GENE EXPRESSION AND ITS DISCONTENTS Developmental disorders as dysfunctions of epigenetic cognition



I(X|Y)=H(X)+H(Y)-H(X,Y),

which contains products of terms and their logs, sub ject
to constraints that the sums of probabilities are 1 and each
probability is itself between 0 and 1. Maximization is done
by varying the channel matrix terms P (y
j |xi) within the con-
straints. This is a difficult problem in nonlinear optimization.
However, for the special case M = L, C
* may be found by
inspection:

If M = L, then choose

P (yj |xi) = δj,i ,

where δi,j is 1 if i = j and 0 otherwise. For this special case

C* H(X),

with P (yk) = P(xk) for all k. Information is thus trans-
mitted without error when the channel becomes ‘typical’ with
respect to the fixed message distribution
P (X).

If M < L, matters reduce to this case, but for L < M infor-
mation must be lost, leading to Rate Distortion limitations.

Thus modifying the channel may be a far more efficient
means of ensuring transmission of an important message than
encoding that message in a ‘natural’ language which maxi-
mizes the rate of transmission of information on a fixed chan-
nel.

We have examined the two limits in which either the dis-
tributions of P (Y ) or of P (X) are kept fixed. The first pro-
vides the usual Shannon Coding Theorem, and the second a
tuning theorem variant, a tunable retina-like Rate Distortion
Manifold. It seems likely, however, than for many important
systems P(X) and P(Y ) will interpenetrate, to use Richard
Levins’ terminology. That is, P (X) and P (Y ) will affect each
other in characteristic ways, so that some form of mutual tun-
ing may be the most effective strategy.

19 Acknowledgments

The author thanks Dr. C. Guerrero-Bosagna for comments
useful in revision.

20 References

Ash R., 1990, Information Theory, Dover Publications, New
York.

Atlan, H., and I. Cohen, 1998, Immune information,
self-organization, and meaning,
International Immunology,
10:711-717.

Atmanspacher, H., 2006, Toward an information theoreti-
cal implementation of contextual conditions for consciousness,
Acta Biotheoretica, 54:157-160.

Baars, B.,1988, A Cognitive Theory of Consciousness,
Cambridge University Press, New York.

Baars, B., 2005, Global workspace theory of conscious-
ness: toward a cognitive neuroscience of human experience,
Progress in Brain Research, 150:45-53.

Backdahl, L., A. Bushell, and S. Beck, 2009, In-
flammatory signalling as mediator of epigenetic modu-
lation in tissue-specific chronic inflammation,
The In-
ternational Journal of Biochemistry and Cell Biology
,
doi:10.1016/j.biocel.2008.08.023.

Bennett, M., and P. Hacker, 2003, Philosophical Founda-
tions of Neuroscience
, Blackwell Publishing.

Bennett, C., 1988, Logical depth and physical complexity.
In
The Universal Turing Machine: A Half-Century Survey,
R. Herkin (ed.), pp. 227-257, Oxford University Press.

Bos, R., 2007, Continuous representations of groupoids,
arXiv:math/0612639.

Bossdorf, O., C. Richards, and M. Pigliucci, 2008, Epige-
netics for ecologists,
Ecology Letters, 11:106-115.

Britten, R., and E. Davidson, 1969, Gene regulation for
higher cells: a theory,
Science, 165:349-357.

Brown, R., 1987, From groups to groupoids: a brief survey,
Bulletin of the London Mathematical Society, 19:113-134.

Buneci, M., 2003, Representare de Groupoizi, Editura Mir-
ton, Timisoara.

Cannas Da Silva, A., and A. Weinstein, 1999, Geometric
Models for Noncommutative Algebras
, American Mathemati-
cal Society, RI.

Champagnat, N., R. Fierriere, and S. Melard, 2006, Uni-
fying evolutionary dynamics: from individual stochastic pro-
cesses to macroscopic models,
Theoretical Population Biology,
69:297-321.

Ciliberti, S., O. Martin, and A. Wagner, 2007a, Robust-
ness can evolve gradually in complex regulatory networks with
varying topology,
PLoS Computational Biology, 3(2):e15.

Cohen, I., 2006, Immune system computation and the im-
munological homunculus. In Nierstrasz, O., J. Whittle, D.
Harel, and G. Reggio (eds.), MoDELS 2006, LNCS, vol. 4199,
pp. 499-512, Springer, Heidelberg.

Cohen, I., and D. Harel, 2007, Explaining a complex living
system: dynamics, multi-scaling, and emergence.
Journal of
the Royal Society: Interface
, 4:175-182.

Cover, T., and J. Thomas, 1991, Elements of Information
Theory
, John Wiley and Sons, New York.

Crews, D., and J. McLachlan, 2006, Epigenetics, evolu-
tion, endocrine disruption, health, and disease,
Endocrinol-
ogy
, 147:S4-S10.

Crews, D., A. Gore, T. Hsu, N. Dangleben, M. Spinetta,
T. Schallert, M. Anway, and M. Skinner, 2007, Transgenera-
tional epigenetic imprints on mate preference,
Proceedings of
the National Academy of Sciences
, 104:5942-5946.

Dehaene, S., and L. Naccache, 2001, Towards a cognitive
neuroscience of consciousness: basic evidence and a workspace
framework,
Cognition, 79:1-37.

Dembo, A., and O. Zeitouni, 1998, Large Deviations: Tech-
niques and Applications
, 2nd edition, Springer, New York.

Dias, A., and I. Stewart, 2004, Symmetry groupoids and
admissible vector fields for coupled cell networks,
Journal of
the London Mathematical Society
, 69:707-736.

24




More intriguing information

1. Inflation and Inflation Uncertainty in the Euro Area
2. The changing face of Chicago: demographic trends in the 1990s
3. Palkkaneuvottelut ja työmarkkinat Pohjoismaissa ja Euroopassa
4. LAND-USE EVALUATION OF KOCAELI UNIVERSITY MAIN CAMPUS AREA
5. RETAIL SALES: DO THEY MEAN REDUCED EXPENDITURES? GERMAN GROCERY EVIDENCE
6. EMU's Decentralized System of Fiscal Policy
7. Achieving the MDGs – A Note
8. The name is absent
9. How to do things without words: Infants, utterance-activity and distributed cognition.
10. The name is absent