NeuroExplorer

NeuroExplorer^® is the industry leading neurophysiological data analysis package that supports sophisticated analyses and professional presentation of the results–and cited by more than 2,100 scientific publications. NeuroExplorer now reads Plexon’s new PL2 file format, enabling ultrafast loading of large neural files. It is important to note that NeuroExplorer does not provide spike sorting capabilities, rather, it assumes that you have already sorted the waveforms – a process for which Plexon’s Offline Sorter™ is uniquely ideal.

**NeuroExplorer 5.022 enabling scripting to be done in Python now available**

For a Demo or latest software upgrades, please visit: http://www.neuroexplorer.com

Description

NeuroExplorer can be used to analyze data files offline, or used in real-time with the OmniPlex^® D Neural Data Acquisition System as well as the original Multichannel Acquisition Processor (MAP) Data Acquisition System control software.

NeuroExplorer is now available in its 5^th version offering the most complete set of spike train analyses in a single package available today. Researchers are also empowered to analyze continuously recorded signals and populations of neurons from multiple perspectives. A powerful built-in scripting language allows for the automation of many analysis tasks, while its open analysis environment allows you to use other programs to extend its capabilities.

Version 5 is a truly significant expansion of functionality over the previous version – seven years in the making! See the notes below for new features and functionality.

NeuroExplorer can read data files in several formats including those created by many popular data acquisition systems, text files, Excel^® spreadsheets and MATLAB^®. To assist in presenting your analysis, NeuroExplorer creates fully editable, publication-quality tables and graphs.

In addition to the new features in version 5 identified by green text below, version 5 also now leverages the increased flexibility of the .NEX5 format not only to analyze and save files greater than 2 GB, but also to save unlimited metadata for the whole file and for every file variable. Another important advance in this release includes the “Find Oscillations” analysis which identifies episodes of oscillatory activity in the specified frequency band in recorded analog signals. More details can be found in the related news release.

NeuroExplorer offers such an extensive list of features and benefits that we will simply list the most prominent features by category below:

Spike train analyses

Vastly IMPROVED spectral analyses of spike trains including single taper and multi-taper calculations of spectra, six available windowing functions, three preprocessing options and jackknife confidence, the ability to replicate MATLAB spectral calculations, up to ten times faster calculation of spectral results and more
NEW spike train analyses featuring firing rate vs. head direction and single trial rate estimation via adaptive kernels
Interspike interval histograms
Rate histograms
Perievent histograms
Perievent rasters
Autocorrelograms
Crosscorrelograms with shift-predictors
Joint peristimulus histograms
Burst analysis
Spectral densities and spectrograms
Perievent histograms versus time
Place cell analysis
Cumulative activity
Instantaneous frequency
Interspike intervals versus time
Poincare maps of interspike intervals
Epoch counts
Coherence analysis

Analysis of continuously recorded signals

NEW analyses of continuous data (LFP) such as perievent rasters, power spectra, coherence, single trial spectrum analysis and phase analysis using Hilbert Transform
NEW digital filtering options for continuous data including seven new IIR and FIR filters
NEW 64-bit build enabling loading/analyzing multi-gigabyte data files and displaying hundreds of millions of rows
NEW immediate preview of data when a data file is loaded
NEW .NEX5 data file format that is more flexible than the previous .NEX format such that it allows saving files greater than 2GB and saves unlimited metadata for the whole file and for every file variable in JSON format
Vastly IMPROVED spectral analyses of continuous channels including single taper and multi-taper calculations of spectra, six available windowing functions, three preprocessing options, jackknife confidence, the ability to replicate MATLAB spectral calculations, up to ten times faster calculation of spectral results and more
MORE EFFICIENT processing as computationally demanding analyses are run in parallel using all CPU cores
Correlations between spike trains and continuous signals
Spike-triggered histograms and rasters
Spectral analysis
Perievent spectrograms

Analysis of populations of neurons

Principal component analysis
Population PST histograms
Spectral analysis
3D network activity animation

Fully editable publication-quality graphics

2D and 3D black-and-white and color graphs
Unlimited number of graphs per figure
Tables of graphs. (e.g. all pairwise correlations within a group of neurons)
Completely customizable figure elements: colors, fonts, tick sizes, etc.
Single-page and multi-page printing
Export of graphics to other applications via the clipboard, Windows metafiles and bitmaps
Completely customizable figure elements (e.g. colors, fonts, tick sizes)
Create lab books of your results in PowerPoint^®

Powerful internal scripting language allows automation of many analysis tasks

Open and close data files
Select data for analysis
Specify analysis parameters
Specify graphics options
Apply analysis templates
Save results as a text file
Send data and results to Excel
Send data and results to MATLAB
Execute MATLAB scripts
Modify existing spike trains and other data
Create new events and spike trains
Read and write text files

Open analysis environment

NEW statistical tests (T-tests, Wilcoxon tests, ANOVA and user-added tests by writing R-scripts) comparing results across conditions that can be implemented via integration with R-project
ENHANCED ability to save and restore results such that it saves all numerical and graphical results in a series of linked files, and a user can open results files without recalculation, as well as replicate results
Copy data to Excel, edit the data in Excel and paste it back to NeuroExplorer
Generate data in MATLAB and transfer it to NeuroExplorer
Copy numerical results to Excel or MATLAB for additional analysis
Execute MATLAB scripts from NeuroExplorer for additional processing
Create a lab book of your results in PowerPoint

NeuroExplorer is an exceptionally sophisticated and trusted data analysis program. All upgrades within a version are free of charge and will be accessible online upon release. If you would like to learn more about NeuroExplorer and its capabilities, Offline Sorter™, or any other Plexon products, you are invited to contact a Plexon Sales Engineer for more information.

Technical Specs

The table below provides a functionality summary and minimum system requirements for NeuroExplorer v5.0. Please see the NeuroExplorer Manual for more information on any topic listed below.

Features	Specifications and Options	Remarks
File types read (import)	Plexon (.PL2, .PLX), AD Instruments, Alpha Omega, Axion Biosystems, Blackrock Microsystems, CED Spike-2, Cortex, DataWave, MultiChannel Systems, Neuralynx, RC Electronics, Tucker-Davis technologies, text files, MATLAB^® and Excel^®
Minimum system requirements:
Computer CPU	Pentium^® III or better
Platform	Windows^® XP, Vista, 7, 8, or 10 and Windows Server 2003, 2008 or 2012 (32-bit or 64-bit). Works on Mac under Parallels.
RAM	256MB minimum	4GB is recommended
Disk space	30MB
Video resolution	1024×768 minimum
Computer interface	USB port
Activation requirement	Version-specific hardware license key	When NeuroExplorer is purchased, it includes 3 license keys. Additional keys may be purchased.

Resources

Manuals/User Guides

NeuroExplorer v5 Manual

NeuroExplorer v4 Manual

Installation Packages/Upgrades

NeuroExplorer is developed by a third party. For the most current information, demos and software updates, visit www.neuroexplorer.com.

Technical Specs and Data Sheets

NeuroExplorer Data Sheet

Videos

How-To Guides

PL2 File System Overview

Loading recorded data

This how-to guide contains an overview of data import methods.

Use File | Open… menu command and then select your data file.

If you are using one of more than 50 supported file formats, the program will load your data file.

If NeuroExplorer complaints about unknown file extension or invalid file format, follow these instructions.

If you can load your data in Matlab, you can either save Matlab data in .nex5 file, or transfer data from Matlab to NeuroExplorer.

If your data is in Excel, you can copy and paste your data from Excel to NeuroExplorer.

Dealing with Unknown File Format Error

This guide explains how NeuroExplorer imports data files created by data acquisition systems.

NeuroExplorer supports more than 50 file formats and tries to identify the data file type from the file extension.

Some file extensions are used by several file formats and NeuroExplorer may be unable to identify what is the file format of the selected file.

For example, a .nev file can be either a Neuralynx data file or Ripple Neuro data file.

Here is what you can do in this situation:

Use specific File | Import Data sub-menu (Plexon Data File, Neuralynx Data File, etc.) to open your data file
Specify what file format corresponds to a specific file extension
- Select View | Data Import Options… menu command
- Click the File Extensions… button
- Select file extension in the left column,
- Click in the right column and select the file type for the extension:

Importing Data from Matlab

This how-to guide explains how to transfer data from Matlab to NeuroExplorer.

You can create spike trains (1 x N or N x 1 matrices with timestamps in seconds) or continuous variables in Matlab and transfer them to NeuroExplorer on the fly. Here is how to do this:

Select File | New menu command.
Select Matlab | Get Data From Matlab | Open Matlab As Engine menu command. NeuroExplorer will open Matlab as engine.

Note

When you run Open Matlab as Engine menu command, a new instance of Matlab is opened. This instance will have no variables in its workspace. Therefore, you need to create (or load from file) the data you want to transfer to NeuroExplorer.

After your data is available in Matlab, select one of the Matlab | Get Data From Matlab menu commands to transfer the data to NeuroExplorer.

Importing Data from Excel

This how-to guide explains how to use Copy/Paste to add data variables to NeuroExplorer.

To paste the following two timestamped variables (BarPress and Reward) from a spreadsheet to NeuroExplorer:

In Excel:

Select the cell range with both variables (A1 to B4)
Select Home | Copy command

In NeuroExplorer:

Select Data view of a file in NeuroExplorer
Select the Timestamps tab of the Data view
Right-click and select Paste menu command:

NeuroExplorer will create two new Event variables and add them to the file.

Note

Using similar approach (copy in Excel and paste in NeuroExplorer) you can import continuous variables (right-click in the Continuous tab) and time intervals (right-click in the Intervals tab).

You need to save the file (use File | Save… or File | SaveAs… menu command) to make this change permanent.

Importing Continuous Data From Text Files

NeuroExplorer can import continuous data from a multicolumn text file where each column corresponds to a continuous variable. Here is an example:

 
ContChannel1    ContChannel2
114.74609       -63.47656
56.15234        -358.88672
-187.98828      -63.47656
-48.82813       388.18359
-26.85547       285.64453

Use File | Import Data | Text File with Continuous Variables (no timestamps)… menu command to import such a data file. The following dialog will be shown:

First line contains variable names – if this option is selected, the fields of the first line of the text file are used as variable names. The second line in the file is the first row of data.
First Data Point Timestamp specifies the timestamp of the first data point in each continuous variable.
Time Between Data Points specifies the time step used in calculation of the timestamp for each row of data. For data row n (n = 1, 2, …) in the text file, the data row timestamp is calculated using the following formula:

 
DataRowTimestamp = FirstDataPoint + (n-1)*TimeBetweenDataPoints

If you have a text file with the timestamps in the first column of the file:

 
Time      ContChannel01
000400  114.746094
000500  56.152344
000600  -187.988281
000700  -48.828125
000800  -26.855469

use File | Import Data | Text File with Continuous Variables (with timestamps)… menu command to import such a data file.

Importing Timestamps From Text Files

NeuroExplorer can import timestamps stored in the following text formats:

1. Multicolumn table of timestamps

 
Neuron01    Neuron02
01        0.001
3         0.05
5         0.1
4
6

In this format, each column in the text file contains the timestamps of a neuron. The first line of the file contains the names of all the variables.

2. Pairs <name> <timestamp>

The text file in this format should contain the pairs of the type

name timestamp

where

name is a character string. The first character of the name should be a letter. If the number is used as the name, NeuroExplorer will add “event” at the beginning of the variable name.

timestamp is a number representing the neuron firing time (or event time) in seconds or in time ticks.

Here is an example of a text file with the timestamps in seconds:

 
Neuron01    0.01
Neuron01    0.3
Neuron02    0.001
Neuron02    0.05
Neuron01    0.5
Neuron02    0.1
Neuron02    0.4

Use File | Import Data | Text File with Timestamps… menu command to import a text file with timestamps. The following dialog will be shown:

The following options can specified in Text Import dialog:

Sampling Frequency – this parameter defines the internal representation of the timestamps that NeuroExplorer will use for this file. Internally, the timestamps are stored as integers representing the number of time ticks from the start of the experiment. The time tick is equal to

1./Sampling_Frequency

Timestamp Units – this parameter defines how the numbers representing the timestamps are treated by NeuroExplorer. If the timestamps are in time ticks, they are stored internally exactly as they are in the text file. If the timestamps are in seconds, NeuroExplorer converts them to time ticks:

Internal_Timestamp_In_Ticks = Timestamp_In_Seconds * Sampling_Frequency

Dealing with sentinel key errors

NeuroExplorer requires a Sentinel key to operate. Sentinel drivers need to be installed so that NeuroExplorer can communicate with the Sentinel keys. These drivers are installed when you run NeuroExplorer setup (NeuroExplorer5Setup64.exe).

Error Messages and Troubleshooting

Message	Troubleshooting
Unable to initialize Sentinel library	Follow instructions in Make Sure Sentinel Drivers are Installed.
Unable to find Sentinel key	Follow instructions in Unable to Find Key Message.
Unable to read Sentinel key data	Contact NeuroExplorer technical support (support@neuroexplorer.com). Sentinel key may be damaged.
Sentinel key does not have version 5 license	You are using NeuroExplorer version 3 or version 4 Sentinel key. Follow instructions in Sentinel Key Does Not Have Version 5 License.

How to customize Analyses Panel

To speed up the access to the analyses you use most often, you can rearrange the order of the analyses in the All Analyses list by dragging the analyses up and down in the list:

There is also Recently Used Analyses list that shows the last 10 analyses that were used.

The layout of the Analyses Panel is saved in the file

 
C:\Users\<user_name>\Documents\NeuroExplorer 5\Layouts\AnalysesPanelLayout.layout

If you want to standardize the order of analyses on all computers in your lab, you can rearrange the analyses on one of the computers, exit NeuroExplorer and copy AnalysesPanelLayout.layout file to
folders on other computers.

C:\Users\<user_name>\Documents\NeuroExplorer 5\Layouts

Publications

Aton SJ, Suresh A, Broussard C, Frank MG. Sleep promotes cortical response potentiation following visual experience. Sleep. 2014 Jul 1;37(7):1163-70.

Dasilva M, Grieve KL, Cudeiro J, Rivadulla C. Anandamide activation of CB1 receptors increases spontaneous bursting and oscillatory activity in the thalamus. Neuroscience. 2014 Apr 18;265:72-82.

Hatori M, Gill S, Mure LS, Goulding M, O’Leary DD, Panda S. Lhx1 maintains synchrony among circadian oscillator neurons of the SCN. Elife. 2014;3.

Hei X, Stoelzel CR, Zhuang J, Bereshpolova Y, Huff JM, Alonso JM, Swadlow HA. Directional selective neurons in the awake LGN: response properties and modulation by brain state. Journal of neurophysiology. 2014 Jul 15;112(2):362-73.

2013

Samuelsen CL, Gardner MP, Fontanini A. Thalamic contribution to cortical processing of taste and expectation. Journal of Neuroscience. 2013 Jan 30;33(5):1815-27.

Whitt JL, Masri R, Pulimood NS, Keller A. Pathological activity in mediodorsal thalamus of rats with spinal cord injury pain. Journal of Neuroscience. 2013 Feb 27;33(9):3915-26.

Wu J, Raver C, Piao C, Keller A, Faden AI. Cell cycle activation contributes to increased neuronal activity in the posterior thalamic nucleus and associated chronic hyperesthesia after rat spinal cord contusion. Neurotherapeutics. 2013 Jul 1;10(3):520-38.

2012

2011

Weiss DG. Neurotoxicity assessment by recording electrical activity from neuronal networks on microelectrode array neurochips. InCell culture techniques 2011 (pp. 467-480). Humana Press.

Cheer JF, Heien ML, Garris PA, Carelli RM, Wightman RM. Simultaneous dopamine and single-unit recordings reveal accumbens GABAergic responses: implications for intracranial self-stimulation. Proceedings of the National Academy of Sciences of the United States of America. 2005 Dec 27;102(52):19150-5.

2004

2002