Information Theory of the Heart Page: Difference between revisions
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''What'': To quantify information transmission within the heart<br> | ''What'': To quantify information transmission within the heart<br> | ||
Potential Metrics<br> | Potential Metrics<br> | ||
Mutual | Mutual information of two separate locations from binary time series (0–resting, 1–excited). A high mutual information suggests electrical coupling.<br> | ||
Permutation Entropy - Temporal uncertainty<br> | Permutation Entropy - Temporal uncertainty. Time series in rational numbers.<br> | ||
Transfer Entropy - Spatial uncertainty<br> | Transfer Entropy - Spatial uncertainty. Time series in rational numbers.<br> | ||
<br> | <br> | ||
'''06/13/2014 Unofficial Brainstorming Session'''<br> | '''06/13/2014 Unofficial Brainstorming Session'''<br> | ||
Revision as of 04:29, 14 June 2014
Contact: Hiroshi (hashika1@jhmi.edu)
Thank you for your interest in the project. Feel free to join us any time and share your thoughts!
06/12/2014 Brainstorming Session
Why: To identify adaptive mechanisms leading to cardiac arrhythmia in diseased hearts. Then localize the origin of arrhythmia (= wavebreak) and treat it before it happens.
Hypothesis: Arrhythmias result from an adaptive mechanism to optimize information transmission in abnormal hearts.
Challenge: Wavebreaks can also occur in normal heart tissue.
How: Time series from a cellular automata model of the 2-D heart tissue. ?Time series of invasive electrogram from animal or human
What: To quantify information transmission within the heart
Potential Metrics
Mutual information of two separate locations from binary time series (0–resting, 1–excited). A high mutual information suggests electrical coupling.
Permutation Entropy - Temporal uncertainty. Time series in rational numbers.
Transfer Entropy - Spatial uncertainty. Time series in rational numbers.
06/13/2014 Unofficial Brainstorming Session
Thank you all for suggesting excellent reference articles. Here is the list:
1. Cao et al., Detecting Dynamical Changes in Time Series Using the Permutation Entropy. Phys Rev E Stat Nonlin Soft Matter Phys 70: 046217, 2004 File:2004 CaoY PRE.pdf
2. Rosso et al., Distinguishing Noise from Chaos. Phys Rev Lett 99: 154102, 2007 File:2007 RossoOA PRL.pdf
3. Lacasa et al., From Time Series to Complex Networks: The Visibility Graph. PNAS 105: 4972, 2008 File:2008 LacasaL PNAS.pdf
4. Lizier et al., Local Information Transfer as a Spatiotemporal Filter for Complex Systems. Phys Rev E Stat Nonlin Soft Matter Phys 77: 026110, 2008 File:2008 LizierJT PRL.pdf
5. Cheong et al., Information Transduction Capacity of Noisy Biochemical Signaling Networks. Science 334: 354, 2011 File:2011 Cheong Science.pdf
Let's read the reference papers above this weekend and discuss what exactly we should measure at the next meeting. The next meeting will be at 02:30pm on Monday 06/16/2014 (after my tutorial[1]) in the lecture hall. If you have any questions I will be around this weekend. You will most certainly find me in the student lounge (or wherever TV is available) at 7pm on Saturday 06/14/2014 for FIFA World Cup Japan vs. Côte d'Ivoire!