Detecting Space-Time Alternating Biological Signals Close to the Bifurcation Point

• Published in: IEEE transactions on biomedical engineering Vol. 57; no. 2; pp. 316 - 324
• Main Authors: Jia, Zhiheng, Bien, Harold, Entcheva, Emilia
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.02.2010; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Alternans detection; Bifurcation; bifurcation point; Biological and medical sciences; Biomedical optical imaging; Cardiac dysrhythmias; Cardiology. Vascular system; Databases, Factual; Electrocardiography - methods; Evolution (biology); Fundamental and applied biological sciences. Psychology; Heart; Medical sciences; Models, Biological; Myocytes, Cardiac - physiology; Noise; Optical noise; Phase detection; Phase measurement; Phase noise; Reproducibility of Results; Signal detection; Signal Processing, Computer-Assisted; space-time; Spatiotemporal phenomena; temporal persistence; Vertebrates: cardiovascular system; White noise; Heart; Human; Arrhythmia; bifurcation point; Biological model; space-time; Electrophysiology; Theoretical study; Cardiovascular disease; Algorithm; Electrodiagnosis; Alternans detection; Heart disease; Cardiomyocyte; Electrocardiography; Signal processing; Physiology; temporal persistence; Circulatory system; Biomedical engineering
• ISSN: 0018-9294; 1558-2531
• DOI: 10.1109/TBME.2009.2028652

Time-alternating biological signals, i.e., alternans, arise in variety of physiological states marked by dynamic instabilities, e.g., period doubling. Normally, a sequence of large-small-large transients, they can exhibit variable patterns over time and space, including spatial discordance. Capture of the early formation of such alternating regions is challenging because of the spatiotemporal similarities between noise and the small-amplitude alternating signals close to the bifurcation point. We present a new approach for automatic detection of alternating signals in large noisy spatiotemporal datasets by exploiting quantitative measures of alternans evolution, e.g., temporal persistence, and by preserving phase information. The technique specifically targets low amplitude, relatively short alternating sequences and is validated by combinatorics-derived probabilities and empirical datasets with white noise. Using high-resolution optical mapping in live cardiomyocyte networks, exhibiting calcium alternans, we reveal for the first time early fine-scale alternans, close to the noise level, which are linked to the later formation of larger regions and evolution of spatially discordant alternans. This robust method aims at quantification and better understanding of the onset of cardiac arrhythmias and can be applied to general analysis of space-time alternating signals, including the vicinity of the bifurcation point.