Understanding the layered brain architecture for motivation: Dynamical systems, computational neuroscience, and robotic approaches

Despite a wealth of details about motivated behavior and the neural systems that generate it, the functional architecture of the mammalian brain that resolves conflicts between motivational systems remains mysterious. We explore the brain substrates for motivation with a particular focus on co-ordination between brainstem and forebrain sub-systems. We argue that conflicts between motivational systems are resolved partly through localized circuits and partly through distributed mechanisms involving multiple layers of the neuraxis that can be understood as forming a layered control architecture. To better understand this functionality a multiscale modeling approach is needed. We first explore dynamical systems perspectives as a means of understanding the resolution of motivational conflicts through attractor dynamics. We next consider computational neuroscience models with a focus on circuits involving the hypothalamus. Finally, we explore how embodied (robotic) modeling can contribute by testing integrated functional architectures in systems that display real-world behavior, and thus complete control loops via the environment.