A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Information Theory".
Deadline for manuscript submissions: 30 December 2018
It is, nowadays, widely acknowledged that the brain and several other organ systems, including the cardiovascular, respiratory, and muscular systems, among others, exhibit complex dynamic behaviors that result from the combined effects of multiple regulatory mechanisms, coupling effects and feedback interactions, acting in both space and time.
The field of information theory is becoming more and more relevant for the theoretical description and quantitative assessment of the dynamics of the brain and physiological networks, defining concepts, such as those of information generation, storage, transfer, and modification. These concepts are quantified by several information measures (e.g., approximate entropy, conditional entropy, multiscale entropy, transfer entropy, redundancy and synergy, and many others), which are being increasingly used to investigate how physiological dynamics arise from the activity and connectivity of different structural units, and evolve across a variety of physiological states and pathological conditions.
This Special Issue focuses on blending theoretical developments in the new emerging field of information dynamics with innovative applications targeted to the analysis of complex brain and physiological networks in health and disease. To favor this multidisciplinary view, contributions are welcome from different fields, ranging from mathematics and physics to biomedical engineering, neuroscience, and physiology.Prof. Dr. Luca Faes
Prof. Dr. Alberto Porta
Prof. Dr. Sebastiano Stramaglia
What is life? When Erwin Schrödinger posed this question in 1944, in a book of the same name, he was 57 years old. He had won the Nobel in Physics eleven years earlier, and was arguably past his glory days. Indeed, at that time he was working mostly on his ill-fated “Unitary Field Theory.” By all accounts, the publication of “What is Life?”—venturing far outside of a theoretical physicist’s field of expertise—raised many eyebrows. How presumptuous for a physicist to take on one of the deepest questions in biology! But Schrödinger argued that science should not be compartmentalized: “Some of us should venture to embark on a synthesis of facts and theories, albeit with second-hand and incomplete knowledge of some of them—and at the risk of making fools of ourselves.” Schrödinger’s “What is Life” has been extraordinarily influential, in one part because he was one of the first who dared to ask the question seriously, and in another because it was the book that was read by a good number of physicists—famously both Francis Crick and James Watson independently, but also many a member of the “Phage group,” a group of scientists that started the field of bacterial genetics—and steered them to new careers in biology. The book is perhaps less famous for the answers Schrödinger suggested, as almost all of them have turned out to be wrong.
Highlights, Quotes, & Marginalia
our existence can succinctly be described as “information that can replicate itself,” the immediate follow-up question is, “Where did this information come from?”
from an information perspective, only the first step in life is difficult. The rest is just a matter of time.
Through decades of work by legions of scientists, we now know that the process of Darwinian evolution tends to lead to an increase in the information coded in genes. That this must happen on average is not difficult to see. Imagine I start out with a genome encoding n bits of information. In an evolutionary process, mutations occur on the many representatives of this information in a population. The mutations can change the amount of information, or they can leave the information unchanged. If the information changes, it can increase or decrease. But very different fates befall those two different changes. The mutation that caused a decrease in information will generally lead to lower fitness, as the information stored in our genes is used to build the organism and survive. If you know less than your competitors about how to do this, you are unlikely to thrive as well as they do. If, on the other hand, you mutate towards more information—meaning better prediction—you are likely to use that information to have an edge in survival.
There are some plants with huge amounts of DNA compared to their “peers”–perhaps these would be interesting test cases for potential experimentation of this?Syndicated copies to:
The ability to integrate information in the brain is considered to be an essential property for cognition and consciousness. Integrated Information Theory (IIT) hypothesizes that the amount of integrated information ( Φ ) in the brain is related to the level of consciousness. IIT proposes that, to quantify information integration in a system as a whole, integrated information should be measured across the partition of the system at which information loss caused by partitioning is minimized, called the Minimum Information Partition (MIP). The computational cost for exhaustively searching for the MIP grows exponentially with system size, making it difficult to apply IIT to real neural data. It has been previously shown that, if a measure of Φ satisfies a mathematical property, submodularity, the MIP can be found in a polynomial order by an optimization algorithm. However, although the first version of Φ is submodular, the later versions are not. In this study, we empirically explore to what extent the algorithm can be applied to the non-submodular measures of Φ by evaluating the accuracy of the algorithm in simulated data and real neural data. We find that the algorithm identifies the MIP in a nearly perfect manner even for the non-submodular measures. Our results show that the algorithm allows us to measure Φ in large systems within a practical amount of time.
A summer school for advanced undergraduates June 11-22, 2018 @ Princeton University What would it mean to have a physicist’s understanding of life? How do DYNAMICS and the EMERGENCE of ORDER affect biological function? How do organisms process INFORMATION, LEARN, ADAPT, and EVOLVE? See how physics problems emerge from thinking about developing embryos, communicating bacteria, dynamic neural networks, animal behaviors, evolution, and more. Learn how ideas and methods from statistical physics, simulation and data analysis, optics and microscopy connect to diverse biological phenomena. Explore these questions, tools, and concepts in an intense two weeks of lectures, seminars, hands-on exercises, and projects.
The year is 4018. German is widely studied by scholars of classical antiquity, but all knowledge of the mysterious English language has died out. Scene: A classics department faculty lounge; a few professors are relaxing.
I worry about things like this all the time. Apparently it’s a terrible affliction that strikes those with a background in information theory at higher rates than the general public.Syndicated copies to:
The International Conference on Complex Systems is a unique interdisciplinary forum that unifies and bridges the traditional domains of science and a multitude of real world systems. Participants will contribute and be exposed to mind expanding concepts and methods from across the diverse field of complex systems science. The conference will be held July 22-27, 2018, in Cambridge, MA, USA. Special Topic - Artificial Intelligence: This year’s conference will include a day on AI, including its development and potential future. This session will be chaired by Iyad Rahwan of MIT's Media Lab.
A great looking conference coming up with a strong line up of people who’s work I appreciate. It could certainly use some more balance however as it’s almost all white men.
In particular I’d want to see:
Albert-László Barabási (Northeastern University, USA)
Nassim Nicholas Taleb (Real World Risk Institute, USA)
Stuart Kauffman (Institute for Systems Biology, USA)
Simon DeDeo (Carnegie Mellon University, USA)
Stephen Wolfram (Wolfram Research)
César Hidalgo (MIT Media Lab, USA)
Marta González (University of California Berkeley, USA)
Peter Turchin (University of Connecticut, USA)
Mercedes Pascual (University of Chicago, USA) Pending confirmation
Iyad Rahwan (MIT Media Lab, USA)
Sandy Pentland (MIT Media Lab, USA)
Theresa Whelan (U.S. Department of Defense) Pending DOD approval
H. Eugene Stanley (Boston University, USA)
Ricardo Hausmann (Harvard University, USA)
Stephen Grossberg (Boston University, USA)
Daniela Rus (MIT Computer Science & Artificial Intelligence Lab, USA) Pending confirmation
Olaf Sporns (Indiana University Network Science Institute, USA)
Michelle Girvan (University of Maryland, USA) Pending confirmation
Cameron Kerry (MIT Media Lab, USA)
Irving Epstein (Brandeis University, USA)
Algorithmic decipherment is a prime example of a truly unsupervised problem. The first step in the decipherment process is the identification of the encrypted language. We propose three methods for determining the source language of a document enciphered with a monoalphabetic substitution cipher. The best method achieves 97% accuracy on 380 languages. We then present an approach to decoding anagrammed substitution ciphers, in which the letters within words have been arbitrarily transposed. It obtains the average decryption word accuracy of 93% on a set of 50 ciphertexts in 5 languages. Finally, we report the results on the Voynich manuscript, an unsolved fifteenth century cipher, which suggest Hebrew as the language of the document.
Aside: It’s been ages since I’ve seen someone with Refbacks listed on their site!
Another high-profile instance of sexual harassment has rocked a major institution — this time Princeton University in New Jersey. And students say administrators didn’t act transparently or strongly enough when disciplining the alleged perpetrator, a decorated professor.
Once you start reaching Sergio Verdu’s age, and particularly with his achievements, your value to the University becomes more geared toward service. How much service can a professor do with an albatross like this hanging around their neck?
It would be nice if Universities were required to register offenders like this so that applicants to programs would be aware of them prior to applying–a sort of Megan’s Law for the professoriate. Naturally they don’t do this because it goes against their interests, but by the same token this is how a lot of issues run out of control within their sports programs as well. If someone did create such a website, I imagine the chilling effects on colleges and universities would be such that they might change their tunes about how these cases are handled. Immediately recent cases like Michigan State’s athletics problem, USC’s Medical School Dean issues, Christian Ott at Caltech come to mind, but I’m sure there must be hundreds if not thousands of others.
Fortunately even given Sergio’s accomplishments and profile, it will probably take forever for web searches for his name to not surface the story within the top couple of links, but this is sad consolation, particularly in a field like Information Theory which is heavily underrepresented already.Syndicated copies to:
Artificial intelligence has allowed scientists to make significant progress in cracking a mysterious ancient text, the meaning of which has eluded scholars for centuries.
Interesting news if it’s really true! Though I do feel a bit sad as there are some methods I had wanted to try on this longstanding puzzle, but never had the time to play with.Syndicated copies to:
DNA as a data storage medium has several advantages, including far greater data density compared to electronic media. We propose that schemes for data storage in the DNA of living organisms may benefit from studying the reconstruction problem, which is applicable whenever multiple reads of noisy data are available. This strategy is uniquely suited to the medium, which inherently replicates stored data in multiple distinct ways, caused by mutations. We consider noise introduced solely by uniform tandem-duplication, and utilize the relation to constant-weight integer codes in the Manhattan metric. By bounding the intersection of the cross-polytope with hyperplanes, we prove the existence of reconstruction codes with greater capacity than known error-correcting codes, which we can determine analytically for any set of parameters.
My ten hour white noise video now has five copyright claims! 🙂 pic.twitter.com/dX9PCM1qGx
— Sebastian Tomczak (@littlescale) January 4, 2018
Information Theory and signal processing FTW!
(Aside: This is a great example of how people really don’t understand our copyright system or science in general.)Syndicated copies to:
This paper answers Bell’s question: What does quantum information refer to? It is about quantum properties represented by subspaces of the quantum Hilbert space, or their projectors, to which standard (Kolmogorov) probabilities can be assigned by using a projective decomposition of the identity (PDI or framework) as a quantum sample space. The single framework rule of consistent histories prevents paradoxes or contradictions. When only one framework is employed, classical (Shannon) information theory can be imported unchanged into the quantum domain. A particular case is the macroscopic world of classical physics whose quantum description needs only a single quasiclassical framework. Nontrivial issues unique to quantum information, those with no classical analog, arise when aspects of two or more incompatible frameworks are compared.
Entropy 2017, 19(12), 645; doi:10.3390/e19120645
This article belongs to the Special Issue Quantum Information and FoundationsSyndicated copies to:
All living things are made of cells, and all cells are powered by electrochemical charges across thin lipid membranes — the ‘proton motive force.’ We know how these electrical charges are generated by protein machines at virtually atomic resolution, but we know very little about how membrane bioenergetics first arose. By tracking back cellular evolution to the last universal common ancestor and beyond, scientist Nick Lane argues that geologically sustained electrochemical charges across semiconducting barriers were central to both energy flow and the formation of new organic matter — growth — at the very origin of life. Dr. Lane is a professor of evolutionary biochemistry in the Department of Genetics, Evolution and Environment at University College London. His research focuses on how energy flow constrains evolution from the origin of life to the traits of complex multicellular organisms. He is a co-director of the new Centre for Life’s Origins and Evolution (CLOE) at UCL, and author of four celebrated books on life’s origins and evolution. His work has been recognized by the Biochemical Society Award in 2015 and the Royal Society Michael Faraday Prize in 2016.