TY - JOUR
T1 - Generative Models for Active Vision
AU - Parr, Thomas
AU - Sajid, Noor
AU - Da Costa, Lancelot
AU - Mirza, M. Berk
AU - Friston, Karl J.
N1 - Funding Information:
LD was supported by the Fonds National de la Recherche, Luxembourg (Project code: 13568875). NS was supported by the Medical Research Council (MR/S502522/1). KF is a Wellcome Principal Research Fellow (Ref: 088130/Z/09/Z).
Funding Information:
Funding. LD was supported by the Fonds National de la Recherche, Luxembourg (Project code: 13568875). NS was supported by the Medical Research Council (MR/S502522/1). KF is a Wellcome Principal Research Fellow (Ref: 088130/Z/09/Z).
Publisher Copyright:
© Copyright © 2021 Parr, Sajid, Da Costa, Mirza and Friston.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/4/13
Y1 - 2021/4/13
N2 - The active visual system comprises the visual cortices, cerebral attention networks, and oculomotor system. While fascinating in its own right, it is also an important model for sensorimotor networks in general. A prominent approach to studying this system is active inference—which assumes the brain makes use of an internal (generative) model to predict proprioceptive and visual input. This approach treats action as ensuring sensations conform to predictions (i.e., by moving the eyes) and posits that visual percepts are the consequence of updating predictions to conform to sensations. Under active inference, the challenge is to identify the form of the generative model that makes these predictions—and thus directs behavior. In this paper, we provide an overview of the generative models that the brain must employ to engage in active vision. This means specifying the processes that explain retinal cell activity and proprioceptive information from oculomotor muscle fibers. In addition to the mechanics of the eyes and retina, these processes include our choices about where to move our eyes. These decisions rest upon beliefs about salient locations, or the potential for information gain and belief-updating. A key theme of this paper is the relationship between “looking” and “seeing” under the brain's implicit generative model of the visual world.
AB - The active visual system comprises the visual cortices, cerebral attention networks, and oculomotor system. While fascinating in its own right, it is also an important model for sensorimotor networks in general. A prominent approach to studying this system is active inference—which assumes the brain makes use of an internal (generative) model to predict proprioceptive and visual input. This approach treats action as ensuring sensations conform to predictions (i.e., by moving the eyes) and posits that visual percepts are the consequence of updating predictions to conform to sensations. Under active inference, the challenge is to identify the form of the generative model that makes these predictions—and thus directs behavior. In this paper, we provide an overview of the generative models that the brain must employ to engage in active vision. This means specifying the processes that explain retinal cell activity and proprioceptive information from oculomotor muscle fibers. In addition to the mechanics of the eyes and retina, these processes include our choices about where to move our eyes. These decisions rest upon beliefs about salient locations, or the potential for information gain and belief-updating. A key theme of this paper is the relationship between “looking” and “seeing” under the brain's implicit generative model of the visual world.
UR - http://www.scopus.com/inward/record.url?scp=85105019616&partnerID=8YFLogxK
U2 - 10.3389/fnbot.2021.651432
DO - 10.3389/fnbot.2021.651432
M3 - Article
SN - 1662-5218
VL - 15
JO - Frontiers in Neurorobotics
JF - Frontiers in Neurorobotics
M1 - 651432
ER -