EEG Session Research Articles

How does foreign accent affect template matching mechanisms? ERP evidence from Polish

Sentential context is believed to have particularly robust effects on the processing of foreign-accented speech (Lev-Ari 2015). However, recent neurolinguistic studies investigating the relation between non-native speech and semantic predictability suggest that anticipation mechanisms are, in fact, hampered during the processing of foreign accents (Romero-Rivas et al. 2016). The current study is an attempt to shed more light on this issue and establish whether the mechanisms responsible for categorical template matching remain active during the processing of non-native speech. The study investigated neural reactions towards high cloze probability template endings (i.e., the endings of fixed phrases selected in a pre-test) and their unexpected counterparts. 120 Polish sentences were recorded by a native Polish speaker and a non-native (L1 Ukrainian) speaker of Polish in order to investigate the reactions towards an easily recognizable foreign accent. The brain activity of 28 monolinguals (L1 Polish) was recorded during the EEG sessions. In native-accented speech, violations of high cloze probability items resulted in a broadly distributed negativity followed by a P600 effect. No comparable effects were observed in the case of foreign-accented speech. These results are compatible with previous findings (Hanulíková et al. 2012; Romero-Rivas et al. 2016) as they confirm that linguistic anticipatory and reanalysis processes are hampered in the case of non-native speech.

Experienced Meditators Exhibit No Differences to Demographically Matched Controls in Theta Phase Synchronization, P200, or P300 During an Auditory Oddball Task

Long-term meditation practice affects the brain’s ability to sustain attention. However, how this occurs is not well understood. Electroencephalography (EEG) studies have found that during dichotic oddball listening tasks, experienced meditators displayed altered attention-related neural markers including theta phase synchronization (TPS) and event-related potentials (ERP; P200 and P300) to target tones while meditating compared to resting, and compared to non-meditators after intensive meditation interventions. Research is yet to establish whether the changes in the aforementioned neural markers are trait changes which may be observable in meditators irrespective of practice setting. The present study expanded on previous research by comparing EEG measures from a dichotic oddball task in a sample of community-based mindfulness meditators (n = 22) to healthy controls with no meditation experience (n = 22). To minimize state effects, neither group practiced meditation during/immediately prior to the EEG session. No group differences were observed in behavioural performance or either the global amplitude or distribution of theta phase synchronization, P200 or P300. Bayes factor analysis suggested evidence against group differences for the P200 and P300. The results suggest that increased P200, P300, and TPS do not reflect trait-related changes in a community sample of mindfulness meditators. The present study used a larger sample size than previous research and power analyses suggested the study was sufficiently powered to detect differences. These results add nuance to our understanding of which processes are affected by meditation and the amount of meditation required to generate differences in specific neural processes.

FMRI signatures of perceptual echoes in early visual cortex

Abstract The visual Impulse Response Function (IRF) can be estimated by cross-correlating random luminance sequences with concurrently recorded EEG. It typically contains a strong 10Hz oscillatory component, suggesting that visual information reverberates in the human brain as a “perceptual echo”. The neural origin of these echoes remains unknown. To address this question, we recorded EEG and fMRI in two separate sessions. In both sessions, a disk whose luminance followed a random (white noise) sequence was presented in the upper left quadrant. Individual IRFs were derived from the EEG session. These IRFs were then used as “response templates” to reconstruct an estimate of the EEG during the fMRI session, by convolution with the corresponding random luminance sequences. The 7-14Hz (alpha) envelope of the reconstructed EEG was finally used as an fMRI regressor, to determine which brain voxels co-varied with the oscillations elicited by the luminance sequence, i.e. the “perceptual echoes”. The reconstructed envelope of EEG alpha was significantly correlated with BOLD responses in V1 and V2. Surprisingly, this correlation was visible outside, but not within the directly (retinotopically) stimulated region. We tentatively interpret this lack of alpha modulation as a BOLD saturation effect, since the overall stimulus-induced BOLD response was inversely related, across voxels, to the signal variability over time. In conclusion, our results suggest that perceptual echoes originate in early visual cortex, driven by widespread activity in V1 and V2, not retinotopically restricted, but possibly reflecting the propagation of a travelling alpha wave.

Biometric identification of listener identity from frequency following responses to speech

Objective. We investigate the biometric specificity of the frequency following response (FFR), an EEG marker of early auditory processing that reflects phase-locked activity from neural ensembles in the auditory cortex and subcortex (Chandrasekaran and Kraus , Bidelman, , , Coffey et al ). Our objective is two-fold: demonstrate that the FFR contains information beyond stimulus properties and broad group-level markers, and to assess the practical viability of the FFR as a biometric across different sounds, auditory experiences, and recording days. Approach. We trained the hidden Markov model (HMM) to decode listener identity from FFR spectro-temporal patterns across multiple frequency bands. Our dataset included FFRs from twenty native speakers of English or Mandarin Chinese (10 per group) listening to Mandarin Chinese tones across three EEG sessions separated by days. We decoded subject identity within the same auditory context (same tone and session) and across different stimuli and recording sessions. Main results. The HMM decoded listeners for averaging sizes as small as one single FFR. However, model performance improved for larger averaging sizes (e.g. 25 FFRs), similarity in auditory context (same tone and day), and lack of familiarity with the sounds (i.e. native English relative to native Chinese listeners). Our results also revealed important biometric contributions from frequency bands in the cortical and subcortical EEG. Significance. Our study provides the first deep and systematic biometric characterization of the FFR and provides the basis for biometric identification systems incorporating this neural signal.

P03-S Repeated baseline EEG measures effectiveness for early detection of at-risk older adults

Background Age and disease related cognitive declines have important socioeconomic implications. Identifying those who are at risk and the underlying mechanisms for accelerated cognitive decline are vital for guiding interventions and improving early prediction of dementia. We propose a novel approach for risk prediction using repeated electrophysiological recording prior to and following visuospatial cognitive stimulation. Methods Forty-six consensus diagnosed, non-demented, community dwelling African American older participants over age 60 years received EEG and NIH Toolbox-Cognition and Brief CogState computer administered cognitive batteries. In between two resting EEG (eyes closed) sessions participants engaged in a visual motion direction discrimination task for approximately 20 min. The outcome measures were % changes of spectral power between pre/post EEGs. Results There was a decrease in spectral power of eyes-closed EEG across all the frequency ranges at post as compared pre-EEG recording, with the greatest at the beta range (12–30 Hz) – 41% (p Conclusions Our preliminary results demonstrate that EEG reactivity, repeated eyes-closed baseline EEG after short visual cognitive stimulation, showed significant decrease primarily in beta range that correlated with neuropsychological performance. Thus, the baseline EEG reactivity findings are very promising in terms of identifying those older adults who are at risk for accelerated cognitive decline.

Don’t you want me, baby? Cardiac and electrocortical concomitants of romantic interest and rejection

Online dating has become a very popular way to find a romantic partner. In the present study, we examined whether romantic interest and rejection in such a setting would evoke differential electrocortical and cardiac responses. For this purpose a database was created, similar to a dating website, where the participants’ personal information and photos were placed. Heterosexual, single participants (N = 61) evaluated the profiles of opposite-sex potential romantic partners and decided whether they would like to date this person or not. Subsequently, participants passively viewed (34 analyzable volunteers participated in the EEG session; 10 male; mean age = 20) the pictures of the potential partners together with their own judgment about the “dateability” of the potential partner, and the potential partner’s judgment of the “dateability” of the participant. After viewing the pictures participants received the email addresses to contact their matches. Electrocortical and cardiac responses to these “match” or “non-match” judgments were measured. A significantly larger P3 response was found when participants received a positive evaluation as compared to negative evaluations. This is in line with an explanation in terms of reward. A significantly larger cardiac deceleration was found when participants received a negative evaluation as compared to positive evaluations, which is in line with an explanation in terms of social pain. Findings are discussed in terms of activation of different parts of the anterior cingulate cortex.

Functional MRI and EEG Index Complementary Attentional Modulations.

Functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) are two noninvasive methods commonly used to study neural mechanisms supporting visual attention in humans. Studies using these tools, which have complementary spatial and temporal resolutions, implicitly assume they index similar underlying neural modulations related to external stimulus and internal attentional manipulations. Accordingly, they are often used interchangeably for constraining understanding about the impact of bottom-up and top-down factors on neural modulations. To test this core assumption, we simultaneously manipulated bottom-up sensory inputs by varying stimulus contrast and top-down cognitive modulations by changing the focus of spatial attention. Each of the male and female subjects participated in both fMRI and EEG sessions performing the same experimental paradigm. We found categorically different patterns of attentional modulation on fMRI activity in early visual cortex and early stimulus-evoked potentials measured via EEG (e.g., the P1 component and steady-state visually-evoked potentials): fMRI activation scaled additively with attention, whereas evoked EEG components scaled multiplicatively with attention. However, across longer time scales, a contralateral negative-going potential and oscillatory EEG signals in the alpha band revealed additive attentional modulation patterns like those observed with fMRI. These results challenge prior assumptions that fMRI and early stimulus-evoked potentials measured with EEG can be interchangeably used to index the same neural mechanisms of attentional modulations at different spatiotemporal scales. Instead, fMRI measures of attentional modulations are more closely linked with later EEG components and alpha-band oscillations. Considered together, hemodynamic and electrophysiological signals can jointly constrain understanding of the neural mechanisms supporting cognition.SIGNIFICANCE STATEMENT fMRI and EEG have been used as tools to measure the location and timing of attentional modulations in visual cortex and are often used interchangeably for constraining computational models under the assumption that they index similar underlying neural processes. However, by varying attentional and stimulus parameters, we found differential patterns of attentional modulations of fMRI activity in early visual cortex and commonly used stimulus-evoked potentials measured via EEG. Instead, across longer time scales, a contralateral negative-going potential and EEG oscillations in the alpha band exhibited attentional modulations similar to those observed with fMRI. Together, these results suggest that different physiological processes assayed by these complementary techniques must be jointly considered when making inferences about the neural underpinnings of cognitive operations.

Standardized music therapy with and without acclimatization, to improve EEG data acquisition in young children with and without disability

IntroductionIn young children, EEG data acquisition during stimulation tasks is difficult due to anxiety, movement and behaviorally-related interruptions, especially in those with disabilities. New methodWe used standardized music therapy (MT) protocols with and without acclimatization, during and prior to time-locked EEG with a published tactile testing protocol. Our prospective study leveraged a larger trial in children with/without cerebral palsy aged 7–27 months. Group1 received no preparation, Group2 received 15-minute MT prior to the EEG session, Group3 received the same as Group2 plus a rubber cap for home practice. All groups received MT procedural support during the EEG session. Sessions were stopped/started to acquire a full dataset. Trials were reviewed using a two-step artifact detection strategy by specialists masked to group allocation. Results64 patients were included, 20 each in Groups 2 and 3, and 24 in Group1. Average age was 16.08 ± 6.33 months. All (100%) of children had data of sufficient quality and quantity for outcomes measurement without a second testing visit. There were no differences in useable trials by procedural group, disability status, age or stimulus condition. EEG recording time was shorter in Group3 vs. 1 (p = 0.02) and more patients in Group1 required repeat trials compared to Groups2 and 3 (p = 0.04 for both). Comparison with old methodOur new methods resulted in no attrition from data loss, an improvement compared to published similar studies with data loss 30–55%. Acclimatization had minimal effects. ConclusionIn children under 3, MT protocols result in high rates of EEG data acquisition, decrease behaviorally-related interruptions and session acquisition time. This method is successful for typically developing children and those with cerebral palsy.

Test-retest reliability of EEG network characteristics in infants.

IntroductionFunctional Electroencephalography (EEG) networks in infants have been proposed as useful biomarkers for developmental brain disorders. However, the reliability of these networks and their characteristics has not been established. We evaluated the reliability of these networks and their characteristics in 10‐month‐old infants.MethodsData were obtained during two EEG sessions 1 week apart and was subsequently analyzed at delta (0.5–3 Hz), theta (3–6 Hz), alpha1 (6–9 Hz), alpha2 (9–12 Hz), beta (12–25 Hz), and low gamma (25–45 Hz) frequency bands. Connectivity matrices were created by calculating the phase lag index between all channel pairs at given frequency bands. To determine the reliability of these connectivity matrices, intra‐class correlations were calculated of global connectivity, local connectivity, and several graph characteristics.ResultsComparing both sessions, global connectivity, as well as global graph characteristics (characteristic path length and average clustering coefficient) are highly reliable across multiple frequency bands; the alpha1 and theta band having the highest reliability in general. In contrast, local connectivity characteristics were less reliable across all frequency bands.ConclusionsWe conclude that global connectivity measures are highly reliable over sessions. Local connectivity measures show lower reliability over sessions. This research therefore underlines the possibility of these global network characteristics to be used both as biomarkers of neurodevelopmental disorders, but also as important factors explaining development of typical behavior.

Age, Sex, and Pathology Effects on Stability of Electroencephalographic Biometric Features Based on Measures of Interaction

Electroencephalographic (EEG) biometric features have attracted considerable interest, but they have also drawn major criticism as having low stability. Moreover, most published studies ignore the potential effect of individual factors interacting with stability on the performance of the examined system. We examined the effects of age, sex, and neurological conditions in 60 subjects: 1) using a single EEG recording; 2) when pooling two EEG sessions; and 3) when performing cross-session cross-validation in a biometric system based on multivariate autoregressive measures, in order to extend previous work on autoregressive coefficients. Feature-level fusion and wrapped feature subset-selection in multivariate autoregressive coefficients (MVAR), power spectral density, and 14 additional measures derived from the MVAR model resulted in a maximum area under the curve of receiver operating characteristics (AUC of ROC)/top equal error rate of 98.85/5.34 for a single EEG, 95.51/9.70 for EEG-pooling, and 85.34/22 for cross-session cross-validation. This best result was obtained by the transfer function polynomial, which outperformed the MVAR coefficients, based on the example data set used in this paper. Age, sex, and pathology significantly interacted with the stability of features ( $p ). We suggest further investigation of frequency-dependent measures derived from the MVAR model. We emphasize the serious problem of ignoring stability in most previously published research and recommend accurate reporting of individual factors when studying EEG biometric features in multiple sessions for enrolment and authentication on separate days.

Proceedings #11: Replay of Endogenous Sleep Rhythms to Produce Sleepiness

Varying modes of non-invasive electrical stimulation techniques have been investigated to induce endogenous sleep-like states (historically called Electrosleep). These include transcranial pulsed current stimulation (tPCS) such as Cranial Electrical Stimulation, transcranial direct current stimulation (tDCS), and transcranial alternating current stimulation (tACS) such as 10 Hz sinusoidal stimulation. Prior efforts used synthetic (simple) waveforms selected to modulate excitability (e.g. tDCS) or reproduce a single predominant frequency of endogenous neuronal rhythms of sleep induction (e.g. 10 Hz). To examine the effects of electrical stimulation with a complete spectrum sleep-related endogenous neural activity, we designed and applied an endogenous sleep-derived stimulation waveform to subjects while assessing a range subjective performance and objective physiological data. We hypothesized that a stimulation with complex high-bandwidth waveform reflecting endogenous sleep-associated neuronal activity patterns (transcranial Endogenous Sleep-Derived; tESD) would be more effective, than synthetic frequency-specific waveforms such at tACS, in supporting the transition to sleepiness. The basis for the transcranial Endogenous Sleep-Derived (tESD) waveform was acquired during a resting, sleepy-state EEG session. Data were examined for markers of sleepiness and corresponding segments were extracted, compressed, and scaled to produce a current signal. Stimulation was applied through a custom, high-bandwidth current-control stimulator. Subjects were supine in a light and sound attenuated environment. Using HD bipolar montage (AF7, AF8) with a maximal current amplitude of 0.5 mA over 10 minutes. tESD was also simulated in a computational model. Physiology (EEG, ECG, respiration, EOG, EMG) and behavior (questionnaires, reaction time) was assessed before, during (only for physiology), and after stimulation. Each subject underwent tESD, 10 Hz tACS, and a no-stimulation (non-interventional) sessions in a counterbalanced manner with at least 24 hours between each session. tESD polarized the frontal lobe. Changes in the no-stimulation condition confirms the testing environment was conducive to a wakefulness–sleep transition. Preliminary data indicate an enhanced shift in physiological measures in directions consistent with a relaxed and sleepy state with tESD compared to tACS and no-stimulation conditions. Behavioral data indicate a delay in reactions times post stimulation and subjective sleepiness reports indicate higher sleepiness post stimulation. tESD was well tolerated and blinding was effective. tESD aims to “replay” the endogenous neuronal signature of sleep. Neurophysiological (EEG), physiological (heart rate, respiration) and behavioral (simple reaction time, PVT) indicate that tESD, directed to frontal brain regions, that are associated with top-down thalamo-cortical sleep control mechanisms, accelerated wakefulness–sleep transition in subjects in a baseline relaxed state.

Does mindfulness training modulate the influence of spatial attention on the processing of intracutaneous electrical stimuli?

Mindfulness based stress reduction (MBSR) training has been proposed to improve attentional skills by modulating thalamo-cortical loops that affect the sensitivity of relevant cortical areas like the somatosensory cortex. This modulation may be reflected in the electroencephalographic (EEG) alpha rhythm, and could affect the processing of subsequently applied intracutaneous electrical stimuli. Participants took part in an MBSR training and participated in two EEG sessions. EEG was measured in variants of an endogenous orienting paradigm in which attention had to be directed to the left or right forearm. After the orienting interval, the electrical stimulus was applied, equally likely on the attended or the unattended forearm. One group of participants took part in the EEG session before and after the training, while the other group took part after the training, and another time, eight weeks later. The influence of the MBSR training and spatial attention were examined with behavioral measures, lateralized alpha power within the orienting interval, and with event-related potentials (ERPs) evoked by the electrical stimuli. Self-reported mindfulness was clearly affected by the training, but no influence was found on other behavioral measures. Alpha power was clearly lateralized due to spatial attention and several ERP components (N130, N180, P340) were modulated by spatial attention but no support was found for an influence of the MBSR training. Finally, analyses revealed that individual differences in training time modulated some of the observed effects, but no support was found for an influence on attentional orienting.

The Effect of Training-Induced Visual Imageability on Electrophysiological Correlates of Novel Word Processing.

The concreteness effect (CE) describes a processing advantage for concrete over abstract words. Electrophysiologically, the CE manifests in higher N400 and N700 amplitudes for concrete words. The contribution of the stimulus-inherent imageability to the electrophysiological correlates of the CE is not yet fully unraveled. This EEG study focused on the role of imageability irrespective of concreteness by examining the effects of training-induced visual imageability on the processing of novel words. In two training sessions, 21 healthy participants learned to associate novel words with pictures of novel objects as well as electron-microscopical structures and were additionally familiarized with novel words without any picture association. During a post-training EEG session, participants categorized trained novel words with or without picture association, together with real concrete and abstract words. Novel words associated with novel object pictures during the training elicited a higher N700 than familiarized novel words without picture-association. Crucially, this training-induced N700 effect resembled the CE found for real words. However, a CE on the N400 was found for real words, but no effect of imageability in novel words. The results suggest that the N400 CE for real words depends on the integration of multiple semantic features, while mere visual imageability might contribute to the CE in the N700 time window.

Neural Responsiveness to Reward as an Index of Depressive Symptom Change Following Cognitive-Behavioral Therapy and SSRI Treatment.

Reward positivity (RewP), a neurophysiologic index of reward responsivity, is consistently reduced in participants with depression and, to a lesser extent, anxiety. It remains unknown, however, whether RewP can be altered as psychiatric symptoms change with treatment. The current study addressed this question by examining differences in RewP within patients before and after 12 weeks of treatment with a selective serotonin reuptake inhibitor (SSRI) or cognitive-behavioral therapy (CBT). We also examined the utility of RewP as a predictor of symptom change during CBT and SSRI treatment. Participants were recruited between 2014 and 2017 and included adults with a primary DSM-5 anxiety or depressive disorder (n = 63) and healthy controls (n = 25). At baseline and 12 weeks, participants completed a monetary award task while electroencephalogram (EEG) was recorded. Between EEG sessions, patients completed CBT or SSRI treatment. At baseline, higher levels of depressive symptoms were associated with a more attenuated RewP. We found no significant differences between patients and healthy controls in the degree of RewP change across the 12 weeks; however, among patients, the extent of increase in RewP robustly correlated with the extent of decline in depressive (t = -2.21, P = .03) and anxiety (t = -2.57, P = .02) symptoms following CBT and SSRI treatment. Additionally, a more attenuated RewP at baseline predicted a greater reduction in depressive symptoms following treatment with SSRIs (t = -2.04, P < .05), but not after CBT. These findings highlight neural responsiveness to reward as both a mechanism and a predictor of depressive symptom change that may be used serve as an objective index of symptom improvement. ClinicalTrials.gov identifier: NCT01903447.

Children's neural processing of moral scenarios provides insight into the formation and reduction of in-group biases.

Survival is dependent on sociality within groups which ensure sustenance and protection. From an early age, children show a natural tendency to sort people into groups and discriminate among them. The computations guiding evaluation of third-party behaviors are complex, requiring integration of intent, consequences, and knowledge of group affiliation. This study examined how perceiving third-party morally laden behavior influences children's likelihood to exhibit or reduce group bias. Following a minimal group paradigm assignment, young children (4-7 years) performed a moral evaluation task where group affiliations and moral actions were systematically juxtaposed, so that they were exposed to disproportionately antisocial in-group and prosocial out-group scenarios. Electroencephalography was recorded, and group preference was assessed with a resource allocation game before and after the EEG session. Across all children, evaluations of others' moral actions arose from early and automatic processing (~150 ms), followed by later interactive processing of affiliation and moral valence (~500 ms). Importantly, individual differences in bias manifestation and attitude change were predicted by children's neural responses. Children with high baseline bias selectively exhibited a rapid detection (~200 ms) of scenarios inconsistent with their bias (in-group harm and out-group help). Changes in bias corresponded to distinct patterns in longer latency neural processing. These new developmental neuroscience findings elucidate the multifaceted processing involved in moral evaluation of others' actions, their group affiliations, the nature of the integration of both into full judgments, and the relation of individual differences in neural responses to social decision-making in childhood.

Impaired mismatch negativity to frequency deviants in individuals at ultra-high risk for psychosis, and preliminary evidence for further impairment with transition to psychosis

BackgroundThere is evidence to suggest that people with established psychotic disorders show impairments in the mismatch negativity induced by a frequency-deviant sound (fMMN), and that these impairments worsen with the deterioration of psychotic symptoms. This study aimed to test whether individuals at ultra-high risk (UHR) for psychosis show pre-morbid impairments in fMMN, and if so, whether fMMN continues to deteriorate with transition to psychosis. MethodfMMN was recorded in a cohort of UHR individuals (n=42) and compared to healthy controls (n=29). Of the 27 UHR participants who returned for a second EEG session, six participants had transitioned to psychosis by 12-month follow-up (UHR-T) and were compared to the 21 participants who did not transition (UHR-NT). ResultsfMMN amplitude was significantly reduced, relative to healthy controls, in the UHR cohort. Furthermore, UHR-T individuals showed a significant decrease in fMMN amplitude over the period from baseline to post-transition; this reduction was not observed in UHR-NT. ConclusionsThese results suggest that fMMN is abnormal in UHR individuals, as has repeatedly been found previously in people with established psychotic disorders. The finding that fMMN impairment worsens with transition to psychosis is consistent with the staging model of psychosis; however, caution must be taken in interpreting these findings, given the extremely small sample size of the UHR-T group.

Structural Integrity in the Genu of Corpus Callosum Predicts Conflict-induced Functional Connectivity Between Medial Frontal Cortex and Right Posterior Parietal Cortex

Studies using the flanker task have reported that response conflict is detected by the medial frontal cortex (MFC). As a conflict alert system, the MFC shows enhanced functional communication with task-related regions. Previous studies have revealed individual differences in functional connectivity during cognitive task performance. However, the mechanisms underlying these individual differences remain unclear. In the current study, electroencephalography (EEG) was recorded while 30 subjects performed a flanker task that was modified to exclude feature integration and contingency learning. The diffusion tensor imaging (DTI) data were collected the day before the EEG session. FCz-P3/4 theta phase synchronization was used to measure functional connectivity between the MFC and posterior parietal cortex (PPC). Hierarchical regression analyses were used to assess the relationship between MFC-PPC conflict-induced theta phase synchronization and white matter integrity in significant regions derived from tract-based spatial statistics (TBSS) analysis. As expected, MFC-PPC theta phase synchronization was significantly enhanced during conflict, suggesting a conflict-induced functional connectivity. However, these findings were only found in the right hemisphere, which may be related to the asymmetrical role of the bilateral PPC in response conflict processing. Furthermore, hierarchical regression analyses revealed that 44% of individual variability in FCz-P4 conflict-induced theta phase synchronization could be explained by variations in axial diffusivity (AD) in the genu of the corpus callosum (gCC). These results demonstrated that structural integrity in the gCC predicts conflict-induced functional connectivity between the MFC and right PPC.

Association of an Electroencephalography-Based Risk Score With Seizure Probability in Hospitalized Patients

Continuous electroencephalography (EEG) use in critically ill patients is expanding. There is no validated method to combine risk factors and guide clinicians in assessing seizure risk. To use seizure risk factors from EEG and clinical history to create a simple scoring system associated with the probability of seizures in patients with acute illness. We used a prospective multicenter (Emory University Hospital, Brigham and Women's Hospital, and Yale University Hospital) database containing clinical and electrographic variables on 5427 continuous EEG sessions from eligible patients if they had continuous EEG for clinical indications, excluding epilepsy monitoring unit admissions. We created a scoring system model to estimate seizure risk in acutely ill patients undergoing continuous EEG. The model was built using a new machine learning method (RiskSLIM) that is designed to produce accurate, risk-calibrated scoring systems with a limited number of variables and small integer weights. We validated the accuracy and risk calibration of our model using cross-validation and compared its performance with models built with state-of-the-art logistic regression methods. The database was developed by the Critical Care EEG Research Consortium and used data collected over 3 years. The EEG variables were interpreted using standardized terminology by certified reviewers. All patients had more than 6 hours of uninterrupted EEG recordings. The main outcome was the average risk calibration error. There were 5427 continuous EEGs performed on 4772 participants (2868 men, 49.9%; median age, 61 years) performed at 3 institutions, without further demographic stratification. Our final model, 2HELPS2B, had an area under the curve of 0.819 and average calibration error of 2.7% (95% CI, 2.0%-3.6%). It included 6 variables with the following point assignments: (1) brief (ictal) rhythmic discharges (B[I]RDs) (2 points); (2) presence of lateralized periodic discharges, lateralized rhythmic delta activity, or bilateral independent periodic discharges (1 point); (3) prior seizure (1 point); (4) sporadic epileptiform discharges (1 point); (5) frequency greater than 2.0 Hz for any periodic or rhythmic pattern (1 point); and (6) presence of "plus" features (superimposed, rhythmic, sharp, or fast activity) (1 point). The probable seizure risk of each score was 5% for a score of 0, 12% for a score of 1, 27% for a score of 2, 50% for a score of 3, 73% for a score of 4, 88% for a score of 5, and greater than 95% for a score of 6 or 7. The 2HELPS2B model is a quick accurate tool to aid clinical judgment of the risk of seizures in critically ill patients.

P 69 Assessing the relation between brain structure and function during motor imagery in stroke patients and controls using EEG and MRI

Background Motor imagery (MI) training, in particular in combination with EEG-based neurofeedback (MI-NF), has been suggested as a potential add-on therapy for rehabilitation of upper limb motor impairments after stroke. Most MI-NF implementations are based on the event-related desynchronization (ERD) in the 8–30 Hz frequency range that is typically observed over sensorimotor areas during motor execution and imagination. The amplitude and consistency of the ERD depends, among other things, on brain structure and function during motor imagery (e.g., Halder et al., 2013 , Zich et al., 2015 ). Because the vast majority of the research on MI-NF has been conducted with young healthy individuals, it is unclear to what degree changes regarding the relationship between MI-induced ERD, MI-induced functional magnetic resonance imaging (fMRI) activation and brain structure in stroke patients are due to normal aging and the stroke, respectively. Objectives (1) to investigate in healthy older adults (>45 years) associations of MI-induced ERD, MI-induced fMRI activation and diffusion tensor imaging (DTI) measures, and (2) to investigate differences in these measures between chronic stroke patients and healthy older adults matched for age and gender. Methods We included 12 chronic stroke patients with residual upper limb motor impairment (mean age 61.5 years – range 49–75 years; 3 females) and 17 healthy older adults (mean age 60.4 years – range 48–77 years; 9 females). All participants completed a 3T MRI session and a 96-electrode EEG session. The MRI session included a high-resolution anatomical scan, DTI, and fMRI during rest, motor execution and kinesthetic MI of repeated hand opening and closing. The EEG session consisted of three blocks: motor execution, kinesthetic MI and kinesthetic MI with real-time EEG-based visual feedback, all with the same hand movement as during fMRI. Each patient also completed a motor assessment consisting of the upper limb section of the Fugl-Mayer Assessment and the Modified Ashworth Scale. Results We will present preliminary results regarding the correlations of ERD and fMRI activation related to motor execution and imagination. Moreover, we will present the results of a replication of the analysis of Halder et al. (2013) that for young healthy adults indicated a significant association between MI-induced ERD and white matter integrity (fractional anisotropy) in subcortical structures.

P 136 Brain network analysis of EEG data in the service of clinical assessment – utilizing big data and prior theoretical knowledge to identify a biomarker for mTBI in adolscents

Mild traumatic brain injury (mTBI) in adolecents has gained increased attention in recent years amongst parents, clinicians, and researchers due to their growing rate and hazardous outcomes. Electroencephalography (EEG) and Event-Related Potential (ERP) have been encouraged as a diagnostic tool for mTBI due to its objectivity and cost-effectiveness. However, extracting clinically meaningful neuro-cognitive information from human EEG/ERP is challenging, particularly in highly variable groups like adolescents. Therefore, it is not surprising that despite them being especially susceptible to the effects of mTBI, no sensitive and specific application of EEG has yet been determined for this age group. To overcome these challenges, we have developed and applied a framework, termed Brain Network Activity (BNA) analysis, which utilizes a hybrid approach of very large datasets, novel signal processing technology, and academic knowledge (see Stern, Y., Reches, A., and Geva A. “Using Spatiotemporal Features in the Brain Network Activation Analysis for Improved Data Classification”. Frontiers in computational neuroscience, 2016). For the BNA core database, spatiotemporal data from 15,100 EEG recording files of healthy individuals performing various computerized cognitive tasks were extracted. Advanced machine learning and prior knowledge from the ERP literature was used to assemble an optimal set of brain network models for various cognitive functions, such as attention, memory, motor control, and sensory processing. This resulted in reference brain network models, to which the BNA of an individual or of a whole patient group can be compared to in terms of quantitative scores and qualitative brain map illustrations. In cases of specific sub-groups such as adolescents with mTBI, these BNA scores and maps may be applied to identify biomarkers specific to that population. In order to generate an mTBI biomarker for adolescents, BNA analysis was applied to EEG recordings of 107 healthy participants and 36 mTBI adolescent patients while they performed an auditory oddball task. The BNA features of all participants were extracted and included in repeated-measures analyses of variance (ANOVA) with EEG session gain (2nd vs 1st, 3rd vs 2nd), interval between sessions ( 2 months) and group (healthy, mTBI) as factors. Results showed a large negative evoked potential component in frontal-central regions between ∼200 and 500 ms following the standard stimulus for both groups (mTBI and healthy) during the baseline EEG recording sessions. The average negative amplitude decreased in the healthy control group’s 2nd EEG recording session. It remained steady in the concussed group’s 2nd (post-mTBI) session, and was significantly different from healthy controls. The pre- to post-mTBI gain in amplitude was correlated with the time interval between recording sessions (r = −0.47, p-value