Quantifying Time-Varying Multiunit Neural Activity Using Entropy-Based Measures

被引:25
作者
Choi, Young-Seok [1 ]
Koenig, Matthew A. [2 ]
Jia, Xiaofeng [3 ]
Thakor, Nitish V. [1 ]
机构
[1] Johns Hopkins Sch Med, Dept Biomed Engn, Baltimore, MD 21205 USA
[2] Johns Hopkins Univ, Sch Med, Dept Neurol, Baltimore, MD 21287 USA
[3] Johns Hopkins Sch Med, Dept Biomed Engn & Phys Med & Rehabil, Baltimore, MD 21205 USA
基金
美国国家卫生研究院;
关键词
Brain injury; cardiac arrest (CA); discrete wavelet transform (DWT); envelope; Kullback-Leibler distance (KLD); multiresolution; multiunit activity (MUA); Shannon entropy; SPIKE DETECTION; QUANTITATIVE EEG; WAVELET ENTROPY; CARDIAC-ARREST; RECORDINGS; HYPOTHERMIA; LEIBLER;
D O I
10.1109/TBME.2010.2049266
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Modern microelectrode arrays make it possible to simultaneously record population neural activity. However, methods to analyze multiunit activity (MUA), which reflects the aggregate spiking activity of a population of neurons, have remained underdeveloped in comparison to those used for studying single unit activity (SUA). In scenarios where SUA is hard to record and maintain or is not representative of brain's response, MUA is informative in deciphering the brain's complex time-varying response to stimuli or to clinical insults. Here, we present two quantitative methods of analysis of the time-varying dynamics of MUA without spike detection. These methods are based on the multiresolution discrete wavelet transform (DWT) of an envelope of MUA (eMUA) followed by information theoretic measures: multiresolution entropy (MRE) and the multiresolution Kullback-Leibler distance (MRKLD). We test the proposed quantifiers on both simulated and experimental MUA recorded from rodent cortex in an experimental model of global hypoxic-ischemic brain injury. First, our results validate the use of the eMUA as an alternative to detecting and analyzing transient and complex spike activity. Second, the MRE and MRKLD are shown to respond to dynamic changes due to the brain's response to global injury and to identify the transient changes in the MUA.
引用
收藏
页码:2771 / 2777
页数:7
相关论文
共 40 条
[1]   Wavelet entropy for subband segmentation of EEG during injury and recovery [J].
Al-Nashash, HA ;
Paul, JS ;
Ziai, WC ;
Hanley, DF ;
Thakor, NV .
ANNALS OF BIOMEDICAL ENGINEERING, 2003, 31 (06) :653-658
[2]  
[Anonymous], 1992, CBMS-NSF Reg. Conf. Ser. in Appl. Math
[3]   Dynamic analyses of information encoding in neural ensembles [J].
Barbieri, R ;
Frank, LM ;
Nguyen, DP ;
Quirk, MC ;
Solo, V ;
Wilson, MA ;
Brown, EN .
NEURAL COMPUTATION, 2004, 16 (02) :277-307
[4]   Time-dependent entropy estimation of EEG rhythm changes following brain ischemia [J].
Bezerianos, A ;
Tong, S ;
Thakor, N .
ANNALS OF BIOMEDICAL ENGINEERING, 2003, 31 (02) :221-232
[5]   Multiple neural spike train data analysis: state-of-the-art and future challenges [J].
Brown, EN ;
Kass, RE ;
Mitra, PP .
NATURE NEUROSCIENCE, 2004, 7 (05) :456-461
[6]   Shannon entropy applied to the measurement of the electroencephalographic effects of desflurane [J].
Bruhn, J ;
Lehmann, LE ;
Röpcke, H ;
Bouillon, TW ;
Hoeft, A .
ANESTHESIOLOGY, 2001, 95 (01) :30-35
[7]   Wavelet methods for spike detection in mouse renal sympathetic nerve activity [J].
Brychta, Robert J. ;
Tuntrakool, Sunti ;
Appalsamy, Martin ;
Keller, Nancy R. ;
Robertson, David ;
Shiavi, Richard G. ;
Diedrich, Andre .
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2007, 54 (01) :82-93
[8]   AMPLITUDES OF BACKGROUND FAST ACTIVITY CHARACTERISTIC OF SPECIFIC BRAIN SITES [J].
BUCHWALD, JS ;
GROVER, FS .
JOURNAL OF NEUROPHYSIOLOGY, 1970, 33 (01) :148-&
[9]   Large-scale recording of neuronal ensembles [J].
Buzsáki, G .
NATURE NEUROSCIENCE, 2004, 7 (05) :446-451
[10]  
Dayan P., 2001, Theoretical neuroscience: computational and mathematical modeling of neural systems