Determination of the Time Window of Event-Related Potential Using Multiple-Set Consensus Clustering.

ObjectiveCluster analysis of spatio-temporal event-related potential (ERP) data is a promising tool for exploring the measurement time window of ERPs. However, even after preprocessing, the remaining noise can result in uncertain cluster maps followed by unreliable time windows while clustering via conventional clustering methods. MethodsWe designed an ensemble deep clustering pipeline to determine a reliable time window for the ERP of interest from temporal concatenated grand average ERP data. The proposed pipeline includes semi-supervised deep clustering methods initialized by consensus clustering and unsupervised deep clustering methods with end-to-end architectures. Ensemble clustering from those deep clusterings was used by the designed adaptive time window determination to estimate the time window. ResultsAfter applying simulated and real ERP data, our method successfully obtained the time window for identifying the P3 components (as the interest of both ERP studies) while additional noise (e.g., adding 20 dB to −5 dB white Gaussian noise) was added to the prepared data. ConclusionCompared to the state-of-the-art clustering methods, a superior clustering performance was yielded from both ERP data. Furthermore, more stable and precise time windows were elicited as the noise increased. SignificanceOur study provides a complementary understanding of identifying the cognitive process using deep clustering analysis to the existing studies. Our finding suggests that deep clustering can be used to identify the ERP of interest when the data is imperfect after preprocessing.

Averaging amplitudes over consecutive time samples (i.e., time window) is widely used to calculate the peak amplitude of event-related potentials (ERPs). Cluster analysis of the spatio-temporal ERP data is a promising tool to determine the time window of an ERP of interest. However, determining an appropriate number of clusters to optimally represent ERPs is still challenging. Here, we develop a new method to estimate the optimal number of clusters utilizing consensus clustering. Various polarity dependent clustering methods, namely, k-means, hierarchical clustering, fuzzy c-means, self-organizing map, spectral clustering, and Gaussian mixture model, are used to configure consensus clustering after assessing them individually. When a range of clusters is applied many times, the optimal number of clusters should correspond to the expectation, which is the average of the obtained mean inner-similarities of estimated time windows across all conditions and groups converge in the satisfactory thresholds. In order to assess our method, the proposed method has been applied to simulated data and prospective memory experiment ERP data aimed to qualify N2 and P3, and N300 and prospective positivity components, respectively. The results of determining the optimal number of clusters meet at six cluster maps for both ERP data. In addition, our results revealed that the proposed method could be reliably applied to ERP data to determine the appropriate time window for the ERP of interest when the measurement interval is not accurately defined.

SummaryThe neural responses that distinguish novel from familiar items in recognition memory tasks are remarkably fast in both humans and nonhuman primates. In humans, the earliest onsets of neural novelty effects emerge at about ∼150–200 ms after stimulus onset [1–5]. However, in recognition memory studies with nonhuman primates, novelty effects can arise at as early as 70–80 ms [6, 7]. Here, we address the possibility that this large species difference in onset latencies is caused experimentally by the necessity of using reward reinforcement to motivate the detection of novel or familiar items in nonhuman primates but not in humans. Via magnetoencephalography in humans, we show in two experiments that the onset of neural novelty signals is accelerated from ∼200 ms to ∼85 ms if correct recognition memory for either novel or familiar items is rewarded. Importantly, this acceleration is independent of whether the detection of the novel or the familiar scenes is rewarded. Furthermore, this early novelty effect contributed to memory retrieval because neural reward responses, which were contingent upon novelty detection, followed ∼100 ms later. Thus, under the contextual influence of reward motivation, behaviorally relevant novelty signals emerge much faster than previously held possible in humans.

Current analysis of event-related potentials (ERP) data is usually based on the a priori selection of channels and time windows of interest for studying the differences between experimental conditions in the spatio-temporal domain. In this work we put forward a new strategy designed for situations when there is not a priori information about 'when' and 'where' these differences appear in the spatio-temporal domain, simultaneously testing numerous hypotheses, which increase the risk of false positives. This issue is known as the problem of multiple comparisons and has been managed with methods that control the false discovery rate (FDR), such as permutation test and FDR methods. Although the former has been previously applied, to our knowledge, the FDR methods have not been introduced in the ERP data analysis. Here we compare the performance (on simulated and real data) of permutation test and two FDR methods (Benjamini and Hochberg (BH) and local-fdr, by Efron). All these methods have been shown to be valid for dealing with the problem of multiple comparisons in the ERP analysis, avoiding the ad hoc selection of channels and/or time windows. FDR methods are a good alternative to the common and computationally more expensive permutation test. The BH method for independent tests gave the best overall performance regarding the balance between type I and type II errors. The local-fdr method is preferable for high dimensional (multichannel) problems where most of the tests conform to the empirical null hypothesis. Differences among the methods according to assumptions, null distributions and dimensionality of the problem are also discussed.

Posner and Cohen (1984) discovered the inhibition of return (IOR) phenomenon, which refers to the individual’s response to targets that appear in previously cued location, is slower than it is to the uncued location when the stimulus-onset asynchrony (SOA) is longer than 300ms. Psychologists agree that IOR is an adaptive and evolved mechanism that enhances the efficiency of attention during a visual search and allows people more easily to process targets that appear in novel positions. The current research uses event-related potentials (ERPs) and adopts a cue-target paradigm to investigate the IOR process during an emotion recognition task and the underlying mechanisms. We conducted a 2 (cue: valid cues, invalid cues) × 3 (target emotional: positive, negative, neutral) within-subject design, and selected the emotional face pictures (40 positive faces; 40 negative faces; 40 neutral faces) as the target stimuli of IOR. Sixteen participants of university students were instructed to complete the task of judging the target as emotional face or neutral one. Electroencephalogram (EEG) signals were recorded using a 64-electrode elastic cap and the Neuroscan ERP workstation. Based on the overall average map and the research literature, we divided the ERP components by the time windows in which they occurred: P1, 80～110 ms; N1, 110～140 ms; and N170, 140～180 ms. We used six electrodes (Po5, Po6, O1, O2, Poz and Oz) to detect the P1 and N1 components in the occipital region and two electrodes (P7 and P8) to detect the N170 component in the temporal occipital region. Repeated measure ANOVAs were conducted on the behavioural data and the measurements derived from ERP waveforms. The results demonstrate that the amplitude of P1 of the valid cues was smaller, while N1 amplitude was larger, compared with those of the invalid cues. N170 amplitudes for positive and negative faces were significantly larger than those for neutral ones. These results indicate that the response to the emotional stimulus are specialized and separated from IOR progress, and this separation consequently leads to the precedence of emotion processing when participants response to the valance of the targets, suggesting that IOR and emotional bias are two adaptation mechanisms which occur in two different neural pathways. Our findings also provide electrophysiological evidences for the research on the correlation of attention and emotion.

Examination of the temporal-spatial dynamics of working memory training-induced neuroplasticity

Film editing has attracted great theoretical and practical interest since the beginnings of cinematography. In recent times, the neural correlates of visual transitions at edit cuts have been at the focus of attention in neurocinematics. Many Event Related Potential (ERP) studies studies have reported the consequences of cuts involving narrative discontinuities, and violations of standard montage rules. However, less is known about edits that are meant to induce continuity. Here, we addressed the neural correlates of continuity editing involving scale, and angle variations across the cut within the same scene, two of the most popular devices used for continuity editing. We recorded the electroencephalographic signal obtained from 20 viewers as they watched four different cinematographic excerpts to extract ERPs at edit points. First, we were able to reproduce the general time and scalp distribution of the typical ERPs to filmic cuts in prior studies. Second, we found significant ERP modulations triggered by scale changes (scale out, scale in, or maintaining the same scale). Edits involving an increase in scale (scale out) led to amplification of the ERP deflection, and scale reduction (scale in) led to decreases, compared to edits that kept scale across the cut. These modulations coincide with the time window of the N300 and N400 components and, according to previous findings, their amplitude has been associated with the likelihood of consciously detecting the edit. Third, we did not detect similar modulations as a function of angle variations across the cut. Based on these findings, we suggest that cuts involving reduction of scale are more likely to go unnoticed, than ones that scale out. This relationship between scale in/out and visibility is documented in film edition manuals. Specifically, in order to achieve fluidity in a scene, the edition is designed from the most opened shots to the most closed ones.

The perception of spatial and successive contexts of auditory information develops during human ontogeny. We compared event-related potentials (ERPs) recorded in 5- to 6-year-old children (N = 15) and adults (N = 15) in response to a digital series with omitted digits to explore age differences in the perception of successive auditory information. In addition, ERPs in response to the sound of falling drops delivered binaurally were obtained to examine the spatial context of auditory information. The ERPs obtained from the omitted digits significantly differed in the amplitude and latency of the N200 and P300 components between adults and children, which supports the hypothesis that the perception of a successive auditory structure is less automated in children compared with adults. Although no significant differences were found in adults, the sound of falling drops presented to the left ears of children elicited ERPs with earlier latencies and higher amplitudes of P300 and N400 components in the right temporal area. Stimulation of the right ear caused increasing amplitude of the N100 component in children. Thus, the observed differences in auditory ERPs of children and adults reflect developmental changes in the perception of spatial and successive auditory information.

What guides the judgment of learning: Memory or heuristics? An event-related potential study

In the present study, subjects selectively attended to the color of checkerboards in a feature-based attention paradigm. Induced gamma band responses (GBRs), the induced alpha band, and the event-related potential (ERP) were analyzed to uncover neuronal dynamics during selective feature processing. Replicating previous ERP findings, the selection negativity (SN) with a latency of about 160 msec was extracted. Furthermore, and similarly to previous EEG studies, a gamma band peak in a time window between 290 and 380 msec was found. This peak had its major energy in the 55- to 70-Hz range and was significantly larger for the attended color. Contrary to previous human induced gamma band studies, a much earlier 40- to 50-Hz peak in a time window between 160 and 220 msec after stimulus onset and, thus, concurrently to the SN was prominent with significantly more energy for attended as opposed to unattended color. The induced alpha band (9.8-11.7 Hz), on the other hand, exhibited a marked suppression for attended color in a time window between 450 and 600 msec after stimulus onset. A comparison of the time course of the 40- to 50-Hz and 55- to 70-Hz induced GBR, the induced alpha band, and the ERP revealed temporal coincidences for changes in the morphology of these brain responses. Despite these similarities in the time domain, the cortical source configuration was found to discriminate between induced GBRs and the SN. Our results suggest that large-scale synchronous high-frequency brain activity as measured in the human GBR play a specific role in attentive processing of stimulus features.

BackgroundElectroencephalogram (EEG)‐based neurofeedback (NF) allows reward of desired brain activity in milliseconds. Compared to frequency power‐based approach during resting state EEG, event‐related potentials (ERPs) based NF during a task is technically challenging because of the cost of computation over a time window. We have previously established that left‐frontal memory‐related potentials discriminate normal cognitive aging from age‐ and education‐ matched older adults with risk of mild cognitive impairment (MCI). To modulate brainwaves during working memory retrieval towards healthier patterns, we develop an ERP‐based neurofeedback protocol to reward better memory‐related potentials.MethodThe training protocol is developed based on a modified delayed match‐to‐sample task also known as Bluegrass working memory paradigm. During each memory trial, a participant holds the sample target image in his/her working memory and responds whether each subsequent image is a Match or Nonmatch to the memory target by pressing the button. Real‐time classification of extracted ERP features is analyzed after stimulus onset, the dynamic machine‐learning program then modifies the stimulus by turning it into vivid color (reward) or leaving it with black‐and‐white (unrewarded). The processing pipeline has been developed using ERPs of older adults with and without MCI. The left frontal sites (F3 and F7) were preprocessed by re‐referencing and filtering with a 0.05 – 40 Hz band‐pass filter. For each participant, the EEG of 5 offline base trials in a 300‐600ms time window was used as a baseline. The ERP difference of the baseline versus the subsequent single trial is calculated to determine whether the image will be colored or left at black‐and‐white.ResultOur newly developed ERP‐neurofeedback protocol has succeeded in providing visual feedback based on fluctuation of single trial ERP in real time. The program was also designed to fit in each individual due to varied sensibility to NF. Currently we are to examine the feasibility and effectiveness of the proposed protocol by measuring memory indicators before and after NF training sessions.ConclusionWe have developed a new protocol using ERP‐based neurofeedback to improve personalized memory retrieval. The program is the first step to intervention trials for enhancing successful memory by rewarding desired memory‐related potentials in older brains.

The role of single trial variability in event related potentials in children with attention deficit hyperactivity disorder

Although the human brain is adapted to function within three-dimensional environments, conventional laboratory research commonly investigates cognitive mechanisms in a reductionist approach using two-dimensional stimuli. However, findings regarding mnemonic processes indicate that realistic experiences in Virtual Reality (VR) are stored in richer and more intertwined engrams than those obtained from the conventional laboratory. Our study aimed to further investigate the generalizability of laboratory findings and to differentiate whether the processes underlying memory formation differ between VR and the conventional laboratory already in early encoding stages. Therefore, we investigated the Repetition Suppression (RS) effect as a correlate of the earliest instance of mnemonic processes under conventional laboratory conditions and in a realistic virtual environment. Analyses of event-related potentials (ERPs) indicate that the ERP deflections at several electrode clusters were lower in VR compared to the PC condition. These results indicate an optimized distribution of cognitive resources in realistic contexts. The typical RS effect was replicated under both conditions at most electrode clusters for a late time window. Additionally, a specific RS effect was found in VR at anterior electrodes for a later time window, indicating more extensive encoding processes in VR compared to the laboratory. Specifically, electrotomographic results (VARETA) indicate multimodal integration involving a broad cortical network and higher cognitive processes during the encoding of realistic objects. Our data suggest that object perception under realistic conditions, in contrast to the conventional laboratory, requires multisensory integration involving an interconnected functional system, facilitating the formation of intertwined memory traces in realistic environments.

Event Abstract Back to Event Evidence for language-specificity of a BCI-based language training Mariacristina Musso1*, David Hübner2, Sarah Schwarzkopf1, Cornelius Weiller1 and Michael Tangermann2 1 Universitätsklinikum Freiburg, Neurology, Germany 2 Brain State Decoding Lab, Germany Introduction: Language therapy for aphasia following stroke generally focuses on patients’ specific language deficits and is guided and controlled by an external person, e.g. by the speech therapist or a trained volunteer [1]. In contrast, closed-loop approaches based on brain-computer interfaces (BCI) have been used successfully for motor impairments after stroke [2] and are guided and controlled by the patients themselves. This study aimed at investigating if a BCI-based approach can also be designed for language training to patients with aphasia. For the first time, we developed and implemented a BCI-based training protocol for chronic aphasia patients after stroke. After attending word stimuli, patients receive feedback based on the strength of task-relevant EEG signals. Feasibility of the protocol was previously evaluated in an offline study with 20 normally-aged controls. Material and Methods: Eight patients with an infarct in the left middle cerebral artery and chronic aphasia underwent about 30 hours of effective BCI-supported online training. During each training session, patients were seated in a ring of 6 loudspeakers (AMUSE paradigm, [3]) and brain signals were measured by EEG (32 channel passive Ag/AgCl electrodes). Patients heard a cueing sentence followed by a series of 6 bisyllabic words (concrete nouns) from which one correctly finished the sentence. After each trial, they received a feedback on whether the attended word predicted by event-related potentials (ERP) responses matched the target word. Before and after the training, all patients underwent an aphasia test battery for language assessment (Aachener Aphasie Test (AAT) [4] and Snodgrass naming test) as well as tests for executive functions (TAP, Corsi, digit span and word-fluency test). Two EEG-sessions (64 EEG channels) without feedback were conducted prior to the training to calibrate the BCI system and to determine parameters of the training protocol (e.g. the stimulation onset asynchrony between two words) for each patient. In addition, one session without feedback was recorded after the training to compare ERP responses. Results: The AAT showed a significant improvement of several subtests such as naming, writing, comprehension and the token subtest. Similarly, the naming performance in the Snodgrass & Vanderwart test also significantly increased. TAP, Corsi, digit span and word-fluency revealed deficits in executive functions in each patient prior to the training. Contrary to the language-related tests, we did not observe any significant improvements in these neuropsychological categories. Further evidence for the language-specificity of the training can be derived from the ERP analysis where word ERP responses showed an increase in amplitude of the P300 and N200 component and a decrease in P300 onset latency whereas the ERP results to tone stimuli did not show significant training-induced changes. Discussion & Conclusion: Our preliminary results showed that our BCI-supported aphasia training was very effective for the recovery of language deficits with an effect that generalizes to language aspects that had not been trained directly (such as writing or reading). This novel therapeutic approach did not train executive functions, but more directly distinct aspects of language-processing. Acknowledgements Acknowledgements: This work was (partly) supported by BrainLinks-BrainTools, Cluster of Excellence funded by the German Research Foundation (DFG), grant number EXC 1086 and by Wissenschaftliche Gesellschaft Freiburg im Breisgau. References References [1] M.C. Brady, H. Kelly, J. Godwin, P. Enderby, P. Campbell, Cochrane Database Syst. Rev. (2016) CD000425. [2] A. Remsik, B. Young, R. Vermilyea, L. Kiekhoefer, J. Abrams, S. Evander Elmore, P. Schultz, V. Nair, D. Edwards, J. Williams, V. Prabhakaran, Expert Rev. Med. Devices 13 (2016) 445–454. [3] M. Schreuder, B. Blankertz, M. Tangermann, PLoS One 5 (2010) e9813. [4] W. Huber, Aachener Aphasie-Test:(AAT), Hogrefe, Verlag für Psychologie, 1983. Keywords: Speech Therapy, Speech Processing, music processing, Executive Function, Stroke Conference: Academy of Aphasia 56th Annual Meeting, Montreal, Canada, 21 Oct - 23 Oct, 2018. Presentation Type: oral presentation Topic: not eligible for a student prize Citation: Musso M, Hübner D, Schwarzkopf S, Weiller C and Tangermann M (2019). Evidence for language-specificity of a BCI-based language training. Conference Abstract: Academy of Aphasia 56th Annual Meeting. doi: 10.3389/conf.fnhum.2018.228.00069 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 05 Apr 2018; Published Online: 22 Jan 2019. * Correspondence: Dr. Mariacristina Musso, Universitätsklinikum Freiburg, Neurology, Freiburg, Germany, mariachristina.musso@uniklinik-freiburg.de Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Mariacristina Musso David Hübner Sarah Schwarzkopf Cornelius Weiller Michael Tangermann Google Mariacristina Musso David Hübner Sarah Schwarzkopf Cornelius Weiller Michael Tangermann Google Scholar Mariacristina Musso David Hübner Sarah Schwarzkopf Cornelius Weiller Michael Tangermann PubMed Mariacristina Musso David Hübner Sarah Schwarzkopf Cornelius Weiller Michael Tangermann Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Comparison of single-word and adjective-noun phrase production using event-related brain potentials