Imagine your brain as a master planner, constantly adapting and adjusting to achieve your goals. In a dynamic and ever-changing world, our brains use a process called Active Inference to support visually-guided actions. This theory suggests that the brain maintains beliefs about the environment and uses motor control signals to fulfill sensory predictions. Researchers propose that the Posterior Parietal Cortex (PPC) in our brain plays a crucial role in this process by computing flexible intentions or motor plans based on our beliefs about targets. They have developed a computational model that simulates this process and have tested it on a proof-of-concept agent performing target-reaching tasks. The agent performed correctly under different conditions and demonstrated the power of Active Inference with flexible intentions in driving goal-directed behavior in varying environments. This study not only provides a normative computational framework for understanding goal-directed behavior but also contributes to mechanistic theories of active biological systems. To dive deeper into this fascinating research, check out the full article!

We present a normative computational theory of how the brain may support visually-guided goal-directed actions in dynamically changing environments. It extends the Active Inference theory of cortical processing according to which the brain maintains beliefs over the environmental state, and motor control signals try to fulfill the corresponding sensory predictions. We propose that the neural circuitry in the Posterior Parietal Cortex (PPC) compute flexible intentions—or motor plans from a belief over targets—to dynamically generate goal-directed actions, and we develop a computational formalization of this process. A proof-of-concept agent embodying visual and proprioceptive sensors and an actuated upper limb was tested on target-reaching tasks. The agent behaved correctly under various conditions, including static and dynamic targets, different sensory feedbacks, sensory precisions, intention gains, and movement policies; limit conditions were individuated, too. Active Inference driven by dynamic and flexible intentions can thus support goal-directed behavior in constantly changing environments, and the PPC might putatively host its core intention mechanism. More broadly, the study provides a normative computational basis for research on goal-directed behavior in end-to-end settings and further advances mechanistic theories of active biological systems.

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