Abstract. Despite the great amount of knowledge produced by the neuroscientific literature affective phenomena, current models tackling noncognitive aspects of behavior are often b...
Marco Mirolli, Francesco Mannella, Gianluca Baldas...
This paper presents an adaptive structure self-organizing finite mixture network for quantification of magnetic resonance (MR) brain image sequences. We present justification fo...
In this paper we provide theoretical and numerical analysis of a geometric activity flow network model which is aimed at explaining mathematically the scale-free functional graph s...
It is a major source of contention in brain dynamics as to whether the electrical rhythms of the brain show signs of chaos. Here we discuss evidence for the existence of chaos in ...
Mathew P. Dafilis, Paul D. Bourke, David T. J. Lil...
Abstract. In the present study, fully nonlinear (i.e. accounting for both geometric and material nonlinearities) patient specific finite element brain model was applied to predict ...
Adam Wittek, Ron Kikinis, Simon K. Warfield, Karol...