Fundamental limits in spike sorting

dc.contributor.advisorJohnson, Don H.en_US
dc.creatorSheikh, Mona A.en_US
dc.date.accessioned2009-06-03T21:06:56Zen_US
dc.date.available2009-06-03T21:06:56Zen_US
dc.date.issued2007en_US
dc.description.abstractSpike sorting refers to the detection and classification of electric potentials (spikes) from multi-neuron recordings. It is a difficult but essential pre-processing step before neural data can be analyzed for information content. While several spike sorting algorithms have been proposed, our goal is to determine the ultimate limits of spike classification, and to characterize this error regardless of sorting algorithm. We have identified and incorporated three important factors that affect the sorting procedure - SNR, spike amplitude ratio and inter-spike correlation - into a signal constellation model to derive error probability bounds on any sorting procedure. We consider the cases of known and unknown time-of-occurrence of the spike(s) in question. We calculate spike timing error estimates in the case of unknown delay. Additionally, we derive a theoretical amplitude distribution for spike amplitudes at the electrode. Finally we introduce the idea of a non-gaussian "corruption" noise component that affects spike waveform.en_US
dc.format.extent75 p.en_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.callnoTHESIS E.E. 2007 SHEIKHen_US
dc.identifier.citationSheikh, Mona A.. "Fundamental limits in spike sorting." (2007) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/20538">https://hdl.handle.net/1911/20538</a>.en_US
dc.identifier.urihttps://hdl.handle.net/1911/20538en_US
dc.language.isoengen_US
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.subjectElectronicsen_US
dc.subjectElectrical engineeringen_US
dc.titleFundamental limits in spike sortingen_US
dc.typeThesisen_US
dc.type.materialTexten_US
thesis.degree.departmentElectrical Engineeringen_US
thesis.degree.disciplineEngineeringen_US
thesis.degree.grantorRice Universityen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Scienceen_US
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