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

From a presentation in November 2006 …

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

Nice graphics too

And more …

And from WaveClus

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

CARMEN Consortium