Computational modeling plays an important role to understand the mechanisms of attention. In this framework, synthetic computational models can uniquely contribute to integrate different explanatory levels and neurocognitive findings, with special reference to the integration of attention and awareness processes. Novel combined experimental and computational investigations can lead to important insights, as in the revived domain of neural correlates of attention- and awareness-related meditation states and traits.
Synthetic computational models of selective attention / Raffone, Antonino. - In: NEURAL NETWORKS. - ISSN 0893-6080. - STAMPA. - 19:9(2006), pp. 1458-1460. [10.1016/j.neunet.2006.09.002]
Synthetic computational models of selective attention
RAFFONE, Antonino
2006
Abstract
Computational modeling plays an important role to understand the mechanisms of attention. In this framework, synthetic computational models can uniquely contribute to integrate different explanatory levels and neurocognitive findings, with special reference to the integration of attention and awareness processes. Novel combined experimental and computational investigations can lead to important insights, as in the revived domain of neural correlates of attention- and awareness-related meditation states and traits.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
