Bernal S D_2010.pdf - University of Plymouth

2.2. HIGH'lM^im,_WEDBACK
2004), and perceptual grouping mechanisms (Roelfsema 2006). Furthermore, some research
(Tiesinga and Buia 2009) has focused on the detailed circuitry required for biased compelilion
10 emerge in V4, and concluded it can feasibly arise as a result of feedforward projections from
VI and surround suppression mechanisms.
2.2.3.3 Feedback in Adaptive Resonance Theory (ART).
Although included in a different category, ART (Carpenter and Grossberg 1987. 1998) can be
considered a type of biased competition model as it has many similar properties. A central
feature in ART is the matching process that compares the bottom-up input with the stored pat­
tern. Unlike other networks, ART encodes only the matched or 'resonant" pattern and not the
actual input, as it suppresses all the portions which do not match the lop-down expectation, A
parameter, which specilies the minimum fraction thiii must remain in the matched palicni for
resonance to occur, ensures thai if the input is too novel or unexpected a new pattern code is
learned by the system.
The LAMINART model (Grossberg 2003. Grossberg et al. 2007, Raizada and Grossberg 2003)
implements the described ART mechanisms, mapping them over laminar visual cortical cir­
cuits. These mechanisms are hypothesized to occur in the neocortex to help stabilize cortical
development and learning. The model employs feedforward, feedback and horizontal interac-
lions to achieve the unification of several processes including development, learning, perceptual
grouping, attention and 3D vision.
A special emphasis has been placed on mtxielling the detailed laminar circuits of V1 and V2 in
order to achieve extra-classical receptive field effects such as perceptual grouping and allenlion.
The authors identify a list of requirements that any successful cortical model of visual percep­
tion should accomplish. Cortical models must allow perceptual grouping to generate activity in
a classical receptive Held with no direct visual stimuli (as happens with illusory contours) but
must prevent lop-down feedback from doing the same (i.e. producing above-threshold activity
on its own) in order to avoid hallucinations. However top-down feedback must be allowed to
provide modulatory sublhreshnid activity to enhance matching incoming sensory signals. This
is known as the prcattentive-attcntive interface problem.
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