Contexts for the Emergence of Significant Neural Dynamics

How may neural dynamics carry conceptual information? In this dissertation, emergence in dynamical systems is considered with attention to intertheoretic reduction and relationships across phenomenal scales, building to a treatment of emergence of polychronous neuronal groups in dynamical systems neuroscience. This assessment motivates a formal notion of causal and existential meaning, in order to help contribute to our understanding of the neural code by relating its dynamics to the systems which underly it. Implications from this work are then applied to topics in computational cognitive neuroscience and philosophy of mind. Acknowledgement of the embeddedness of the significance of neural dynamics then motivates an extensive parametric study of the relationship between particular neural network structures and the emergence of significant neural dynamics. Results imply that network structure determines critical points in the network, which changes what dynamics can be propagated without catastrophic interference. In a context of a tonic rate coded stimulus, networks with larger ranges in moderately ranged delay enabled the stability of more densely connected networks by increasing their modularity through sparsity of receipt. Within a densely connected, small world brain structure, these results suggest that the naturalistic asymmetry between distally projecting cortico-cortical patches with locally inhibited nucleic dynamics may provide utility for the emergence of significant emergent dynamics. Furthermore, considering clustered networks with delays that are too short may facilitate catastrophic hypersensitivity, obscuring near-future information and establishing metabolistically dangerous network interactions. Importantly, these results suggest that the rate coded firing of an excitatory neuron in a densely connected cortical network cannot be assumed simply because it received rate coded synaptic stimulation