A BCI-Based Vibrotactile Neurofeedback Training Improves Motor Cortical Excitability During Motor Imagery.

In this study, we address the issue of whether vibrotactile feedback can enhance the motor cortex excitability translated into the plastic changes in local cortical areas during motor imagery (MI) BCI-based training. For this purpose, we focused on two of the most notable neurophysiological effects of MI - the event-related desynchronization (ERD) level and the increase in cortical excitability assessed with navigated transcranial magnetic stimulation (nTMS). For TMS navigation, we used individual high-resolution 3D brain MRIs. Ten BCI-naive and healthy adults participated in this study. The MI (rest or left/right hand imagery using Graz-BCI paradigm) tasks were performed separately in the presence and absence of feedback. To investigate how much the presence/absence of vibrotactile feedback in MI BCI-based training could contribute to the sensorimotor cortical activations, we compared the MEPs amplitude during MI after training with and without feedback. In addition, the ERD levels during MI BCI-based training were investigated. Our findings provide evidence that applying vibrotactile feedback during MI training leads to (i) an enhancement of the desynchronization level of mu-rhythm EEG patterns over the contralateral motor cortex area corresponding to the MI of the non-dominant hand; (ii) an increase in motor cortical excitability in hand muscle representation corresponding to a muscle engaged by the MI.

N1 wave in the P300 BCI is not sensitive to the physical characteristics of stimuli.

One of the widely used paradigms for the brain-computer interface (BCI), the P300 BCI, was proposed by Farwell and Donchin as a variation of the classical visual oddball paradigm, known to elicit the P300 component of the brain event-related potentials (ERP). We show that this paradigm, unlike the standard oddball paradigm, elicit not only the P300 wave but also a strong posterior N1 wave. Moreover, we present evidence that the sensitivity of this ERP component to targets cannot be explained by the variations of the perceived stimuli energy. This evidence is based on comparing the ERP obtained for usual P300 BCI stimuli and for the "inverted" stimulation scheme with low stimulus related variations of light energy (gray letters on the light gray background, "highlighted" by very light darkening). Despite the dramatic difference between the stimuli in the standard and "inverted" schemes, no difference between N1 amplitudes were found, supporting the view that this component's sensitivity to targets cannot be based simply on "foveating" the target, but may be related to spatial attention mechanisms, which involvement is natural for the P300 BCI. Efforts to optimize the P300 BCI should address better use of both P300 and N1 waves.

Interictal EEG as a physiological adaptation. Part I. Composition of brain oscillations in interictal EEG.

OBJECTIVE: In the present experimental study, we examined the compositions of brain oscillations and their temporal behavior in broad frequency band (0.5-30 Hz) in interictal EEG without epileptiform abnormalities during generalized epilepsy in resting conditions. METHODS: The exact compositions of brain oscillations and their percent ratio were assessed by a probability-classification analysis of short-term EEG spectral patterns (SPs), which reveals temporal dynamics of these SPs and results in the probability-classification profile. RESULTS: It has been demonstrated that the interictal EEG was characterized by (a) a shift towards higher frequencies in all observed brain oscillations, (b) an increased amount of polyrhythmic activity, (c) a decrease in SP types diversity, (d) a decreased relative incidence of the SP type change in the transition between neighboring EEG epochs of the same EEG, and (e) an increased temporal stabilization periods of polyrhythmic activity. All these were observed in distributed brain areas. CONCLUSIONS: It was suggested that these findings reflect a disorganization of neurodynamics in the epileptic brain. At the same time, the fact that all these indices were significantly different from surrogate EEG reflects a non-occasional and thus, most likely, an adaptive nature of the microstructural reorganization of interictal EEG. SIGNIFICANCE: Parameters of interictal EEG without the signs of epileptiform activity can be considered as additional information in premorbid diagnostics of epistatus.

Interictal EEG as a physiological adaptation. Part II. Topographic variability of composition of brain oscillations in interictal EEG.

OBJECTIVE: In the present experimental study, we examined topographic variability of composition of brain oscillations and their temporal behavior in frequencies from 0.5 to 30 Hz of interictal EEG without epileptiform abnormalities and healthy EEG. METHODS: Spatio-temporal variability of brain oscillations (indexed by short-term EEG spectral patterns (SPs)) was assessed by the probability-classification analysis of SPs. As a result, multi-dimensional SP-vector for each analysis EEG epoch was obtained. RESULTS: It was demonstrated that interictal EEG was characterized (a) by a significant decrease of spatio-temporal variability of brain oscillations, (b) by longer periods of temporal stabilization for operational modules which comprise larger number of cortical areas, and (c) by significantly more intermittent recurrence when compared with EEG of control subjects. Generally it was shown that EEG channels display different states of coordination independently on their correlation and coherence using brain oscillations at multiple frequencies. CONCLUSIONS: Results of this study suggested that EEG correlate of chronic epileptogenesis in the brain is a particular metastable state of biopotential field, which can be estimated by SP-vector. The fact that all results were significantly different from surrogate EEGs reflects a nonoccasional and thus, most likely, an adaptive nature of spatio-temporal reorganization in interictal EEG. SIGNIFICANCE: Parameters of spatio-temporal organization of interictal EEG without the signs of epileptiform activity can be considered as additional information in premorbid diagnostics of status epilepticus, and may also provide insights into basic laws that govern brain oscillations in general.

Stability, reliability and consistency of the compositions of brain oscillations.

In the present experimental study, we examined the compositions of electroencephalographic (EEG) brain oscillations and their percent ratio in 12 subjects during resting conditions (closed and open eyes) and during the memory task (waiting, encoding and keeping-in-mind stages). The exact compositions of brain oscillations and their percent ratio were assessed by the probability-classification analysis of short-term EEG spectral patterns, which results in the probability-classification profile (PCP). Within sessions the PCPs are found to be stable, as reflected by a relatively low coefficient of variability, and between sessions the PCPs are highly reproducible. Finally, test-retest reliability of subject's PCPs shows a dependency on task, being higher for the memory task, and in particular for the encoding stage. It was suggested that these findings support and strengthen the superposition principle where integrative brain functions are manifested in the superposition of distributed multiple oscillations.

The regularities of the discrete nature of multi-variability of EEG spectral patterns.

The short-term structure of electroencephalogram (EEG) spectral transformations during different brain functional states (closed/opened eyes and memory task) was studied. It was shown that approximately 50% of spectral pattern (SP) types occur not more than 2-3 times per 149 analysis epochs in a 1-min EEG. The remaining 50% of SP types were the same for the different EEG channels, in all subjects and various brain functional states. Additionally, a high incidence of the neighboring SP types in strongly overlapping (by 80%) 2-s analysis epochs of the EEG was shown. The SP identified in a given epoch has only a limited predictive value on the SPs identified in the subsequent epochs. The incidence effect was restricted by the limited SP set and by a 50% reduction in the functionally active SPs, which resulted in a temporary stabilization of SPs in sequential combinations. The parameters of temporary stabilization of SPs were significantly different from 'random' EEG which provides evidence of the non-occasional character of stabilization of the main dynamic parameters of neuronal activity. Thus, the findings suggest that the multi-variability of neuronal nets is discrete in time, and limited by the dynamics of the short quasi-stable brain states.

Event-related potentials in a moving matrix modification of the P300 brain-computer interface paradigm.

In the standard design of the brain-computer interfaces (BCI) based on the P300 component of the event-related potentials (ERP), target and non-target stimuli are presented at fixed positions in a motionless matrix. Can we let this matrix be moving (e.g., if attached to a robot) without loosing the efficiency of BCI? We assessed changes of the positive peak at Pz in the time interval 300-500 ms after the stimulus onset (P300) and the negative peak at the occipital electrodes in the range 140-240 ms (N1), both important for the operation of the P300 BCI, during fixating a target cell of a moving matrix in healthy participants (n=12). N1 amplitude in the difference (target-non-target) waveforms decreased with the velocity, although remained high (M=-4.3, SD=2.1) even at highest velocity (20°/s). In general, the amplitudes and latencies of these ERP components were remarkably stable in studied types of matrix movement and all velocities of horizontal movement (5, 10 and 20°/s) comparing to matrix in fixed position. These data suggest that, for the users controlling their gaze, the P300 BCI design can be extended to modifications requiring stimuli matrix motion.

Unconscious operant conditioning in the paradigm of brain-computer interface based on color perception.

This study investigate the mutual fine-tuning of ongoing EEG rhythmic features with RGB values controlling color shades of computer screen during neuro-feedback training. Fifteen participants had not been informed about the existence of neurofeedback loop (NF), but were guided only to look at the computer screen. It was found that during such unconscious NF training, a variety of color shades on the screen gradually changed from rather various types to the main one within the framework of color palette specified for each individual. This phenomenon was not observed in control experiments with simulated neuro-feedback. Individual color patterns induced on the screen during NF did not depend on the schema of connection between of EEG rhythms and RGB controller. It is suggested that the basic neurophysiological mechanism of described NF training consists of the directed selection of EEG patterns reinforced by comfortable color shades without conscious control.

Systematic rules underlying spectral pattern variability: experimental results and a review of the evidence.

On the basis of three different experiments: oddball task (visual, auditory, and audio-visual stimuli), modified Sternberg's, and multistage memory tasks, it was shown that: a) there was not a single typical spectral pattern type that would characterize the majority of the trials; b) the total number of the different spectral pattern types was limited; c) different spectral pattern types had different importance to the brain--their occurrence was more or less probable; d) the total number and the number of the most probable spectral pattern types were dependent on the functional brain state; e) actual spectral pattern of variability during rest with closed eyes was relatively high (around 65% from the maximum possible rate), but significantly less than stochastic spectral pattern variability. It is suggested that identical sensory events can potentially trigger a limited number of several different alternative reaction patterns in EEG/MEG, depending on the situational context.