Information Theory of the Heart Page: Difference between revisions
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''' | ''Contact'': Hiroshi (hashika1@jhmi.edu)<br> | ||
<br> | <br> | ||
Thank you for your interest in the project, "''Information Theory of the Heart.''" Please join us any time and share your thoughts!<br> | Thank you for your interest in the project, "''Information Theory of the Heart.''" Please join us any time and share your thoughts!<br> | ||
<br> | <br> | ||
'''06/12/2014 04:30pm Brainstorming session'''<br> | '''06/12/2014 04:30pm Brainstorming session'''<br> | ||
<br> | |||
''Why'': To identify adaptive mechanisms leading to cardiac arrhythmia in diseased hearts. To localize the origin of arrhythmia (= wavebreak) and treat it before it happens.<br> | ''Why'': To identify adaptive mechanisms leading to cardiac arrhythmia in diseased hearts. To localize the origin of arrhythmia (= wavebreak) and treat it before it happens.<br> | ||
<br> | <br> | ||
''Hypothesis'': Arrhythmias result from an adaptive mechanism to optimize information transmission in abnormal hearts.<br> | ''Hypothesis'': Arrhythmias result from an adaptive mechanism to optimize information transmission in abnormal hearts.<br> | ||
<br> | |||
''Challenge'': Wavebreaks can occur in normal heart tissue.<br> | ''Challenge'': Wavebreaks can occur in normal heart tissue.<br> | ||
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''How'': Time series from a cellular automata model of the 2-D heart tissue. ?Time series of invasive electrogram from animal or human<br> | ''How'': Time series from a cellular automata model of the 2-D heart tissue. ?Time series of invasive electrogram from animal or human<br> | ||
<br> | |||
''What'': To quantify information transmission within the heart<br> | ''What'': To quantify information transmission within the heart<br> | ||
Potential Metrics<br> | |||
Mutual information - Calculate mutual information of two separate locations from binary time series (0–resting, 1–excited). A high mutual information suggests electrical coupling.<br> | |||
Permutation Entropy - <br> | |||
Transfer Entropy - <br> | |||
Revision as of 04:08, 14 June 2014
Contact: Hiroshi (hashika1@jhmi.edu)
Thank you for your interest in the project, "Information Theory of the Heart." Please join us any time and share your thoughts!
06/12/2014 04:30pm Brainstorming session
Why: To identify adaptive mechanisms leading to cardiac arrhythmia in diseased hearts. To 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 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 - Calculate mutual information of two separate locations from binary time series (0–resting, 1–excited). A high mutual information suggests electrical coupling.
Permutation Entropy -
Transfer Entropy -
Thank you all for suggesting useful 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