Comparing linear and quadratic models of the human auditory system using EEG

Recent studies have highlighted the importance of system identification as an approach for assessing sensory processing in humans using electroencephalography (EEG). These studies typically use linear impulse response estimates of visual and, more recently, auditory function. These methods, which are known as the VESPA and AESPA (Visual/Auditory Evoked Spread Spectrum Analysis) respectively, have been found to be useful for studying sensory processing in both healthy populations and clinical groups and for studying the effects of cognition on sensory processing. While a nonlinear extension of the VESPA has been previously described, no such extension has yet been examined for the AESPA. This paper investigates such an extension and quantifies the relative contribution of linear and quadratic processes to the EEG in response to novel auditory stimuli. While the ability to accurately predict novel EEG is poor, it is highly significant, with a slightly, but again significantly, greater ability to predict using a quadratic model (r=0.0418) over a linear model (r=0.0361).

[1]  K. Naka,et al.  White-Noise Analysis of a Neuron Chain: An Application of the Wiener Theory , 1972, Science.

[2]  V. Z. Marmarelis A family of quasi-white random signals and its optimal use in biological system identification , 2004, Biological Cybernetics.

[3]  John J. Foxe,et al.  Neural responses to uninterrupted natural speech can be extracted with precise temporal resolution , 2010, The European journal of neuroscience.

[4]  John J. Foxe,et al.  Visual evoked spread spectrum analysis (VESPA) responses to stimuli biased towards magnocellular and parvocellular pathways , 2009, Vision Research.

[5]  Barak A. Pearlmutter,et al.  The VESPA: A method for the rapid estimation of a visual evoked potential , 2006, NeuroImage.

[6]  Barak A. Pearlmutter,et al.  Dissecting the cellular contributions to early visual sensory processing deficits in schizophrenia using the VESPA evoked response , 2008, Schizophrenia Research.

[7]  Barak A. Pearlmutter,et al.  Isolating endogenous visuo-spatial attentional effects using the novel visual-evoked spread spectrum analysis (VESPA) technique , 2007, The European journal of neuroscience.

[8]  John J. Foxe,et al.  Resolving precise temporal processing properties of the auditory system using continuous stimuli. , 2009, Journal of neurophysiology.

[9]  Richard Coppola,et al.  A SYSTEM TRANSFER FUNCTION FOR VISUAL EVOKED POTENTIALS , 1979 .

[10]  N. Wiener,et al.  Nonlinear Problems in Random Theory , 1964 .

[11]  David M. Green,et al.  Profile Analysis: Auditory Intensity Discrimination , 1987 .

[12]  Edmund C. Lalor Modeling the human visual system using the white-noise approach , 2009, 2009 4th International IEEE/EMBS Conference on Neural Engineering.

[13]  Edmund C Lalor,et al.  Endogenous auditory spatial attention modulates obligatory sensory activity in auditory cortex. , 2011, Cerebral cortex.

[14]  G. D. Mccann,et al.  A family of quasi-white random signals and its optimal use in biological system identification , 1977, Biological Cybernetics.