Özet
In extracellular neural recording data analysis, the quest for optimal amplitude thresholds for robust information extraction stands as a critical endeavor. Our study delves into two distinct thresholding methodologies: Truncation Thresholds and Otsu-based thresholds. The mean and the standard deviation of the subthreshold data segmented by the truncation thresholds are known to be good predictors of behavioral variables. On the other hand, Otsu-based thresholds have been shown to estimate subthreshold data's standard deviation more accurately in simulated data. The present study applies both methods to a real data set and reveals that the mean and the standard deviation of the subthreshold data segmented by either method are equivalent predictors of behavioral variables. We systematically gauge the prediction accuracy of the two methods and assess their computational efficiency. In light of computational considerations and real-time applicability, our research contributes to the evolution of amplitude thresholding techniques, thereby promoting their refinement for behavior prediction from neural recordings.
Orijinal dil | İngilizce |
---|---|
Ana bilgisayar yayını başlığı | TIPTEKNO 2023 - Medical Technologies Congress, Proceedings |
Yayınlayan | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Elektronik) | 9798350328967 |
DOI'lar | |
Yayın durumu | Yayınlandı - 2023 |
Etkinlik | 2023 Medical Technologies Congress, TIPTEKNO 2023 - Famagusta, Cyprus Süre: 10 Kas 2023 → 12 Kas 2023 |
Yayın serisi
Adı | TIPTEKNO 2023 - Medical Technologies Congress, Proceedings |
---|
???event.eventtypes.event.conference???
???event.eventtypes.event.conference??? | 2023 Medical Technologies Congress, TIPTEKNO 2023 |
---|---|
Ülke/Bölge | Cyprus |
Şehir | Famagusta |
Periyot | 10/11/23 → 12/11/23 |
Bibliyografik not
Publisher Copyright:© 2023 IEEE.