Individual differences in the human electroencephalogram during quiet wakefulness

EEG temporal-spatial transformer for person identification

An increasing number of studies have been devoted to electroencephalogram (EEG) identity recognition since EEG signals are not easily stolen. Most of the existing studies on EEG person identification have only addressed brain signals in a single state, depending upon specific and repetitive sensory stimuli. However, in reality, human states are diverse and rapidly changing, which limits their practicality in realistic settings. Among many potential solutions, transformer is widely used and achieves an excellent performance in natural language processing, which demonstrates the outstanding ability of the attention mechanism to model temporal signals. In this paper, we propose a transformer-based approach for the EEG person identification task that extracts features in the temporal and spatial domains using a self-attention mechanism. We conduct an extensive study to evaluate the generalization ability of the proposed method among different states. Our method is compared with the most advanced EEG biometrics techniques and the results show that our method reaches state-of-the-art results. Notably, we do not need to extract any features manually.

Arrangements of Resting State Electroencephalography as the Input to Convolutional Neural Network for Biometric Identification

Biometric is an important field that enables identification of an individual to access their sensitive information and asset. In recent years, electroencephalography- (EEG-) based biometrics have been popularly explored by researchers because EEG is able to distinct between two individuals. The literature reviews have shown that convolutional neural network (CNN) is one of the classification approaches that can avoid the complex stages of preprocessing, feature extraction, and feature selection. Therefore, CNN is suggested to be one of the efficient classifiers for biometric identification. Conventionally, input to CNN can be in image or matrix form. The objective of this paper is to explore the arrangement of EEG for CNN input to investigate the most suitable input arrangement of EEG towards the performance of EEG-based identification. EEG datasets that are used in this paper are resting state eyes open (REO) and resting state eyes close (REC) EEG. Six types of data arrangement are compared in this paper. They are matrix of amplitude versus time, matrix of energy versus time, matrix of amplitude versus time for rearranged channels, image of amplitude versus time, image of energy versus time, and image of amplitude versus time for rearranged channels. It was found that the matrix of amplitude versus time for each rearranged channels using the combination of REC and REO performed the best for biometric identification, achieving validation accuracy and test accuracy of 83.21% and 79.08%, respectively.

Combining Cryptography with EEG Biometrics

Cryptographic frameworks depend on key sharing for ensuring security of data. While the keys in cryptographic frameworks must be correctly reproducible and not unequivocally connected to the identity of a user, in biometric frameworks this is different. Joining cryptography techniques with biometrics can solve these issues. We present a biometric authentication method based on the discrete logarithm problem and Bose-Chaudhuri-Hocquenghem (BCH) codes, perform its security analysis, and demonstrate its security characteristics. We evaluate a biometric cryptosystem using our own dataset of electroencephalography (EEG) data collected from 42 subjects. The experimental results show that the described biometric user authentication system is effective, achieving an Equal Error Rate (ERR) of 0.024.

Resting State EEG-based biometrics for individual identification using convolutional neural networks

Biometrics is a growing field, which permits identification of individuals by means of unique physical features. Electroencephalography (EEG)-based biometrics utilizes the small intra-personal differences and large inter-personal differences between individuals' brainwave patterns. In the past, such methods have used features derived from manually-designed procedures for this purpose. Another possibility is to use convolutional neural networks (CNN) to automatically extract an individual's best and most unique neural features and conduct classification, using EEG data derived from both Resting State with Open Eyes (REO) and Resting State with Closed Eyes (REC). Results indicate that this CNN-based joint-optimized EEG-based Biometric System yields a high degree of accuracy of identification (88%) for 10-class classification. Furthermore, rich inter-personal difference can be found using a very low frequency band (0-2Hz). Additionally, results suggest that the temporal portions over which subjects can be individualized is less than 200 ms.

Individual EEG differences in affective valence processing in women with low and high neuroticism

OBJECTIVE

In this study, individual differences in brain electrophysiology during positive and negative affective valence processing in women with different neuroticism scores are quantified.

METHODS

Twenty-six women scoring high and low on neuroticism participated on this experiment. A support vector machine (SVM)-based classifier was applied on the EEG single trials elicited by high arousal pictures with negative and positive valence scores. Based on the accuracy values obtained from subject identification tasks, the most distinguishing EEG channels among participants were detected, pointing which scalp regions show more distinct patterns.

RESULTS

Significant differences were obtained, in the EEG heterogeneity between positive and negative valence stimuli, yielding higher accuracy in subject identification using negative pictures. Regarding the topographical analysis, significantly higher accuracy values were reached in occipital areas and in the right hemisphere (p < 0.001).

CONCLUSIONS

Mainly, individual differences in EEG can be located in parietooccipital regions. These differences are likely to be due to the different reactivity and coping strategies to unpleasant stimuli in individuals with high neuroticism. In addition, the right hemisphere shows a greater individual specificity.

SIGNIFICANCE

An SVM-based classifier asserts the individual specificity and its topographical differences in electrophysiological activity for women with high neuroticism compared to low neuroticism.

Peak individual alpha frequency qualifies as a stable neurophysiological trait marker in healthy younger and older adults

The individual alpha frequency (IAF) of the human EEG reflects systemic properties of the brain, is highly heritable, and relates to cognitive functioning. Not much is known about the modifiability of IAF by cognitive interventions. We report analyses of resting EEG from a large-scale training study in which healthy younger (20-31 years, N = 30) and older (65-80 years, N = 28) adults practiced 12 cognitive tasks for ∼100 1-h sessions. EEG was recorded before and after the cognitive training intervention. In both age groups, IAF (and, in a control analysis, alpha amplitude) did not change, despite large gains in cognitive performance. As within-session reliability and test-retest stability were high for both age groups, imprecise measurements cannot account for the findings. In sum, IAF is highly stable in healthy adults up to 80 years, not easily modifiable by cognitive interventions alone, and thus qualifies as a stable neurophysiological trait marker.

Effect of test duration on the visual-evoked potential (VEP) and alpha-wave responses

PRIMARY OBJECTIVE

The purpose of this study was to assess the effect of test duration on the visual-evoked potential (VEP) and related alpha power spectrum measures.

DESIGN AND METHODS

Two conditions (eyes-closed and eyes-open) were tested using four different durations: 10, 20, 45, and 60 s. The Diopsys™ NOVA-TR system was used to obtain the visual-evoked potential (VEP) and extracted alpha wave with its related power spectrum. Sixteen visually normal, young-adult subjects (aged 22-25 years) participated in the experiment. The stimulus for the eyes-open condition consisted of a black-and-white, alternating checkerboard pattern with a small central fixation target. All trials were performed during one session.

RESULTS

Regarding the VEP parameters, only variability of the VEP amplitude changed significantly with test duration. Sentence should end with a period, not a colon. It decreased with increasing test duration, with the 45- and 60-s trials showing similarly low variability. Regarding the alpha-wave parameters, test duration did not have a significant effect on either the mean alpha power or its variability across trials.

CONCLUSIONS

The findings demonstrate that forty-five-second test durations are sufficient to minimize intra-session variability of the VEP amplitude and latency measurements, whereas 10-s test durations may be sufficient for accurate measurement of the alpha wave. Optimization of test duration allows for repeatable measures with less total test time. This is especially important for special clinical populations.

Action-related semantic content and negation polarity modulate motor areas during sentence reading: an event-related desynchronization study

Our study evaluated motor cortex involvement during silent reading of sentences referring to hand actions. We aimed at defining whether sentential polarity (affirmative vs. negative) would modulate motor cortex activation using the event-related desynchronization (ERD) analysis of the mu rhythm. Eleven healthy volunteers performed a reading task involving 160 sentences (80 affirmative: 40 hand-related, 40 abstract; 80 negative: 40 hand-related, 40 abstract). After reading each sentence, subjects had to decide whether the verb was high or low frequency in Italian. Electroencephalographic (EEG) activity was recorded with 32 surface electrodes and mu ERD analyses were performed for each subject. Hand-action related sentences induced a greater mu ERD over the left premotor and motor hand areas compared to abstract sentences. Mu ERD was greater and temporally delayed when the hand-related verbs were presented in the negative versus affirmative form. As predicted by the "embodied semantic" theory of language understanding, motor areas were activated during sentences referring to hand actions. In addition, motor cortex activation was larger for negative than affirmative motor sentences, a finding compatible with the hypothesis that comprehension is more demanding in the specific case of motor content negation.

Within-subject reliability and inter-session stability of EEG power and coherent activity in women evaluated monthly over nine months

OBJECTIVE

Quantitative EEG parameters during resting conditions are used as baseline in research on cognition and in serial-EEG recordings. Despite its increasing use in cognitive research and the numerous evidences of the existence of sex differences in EEG, EEG stability has been mainly investigated in men. Particularly, studies on stability of coherent activity are scarce. The aim of this study was to investigate within-subject reliability and inter-session stability of resting EEG over a nine-month period in women.

METHODS

Within-subject reliability and inter-session stability were analyzed for absolute power and inter- and intrahemispheric coherent activity at central and posterior regions, once a month, in resting conditions, with eyes open and closed.

RESULTS

Within-subject reliability was very high (r>0.89) for all subjects and EEG parameters. Inter-session stability was higher with eyes closed and for interhemispheric coherent activity, and poorer with eyes open especially in the alpha band.

CONCLUSIONS

Present results indicate high reliability of the pattern of power and coherent activity of each individual woman during rest, and group stability of EEG activity with eyes closed at least over a nine-month period.

SIGNIFICANCE

These results provide information on EEG stability in women over a long period.

Long-term stability and consistency of EEG event-related (de-)synchronization across different cognitive tasks

OBJECTIVE

We examined whether task-related band power changes (event-related desynchronization/synchronization; ERD/ERS) that have been linked to individual differences in cognitive ability demonstrate satisfying temporal stability and cross-situational consistency.

METHODS

Multi-channel EEG recordings from 29 adults, assessed at three different occasions over 2 years were examined. Between-session correlations and consistency coefficients (Cronbach's alpha) across the three experiments were evaluated for both, spectral power features of the resting EEG and ERD/ERS estimates while the participants performed some cognitive task (i.e. different elementary cognitive tasks that put comparable demands on the participants).

RESULTS

ERD/ERS values, while subjects performed a cognitive task, demonstrated satisfactory stability and consistency (i.e. >0.7), whereby the degree of consistency varied as a function of frequency band and brain region. Highest consistency was found for the 8-10 Hz ERD in parieto-occipital recording sites (i.e. >0.9). In resting EEG, mean alpha (gravity) frequency was the most stable EEG feature.

CONCLUSIONS

The present data suggest that ERD/ERS phenomena in different narrow frequency bands are rather stable over time and across different situations. The relatively high reproducibility of ERD/ERS promotes the usefulness of this measure in assessing individual differences of physiological activation patterns accompanying cognitive performance.

SIGNIFICANCE

This study addresses the issue of reproducibility of EEG in general and ERD/ERS experiments in particular, which is a prerequisite for both basic research and clinical studies.

Time course and variability of power in different frequency bands of EEG during resting conditions

The aim of the present study was to evaluate the variability of EEG power spectrum data, considering the time course of the EEG spectrum in resting conditions, and the relationship between the spectral parameters and the length of the analyzed segments. Recordings were performed in 57 normal subjects, with a protocol consisting of regular cycles with open eyes (5 s) followed by closed eyes (55 s) repeated during 10 min. Towards the end of the recording there was a decrease in the alpha and beta power and an increase in the delta and theta power. The coefficient of variation (CV) for the power of 4 s epochs was in the range 0.49-0.67 (delta), 0.53-0.58 (theta), 0.58-0.76 (alpha), 0.37-0.49 (beta) and 0.09-0.12 for the alpha peak frequency. CV decreased with the increase of the sample size, being inversely proportional to the square root of the sample size. Increasing the recording length from 40 to 400 s increased CV by 36% (alpha), 41% (beta), 29% (delta) and 35% (theta), while the standard error of the mean decreased by 55-60%. It is concluded that the power estimates of the EEG activity are heavily dependent on the length of the analyzed segments, and the way they are selected. This observation is particularly relevant for clinical and drug studies where short recordings are often used, thus significantly biasing the estimation of the EEG parameters. The present data provide an estimate on the minimal length of EEG required for a given level of variability.

Quantitative electroencephalography in mild cognitive impairment: longitudinal changes and possible prediction of Alzheimer's disease

The present study evaluated the clinical course of patients with mild cognitive impairment (MCI), the pattern of electroencephalography (EEG) changes following cognitive deterioration, as well as the potential of neurophysiological measures in predicting dementia. Twenty-seven subjects with MCI were followed for a mean follow up period of 21 months. Fourteen subjects (52%) progressed (P MCI) to clinically manifest Alzheimer's disease (AD), and 13 (48%) remained stable (S MCI). The two MCI subgroups did not differ in baseline EEG measures between each other and the healthy controls (n = 16), but had significantly lower theta relative power at left temporal, temporo-occipital, centro-parietal, and right temporo-occipital derivation when compared to the reference AD group (n = 15). The P MCI baseline alpha band temporo-parietal coherence, alpha relative power values at left temporal and temporo-occipital derivations, theta relative power values at frontal derivations, and the mean frequency at centro-parietal and temporo-occipital derivations overlapped with those for AD and control groups. After the follow-up, the P MCI patients had significantly higher theta relative power and lower beta relative power and mean frequency at the temporal and temporo-occipital derivations. A logistic regression model of baseline EEG values adjusted for baseline Mini-Mental Test Examination showed that the important predictors were alpha and theta relative power and mean frequency from left temporo-occipital derivation (T5-O1), which classified 85% of MCI subjects correctly.

Long-term intra-individual variability of the background EEG in normals

OBJECTIVES

Forty-five healthy adult volunteers underwent repeated qEEG examinations with retest intervals 25-62 months in order to investigate the long-term intra-individual variability of several qEEG features such as, absolute and relative power, power asymmetry, coherence, mean and peak frequency and entropy. Prior to any computations all parameters were transformed to Z-scores on the basis of a normal database.

METHODS

Correlation coefficients were used to test the effect of the time on the test-retest differences. Correlation coefficients were also computed between baseline and retest values, as a measure of intra-individual stability, to make our results comparable to most literature data. By computing the standard deviations for test-retest differences, the intra-individual variabilities of the examined parameters were obtained in the unit of inter-individual variability of normal population. The same calculations were carried out with values obtained from the odd and even numbered epochs of the same EEG sections. This way, that portion of the intra-individual variability was estimated that might be introduced even by chance only when the epochs were selected randomly from the same section of EEG conforming to selection criteria.

RESULTS

As for our results, further increase of test-retest differences with time after 25 months might be so insignificant that it could not be demonstrated in our test material. The long-term intra-individual variability for most parameters, especially for total absolute power and alpha mean frequency, was less than the inter-individual variability in the normal population. The moment-to-moment variability was least in the case of the absolute power.

CONCLUSIONS

Estimates for intra-individual variability expressed this way in Z-scores might easily be used in the follow-up of patients even for a few years.

Effects of alcohol, at two times of day, on EEG-derived indices of physiological arousal

Effects of alcohol consumption (0.8 ml/kg) on sleep propensity, spectral characteristics of the EEG and self-rated activation in 16 young male subjects, were investigated during sessions at each of two times of day (08.00 and 16.00). Within-session, time-related changes in the pattern of stage-1 sleep occurrence, and of spectral power in different EEG bands indicated that, irrespective of time of day, physiological arousal increased as estimated blood alcohol concentration (BAC) was rising, and decreased as BAC was falling. Subjective activation was reduced by alcohol during both phases of the BAC curve. A pattern of reduced stage-1 sleep occurrence, higher absolute high alpha power and higher ratings of activation suggested that, irrespective of alcohol condition, physiological and subjective arousal was higher during sessions starting at 16.00 than during those starting at 08.00. There were no significant interactions between alcohol and time of day in respect of any dependent variable. However, the degree to which effects reflecting circadian variation may have been masked by effects of limited sleep restriction prior to morning sessions remains unclear. Subjects reported having slept on only 23.5% of occasions when sleep was scored. Comparison of patterns of statistically significant changes in absolute and relative power in different bands indicated that the two indices do not provide exactly equivalent information about changes in the EEG.

Psychometric properties of resting anterior EEG asymmetry: temporal stability and internal consistency

We examined whether resting anterior electroencephalographic (EEG) asymmetry in the alpha frequency band has psychometric properties that would be expected of a measure assessing individual differences. In each of two experimental sessions, separated by three weeks, resting EEG in midfrontal and anterior temporal sites was recorded from 85 female adults during eight 60-s baselines. Resting alpha asymmetry demonstrated acceptable test-retest stability and excellent internal consistency reliability. Analyses including other frequency bands indicated that degree of stability varied somewhat as a function of band and region. In addition, asymmetry was less stable than absolute power. Discussion focuses on the implications of the present findings for the measurement and conceptualization of resting anterior asymmetry.

Test-retest reliability in EEG frequency analysis

This study was performed to gain a better understanding of EEG frequency analysis test-retest reliability in normal healthy adults, and to evaluate factors which could influence the measured inter-record differences. Nineteen subjects underwent serial EEG recordings at 5 min and 12-16 week intervals. Records were visually edited using a standardized protocol, and FFT frequency analysis performed on segments of 60, 40, or 20 sec total length. Correlation coefficients for broad band features averaged 0.92 over the 5 min retest interval and 0.84 over the 12-16 week interval. There was essentially no difference between correlation coefficients of absolute and relative power features. Coefficients based on 60 sec records were marginally higher than those of 40 or 20 sec records. On the other hand, test-retest percent differences were typically lower for relative as opposed to absolute power features, and 60 sec records showed consistently lower percent differences than did 40 or particularly 20 sec records. Peak alpha frequency and mean frequency were the most stable EEG features at either interval. Montage had significant effects on test-retest differences at the 12-16 week interval. A significant association between intra-record and inter-record variability could not be demonstrated.

Reliability of topographic quantitative EEG amplitude in healthy late-middle-aged and elderly subjects

Reliabilities of quantitative measures of absolute and relative EEG amplitudes were assessed in healthy older adults under the eyes closed (n = 46) and eyes opened (n = 45) conditions. For the theta, alpha, beta 1, and beta 2 bands, reliabilities of 28 scalp derivations were stable over the 4.5 month test interval. Reliabilities of delta were lower. When appropriate transformations were applied, the reliabilities of absolute EEG amplitude measures tended to exceed those of relative measures. There were not, however, striking differences in reliabilities under the eyes closed, as compared to eyes opened condition. We concluded that when coupled with the criterion of interpretability, the generally higher reliabilities of absolute, as opposed to relative, amplitude measures render them preferable in clinical research.

Reliability, validity and follow-up of the EEG in senile dementia: sequelae of sequential measurement

In a longitudinal study, slowing of the EEG in SDAT patients and elderly controls is investigated using both visual and power spectral analyses. For this a reliability study in 20 SDAT patients is performed and results for intra-rater, inter-rater and test-retest reliability (in 24 h) are used in the selection of parameters. Next, the diagnostic efficacy of the chosen parameters for SDAT is confirmed in a validity study in 43 SDAT patients, 41 elderly non-organic psychiatric patients and 51 elderly normals. In the longitudinal study 78 of these subjects could be retested after 20 months. The parameter for visual analysis appeared to be superior in actually showing a progress of slowing of the EEG in 20/21 SDAT patients over time. The parameter for power spectral analysis was superior in measuring the more subtle processes in the normal elderly. Results of these studies are used to discuss some problems in the measurement of EEG in SDAT over time.

Quantitative, waking EEG research on depression

Research published in the past decade that used quantitative indices to evaluate the waking EEG characteristics of depressed patients is reviewed. Methodological problems that make results of different research laboratories difficult to compare include diagnostic heterogeneity of depressed groups, lack of inclusion of control subjects, and differences in the EEG techniques. Despite interpretive problems that arise from such substantial variation, consistencies nevertheless emerge. Unmedicated, actively depressed patients appear to exhibit elevated EEG alpha and beta compared to control subjects. Delta and theta distinguished depressed patients from controls in some single studies, but variation in age, specific diagnostic depression categories, and EEG acquisition and analysis techniques rendered these results less definitive. Quantitative EEG differences that may distinguish depressed subject samples from those with other psychiatric disorders are considered. Factors that limit comparability of the findings are discussed in conjunction with strategies that deserve systematic study in future research.

Short-term variability in EEG frequency analysis

Knowledge of short-term EEG variability in computerized analysis is important before interpreting spectral EEGs or assessing changes that may be due to inherent variability and not necessarily related to a task (e.g., listening to a story), therapy or changes in underlying disease. Eighty to 120 sec of 14-channel, edited, bipolar EEG were recorded in normal subjects and analyzed using an FFT. Absolute and relative power in 5 standard frequency bands, and median and peak power frequencies were obtained for each 4 sec epoch, and the mean and standard deviation calculated for each parameter. The average variation of the mean power, absolute and relative, in the frequency bands was less than 10% although some parameters varied by up to 50% in an individual subject. Median and peak power had the least variability, about 3%. Changes in total power correlated positively with relative alpha power, but negatively or not at all with the other relative power measures. This suggests that interpretation of relative measures of delta, theta and beta in individual spectra may be dependent on total power or absolute alpha power. In addition, mathematical transformations were necessary to normalize the epoch data, suggesting that the mean and standard deviation of data from a series of epochs may not have maximal value unless a transformation is used. These results also indicate that caution is needed in interpreting changes in EEG frequency analysis data that are of the same magnitude as spontaneous EEG variability.

Temporal stability of multichannel, multimodal ERP recordings

Personnel assessment applications of event related brain potentials (ERP) require temporal stability. Visual, auditory and bimodal ERP records were obtained about two hours apart for a group of young adult males. Similar records were obtained from a group of older adults about two months apart. No ERP amplitude or temporal stability differences were found between the two groups. Age was positively correlated with visual stability measures and negatively correlated with auditory stability measures. No correlation of age with bimodal stability measures was found. Large individual subject differences were found for the ERP analog waveform and temporal stability. The ERPs were highly stable within subjects from session to session, whether recorded hours or months apart. Greatest stability was obtained for bimodal presentation, less for visual and least for the auditory records. Differences in patterns of waveform stability were found for site and modality conditions across individuals.

Microcomputer analysis of cortical power spectrum: calibration and correlates of behavioral artifacts

Cortical power spectrum (CPS) is a quantitative estimate of EEG spectral power density. The CPS provides suitably precise data for quantification and statistical inference compared to the qualitative evaluation of EGG when interpreted by clinicians or researchers. In the past decade, the CPS has been applied to the studies of cognitive functions, memory, psi phenomena, speech laterality, and states of consciousness including coma, sleep, anesthesia, pathophysiology and pain state. However, few systematic evaluations of CPS methodology have been reported, rendering cross-laboratory comparisons difficult and external validity of experimental results uncertain. This report first describes a calibration procedure employing a microcomputer system for measuring the functional relationship between input signals and output cortical powers. Second, we examine controlled behavioral artifact effects on the CPS. The behavioral artifacts observed in the CPS can provide a measurement anchor for less ambiguous interpretation of CPS experiments conducted in clinical or laboratory settings.

Computerized recognition of persons by EEG spectral patterns

Modified techniques of communication theory in connection with multivariate statistical procedures were applied to a sample of 82 patients for the purpose of defining EEG spectral patterns and for solving the relevant classification problems. Ten measurements per patient were made and it could be shown that a subject can be characterized and be recognized by his EEG spectral pattern with high reliability and a confidence probability of almost 90%. This result is valid not only for normal adults but also for schizophrenic patients, implying a close relationship between the EEG spectral pattern and the individual person. At the moment the nature of this relationship is not clear; in particular the supposed relationship to psychopathology could not be proved.