Assessment of long-term habituation correlates in event-related potentials using a von Mises model.

In our preliminary work we were able to demonstrate habituation by analyzing attention correlates in single-trial sequences of auditory event-related potentials (ERPs). Despite different quantitative studies of instantaneous phase of ERPs in long-term habituation, there have been no former studies in generative process underlying the distribution of instantaneous phase information in the context of long-term habituation and its relation to attentional binding. For this means we used a von Mises model, representing the phase information over a set of single trial responses. Additionally we use a quantitative neurofunctional model to predict the dynamics of the instantaneous phase in single-trial ERP data during the long-term habituation. Measured habituation data is used to cross-validate the model's prediction. We conclude that the described method allows for an assessment of dynamic changes in the course of long-term habituation. The results also reinforce our neurofunctional multiscale model of long-term habituation and show the applicability of the described method for the experimental/clinical neurodiagnostic assessment of attentional binding.

Dysfunctional cortical inhibition in adult ADHD: neural correlates in auditory event-related potentials.

In recent times, the relevance of an accurate diagnosis of attention-deficit/hyperactivity disorder (ADHD) in adults has been the focus of several studies. No longer considered a pathology exclusive to children and adolescents, and taking into account its social implications, developing enhanced support tools for the current diagnostic procedure becomes a priority. Here we present a method for the objective assessment of ADHD in adults using chirp-evoked, paired auditory late responses (ALRs) combined with a two-dimensional ALR denoising scheme to extract correlates of intracortical inhibition. Our method allows for an effective single-sweep denoising, thus requiring less trials to obtain recognizable physiological features, useful as pointers of cortical impairment. Results allow an optimized diagnosis, reduction of data loss and acquisition time; moreover, they do not account exclusively for critical elements within clinical evaluations, but also allow studying the pathophysiology of the condition by providing objective information regarding impaired cortical functions.

Detection of change points in phase data: a Bayesian analysis of habituation processes.

Given a time series of data points, as obtained in biosignal monitoring, the change point problem poses the question of identifying times of sudden variations in the parameters of the underlying data distribution. We propose a method for extracting a discrete set of change points from directional data. Our method is based on a combination of the Bayesian change point model (CPM) and the Viterbi algorithm. We apply our method to the instantaneous phase information of single-trial auditory event-related potentials (ERPs) in a long term habituation paradigm. We have seen in previous studies that the phase information enters a phase-locked mode with respect to the repetition of a stimulus in the state of focused attention. With adaptation to an insignificant stimulus, attention tends to trail away (long-term habituation), characterized by changes in the phase signature, becoming more diffuse across trials. We demonstrate that the proposed method is suitable for detecting the effects of long-term habituation on phase information in our experimental setting.