Decoding results from feature-based attention simulations with multiplicative attention modulation.

Decoding results from feature-based attention simulations with multiplicative attention modulation.

<p><b>A.</b> Histograms of the predicted identity of the attended stimulus for every trial in the <i>attention</i> task for the stimulated sub-network based on a circular ridge regression model trained on the <i>sensory</i> task, for a single network initial...

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מחבר ראשי:	Sunyoung Park (507160) (author)
מחברים אחרים:	John T. Serences (7181243) (author)
יצא לאור:	2025
נושאים:	Neuroscience Sociology Mental Health Biological Sciences not elsewhere classified Information Systems not elsewhere classified globally prime sensitivity early sensory areas random connections averaged completely random connections like representations arose behaviorally relevant stimuli second layer neurons based attentional modulations unstimulated sensory neurons different sensory neurons based attention </ spurious stimulus representations relevant stimulus led corresponding gain modulations modulating neurons tuned dimensional feature tuning feature selective neurons div >< p sensory neurons based attention spurious stimulus selective modulations relevant stimulus dimensional tuning neurons selective reciprocal connections relevant features neurons tuned without leading visual search subtly increasing spatial location single features results suggest responded robustly respond directly prefrontal cortex multiple features might interfere location – like high irrelevant features giving rise even modulate directly driven delicate balance cancelling benefits
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