Neuromodulated attention and goal-driven perception in uncertain domains.
Neural Netw
; 125: 56-69, 2020 May.
Article
en En
| MEDLINE
| ID: mdl-32070856
ABSTRACT
In uncertain domains, the goals are often unknown and need to be predicted by the organism or system. In this paper, contrastive Excitation Backprop (c-EB) was used in two goal-driven perception tasks - one with pairs of noisy MNIST digits and the other with a robot in an action-based attention scenario. The first task included attending to even, odd, low, and high digits, whereas the second task included action goals, such as "eat", "work-on-computer", "read", and "say-hi" that led to attention to objects associated with those actions. The system needed to increase attention to target items and decrease attention to distractor items and background noise. Because the valid goal was unknown, an online learning model based on the cholinergic and noradrenergic neuromodulatory systems was used to predict a noisy goal (expected uncertainty) and re-adapt when the goal changed (unexpected uncertainty). This neurobiologically plausible model demonstrates how neuromodulatory systems can predict goals in uncertain domains and how attentional mechanisms can enhance the perception for that goal.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Atención
/
Redes Neurales de la Computación
/
Incertidumbre
/
Modelos Neurológicos
Tipo de estudio:
Prognostic_studies
Límite:
Humans
Idioma:
En
Revista:
Neural Netw
Asunto de la revista:
NEUROLOGIA
Año:
2020
Tipo del documento:
Article