[Fis] Information-as-Process
Pedro C. Marijuan
pcmarijuan.iacs at aragon.es
Fri Dec 12 14:19:33 CET 2014
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. Shannon’s 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)
>
> loet at leydesdorff.net <mailto:loet at 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:* stevenzenith at gmail.com [mailto:stevenzenith at gmail.com] *On
> Behalf Of *Steven Ericsson-Zenith
> *Sent:* Tuesday, December 09, 2014 10:13 PM
> *To:* loet at 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
> <loet at leydesdorff.net <mailto:loet at leydesdorff.net>> wrote:
>
> Dear colleagues,
>
>
>
> Shannon’s information theory can be considered as a calculus
> because it allows for the dynamic extension. Theil
> (1972)—Statistical decomposition analysis (North
> Holland)—distinguished between static and dynamic information
> measures. In addition to Shannon’s 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/…), 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)
>
> loet at leydesdorff.net <mailto:loet at 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-bounces at listas.unizar.es
> <mailto:fis-bounces at 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.iacs at aragon.es
http://sites.google.com/site/pedrocmarijuan/
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