NeuroExplorer 5.023 (released on December 16, 2015) adds a new option in Spectrogram Analysis – ability to draw analog signal above each spectrogram. The signal is drawn for the time values specified in the spectrogram X axis. It is recommended that the Spectrogram analysis option ‘X Axis corresponds to the Center of Sliding Window’ is used.
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.
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.
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.
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.
NeuroExplorer 5.017 released on July 22, 2015 has two new analyses: Find Oscillations analysis and Firing Phase analysis.
Find Oscillations analysis identifies episodes of oscillatory activity in the specified frequency band in recorded analog signals. The algorithm is described in Klausberger, Magill, Marton, Roberts, Cobden, Buzsaki and Somogyi. Brain-state- and cell-type-specific firing of hippocampal interneurons in vivo. Nature, 2003 Feb 20;421(6925):844-8
The user specifies two frequency bands (for example, theta band and delta band). NeuroExplorer finds the segments of LFP signal where theta to delta frequency power ratio exceeds a certain threshold. The LFP signal is then band-filtered and oscillation cycle start times are identified via Hilbert transform. This analysis adds several new variables to the data file. The data viewer screenshot below shows the results of analyzing variable LFP01. NeuroExplorer added three new variables: Theta_Epochs, Theta_Filtered and Theta_ZeroPhase:
The LFP01_Theta_ZeroPhase event is than used in Firing Phase analysis that calculates probability of a neuron firing in a certain phase of theta cycle:
By the way, I added these new analyses after several users asked me whether a phase-of-firing analysis is available in NeuroExplorer.
Do you need new analyses or new features in NeuroExplorer? Please send your requests to [email protected]