Bernal S D_2010.pdf - University of Plymouth

3.4. EXISTING MODELS
Oulgoing
teedlorward
messages
IFI.GH.LM.LU)
|F1. QH. LM)
(F2,GH. LUI y
Incoming
teedOack
messages
11^1. LUl
(F1.GH. LU)
Outgoing Incoming
feedbac)! feedforward
messages messages
Kfiv IP ref&ronces
Fl -Fusion. 2006
F2-Fn>ton. 201D
GH -Gmrgea Kawkrns. 2010
LM-LEe8Muinlora.3lW3
LU-Lilva* S, Ullnian. 20M
Belief
catculaUon (LU)
Bdier
calculation (pagaii()n in a Bayt^sian network. Ri^hi) Potential mapping of this
scheme on the laminar cortical structure according lo four diftereni key references
which are labelled in the lop-right box. Arrows represent the origin or target
layer of the four differenl incuming/ouigoing feedforward/feedback message
lypes, together with ihe relevant references which support this view. Additionally,
the diagram also compares Ihe cortical layer hypLiihesized to implement the
belief calculation in two of the proposed mappings.
are major target of feedback connections. The mapping for the calculation of the belief (conver­
gence of feedforward and feedback infomialion) is also a major point of disagreement. While
George and Hawkins (2009) suggests it occurs at layer 5. (Litvak and Ullman 2(K)9) suggests
either the synapses between layer (i and 4 neurons, or (he strongly laterally connected layer
2/3 neurons, are responsible for the higher and lower information interaction. The discrepancy
might result from the ambiguous detinition of belief, which can be considered equivalent to the
output messages in some of the specific algorithms (Friston 2010, Litvak and Ullman 2009, Lee
and Mumford 2003).
The mapping of belief propagation models lo the cortical architecture is highly speculative and
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