Figure 9.

This figure shows the generative process and model used in the simulations of sensory attenuation. The generative process (on the left) models real-world states and causes, while the model on the right is the generative model used by the subject. In the real world, the hidden state x_i corresponds to self-generated pressures that are sensed by both somatosensory s_s and proprioceptive s_p input channels. External forces are modeled with the hidden cause v_e and are sensed only by the somatosensory channel. Action causes the self-generated force x_i to increase and is modified by a sigmoid squashing function σ. The hidden state decays slowly over four time bins. In the generative model, causes of sensory data are divided into internal v_i and external causes v_e. The hidden cause excites dynamics in hidden states x_i and x_e, which decay slowly. Internal force is perceived by both proprioceptive and somatosensory receptors, as before, while external force is perceived only by somatosensory receptors. Crucially, the precision of the sensory input ω_s is influenced by the level of internal force, again modulated by a squashing function, and controlled by a parameter γ that governs the level of attenuation of precision. The generalized predictive coding scheme associated with this generative model is shown schematically in the next figure.