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Data
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Human Attentional Networks: A Connectionist Model (Wang and Fan 2007)
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"... We describe a connectionist model of human attentional networks to explore the
possible interplays among the networks from a computational
perspective. This model is developed in the framework of
leabra (local, error-driven, and associative, biologically realistic
algorithm) and simultaneously involves these attentional networks
connected in a biologically inspired way. ...
We evaluate the model by simulating the empirical data collected on normal human
subjects using the Attentional Network Test (ANT).
The simulation results fit the experimental data well.
In addition, we show that the same model, with a single parameter change that
affects executive control, is able to simulate the empirical data collected
from patients with schizophrenia.
This model represents a plausible connectionist explanation for the functional structure
and interaction of human attentional networks."
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