It has been suggested that emotional visual input is processed along both a slower cortical pathway and a faster subcortical pathway which comprises the lateral geniculate nucleus (LGN), the superior colliculus, the pulvinar, and finally the amygdala. However, anatomical as well as functional evidence concerning the subcortical route is lacking. Here, we adopt a computational approach in order to investigate whether the visual representation that is achieved in the LGN may support emotion recognition and emotional response along the subcortical route. In four experiments, we show that the outputs of LGN Y-cells support neither facial expression categorization nor the same/different expression matching by an artificial classificator. However, the same classificator is able to perform at an above chance level in a statistics-based categorization of scenes containing animals and scenes containing people and of light and dark patterns. It is concluded that the visual representation achieved in the LGN is insufficient to allow for the recognition of emotional facial expression.

De Cesarei, A., Codispoti, M. (2015). Can the Outputs of LGN Y-Cells Support Emotion Recognition? A Computational Study. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2015, 1-9 [10.1155/2015/695921].

Can the Outputs of LGN Y-Cells Support Emotion Recognition? A Computational Study

De Cesarei, A.
;
Codispoti, M.
2015

Abstract

It has been suggested that emotional visual input is processed along both a slower cortical pathway and a faster subcortical pathway which comprises the lateral geniculate nucleus (LGN), the superior colliculus, the pulvinar, and finally the amygdala. However, anatomical as well as functional evidence concerning the subcortical route is lacking. Here, we adopt a computational approach in order to investigate whether the visual representation that is achieved in the LGN may support emotion recognition and emotional response along the subcortical route. In four experiments, we show that the outputs of LGN Y-cells support neither facial expression categorization nor the same/different expression matching by an artificial classificator. However, the same classificator is able to perform at an above chance level in a statistics-based categorization of scenes containing animals and scenes containing people and of light and dark patterns. It is concluded that the visual representation achieved in the LGN is insufficient to allow for the recognition of emotional facial expression.
2015
De Cesarei, A., Codispoti, M. (2015). Can the Outputs of LGN Y-Cells Support Emotion Recognition? A Computational Study. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2015, 1-9 [10.1155/2015/695921].
De Cesarei, A.; Codispoti, M.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/517898
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