![](bg6.png)
5 CONCLUSIONS
In standard neural modeling, neurons are assumed to
show an integrate-and-fire-behavior. We have devel-
oped a computer simulation which also takes lateral
connections between neurons into account. Neurons
having the same function, i.e. neurons responding to
input in the same way, are assumed to be laterally con-
nected through gap junctions. The neurons integrate
their input. If this activation of the neuron is large
enough, then the neuron fires. The generated spike
train of the neuron is temporally and spatially inte-
grated. If the temporal average of the output is above
the average spatial average, then the neuron opens its
gap junctions to nearby neurons. Once this happens,
then the connected neurons synchronize their firing
behavior. This is a marker of consciousness. We
have shown how a virtual sheet of neurons responds
to visual input on a simulated retina segmenting fig-
ure from ground. Higher brain areas can use this data
for behaviors such as reaching or grasping.
REFERENCES
Carroll, T. L. and Pecora, L. M. (1991). Synchronizing
chaotic circuits. IEEE Trans. on Circuits and Systems,
38(4):453–456.
Chaumette, F. and Hutchinson, S. (2006). Visual servo con-
trol part I: Basic approaches. IEEE Robotics & Au-
tomation Magazine, 13(4):82–90.
Chaumette, F. and Hutchinson, S. (2007). Visual servo con-
trol part II: Advanced approaches. IEEE Robotics &
Automation Magazine, 14(1):109–118.
Crick, F. and Koch, C. (1995). Are we aware of neural
activity in primary visual cortex? Nature, 375:121–
123.
Dartnall, H. J. A., Bowmaker, J. K., and Mollon, J. D.
(1983). Human visual pigments: microspectrophoto-
metric results from the eyes of seven persons. Proc.
R. Soc. Lond. B, 220:115–130.
Eckhorn, R., Reitboeck, H. J., Arndt, M., and Dicke, P.
(1990). Feature linking via synchronization among
distributed assemblies: Simulations of results from cat
visual cortex. Neural Comput., 2:293–307.
Gerstner, W. and Kistler, W. (2002). Spiking Neuron Mod-
els. Cambridge University Press, Cambridge, UK.
Gray, C. M. and Singer, W. (1989). Stimulus-specific neu-
ronal oscillations in orientation columns of cat visual
cortex. PNAS, 86:1698–1702.
Hameroff, S. (2010). The “conscious pilot” – dendritic syn-
chrony moves through the brain to mediate conscious-
ness. Journal of Biological Physics, 36:71–93.
Herault, J. (1996). A model of colour processing in the
retina of vertebrates: From photoreceptors to colour
opposition and colour constancy phenomena. Neuro-
computing, 12:113–129.
Izhikevich, E. M. and Edelman, G. M. (2008). Large-scale
model of mammalian thalamocortical systems. PNAS,
105(9):3593–3598.
K¨onig, P. and Schillen, T. B. (1991). Stimulus-dependent
assembly formation of oscillatory responses: I. syn-
chronization. Neural Comput., 3:155–166.
Kouider, S. (2009). Neurobiological theories of conscious-
ness. In Banks, W. P., editor, Encyclopedia of Con-
sciousness, pages 87–100. Elsevier.
Lamme, V. A. F. (2006). Towards a true neural stance
on consciousness. Trends in Cognitive Sciences,
10(11):494–501.
Mountcastle, V. B. (1997). The columnar organization of
the neocortex. Brain, 120:701–722.
Pecora, L. M. and Carroll, T. L. (1990). Synchronization in
chaotic systems. Phys. Rev. Lett., 64(8):821–824.
Poynton, C. (2003). Digital Video and HDTV. Algorithms
and Interfaces. Morgan Kaufmann Publishers.
Ribary, U., Ioannides, A. A., Singh, K. D., Hasson, R.,
Bolton, J. P. R., Lado, F., Mogilner, A., and Llin´as,
R. (1991). Magnetic field tomography of coherent
thalamocortical 40-hz oscillations. PNAS, 88:11037–
11041.
Schillen, T. B. and K¨onig, P. (1991). Stimulus-dependent
assembly formation of oscillatory responses: II.
desynchronization. Neural Comput., 3:167–178.
Singer, W. (1999). Neuronal synchrony: A versatile code
for the definition of relations? Neuron, 24:49–65.
Terman, D. and Wang, D. (1995). Global competition and
local cooperation in a network of neural oscillators.
Physica D, 81:148–176.
Thivierge, J.-P. and Cisek, P. (2008). Nonperiodic synchro-
nization in heterogeneous networks of spiking neu-
rons. The Journal of Neuroscience, 28(32):7968–
7978.
Tononi, G. and Edelman, G. M. (1998). Consciousness and
complexity. Science, 282:1846–1851.
Tov´ee, M. J. (1996). An introduction to the visual system.
Cambridge University Press, Cambridge.
Traub, R. D., Kopell, N., Bibbig, A., Buhl, E. H., LeBeau, F.
E. N., and Whittington, M. A. (2001). Gap junctions
between interneuron dendrites can enhance synchrony
of gamma oscillations in distributed networks. The
Journal of Neuroscience, 21(23):9478–9486.
Veruki, M. L. and Hartveit, E. (2002). All (rod) amacrine
cells form a network of electrically coupled interneu-
rons in the mammalian retina. Neuron, 33:935–946.
Volos, C. K., Kyprianidis, I. M., and Stouboulos, I. N.
(2008). Experimental synchronization of two resis-
tively coupled Duffing-type circuits. Nonlinear Phe-
nomena in Complex Systems, 11(2):187–192.
Wang, D. (1995). Emergent synchrony in locally coupled
neural oscillators. IEEE Trans. on Neural Networks,
6(4):941–948.
A COMPUTATIONAL MODEL FOR CONSCIOUS VISUAL PERCEPTION AND FIGURE/GROUND SEPARATION
117