Rick A Adams

Fri, 01 Jan 2016 00:00:00 +0000

Collaborative publications

I had the chance to visit the theoretical group of Karl Friston at the Wellcome Trust Centre for Neuroimaging (University College London) from November 2010 to February 2012. During this period we built a series of active‑inference models of eye‑movement control. First, we introduced a generative model of saccadic behaviour Friston et al., 2012. We then extended the framework to clinical populations, demonstrating that neuromodulation may critically shape model predictions in participants with and without schizophrenia (Adams et al., 2012). Finally, we incorporated realistic sensory‑motor transmission delays, providing a more accurate account of the timing of perception‑action cycles Perrinet et al., 2014.

modelling eye movements using active inference
Karl Friston, Rick A Adams, Laurent U Perrinet, Michael Breakspear (2012). Perceptions as Hypotheses: Saccades as Experiments. Frontiers in Psychology.
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applying the model to individuals with and without schizophrenia and demonstrating the role of neuromodulation in eye‑movement contro
Rick A Adams, Laurent U Perrinet, Karl Friston (2012). Smooth Pursuit and Visual Occlusion: Active Inference and Oculomotor Control in Schizophrenia. PLoS ONE.
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extending the framework to incorporate sensory‑motor delays
Laurent U Perrinet, Rick A Adams, Karl Friston (2014). Active inference, eye movements and oculomotor delays. Biological Cybernetics.
Cite DOI URL arXiv

This schematic shows the dependencies among various quantities that are assumed when modeling the exchanges of a self organizing system like the brain with the environment. The top panel describes the states of the environment and the system or agent in terms of a probabilistic dependency graph, where connections denote directed dependencies. The quantities are described within the nodes of this graph with exemplar forms for their dependencies on other variables (see main text). Here, hidden and internal states are separated by action and sensory states. Both action and internal states encoding a conditional density minimize free energy, while internal states encoding prior beliefs maximize salience. Both free energy and salience are defined in terms of a generative model that is shown as fictive dependency graph in the lower panel. Note that the variables in the real world and the form of their dynamics are different from that assumed by the generative model; this is why external states are in bold. Furthermore, note that action is a state in the model of the brain but is replaced by hidden controls in the brain’s model of its world. This means that the agent is not aware of action but has beliefs about hidden causes in the world that action can fulfill through minimizing free energy. These beliefs correspond to prior expectations that sensory states will be sampled in a way that optimizes conditional confidence or salience.

Smooth Pursuit and Visual Occlusion: Active Inference and Oculomotor Control in Schizophrenia

Fri, 26 Oct 2012 00:00:00 +0000

Kevin Mairot

Mon, 01 Jan 0001 00:00:00 +0000

PhD Student (2023-10 / 2027-09): L’intelligence artificielle comme aide au diagnostic des dystrophies rétiniennes

Institut des Neurosciences de la Timone, Aix-Marseille Université / CNRS
Thesis co-direction: Laurent Perrinet (principal supervisor) and Frédéric Matonti (ophtalmologue, Marseille)

Clinical Neuroscience | Laurent Perrinet

Rick A Adams

Collaborative publications

Smooth Pursuit and Visual Occlusion: Active Inference and Oculomotor Control in Schizophrenia

Kevin Mairot

PhD Student (2023-10 / 2027-09): L’intelligence artificielle comme aide au diagnostic des dystrophies rétiniennes