Brain circuitry behavioral control emerging from complexity of nested recurrent loops extending into the body

Abstract

Behaviors and thoughts are driven by a multitude of nested neuronal circuitry loops. They cause complex brain activity dynamics that remain poorly understood. We show that closed-loop neuronal network operation results in an activity state space that can be best understood as a vector field with an attractor point, which controls the activity dynamics across the neuronal population. We show that brain activity in vivo, however, indicates the attractor point is continually moving along a trajectory, which requires the presence of dynamic sensory input or independent activity generation within neurons. Using a spinal network model receiving sensory feedback from a dynamical biomechanical system, we show how these two independent dynamical systems mutually drive each others activity trajectories to generate behavior. Similarly, independent self-generated activity within each thalamic neuron, in closed loop with cortical subpopulations, results in a multitude of dynamical subnetworks that shape each others activity trajectories to control cortical populations. Although the attractor trajectories reflect emergent stability, we show them to be susceptible to criticality effects where minor changes in synaptic inputs can cause the attractor trajectory to switch to cause alternative behaviors. This renders the mutual perturbations between neural and biomechanical dynamics, and between subnetworks within the CNS, an effective operational mode to achieve behavioral flexibility and to simplify learning of apparently complex behaviors. We illustrate how this mode of operation necessitates anticipatory control, thoughts, by the cortex and discuss how it can encompass also the other CNS structures involved in somatic sensorimotor control.