HDF5 Files in NeuroExplorer

Several open source projects (KlustaSuite, Neo, NIX, LBNL Brain, Orca, Neurodata Without Borders) utilize open source Hierarchical Data Format (HDF5) to store neurophysiological data. NeuroExplorer 5.023 (released on December 16, 2015) can import KlustaSuite .kwik files with data stored in HDF5 format.

If you are using any other HDF5-based file format and would like to import this file format directly in NeuroExplorer, send an e-mail to [email protected] With all the basic code to read data from HDF5 files in place, I can add import of another HDF5 file format to NeuroExplorer in a few days.

Python Scripting in NeuroExplorer

For many years, NeuroExplorer has had the capability to automate repetitive tasks:

  • Repeat analysis on all the data files in a folder,
  • Edit data or post-process analysis results without sending data or results to an external program

To support scripting, a custom NexScript language was developed. NexScript supports simple variables and has basic flow control capabilities. However, there are many limitations of NexScript that make writing scripts difficult. Adding new capabilities to NexScript (for example, adding support for arrays) would require a considerable effort. An alternative approach is to integrate existing programming language into NeuroExplorer.

We are pleased to announce that starting with version 5.022, NeuroExplorer scripts can also be written in Python.

NexScript - RepeatAnalysis2

Here are some of the benefits of using Python:

  • Python is very well documented
  • Shorter scripts
    • Access to NeuroExplorer data via Python lists eliminate many loops
    • User-defined functions replace repetitive code
  • Scripts can use thousands of Python functions

Old NexScript scripts can be automatically converted to Python using Tools | Convert to Python menu command in NexScript editor.

NeuroExplorer uses Python 2.7.10. There is no need to install Python. All the Python files needed for scripting are installed by NeuroExplorer setup program.

How to Store Analog Data

NeuroExplorer up to version 5.020 always stored analog data internally as 16-bit integers. The reason? Most data acquisition systems use analog to digital converters that have 12-bit or 16-bit resolution and store A/D data as 16-bit integers.

To display real signal values, we use scaling. For example, if analog to digital converter has input range from -1000mV to +1000mV and 10X amplification was used, then maximum 16-bit value 32767 corresponds to 1000mV/10 (non-amplified signal value). This means that 32767*ScalingFactor = 100, and ScalingFactor is 100.0/32767.

16-bit storage model seems perfect — we do not loose any signal resolution and we save on storage space. However, if we import data from Matlab (where the data values are stored as floating point numbers), we have to calculate ScalingFactor to fit floating point values into 16-bit range. As a result, we loose signal resolution (especially when the signal has a few large peaks and lots of small values).

There are also clipping issues when we try to modify signal values in NexScript. If we try to assign the value that is outside the original  non-amplified  range, we would have to clip the value since we have hard limits for 16-bit internal representation of signals.

Things, however, are changing with NeuroExplorer 5.021. Now NeuroExplorer can store analog data both as 16-bit integers and as 32-bit floating point numbers.

Analog signals imported from data files created by data acquisition system are still stored as 16-bit integers.

Continuous channels imported from Matlab or generated in NeuroExplorer (using frequency filtering, etc.) are now stored as 32-bit floating point values. Both data representations can be saved and loaded using .nex5 data files.

Matlab scripts for reading and writing .nex5 files (HowToReadAndWriteNexAndNex5FilesInMatlab.zip) have been updated and can be used to read and write .nex5 files with analog data stored as 32-bit floats.

Dealing with Noise and Artifacts in Data Viewer

Often you can visually identify periods of noise or artifacts in 1D Data Viewer:

scratching artifact2

In NeuroExplorer version 5.014 or later, you can identify time intervals corresponding to artifacts using mouse:

– Right-click in 1D View to invoke context menu:


– Specify ‘Select Interval Variable…’ menu command. NeuroExplorer will display the following dialog:

Specify Interval Variable to Add Intervals to

– Click ‘Create New Interval Variable…’ button:

New Variable Name

– Let’s create a new interval variable with the name noise. Type ‘noise’ (without quotes) and click OK to close this dialog, then click OK to close Select Interval Variable dialog.

– Note that the cursor now has ‘plus interval’ graphic:


– Press the left mouse button at the start of the noise interval, then drag the mouse until the end of the noise interval and release left mouse button. The new interval is added to noise interval variable:

added interval

– Add a second interval:


– Hit ESC key to exit Add Interval mode

– We want to analyze data that is NOT in the noise intervals. To make this possible, right-click in 1D view again and select ‘Invert Interval Variable’ menu command:


– In the Invert Interval Variable dialog, select noise variable to be inverted:

Invert Interval Variable

– Now noise_inverted interval variable contains time intervals corresponding to our data without noise:


– We can use noise_inverted variable in a Data Selection page of analysis properties dialog:

Analysis Properties data sel

and the data in noise intervals will be ignored.

There is also a faster way to get rid of noisy data — you can delete all the data in specified time intervals. To do this, right-click in 1D view and select ‘On Mouse Click and Drag, Delete…’ menu command:


– Now when you click and drag with the left mouse button, all the data in selected time interval are deleted:



Note that delete operation cannot be undone right away. You will need to reload the data file to restore original data.


How to Save and Restore Your Work in NeuroExplorer

When you work in NeuroExplorer, the program creates a number of data and analysis results windows.  By default, these windows are not restored when you close and reopen the program.  If you would like to save and restore all your current work in NeuroExplorer, use File | Save NeuroExplorer State and File | Restore NeuroExplorer State menu commands:


You can also restore the last analysis of this or previous NeuroExplorer analysis session using File | Restore Last Analysis menu command.  The program will do the following:

  • Load the data file used in last analysis
  • Select the variables used in last analysis
  • Run the analysis

See also Working with Results Files.