Dear Ken & Pedro, Unfortunately, I have not read Friston's thesis. In his abstract he writes, "Furthermore, if we look closely at what is optimized, the same quantity keeps emerging, namely value (expected reward, expected utility) or its complement, surprise (prediction error, expected cost). This is the quantity that is optimized under the free-energy principle..."
When one is dealing with complementary values, optimization usually infers some balance. Is this what Friston means? If so, that is quite similar to the balance between mutually-exclusive attributes that we observe when we apply Shannon-like calculus to ecosystem trophic exchange networks. (See Fig 7 on p1890 in <http://people.biology.ufl.edu/ulan/pubs/Dual.pdf>.) Very interesting! Bob U. > Nature Reviews Neuroscience 11, 127-138 (February 2010) | doi > :10.1038/nrn2787 > http://www.nature.com/nrn/journal/v11/n2/full/nrn2787.html > > :) Ken > > On Fri, Dec 12, 2014 at 8:19 AM, Pedro C. Marijuan < > pcmarijuan.i...@aragon.es> wrote: >> >> Dear Loet, Steven, and colleagues, >> >> During last ten years or so, with particular success in most recent >> years, >> Karl Friston has developed his free energy optimization principle, based >> on >> Shannon's information theory and optimal control theory as well as on >> the >> Bayesian brain hypothesis. I think this is the most advanced work >> towards a >> unified brain theory today. The minimization dynamics of the cerebral >> free >> energy construct (it is a sort of Helmoltz program revisited) becomes a >> generative process of perception, action, learning and adaptive >> behaviors >> in general. The 2010 paper (Nature Reviews Neurosceince, doi: >> 10.138/nrn2787) where he precisely argues about a unified brain theory, >> is >> quite representative of his proposals. On a personal basis, during last >> two >> decades I was following and cooperating with Kenneth Paul Collins (we >> published a book in Spanish about the emergence of behavior from brain >> dynamics). Our scheme was based on the minimization of a collective >> variable supposedly a sort of "entropy" of excitation/inhibition ratios >> topologically distributed among neuronal surfaces of the cortex that was >> performed essentially by the medial parts of the brain. Although very >> rich >> in qualitative and behavioral aspects, the formal part was too weak >> (awfully weak). Until recent years I could not connect meaningfully >> Collin's approach with other works, and unfortunately he left scientific >> research long ago--but now the marriage with Friston's is remarkable. >> Putting them together may be a very fertile exploratory avenue. >> >> best ---Pedro >> >> Loet Leydesdorff wrote: >> >>> >>> Dear Steven and colleagues, >>> >>> >>> I did not (yet) study your approach. Is there a paper that can be read >>> as >>> an introduction? >>> >>> >>> It seems to me that one can distinguish between formal and substantial >>> theories of information. Shannonâs mathematical theory is a formal >>> apparatus: the design and the results do not yet have meaning without >>> an >>> interpretation in a substantial context. On the other side, a theory >>> about, >>> for example, neuro-information is a special theory. One can in this >>> context >>> use information theory as a statistical tool (among other tools). >>> Sometimes, one can move beyond description. J >>> >>> >>> The advantage of information theory, from this perspective of special >>> theories, is that the formal apparatus allows us sometimes to move >>> between >>> domains heuristically. For example, a model of the brain can perhaps be >>> used metaphorically for culture or the economy (or vice versa). The >>> advantages have to be shown in empirical research: which questions can >>> be >>> addressed and which puzzles be solved? >>> >>> >>> Best, >>> >>> Loet >>> >>> >>> ------------------------------------------------------------------------ >>> >>> Loet Leydesdorff >>> >>> /Emeritus/ University of Amsterdam >>> Amsterdam School of Communications Research (ASCoR) >>> >>> l...@leydesdorff.net <mailto:l...@leydesdorff.net>; >>> http://www.leydesdorff.net/ >>> Honorary Professor, SPRU, <http://www.sussex.ac.uk/spru/>University of >>> Sussex; >>> >>> Guest Professor Zhejiang Univ. <http://www.zju.edu.cn/english/>, >>> Hangzhou; Visiting Professor, ISTIC, <http://www.istic.ac.cn/Eng/ >>> brief_en.html>Beijing; >>> >>> Visiting Professor, Birkbeck <http://www.bbk.ac.uk/>, University of >>> London; >>> >>> http://scholar.google.com/citations?user=ych9gNYAAAAJ&hl=en < >>> http://scholar.google.com/citations?user=ych9gNYAAAAJ&hl=en> >>> >>> >>> *From:* stevenzen...@gmail.com [mailto:stevenzen...@gmail.com] *On >>> Behalf Of *Steven Ericsson-Zenith >>> *Sent:* Tuesday, December 09, 2014 10:13 PM >>> *To:* l...@leydesdorff.net >>> *Cc:* Joseph Brenner; fis >>> *Subject:* Re: [Fis] Information-as-Process >>> >>> >>> The problem with this approach (and approaches like it) is that it is >>> descriptive and not explanatory. The distribution of the shape, in my >>> model, can be described, perhaps, but the process or action decision >>> point >>> and response covariance is impossible to consider. >>> >>> It is for this reason that I use holomorphic functors and >>> hyper-functors >>> in which I can express the explicit role of a base universal (per >>> gravitation). >>> >>> >>> Nor is it clear to me that this is what Joe referred to as "information >>> as process." >>> >>> >>> On Mon, Dec 8, 2014 at 10:20 PM, Loet Leydesdorff <l...@leydesdorff.net >>> <mailto:l...@leydesdorff.net>> wrote: >>> >>> Dear colleagues, >>> >>> >>> Shannonâs information theory can be considered as a calculus >>> because it allows for the dynamic extension. Theil >>> (1972)âStatistical decomposition analysis (North >>> Holland)âdistinguished between static and dynamic information >>> measures. In addition to Shannonâs statical H, one can write: >>> >>> >>> mailbox:///C|/Documents%20and% >>> 20Settings/pcmarijuan.iacs/Datos%20de%20programa/ >>> Thunderbird/Profiles/2vg9i0k9.default/Mail/pop3.aragon-1.es/ >>> Inbox?number=1793468636&header=quotebody&part=1.1.2&filename=image001.png >>> >>> >>> in which >>> mailbox:///C|/Documents%20and%20Settings/pcmarijuan.iacs/ >>> Datos%20de%20programa/Thunderbird/Profiles/2vg9i0k9.default/Mail/ >>> pop3.aragon-1.es/Inbox?number=1793468636&header=quotebody&part=1.1.3& >>> filename=image002.pngcan >>> be considered as the a posteriori and >>> mailbox:///C|/Documents%20and%20Settings/pcmarijuan.iacs/ >>> Datos%20de%20programa/Thunderbird/Profiles/2vg9i0k9.default/Mail/ >>> pop3.aragon-1.es/Inbox?number=1793468636&header=quotebody&part=1.1.4& >>> filename=image003.pngthe >>> a priori distribution. This dynamic information measure can be >>> decomposed and aggregated. One can also develop measures for >>> systemic developments and critical transitions. In other words, >>> information as a process can also be measured in bits of >>> information. Of course, one can extend the dimensionality (/i/) >>> for the multivariate case (/ijk/â¦), and thus use information >>> theory for network analysis (including time). >>> >>> >>> Best, >>> >>> Loet >>> >>> >>> References: >>> >>> · Leydesdorff, L. (1991). The Static and Dynamic Analysis >>> of Network Data Using Information Theory. /Social Networks, >>> 13/(4), 301-345. >>> >>> · Theil, H. (1972). /Statistical Decomposition Analysis/. >>> Amsterdam/ London: North-Holland. >>> >>> >>> >>> ------------------------------------------------------------ >>> ------------ >>> >>> Loet Leydesdorff >>> >>> /Emeritus/ University of Amsterdam >>> Amsterdam School of Communications Research (ASCoR) >>> >>> l...@leydesdorff.net <mailto:l...@leydesdorff.net>; >>> http://www.leydesdorff.net/ >>> Honorary Professor, SPRU, >>> <http://www.sussex.ac.uk/spru/>University of Sussex; >>> >>> Guest Professor Zhejiang Univ. <http://www.zju.edu.cn/english/>, >>> Hangzhou; Visiting Professor, ISTIC, >>> <http://www.istic.ac.cn/Eng/brief_en.html>Beijing; >>> >>> Visiting Professor, Birkbeck <http://www.bbk.ac.uk/>, University >>> of London; >>> >>> http://scholar.google.com/citations?user=ych9gNYAAAAJ&hl=en >>> <http://scholar.google.com/citations?user=ych9gNYAAAAJ&hl=en> >>> >>> >>> *From:* Fis [mailto:fis-boun...@listas.unizar.es >>> <mailto:fis-boun...@listas.unizar.es>] *On Behalf Of *Steven >>> Ericsson-Zenith >>> *Sent:* Monday, December 08, 2014 10:22 PM >>> *To:* Joseph Brenner >>> *Cc:* fis >>> *Subject:* Re: [Fis] Information-as-Process >>> >>> >>> I am a little mystified by your assertion of "information as >>> process." What, exactly, is this and how does it differ fro >>> information in general (Shannon). Is it related to Whitehead's >>> process notions? >>> >>> >>> In terms of neuroscience it is important to move away from >>> connectionism and modern computational ideas I believe. It is not >>> clear to me how information theory can be applied to the operation >>> of the brain at the synaptic level because the actions and the >>> decisions made are made across the structure and not at a single >>> location. >>> >>> Recognition, for example, is not a point event but occurs rather >>> when a particular shape is formed in the structure (of the CNS, >>> for example) and is immediately covariant with the "appropriate" >>> response (another shape) which may be characterized as a >>> hyper-functor (which may or may not include neurons and astrocytes >>> in the brain). >>> >>> >>> Regards, >>> >>> Steven >>> >>> >>> >>> >>> >> >> >> -- >> ------------------------------------------------- >> Pedro C. Marijuán >> Grupo de Bioinformación / Bioinformation Group >> Instituto Aragonés de Ciencias de la Salud >> Centro de Investigación Biomédica de Aragón (CIBA) >> Avda. San Juan Bosco, 13, planta X >> 50009 Zaragoza, Spain >> Tfno. +34 976 71 3526 (& 6818) >> pcmarijuan.i...@aragon.es >> http://sites.google.com/site/pedrocmarijuan/ >> ------------------------------------------------- >> >> >> _______________________________________________ >> Fis mailing list >> Fis@listas.unizar.es >> http://listas.unizar.es/cgi-bin/mailman/listinfo/fis >> > > > -- > Ken Herold > Director, Library Information Systems > Hamilton College > 198 College Hill Road > Clinton, NY 13323 > 315-859-4487 > kher...@hamilton.edu > _______________________________________________ > Fis mailing list > Fis@listas.unizar.es > http://listas.unizar.es/cgi-bin/mailman/listinfo/fis > _______________________________________________ Fis mailing list Fis@listas.unizar.es http://listas.unizar.es/cgi-bin/mailman/listinfo/fis
