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Processing raw electrophysiological signals in CARMEN:detecting and sorting spikes
Leslie Smith
University of Stirling
Spike detection and sorting: overview of talk
• What we originally envisaged• What we set about and did• What we have now• What it would be useful to have
Way back when….(2005)
• My RF, Nhamo Mtetwa spoke here in Newcastle …– And later when we had the initial meetings of what
became the CARMEN consortium• Something to bring electro-neurophysiological data
analysis into the 1990’s– Sharing datasets for multiple analysis
• Re-analysing datasets with different tools
– Aggregating datasets from related experiments by different people
Slide 5
Work Packages
WP 0Data Storage
& Analysis
WP1 Spike Detection& Sorting
WP2 Information TheoreticAnalysis of Derived Signals
WP 3 Data-Driven ParameterDetermination in
Conductance-Based Models
WP4 Measurement and Visualisationof Spike Synchronisation
WP5 Multilevel Analysis andModelling in Networks
WP4 Intelligent Database Querying
CARMEN and spike detection and sorting
Idea is to provide many services
Several different types of spike detection algorithmsSeveral different types of spike sorting techniques
(including different types of data reduction, as well as different types of clustering)
Allow the user to test with a variety of techniques, and then choose the techniques they prefer
High speed links should allow immediate transfer of some datasets to Grid based systems
Allow experimentalist to choose near-real-time detection and sorting for immediate feedback
To assist during the experimentSlower (and more effective) techniques for later analysis off-line.
Allow comparison of different techniques on a wide variety of dataWhich is best, and for what?
Where we are now
• NDF-based services related to spike detection and sorting– NDF High Pass Filter Service– Waveclus NDF High-Pass Filter– NDF Spike Detector – spbyplain– NDF Spike Sorter Service– Waveclus NDF Spike Detector– Waveclus NDF Spike Feature Extractor– Waveclus NDF Spike Sorter
• There are other non-NDF routines as well– Spike Detector – NEO– Spike Detector – Wave– Spike Detector – COB– Spike Detector – Morphological– Spike Detector - NEO– DUDE Service
Running these …
• These services may be run one at a time. – Each service requires the parameters to be selected
individually• Performing spike sorting needs several services to be
performed one after the other– Sequentially: each needs the output of the one before
• It all works– But it’s time consuming to try out (e.g.) a parameter
sweep.– Or to perform the same service sequence on a number
of datasets
What we’d like to have (1)
• All services to be available for NDF files• The ability to run parameter sweeps for spike sorting
– E.g. to try different spike detection techniques and parameters
• Simple thresholding• Energy based• Higher order statistics (Cepstrum of Bispectrum)
– To try different spike sorting parameters• The ability to run through a sequence of datasets
– Without running them one by one.
• And these need W*******s.
What we’d like to have (2)
• The ability to connect the processing to the timing of the stimulus
• Many files consist of recordings in response to some repeated stimulus– Manipulation of mouse vibrissae – Playing a sound to the animal, etc.
• This information is recorded in the stimulus file– we’d like to be able to use the stimulus time to determine
what processing should be done.
• This requires some standardisation of stimulus files (difficult)• And possibly a PSTH-like data format added to NDF
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