.. title: A neurocentric approach to Bayesian inference
.. slug: 2010-09-03-A-neurocentric-approach-to-Bayesian-inference
.. date: 2010-09-03 13:36:57
.. type: text
.. tags: sciblog
- one-page paper arguing that Friston's free-energy view may not be
complete. Some points made are
#. the inversion operated assumes a generative model
#. the use of surprise is defined using a frequentist approach not
informational
- one idea : from the frequentist measure one one can derive a
conditional probability (a Xhi-2 distribution) of the
probability. Not very far to the idea of Sahani & Dayan of a
double probabilistic distribution
#. explore surprise or avoid it: Fiorillo makes here a confusion of
time scales. On the long term (learning) one tends to avoid
surprise, on the short term (coding) this implies one jumps one
surprise.
#. points to his PLoS one paper: Fiorillo, C. D. Towards a general
theory of neural computation based on prediction by single
neurons. `PLoS ONE 3, e3298
(2008) `__
.. TEASER_END
- once again, people love bipolarity: frequentists against
probabilists, top-down vs. bottom-up, neurocentric vs global.
neurons, areas, brains, groups of brains just don't care and evolve.
it is our description that can be multiple. does a single one
("unified theory") exists iun today's language? at least I am
convinced that (over generations) neurons adapt to behavior not the
inverse, thus that if one has to seek for an information measure, it
is certainly not in a ion's channel dynamic *only*.
- the answer of Friston goes into that direction / correctly defines
surprise / nice figure showing how one can learn "to be a Lorenz
attractor" (certainly assuming a generative model of dynamics)
- the open question is rather "how is the free-energy principle encoded
in the brain's architecture and dynamics?"
reference
---------
- Christopher D. Fiorillo. A neurocentric approach to Bayesian
inference, `URL `__ . *Nature
Reviews Neuroscience*, **11**\ (8):605, 2010
A primary function of the brain is to infer the state of the world in
order to determine which motor behaviours will best promote adaptive
fitness. Bayesian probability theory formally describes how rational
inferences ought to be made, and it has been used with great success
in recent years to explain a range of perceptual and sensorimotor
phenomena1, 2, 3, 4, 5.
.
- Karl Friston. Is the free-energy principle neurocentric?,
`URL `__ . *Nature Reviews
Neuroscience*, **11**\ (8):605, 2010
Recently, a free-energy formulation of brain function was reviewed in
relation to several other neurobiological theories (The free-energy
principle: a unified brain theory? Nature Rev. Neurosci. 11, 127–138
(2010)
.