Amarender R. Bogadhi
Affiliations: | Aix-Marseille University |
Area:
Motion Integration, Smooth Pursuit, Prediction, Hierarchical recurrent bayesian, ModelGoogle:
"Amarender Bogadhi"Mean distance: (not calculated yet)
Parents
Sign in to add mentor| Guillaume Masson | grad student | 2012 | Aix-Marseille University | |
| (Une étude expérimentale et théorique de l'intégration de mouvement pour la poursuite lente : Un modèle Bayesien récurrent et hiérarchique) | ||||
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Publications
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| Bogadhi AR, Bollimunta A, Leopold DA, et al. (2019) Spatial Attention Deficits Are Causally Linked to an Area in Macaque Temporal Cortex. Current Biology : Cb |
| Bogadhi AR, Bollimunta A, Leopold DA, et al. (2018) Brain regions modulated during covert visual attention in the macaque. Scientific Reports. 8: 15237 |
| Bollimunta A, Bogadhi AR, Krauzlis RJ. (2018) Comparing frontal eye field and superior colliculus contributions to covert spatial attention. Nature Communications. 9: 3553 |
| Krauzlis RJ, Bogadhi AR, Herman JP, et al. (2017) Selective attention without a neocortex. Cortex; a Journal Devoted to the Study of the Nervous System and Behavior |
| Bollimunta A, Bogadhi A, Leopold D, et al. (2016) Attention-related BOLD modulation with and without superior colliculus inactivation Journal of Vision. 16: 1305 |
| Herman JP, Bogadhi AR, Krauzlis RJ. (2015) Effects of spatial cues on color-change detection in humans. Journal of Vision. 15: 3 |
| Bogadhi AR, Montagnini A, Masson GS. (2013) Dynamic interaction between retinal and extraretinal signals in motion integration for smooth pursuit. Journal of Vision. 13: 5 |
| Herman J, Bogadhi A, Krauzlis R. (2013) Novel color stimuli for studying spatial attention F1000research. 13: 1124-1124 |
| Montagnini A, Bogadhi A, Masson G. (2012) Dynamical integration of retinal and extra-retinal signals for smooth pursuit eye movements: a two-stage Bayesian model Perception. 41: 166-166 |
| Bogadhi AR, Montagnini A, Mamassian P, et al. (2011) Pursuing motion illusions: a realistic oculomotor framework for Bayesian inference. Vision Research. 51: 867-80 |