title: Building neurocognitive networks with a distributed functional architecture.
abstract: In the past few decades, behavioral and cognitive science have demonstrated that many human behaviors can be captured by low-dimensional observations and models, even though the neuromuscular systems possess orders of magnitude more potential degrees of freedom than are found in a specific behavior. We suggest that this difference, due to a separation in the time scales of the dynamics guiding neural processes and the overall behavioral expression, is a key point in understanding the implementation of cognitive processes in general. In this paper we use Structured Flows on Manifolds (SFM) to understand the organization of behavioral dynamics possessing this property. Next, we discuss how this form of behavioral dynamics can be distributed across a network, such as those recruited in the brain for particular cognitive functions. Finally, we provide an example of an SFM style functional architecture of handwriting, motivated by studies in human movement sciences, that demonstrates hierarchical sequencing of behavioral processes.
authors: Theoretical Neuroscience Group, Université de la Méditerranée, Marseille, France. mwoodman@fau.edu
authors: Marmaduke
authors: M
authors: Woodman
authors: Dionysios
authors: D
authors: Perdikis
authors: Ajay S
authors: AS
authors: Pillai
authors: Silke
authors: S
authors: Dodel
authors: Raoul
authors: R
authors: Huys
authors: Steven
authors: S
authors: Bressler
authors: Viktor
authors: V
authors: Jirsa
mesh_terms: D003071:Cognition; D008962:Models, Theoretical; D009415:Nerve Net