/04/12 13:58

China Wholesale Machine Welding Ppr Suppliers セリーヌバッグスーパーコピー

エルメスブレスレット偽物, 2021/04/13 09:32

Suit Trousers Fabric N級品バーバリー靴コピー

ブライトリング時計コピー通販店, 2021/04/13 14:01

Anti Aging Machine タグホイヤー時計スーパーコピー激安

BBQ charcoal briquette machine, 2021/04/13 19:17

グッチバッグコピー優良サイト BBQ charcoal briquette machine

スーパーコピーブランドgucci, 2021/04/14 13:12

在线赌场游戏 スーパーコピーブランドgucci

Mineral Wool Sandwich Panel, 2021/04/14 15:03

ロエベバッグスーパーコピー販売店 Mineral Wool Sandwich Panel

エムシーエム財布スーパーコピー販売店, 2021/04/14 17:57

Colour Coating Fabric コピーブランドポーチ

バレンシアガ帽子コピー代引き, 2021/04/14 19:48

Bottle With Logo フェンディ靴コピー優良サイト

ジバンシィ靴スーパーコピー販売店, 2021/04/15 07:49

water supply pipe ブランドコピーアマゾン

About Hemodialysis, 2021/04/15 11:34

グッチピアスコピー優良サイト About Hemodialysis

iphonexrブランドコピー, 2021/04/15 13:24

China Fe2o3 iphonexrブランドコピー

カルティエスーパーコピー時計, 2021/04/15 15:16

2 In 1 Plastic Shaker Bottle iphone8プラスケースブランドコピー

ルイヴィトン指輪偽物, 2021/04/15 17:06

Anti Humidity Hair Spray IWC時計コピー通販店

シャネル財布スーパーコピー激安, 2021/04/15 19:01

PHMD1010 ブランド指輪スーパーコピー専門店

iphonexsブランドコピー, 2021/04/16 07:25

86x block camera ピアジェ時計コピー

パテックフィリップ時計コピー, 2021/04/16 11:03

Other Series ブランド携帯ケースコピー

グッチ時計コピー国内発送, 2021/04/16 11:56

Nickel Mining Pe Pipe Supplier バレンシアガ帽子スーパーコピー代引き

本物と同じステラマッカートニーバッグコピー, 2021/04/16 19:17

Battery Capacity Tester Battery Dc Load Control ティファニーネックレス偽物

ロレックス時計ブラントコピー代引き, 2021/04/17 07:52

3 Yard Loader Bucket マイケルコース財布スーパーコピー代引き

Homemade Mud Pump Supplier, 2021/04/17 13:38

ブランド時計コピー販売店 China Homemade Mud Pump

シャネル指輪スーパーコピー, 2021/04/17 21:05

2 Phase Stator グッチ時計コピー国内発送

N級品シャネルサングラスコピー, 2021/04/17 21:58

Brown Paper Block Bottom Bags ボッテガヴェネタ靴スーパーコピー販売店

3 Way Poly Ball Valve, 2021/04/18 05:31

コピーブランドランク 3 Way Poly Ball Valve

ブランドバッグ激安, 2021/04/18 09:19

Float Type Level Gauge ブランド携帯ケーススーパーコピーN級品

iphone11ケースブランドコピー激安, 2021/04/18 13:40

Semipermanent Nail Polish ブランド指輪最高级コピー

Triethyl Phosphate (Tep), 2021/04/18 15:31

ブランド靴偽物 Triethyl Phosphate (Tep)

Floor Tile Machine Price, 2021/04/18 17:27

セリーヌ靴スーパーコピー通販店 Floor Tile Machine Price

高品質セリーヌ靴コピー, 2021/04/18 19:26

Bagasse Bowl ルイヴィトンピアススーパーコピー

air jordan 4 grape, 2021/04/19 11:53

バレンシアガ靴コピー国内発送 Ceiling Fan Led Lights air jordan 6 marron