Multivariate tests for the evaluation of high-dimensional EEG data

Binaural Beat Effects on Attention: A Study Based on the Oddball Paradigm

The impact of binaural beats (BBs) on human cognition and behavior remains and various methods have been used to measure their effect, including neurophysiological, psychometric, and human performance evaluations. The few approaches where the level of neural synchronicity and connectivity were measured by neuroimaging techniques have only been undertaken in spontaneous mode. The present research proposes an approach based on the oddball paradigm to study BB effect by estimating the level of attention induced by BBs. Evoked activity of 25 young adults between 19 and 24 years old with no hearing impairments nor clinical neurological history were analyzed. The experiment was conducted in two different sessions of 24.5 min. The first part consisted of 20-min BB stimulation in either theta (BBθ) or beta (BBβ). After the BB stimulation, an oddball paradigm was applied in each BB condition to assess the attentional effect induced by BBs. Attention enhancement is expected for BBβ with respect to BBθ. Target event related potentials (ERPs) were mainly analyzed in the time and time-frequency domains. The frequency analysis was based on continuous wavelet transform (CWT), event-related spectral perturbation (ERSP), and inter-trial phase coherence (ITPC). The study revealed that the P300 component was not significantly different between conditions (BBθ vs. BBβ). However, the target grand average ERP in BBθ condition was mainly composed of 8 Hz-frequency components, appearing before 400 ms post-stimulus, and mainly on the centro-parietal regions. In contrast, the target grand average ERP in BBβ condition was mainly composed of frequency components below 6 Hz, mainly appearing at 400 ms post-stimulus on the parieto-occipital regions. Furthermore, ERPs in the BBθ condition were more phase locked than the BBβ condition.

Arcuate fasciculus architecture is associated with individual differences in pre-attentive detection of unpredicted music changes

The mismatch negativity (MMN) is an event related brain potential (ERP) elicited by unpredicted sounds presented in a sequence of repeated auditory stimuli. The neural sources of the MMN have been previously attributed to a fronto-temporo-parietal network which crucially overlaps with the so-called auditory dorsal stream, involving inferior and middle frontal, inferior parietal, and superior and middle temporal regions. These cortical areas are structurally connected by the arcuate fasciculus (AF), a three-branch pathway supporting the feedback-feedforward loop involved in auditory-motor integration, auditory working memory, storage of acoustic templates, as well as comparison and update of those templates. Here, we characterized the individual differences in the white-matter macrostructural properties of the AF and explored their link to the electrophysiological marker of passive change detection gathered in a melodic multifeature MMN-EEG paradigm in 26 healthy young adults without musical training. Our results show that left fronto-temporal white-matter connectivity plays an important role in the pre-attentive detection of rhythm modulations within a melody. Previous studies have shown that this AF segment is also critical for language processing and learning. This strong coupling between structure and function in auditory change detection might be related to life-time linguistic (and possibly musical) exposure and experiences, as well as to timing processing specialization of the left auditory cortex. To the best of our knowledge, this is the first time in which the relationship between neurophysiological (EEG) and brain white-matter connectivity indexes using DTI-tractography are studied together. Thus, the present results, although still exploratory, add to the existing evidence on the importance of studying the constraints imposed on cognitive functions by the underlying structural connectivity.

Enteric neurons from Parkinson's disease patients display ex vivo aberrations in mitochondrial structure

Based on autopsy material mitochondrial dysfunction has been proposed being part of the pathophysiological cascade of Parkinson's disease (PD). However, in living patients, evidence for such dysfunction is scarce. As the disease presumably starts at the enteric level, we studied ganglionic and mitochondrial morphometrics of enteric neurons. We compared 65 ganglia from 11 PD patients without intestinal symptoms and 41 ganglia from 4 age-matched control subjects. We found that colon ganglia from PD patients had smaller volume, contained significantly more mitochondria per ganglion volume, and displayed a higher total mitochondrial mass relative to controls. This suggests involvement of mitochondrial dysfunction in PD at the enteric level. Moreover, in PD patients the mean mitochondrial volume declined in parallel with motor performance. Ganglionic shrinking was evident in the right but not in the left colon. In contrast, mitochondrial changes prevailed in the left colon suggesting that a compensatory increase in mitochondrial mass might counterbalance mitochondrial dysfunction in the left colon but not in the right colon. Reduction in ganglia volume and combined mitochondrial morphometrics had both predictive power to discriminate between PD patients and control subjects, suggesting that both parameters could be used for early discrimination between PD patients and healthy individuals.

Sensorimotor synchronization: neurophysiological markers of the asynchrony in a finger-tapping task

Sensorimotor synchronization (SMS) is a form of referential behavior in which an action is coordinated with a predictable external stimulus. The neural bases of the synchronization ability remain unknown, even in the simpler, paradigmatic task of finger tapping to a metronome. In this task the subject is instructed to tap in synchrony with a periodic sequence of brief tones, and the time difference between each response and the corresponding stimulus tone (asynchrony) is recorded. We make a step towards the identification of the neurophysiological markers of SMS by recording high-density EEG event-related potentials and the concurrent behavioral response-stimulus asynchronies during an isochronous paced finger-tapping task. Using principal component analysis, we found an asymmetry between the traces for advanced and delayed responses to the stimulus, in accordance with previous behavioral observations from perturbation studies. We also found that the amplitude of the second component encodes the higher-level percept of asynchrony 100 ms after the current stimulus. Furthermore, its amplitude predicts the asynchrony of the next step, past 300 ms from the previous stimulus, independently of the period length. Moreover, the neurophysiological processing of synchronization errors is performed within a fixed-duration interval after the stimulus. Our results suggest that the correction of a large asynchrony in a periodic task and the recovery of synchrony after a perturbation could be driven by similar neural processes.

Enhanced functional synchronization of medial and lateral PFC underlies internally-guided action planning

Actions are often internally guided, reflecting our covert will and intentions. The dorsomedial prefrontal cortex, including the pre-Supplementary Motor Area (pre-SMA), has been implicated in the internally generated aspects of action planning, such as choice and intention. Yet, the mechanism by which this area interacts with other cognitive brain regions such as the dorsolateral prefrontal cortex, a central node in decision-making, is still unclear. To shed light on this mechanism, brain activity was measured via fMRI and intracranial EEG in two studies during the performance of visually cued repeated finger tapping in which the choice of finger was guided by either a presented number (external) or self-choice (internal). A functional-MRI (fMRI) study in 15 healthy participants demonstrated that the pre-SMA, compared to the SMA proper, was more active and also more functionally correlated with the dorsolateral prefrontal cortex during internally compared to externally guided action planning (p < 0.05, random effect). In a similar manner, an intracranial-EEG study in five epilepsy patients showed greater inter-regional gamma-related connectivity between electrodes situated in medial and lateral aspects of the prefrontal cortex for internally compared to externally guided actions. Although this finding was observed for groups of electrodes situated both in the pre-SMA and SMA-proper, increased intra-cluster gamma-related connectivity was only observed for the pre-SMA (sign-test, p < 0.0001). Overall our findings provide multi-scale indications for the involvement of the dorsomedial prefrontal cortex, and especially the pre-SMA, in generating internally guided motor planning. Our intracranial-EEG results further point to enhanced functional connectivity between decision-making- and motor planning aspects of the PFC, as a possible neural mechanism for internally generated action planning.

Structured multiplicity and confirmatory statistical analyses in pharmacodynamic studies using the quantitative electroencephalogram

Pharmacodynamic (PD) clinical studies are characterised by a high degree of multiplicity. This multiplicity is the result of the design of these studies that typically investigate effects of a number of biomarkers at various doses and multiple time points. Measurements are taken at many or all points of a "hyper-grid" that can be understood as the cross-product of a number of dimensions each of which has typically 3-30 discrete values. This exploratory design helps understanding the phenomena under investigation, but has made a confirmatory statistical analysis of these studies difficult, so that such an analysis is often missing in this type of studies. In this contribution we show that the cross-product structure of PD studies allows to combine several well-known techniques to address multiplicity in an effective way, so that a confirmatory analysis of these studies becomes feasible without unrealistic loss of power. We demonstrate the application of this technique in two studies that use the quantitative EEG (qEEG) as biomarker for drug activity at the GABA-A receptor. QEEG studies suffer particularly from the curse of multiplicity, since, in addition to the common dimensions like dose and time, the qEEG is measured at many locations over the scalp and in a number of frequency bands which inflate the multiplicity by a factor of about 250.

Mass univariate analysis of event-related brain potentials/fields I: a critical tutorial review

Event-related potentials (ERPs) and magnetic fields (ERFs) are typically analyzed via ANOVAs on mean activity in a priori windows. Advances in computing power and statistics have produced an alternative, mass univariate analyses consisting of thousands of statistical tests and powerful corrections for multiple comparisons. Such analyses are most useful when one has little a priori knowledge of effect locations or latencies, and for delineating effect boundaries. Mass univariate analyses complement and, at times, obviate traditional analyses. Here we review this approach as applied to ERP/ERF data and four methods for multiple comparison correction: strong control of the familywise error rate (FWER) via permutation tests, weak control of FWER via cluster-based permutation tests, false discovery rate control, and control of the generalized FWER. We end with recommendations for their use and introduce free MATLAB software for their implementation.

Mass univariate analysis of event-related brain potentials/fields II: Simulation studies

Mass univariate analysis is a relatively new approach for the study of ERPs/ERFs. It consists of many statistical tests and one of several powerful corrections for multiple comparisons. Multiple comparison corrections differ in their power and permissiveness. Moreover, some methods are not guaranteed to work or may be overly sensitive to uninteresting deviations from the null hypothesis. Here we report the results of simulations assessing the accuracy, permissiveness, and power of six popular multiple comparison corrections (permutation-based control of the familywise error rate [FWER], weak control of FWER via cluster-based permutation tests, permutation-based control of the generalized FWER, and three false discovery rate control procedures) using realistic ERP data. In addition, we look at the sensitivity of permutation tests to differences in population variance. These results will help researchers apply and interpret these procedures.

The phonemic restoration effect reveals pre-N400 effect of supportive sentence context in speech perception

The phonemic restoration effect refers to the tendency for people to hallucinate a phoneme replaced by a non-speech sound (e.g., a tone) in a word. This illusion can be influenced by preceding sentential context providing information about the likelihood of the missing phoneme. The saliency of the illusion suggests that supportive context can affect relatively low (phonemic or lower) levels of speech processing. Indeed, a previous event-related brain potential (ERP) investigation of the phonemic restoration effect found that the processing of coughs replacing high versus low probability phonemes in sentential words differed from each other as early as the auditory N1 (120-180 ms post-stimulus); this result, however, was confounded by physical differences between the high and low probability speech stimuli, thus it could have been caused by factors such as habituation and not by supportive context. We conducted a similar ERP experiment avoiding this confound by using the same auditory stimuli preceded by text that made critical phonemes more or less probable. We too found the robust N400 effect of phoneme/word probability, but did not observe the early N1 effect. We did however observe a left posterior effect of phoneme/word probability around 192-224 ms-clear evidence of a relatively early effect of supportive sentence context in speech comprehension distinct from the N400.

New concepts of multiple tests and their use for evaluating high-dimensional EEG data

Recently, new concepts of type I error control in multiple comparisons have been proposed, in addition to FWE and FDR control. We introduce these criteria and investigate in simulations how the powers of corresponding test procedures for multiple endpoints depend on various quantities such as number and correlation of endpoints, percentage of false hypotheses, etc. We applied the different multiple tests to EEG coherence data. We compared the memory encoding of subsequently recalled and not recalled nouns. The results show that subsequently recalled nouns elicited significantly higher coherence than not recalled ones.

Multiple test procedures using an upper bound of the number of true hypotheses and their use for evaluating high-dimensional EEG data

Frequency analyses of EEG data yield large data sets, which are high-dimensional and have to be evaluated statistically without a large number of false positive statements. There exist several methods to deal with this problem in multiple comparisons. Knowing the number of true hypotheses increases the power of some multiple test procedures, however the number of true hypotheses is unknown, in general, and must be estimated. In this paper, we derive two new multiple test procedures by using an upper bound for the number of true hypotheses. Our first procedure controls the generalized family-wise error rate, and thus is an improvement of the step-down procedure of Hommel and Hoffmann [Hommel G., Hoffmann T. Controlled uncertainty. In: Bauer P. Hommel G. Sonnemann E., editors. Multiple Hypotheses Testing, Heidelberg: Springer 1987;ISBN 3540505598:p. 154-61]. The second new procedure controls the false discovery proportion and improves upon the approach of Lehmann and Romano [Lehmann E.L., Romano J.P. Generalizations of the familywise error rate. Ann. Stat. 2005;33:1138-54]. By Monte-Carlo simulations, we show how the gain in power depends upon the accuracy of the estimate of the number of true hypotheses. The gain in power of our procedures is demonstrated in an example using EEG data on the processing of memorized lexical items.

Comparison of Independent Samples of High-Dimensional Data by Pairwise Distance Measures

Pairwise distance or association measures of sample elements are often used as a basis for hierarchical cluster analyses. They can also be used in tests for the comparison of pre-defined subgroups of the total sample. Usually this is done with permutation tests In this paper, we compare such a procedure with alternative tests for high-dimensional data based on spherically distributed scores in simulation experiments and with real data. The tests based on the pairwise distance or similarity measures perform quite well in this comparison. As the number of possible permutations is small in very small samples, this might restrict the use of the test. Therefore, we propose an exact parametric small sample version of the test using randomly rotated samples.

A distributed computing system for multivariate time series analyses of multichannel neurophysiological data

We present a client-server application for the distributed multivariate analysis of time series using standard PCs. We here concentrate on analyses of multichannel EEG/MEG data, but our method can easily be adapted to other time series. Due to the rapid development of new analysis techniques, the focus in the design of our application was not only on computational performance, but also on high flexibility and expandability of both the client and the server programs. For this purpose, the communication between the server and the clients as well as the building of the computational tasks has been realized via the Extensible Markup Language (XML). Running our newly developed method in an asynchronous distributed environment with random availability of remote and heterogeneous resources, we tested the system's performance for a number of different univariate and bivariate analysis techniques. Results indicate that for most of the currently available analysis techniques, calculations can be performed in real time, which, in principle, allows on-line analyses at relatively low cost.

Characteristic functional networks in high- versus low-proficiency second language speakers detected also during native language processing: an explorative EEG coherence study in 6 frequency bands

An EEG coherence study was performed with a twofold objective: first, to scrutinize the theoretical concept of "cortical efficiency" in connection with second language (L2) acquisition and, second, to detect cooperations between cortical areas in specific frequency bands indicative for highly proficient L2 processing. Two groups differing only in their level of L2 proficiency were contrasted during presentation of natural language videos in English (L2) and German (native language, L1), with explorative coherence analysis in 6 frequency bands (0.5-31.5 Hz). The coherence brain maps revealed more pronounced and widespread increases in coherences in the alpha1-band (8-10 Hz) in low-proficiency than in the high-proficiency L2 speakers. Surprisingly, this difference was obtained also during L1 processing and corroborated for both languages by multivariate permutation tests. These tests revealed additional differences between the low- and the high-proficiency group also for coherences within the beta1- (13-18 Hz) and the beta2-band (18.5-31.5 Hz), again during L2 and L1 processing. Since the same group differences were observed during L1 and L2 processing, our high-proficiency group might have profited from a more generic advantage in language or text processing strategy. This strategic advantage was most evident at alpha1 frequencies, possibly related to a specific way of processing internal mental states (top-down processing).