Metastable Dynamical Regimes in an Oscillatory Network Modulated by an Agent's

The last two decades have witnessed an increasing focus on oscillatory brain dynamics as a means of under- standing a variety of cognitive phenomena. Most theoretical and mathematical approaches in this area have mainly worked under two assumptions: a) that the most significant aspect of oscillatory brain dynamics is synchronization; and, b) that most part of functional brain dynamics can be understood without incorporating the sensorimotor loop into the picture. Although significant progress has been achieved with these assumptions, we believe they might limit future development of dynamical approaches to brain functioning and cognitive behaviour. Looking at the whole picture of brain dynamics, rather than only moments of synchronization, and analysing it inside the sensorimotor loop can provide new insights on how the brain operates. In this paper we present a robotic agent capable of performing phototaxis controlled by a Kuramoto-model based oscillatory neural network. The network parameters were optimized using a genetic algorithm. The resulting brain and behavioural dynamics are analysed within Kelso's Coordination dynamic framework. We found that: a) during a whole behavioural episode of photo- taxis the robot's brain undergoes different metastable dynamical regimes of phase-lock and phase-scattering, represented by the relative phase and phase coherence among oscillators; b) even for a simple task, metastable coordination patterns and functional behaviour emerges without the need for a specific synchronization signature; and, c) sensorimotor loop dynamics plays a critical role generating and sustaining functional metastable regimes of brain activity by modulating the network's control parameter.