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Contact: Hiroshi (hashika1@jhmi.edu)<br>
Contact: Hiroshi (hashika1@jhmi.edu)<br>
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<br>
Thank you for your interest in the project, "''Information Theory of the Heart.''"  You can join us any time! Everyone is welcome.<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>
06/12/2014 04:30pm Brainstorming session<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>
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<br>
What: To quantify information transmission within the heart<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.
 
 


06/12/2014
We will be doing the 1st brainstorming session today at 4:15pm in the lecture hall.





Revision as of 04:03, 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.
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
Mutual information - Calculate mutual information of two separate locations from binary time series (0–resting, 1–excited). A high mutual information suggests electrical coupling.



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