Neurodynamics

Neurodynamics is an area of research in the brain sciences which places a strong focus upon the spatio-temporal (dynamic) character of neural activity in describing brain function. Neurodynamics reflects a contemporary theoretical neurobiology which has embraced recent advances in nonlinear dynamics, complexity theory and statistical physics. Neurodynmaics is often contrasted with the popular computational and modular approaches of cognitive neuroscience.

Origin
The term neurodynamics dates back before the 1940s. The field of study "neurodynamics", also called Neural Field Theory, is an offshoot of neuro cybernetics, which uses differential equations to describe activity patterns in bulk neural matter. Research for neurodynamics involves the interdisciplinary areas of Statistics and nonlinear physics and sensory neurobiology. On the physics side, topics of interest include information measures, oscillators, stochastic resonance, unstable periodic orbits, and pattern formation in ensembles of agents.

Overview
Neurodynamics is a term used to represent a conceptual and eclectic methodological approach to understanding neural network activity, and to use this perspective to bridge neuroscience to cognitive science to conscious experience and to behavior. Conventional neural network architectures are often simplistic feed forward or recurrent models where the timing of events is not important to the processing being done. Dynamics studies causal systems where timing is a key consideration. Dynamics underlies all “computation” which is the preeminent and overworked paradigm in all areas of science today.

Research
Recent work focuses on models and algorithms for auditory scene analysis. In order to achieve the ultimate goal of constructing a cocktail party processor that possesses the human ability in cocktail party environments, one must understand individual analyses, such as pitch, location, amplitude and frequency modulation, onset/offset, rhythm, and so on. One must also incorporate top-down information including attention and recognition. To do this, one conducts research on a variety of topics under the general theme of computational audition. The general strategy adopted by this lab is to focus on challenging problems that arise from real-world perception, and then attack them with multidisciplinary approaches. The analysis includes computational, cognitive/perceptual, neurobiological perspectives. While paying close attention to cognitive and neurobiological processes, the thrust of the work conducted in this lab is computational.