Truncation thresholds: a pair of spike detection thresholds computed using   truncated probability distributions

Murat OKATAN; Mehmet KOCATÜRK

Makale detayları

Truncation thresholds: a pair of spike detection thresholds computed using truncated probability distributions

Yazarlar:

Murat OKATAN | Mehmet KOCATÜRK

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2017 Vol.25 Issue 2, pp.1436-1447

Belge Tipi:

Makale

Yayın Tarihi:

3/2017

Belge Dili:

Türkçe

Document ID (Org No.):

2000741130

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632

Özet:

 

We describe a method for computing a pair of spike   detection thresholds, called `truncation thresholds', using truncated   probability distributions, for extracellular recordings. In existing methods   the threshold is usually set to a multiple of an estimate of the standard   deviation of the noise in the recording, with the multiplication factor   being chosen between 3 and 5 according to the researcher's preferences. Our   method has the following advantages over these methods. First, because the   standard deviation is usually estimated from the entire recording, which   includes the spikes, it increases with firing rate. By contrast, truncation   thresholds decrease in absolute value with increasing firing rate, thereby   capturing more of the signal. Second, the parameters of the selected noise   distribution are estimated more accurately by maximum likelihood fitting of   the truncated distribution to the data delimited by the truncation   thresholds. Third, the computation of the truncation thresholds is   completely data-driven. It does not involve a user-defined multiplication   factor. Fourth, methods that use a threshold that is proportional to the   estimated standard deviation of the noise assume that the noise distribution   is symmetrical around the mean. By contrast, truncation thresholds are not   linked to each other by an assumption of symmetry about some axis. Fifth,   existing methods do not verify that subthreshold data obey a noise   distribution. Truncation thresholds, however, are defined by the fact that   the distribution of the data they delimit is statistically   indistinguishable, according to the Kolmogorov--Smirnov test, from a   selected distribution, truncated at those thresholds. Application of the   method is illustrated using recordings from cortical area M1 in awake   behaving rats, as well as in simulated recordings. Source code and   executables of a software suite that computes the truncation thresholds are   provided for the case when the noise distribution is modeled as truncated   normal.

Makale detayları

Truncation thresholds: a pair of spike detection thresholds computed using truncated probability distributions

Yazarlar: Murat OKATAN | Mehmet KOCATÜRK

Yayıncı: TUBITAK

Dergi: Turkish Journal of Electrical Engineering and Computer Science 2017 Vol.25 Issue 2, pp.1436-1447

Belge Tipi: Makale

Yayın Tarihi: 3/2017

Belge Dili: Türkçe

Document ID (Org No.): 2000741130

Sıklık: İki Aylık

eISSN: 1303-6203

pISSN: 1300-0632

Sayı

Yazarlar:

Murat OKATAN | Mehmet KOCATÜRK

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2017 Vol.25 Issue 2, pp.1436-1447

Belge Tipi:

Makale

Yayın Tarihi:

3/2017

Belge Dili:

Türkçe

Document ID (Org No.):

2000741130

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632