Distraction descriptor for brainprint authentication modelling using probability-based Incremental Fuzzy-Rough Nearest Neighbour.

This paper aims to design distraction descriptor, elicited through the object variation, to refine the granular knowledge incrementally, using the proposed probability-based incremental update strategy in Incremental Fuzzy-Rough Nearest Neighbour (IncFRNN) technique. Most of the brainprint authentication models were tested in well-controlled environments to minimize the influence of ambient disturbance on the EEG signals. These settings significantly contradict the real-world situations. Thus, making use of the distraction is wiser than eliminating it. The proposed probability-based incremental update strategy is benchmarked with the ground truth (actual class) incremental update strategy. Besides, the proposed technique is also benchmarked with First-In-First-Out (FIFO) incremental update strategy in K-Nearest Neighbour (KNN). The experimental results have shown equivalence discriminatory performance in both high distraction and quiet conditions. This has proven that the proposed distraction descriptor is able to utilize the unique EEG response towards ambient distraction to complement person authentication modelling in uncontrolled environment. The proposed probability-based IncFRNN technique has significantly outperformed the KNN technique for both with and without defining the window size threshold. Nevertheless, its performance is slightly worse than the actual class incremental update strategy since the ground truth represents the gold standard. In overall, this study demonstrated a more practical brainprint authentication model with the proposed distraction descriptor and the probability-based incremental update strategy. However, the EEG distraction descriptor may vary due to intersession variability. Future research may focus on the intersession variability to enhance the robustness of the brainprint authentication model.

Statistical models for brain signals with properties that evolve across trials.

Most neuroscience cognitive experiments involve repeated presentations of various stimuli across several minutes or a few hours. It has been observed that brain responses, even to the same stimulus, evolve over the course of the experiment. These changes in brain activation and connectivity are believed to be associated with learning and/or habituation. In this paper, we present two general approaches to modeling dynamic brain connectivity using electroencephalograms (EEGs) recorded across replicated trials in an experiment. The first approach is the Markovian regime-switching vector autoregressive model (MS-VAR) which treats EEGs as realizations of an underlying brain process that switches between different states both within a trial and across trials in the entire experiment. The second is the slowly evolutionary locally stationary process (SEv-LSP) which characterizes the observed EEGs as a mixture of oscillatory activities at various frequency bands. The SEv-LSP model captures the dynamic nature of the amplitudes of the band-oscillations and cross-correlations between them. The MS-VAR model is able to capture abrupt changes in the dynamics while the SEv-LSP directly gives interpretable results. Moreover, it is nonparametric and hence does not suffer from model misspecification. For both of these models, time-evolving connectivity metrics in the frequency domain are derived from the model parameters for both functional and effective connectivity. We illustrate these two models for estimating cross-trial connectivity in selective attention using EEG data from an oddball paradigm auditory experiment where the goal is to characterize the evolution of brain responses to target stimuli and to standard tones presented randomly throughout the entire experiment. The results suggest dynamic changes in connectivity patterns over trials with inter-subject variability.

Assessment of post-excitatory long-interval cortical inhibition in adult attention-deficit/hyperactivity disorder.

In order to further examine cortical impairment in adult ADHD patients and to test the hypothesis of a disturbed neuronal inhibition in adults with ADHD, late auditory evoked potentials were measured. By using paired-chirp auditory late responses, we compared 15 adults with ADHD with 15 control subjects, focusing on the inhibition elicited by the stimuli. Besides amplitude measurements, a time-frequency phase coherence study using the wavelet phase synchronization stability (WPSS) was performed. ADHD was diagnosed according to DSM-IV criteria. All ADHD subjects were without medication and did not suffer from any further axis I disorder. WPSS analysis revealed impaired auditory inhibition for ADHD patients for interstimulus intervals (ISI) between 500 and 1,100 ms as compared with healthy controls. By analyzing the WPSS in the interval from 80 ms to 220 ms, mean inhibition of the test chirp was found to be 6% in the ADHD group and 38.5% in the control subjects (p = 0.01). Moreover, overall smaller amplitudes in the N100 and P200 waves at all ISI were found (p = 0.04 and p = 0.02). However, reproducibility indices in the amplitude measurements were low, thus supporting the use of the instantaneous phase-based analysis method. The results support the hypothesis of reduced intracortical inhibition as a correlate of disturbed brain function in adults with ADHD.

A performance study of the wavelet-phase stability (WPS) in auditory selective attention.

Large-scale neural correlates of auditory selective attention reflected in the electroencephalogram (EEG) have been identified by using the complex wavelet-phase stability measure (WPS). In this paper, we study the feasibility of using this amplitude independent measure, the WPS in extracting the correlates of attention by comparing its performance to the widely used linear interdependency measures, i.e., the wavelet coherence and the correlation coefficient. The outcome reveals that the WPS outperforms the other two measures in discriminating both the attended and unattended single sweep auditory late responses (ALRs). It is concluded that the proposed WPS provides a faster (in terms of less sweeps which are required) and robust objective quantification of selective attention.

An investigation on the effects of single pulse transcranial magnetic stimulation in a modified maximum entropy auditory stimulation paradigm.

In this paper, we intend to investigate further the effects of single pulse TMS (sTMS) on auditory attention through an experimental design that combines a modified version of maximum entropy stimulation paradigm. Single pulses of TMS with 4.4s inter-stimulus interval (ISI) were applied to the left temporal lobe of subjects while three randomized auditory stimuli with constant ISI of 1.1s were delivered to the contralateral side within the TMS stimulation duration. Our main focus was to examine the time course of the auditory late responses (ALRs) due to TMS stimulation by a phase clustering on the unit circle measure and an adaptive shift- invariant feature extraction method. In the attention scheme, a significant difference in the phase stability between TMS and no-TMS was found in the range of the N1 wave of ALRs. However, the difference occurs only for the data after 1.1s. Furthermore, there is an absence of differences in the amplitude of the ALR. In addition, the effects of TMS and attention can also be discriminated very well and illuminate the effects of TMS in auditory attention. It is concluded that even sTMS might have the potential to alter the attentional states and the effects can last about 1s, at least when considering the large- scale neural correlates of attention in ALR sequences.

EEG phase reset due to auditory attention: an inverse time-scale approach.

We propose a novel tool to evaluate the electroencephalograph (EEG) phase reset due to auditory attention by utilizing an inverse analysis of the instantaneous phase for the first time. EEGs were acquired through auditory attention experiments with a maximum entropy stimulation paradigm. We examined single sweeps of auditory late response (ALR) with the complex continuous wavelet transform. The phase in the frequency band that is associated with auditory attention (6-10 Hz, termed as theta-alpha border) was reset to the mean phase of the averaged EEGs. The inverse transform was applied to reconstruct the phase-modified signal. We found significant enhancement of the N100 wave in the reconstructed signal. Analysis of the phase noise shows the effects of phase jittering on the generation of the N100 wave implying that a preferred phase is necessary to generate the event-related potential (ERP). Power spectrum analysis shows a remarkable increase of evoked power but little change of total power after stabilizing the phase of EEGs. Furthermore, by resetting the phase only at the theta border of no attention data to the mean phase of attention data yields a result that resembles attention data. These results show strong connections between EEGs and ERP, in particular, we suggest that the presentation of an auditory stimulus triggers the phase reset process at the theta-alpha border which leads to the emergence of the N100 wave. It is concluded that our study reinforces other studies on the importance of the EEG in ERP genesis.

Alterations in Event Related Potentials (ERP) associated with tinnitus distress and attention.

Tinnitus related distress corresponds to different degrees of attention paid to the tinnitus. Shifting attention to a signal other than the tinnitus is therefore particularly difficult for patients with high tinnitus related distress. As attention effects on Event Related Potentials (ERP) have been shown this should be reflected in ERP measurements (N100, phase locking). In order to prove this hypothesis single sweep ERP recordings were obtained in 41 tinnitus patients as well as 10 control subjects during a period of time when attention was shifted to a tone (attended) and during a second phase (unattended) when they did not focus attention to the tone. Whereas tinnitus patients with low distress showed a significant reduction in both N100 amplitude and phase locking when comparing the attended and unattended measurement condition a group of patients with high tinnitus related distress did not show such ERP alterations. Using single sweep ERP measurements the results of our study show, that attention in high tinnitus related distress patients is captured by their tinnitus significantly more than in low distress patients. Furthermore our results provide the basis for future neurofeedback based tinnitus therapies aiming at maximizing the ability to shift attention away from the tinnitus.

Objective quantification of the tinnitus decompensation by synchronization measures of auditory evoked single sweeps.

Large-scale neural correlates of the tinnitus decompensation might be used for an objective evaluation of therapies and neurofeedback based therapeutic approaches. In this study, we try to identify large-scale neural correlates of the tinnitus decompensation using wavelet phase stability criteria of single sweep sequences of late auditory evoked potentials as synchronization stability measure. The extracted measure provided an objective quantification of the tinnitus decompensation and allowed for a reliable discrimination between a group of compensated and decompensated tinnitus patients. We provide an interpretation for our results by a neural model of top-down projections based on the Jastreboff tinnitus model combined with the adaptive resonance theory which has not been applied to model tinnitus so far. Using this model, our stability measure of evoked potentials can be linked to the focus of attention on the tinnitus signal. It is concluded that the wavelet phase stability of late auditory evoked potential single sweeps might be used as objective tinnitus decompensation measure and can be interpreted in the framework of the Jastreboff tinnitus model and adaptive resonance theory.

Evaluation of a compact tinnitus therapy by electrophysiological tinnitus decompensation measures.

Large-scale neural correlates of the tinnitus decompensation have been identified by using wavelet phase stability criteria of single sweep sequences of auditory late responses (ALRs). Our previous work showed that the synchronization stability in ALR sequences might be used for objective quantification of the tinnitus decompensation and attention which link to Jastreboff tinnitus model. In this study, we intend to provide an objective evaluation for quantifying the effect of music therapy in tinnitus patients. We examined neural correlates of the attentional mechanism in single sweep sequences of ALRs in chronic tinnitus patients who underwent compact therapy course by using the maximum entropy auditory paradigm. Results by our measure showed that the extent of differentiation between attended and unattended conditions improved significantly after the therapy. It is concluded that the wavelet phase synchronization stability of ALRs single sweeps can be used for the objective evaluation of tinnitus therapies, in this case the compact tinnitus music therapy.

Neurofeedback by neural correlates of auditory selective attention as possible application for tinnitus therapies.

More and more people are suffering from tinnitus. There are many treatments for tinnitus that have been claimed based on different causes. Unfortunately, until now none of the existing treatments has been found to be effective in general. Here, we would like to suggest a treatment to tinnitus based on neurofeedback using neural correlates of auditory selective evoked potentials (ASEPs). We have shown that the wavelet phase synchronization of auditory late responses (ALR) single sweeps allows for a direct online monitoring of phase locked auditory attention. The results show that after a simple training, subjects learned to control their attention to the auditory modality. To improve the ability in the attention control system is an objective of many tinnitus treatments, so that the perception of the patients towards the tinnitus noise can be reduced to a minimum. It is concluded that our proposed neurofeedback system by wavelet phase synchronization measure might be used in a clinical treatment of tinnitus patients and it is possible to extent to other therapeutic based control systems.

The role of attention in the tinnitus decompensation: reinforcement of a large-scale neural decompensation measure.

Large-scale neural correlates of the tinnitus decompensation have been identified by using wavelet phase stability criteria of single sweep sequences of auditory late responses (ALRs). The suggested measure provided an objective quantification of the tinnitus decompensation and allowed for a reliable discrimination between a group of compensated and decompensated tinnitus patients. By interpreting our results with an oscillatory tinnitus model, our synchronization stability measure of ALRs can be linked to the focus of attention on the tinnitus signal. In the following study, we examined in detail the correlates of this attentional mechanism in healthy subjects. The results support our previous findings of the phase synchronization stability measure that reflected neural correlates of the fixation of attention to the tinnitus signal. In this case, enabling the differentiation between the attended and unattended conditions. It is concluded that the wavelet phase synchronization stability of ALRs single sweeps can be used as objective tinnitus decompensation measure and can be interpreted in the framework of the Jastreboff tinnitus model and adaptive resonance theory. Our studies confirm that the synchronization stability in ALR sequences is linked to attention. This measure is not only able to serve as objective quantification of the tinnitus decompensation, but also can be applied in all online and real time neurofeedback therapeutic approach where a direct stimulus locked attention monitoring is compulsory as if it based on a single sweeps processing.

Large-scale inverse and forward modeling of adaptive resonance in the tinnitus decompensation.

Neural correlates of psychophysiological tinnitus models in humans may be used for their neurophysiological validation as well as for their refinement and improvement to better understand the pathogenesis of the tinnitus decompensation and to develop new therapeutic approaches. In this paper we make use of neural correlates of top-down projections, particularly, a recently introduced synchronization stability measure, together with a multiscale evoked response potential (ERP) model in order to study and evaluate the tinnitus decompensation by using a hybrid inverse-forward mathematical methodology. The neural synchronization stability, which according to the underlying model is linked to the focus of attention on the tinnitus signal, follows the experimental and inverse way and allows to discriminate between a group of compensated and decompensated tinnitus patients. The multiscale ERP model, which works in the forward direction, is used to consolidate hypotheses which are derived from the experiments for a known neural source dynamics related to attention. It is concluded that both methodologies agree and support each other in the description of the discriminatory character of the neural correlate proposed, but also help to fill the gap between the top-down adaptive resonance theory and the Jastreboff model of tinnitus.