Detecting long-range correlations in time series of neuronal discharges
✍ Scribed by S. Blesić; S. Milošević; Dj. Stratimirović; M. Ljubisavljević
- Publisher
- Elsevier Science
- Year
- 2003
- Tongue
- English
- Weight
- 315 KB
- Volume
- 330
- Category
- Article
- ISSN
- 0378-4371
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✦ Synopsis
We have studied the discharge dynamics of dorsal horn neurons (DHN) by applying the detrended uctuation analysis (DFA) and the wavelet transform (WT) technique. We have adopted that discharge dynamics is manifested by the random time series of the interspike intervals (ISI), that is, by intervals between two consecutive neuronal electrical activities. In all cases studied, we found two di erent power-law type behaviors across ISI enumeration scale, that are separated by a crossover region. Our results reveal that complex neuronal dynamics may change in the presence of external stimulation, which is manifested by changing the noise characteristics that appear before the crossover region (the noise after the crossover region is of the 1=f type).
📜 SIMILAR VOLUMES
Suppose our data {Xn} come from the model Xt = ∞ j = 0 cjZt-j, where {Zn} are i.i.d. with a symmetric distribution function which lies in the domain of normal attraction of a stable law with index ∈ (1; 2). Further we assume that cj = j d-1 L(j), where parameter d ∈ (0; 1 -1= ) and L is a normalized