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Abstract:
We present new simulation results, in which a computational
model of interacting visual neurons simultaneously predicts the
modulation of spatial vision thresholds by focal visual
attention, for five dual-task human psychophysics experiments.
This new study complements our previous findings that attention
activates a winner-take-all competition among early visual
neurons within one cortical hypercolumn. This ``intensified
competition'' hypothesis assumed that attention equally affects
all neurons, and yielded two single-unit predictions: an increase
in gain and a sharpening of tuning with attention. While both
effects have been separately observed in electrophysiology, no
single-unit study has yet shown them simultaneously. Hence, we
here explore whether our model could still predict our data if
attention might only modulate neuronal gain, but do so
non-uniformly across neurons and tasks. Specifically, we
investigate whether modulating the gain of only the neurons that
are loudest, best-tuned, or most informative about the stimulus,
or of all neurons equally but in a task-dependent manner, may
account for the data. We find that none of these hypotheses
yields predictions as plausible as the intensified competition
hypothesis, hence providing additional support for our original
findings.
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