Neurons, the fundamental processing unit
of the nervous system, produce electric signals called action
potentials or "spikes. Basic questions of how information
is coded and processed using these signals remain largely
unanswered. Comprehensive understanding of neural
coding will require collaboration between many
independent researchers recording from and analyzing the
temporal firing patterns of large ensembles of neurons.
Historically, electrophysiologists recorded the electrical
activity of single neurons as single-unit recordings. Advances
in multi-electrode recording techniques have allowed researchers
to record the simultaneous activity of increasingly larger
ensembles of neurons (up to hundreds of neurons), creating
“multi-unit” extra-cellular recordings. Preliminary
analysis of these multi-unit ensemble recordings indicates
that information may be coded in the joint activity
of multiple neurons. Unfortunately, proven techniques
to fully analyze this data are lacking.
Analysis tools for ensemble spike train data
are needed that can analyze a large number of responses
without sacrificing temporal resolution that may contain
key details of the information coding. NeuroMAX provides
many of these tools in the Spike Detection,
Spike Sorting, and Spike Train
Analysis toolboxes, and facilitates development
of new analysis tools.
Because you can mix and vary the NeuroMAX tools that you
use for analysis, you’ll be able to create a unique
processing sequence that’s customized to provide the
greatest insight possible into your data.
Spike Detection
The first challenges to deciphering your recorded extra-cellular
recording include separating the spike train from the background
noise and detecting individual spikes. The
Spike Detection
Toolbox provides Preprocess tools, such as the
FilterTool,
that readily pull potential spikes out of a confusing channel
of noisy data.
WaterfillThresh is one of
our Fragmentation tools that is immediately available to detect
spike activity before sending the processed results to the
next step in the analysis sequence:
Spike Sorting.
Spike Sorting
A series of detected spikes is only the beginning of the analysis
process. Next, you'll want to classify these potential spikes
to identify unique neuron firings, and to discard any spikes
that are actually noise.
A combination of NeuroMAX
Spike Sorting tools
(such as
FeatureExtract and
CreateSimulation)
as well as third party tools (such as
KMeansCluster
or
MClust) can be linked together through
NeuroMAX.
Spike Train Analysis
Action potentials have a stereotyped waveform that is not
generally stimulus dependent. It is generally assumed that
most information is conveyed by the
action potentials'
occurrence times. In some neural systems, it has
been demonstrated that gross firing rate is related to the
stimulus condition. However, the precise timing exhibited
by some neural systems, especially related to stimulus onset,
seems to indicate that the actual timing may also be important
for information coding.
One theory as to why
spike timing may be critical
is that information is coded in the temporal, correlated action
potential firing patterns of groups of neurons. Examples from
multi-unit recordings indicate that inter-neuronal correlated
firing patterns do occur and may be significant for information
coding. For example, the timing of specific neuronal firings
can be correlated to gross neurological activity. Tools in
the NeuroMAX
Spike Train Analysis toolbox
that assist with this correlation include the
Post-Stimulus
Time (PST) Histogram, which can show any correlation
of nerve firings with stimuli.
Display Tools
The power of the NeuroMAX
Display Tools is
the ability to combine raw data with processed data on the
same graphics display. Making a visual comparison of data
with different display options can often open the door to
new insight. In addition, a powerful graphics display lets
you print and publish results or share them with colleagues.
