A Python Code for Maximum Likelihood Estimation of the Location and Scale Parameters of the Truncated Normal Distribution

Melih Yilmaz Ogutcen, Mehmet Kocaturk, Murat Okatan

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde BölümKonferans katkısıbilirkişi

Özet

Extracellular neural recordings obtained from chronically implanted microelectrode arrays are widely used in behavioral neurophysiology and invasive brain-machine interfaces. After the raw recordings are band-pass filtered within a frequency band suitable for spike detection, spikes are often detected by amplitude thresholding. Developing principled methods for computing amplitude thresholds is an active research area. 'Truncation thresholds' are a pair of amplitude thresholds that are computed using a recently proposed algorithm. As part of an effort that aims to integrate this algorithm into a real-Time data acquisition and spike detection system, here we present a Python code for maximum likelihood estimation of the location and scale parameters of the truncated Normal distribution, which is one of the steps involved in the computation of truncation thresholds.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığıTIPTEKNO 2021 - Tip Teknolojileri Kongresi - 2021 Medical Technologies Congress
YayınlayanInstitute of Electrical and Electronics Engineers Inc.
ISBN (Elektronik)9781665436632
DOI'lar
Yayın durumuYayınlandı - 2021
Etkinlik2021 Medical Technologies Congress, TIPTEKNO 2021 - Antalya, Turkey
Süre: 4 Kas 20216 Kas 2021

Yayın serisi

AdıTIPTEKNO 2021 - Tip Teknolojileri Kongresi - 2021 Medical Technologies Congress

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???event.eventtypes.event.conference???2021 Medical Technologies Congress, TIPTEKNO 2021
Ülke/BölgeTurkey
ŞehirAntalya
Periyot4/11/216/11/21

Bibliyografik not

Publisher Copyright:
© 2021 IEEE.

Finansman

This work was supported by Research Fund of the Istanbul Technical University. Project Number: MAB-2020-42808.

FinansörlerFinansör numarası
Istanbul Teknik ÜniversitesiMAB-2020-42808

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