A neural network model is developed to explain how visual thalamocorti
cal interactions give rise to boundary percepts such as illusory conto
urs and surface percepts such as filled-in brightnesses. Top-down feed
back interactions are needed in addition to bottom-up feed-forward int
eractions to simulate these data. One feedback loop is modeled between
lateral geniculate nucleus (LGN) and cortical area V1, and another wi
thin cortical areas V1 and V2. The first feedback loop realizes a matc
hing process which enhances LGN cell activities that are consistent wi
th those of active cortical cells, and suppresses LGN activities that
are not. This corticogeniculate feedback, being endstopped and oriente
d, also enhances LGN ON cell activations at the ends of thin dark line
s, thereby leading to enhanced cortical brightness percepts when the l
ines group into closed illusory contours. The second feedback loop gen
erates boundary representations, including illusory contours, that coh
erently bind distributed cortical features together. Brightness percep
ts form within the surface representations through a diffusive filling
-in process that is contained by resistive gating signals from the bou
ndary representations. The model is used to simulate illusory contours
and surface brightnesses induced by Ehrenstein disks, Kanizsa squares
, Glass patterns, and cafe wall patterns in single contrast, reverse c
ontrast, and mixed contrast configurations. These examples illustrate
how boundary and surface mechanisms can generate percepts that are hig
hly context-sensitive, including how illusory contours can be amodally
recognized without being seen, how model simple cells in V1 respond p
referentially to luminance discontinuities using inputs from both LGN
ON and OFF cells, how model bipole cells in V2 with two colinear recep
tive fields can help to complete curved illusory contours, how short-r
ange simple cell groupings and long-range bipole cell groupings can so
metimes generate different outcomes, and how model double-opponent, fi
lling-in and boundary segmentation mechanisms in V4 interact to genera
te surface brightness percepts in which filling-in of enhanced brightn
ess and darkness can occur before the net brightness distribution is c
omputed by double-opponent interactions.