How multiple repetitions influence the processing of self-, famous and unknown names and faces: an ERP study.

Because we live in an extremely complex social environment, people require the ability to memorize hundreds or thousands of social stimuli. The aim of this study was to investigate the effect of multiple repetitions on the processing of names and faces varying in terms of pre-experimental familiarity. We measured both behavioral and electrophysiological responses to self-, famous and unknown names and faces in three phases of the experiment (in every phase, each type of stimuli was repeated a pre-determined number of times). We found that the negative brain potential in posterior scalp sites observed approximately 170 ms after the stimulus onset (N170) was insensitive to pre-experimental familiarity but showed slight enhancement with each repetition. The negative wave in the inferior-temporal regions observed at approximately 250 ms (N250) was affected by both pre-experimental (famous>unknown) and intra-experimental familiarity (the more repetitions, the larger N250). In addition, N170 and N250 for names were larger in the left inferior-temporal region, whereas right-hemispheric or bilateral patterns of activity for faces were observed. The subsequent presentations of famous and unknown names and faces were also associated with higher amplitudes of the positive waveform in the central-parietal sites analyzed in the 320-900 ms time-window (P300). In contrast, P300 remained unchanged after the subsequent presentations of self-name and self-face. Moreover, the P300 for unknown faces grew more quickly than for unknown names. The latter suggests that the process of learning faces is more effective than learning names, possibly because faces carry more semantic information.

A new electrophysiological index for working memory load in humans.

Working memory, the ability to store and simultaneously manipulate information, is affected in several neuropsychiatric disorders which lead to severe cognitive and functional deficits. An electrophysiological marker for this process could help identify early cerebral function abnormalities. In subjects performing working memory-specific n-back tasks, event-related potential analysis revealed a positive-negative waveform (PNwm) component modulated in amplitude by working memory load. It occurs in the expected time range for this process, 140-280 ms after stimulus onset, superimposed on the classical P200 and N200 components. Independent Component Analysis extracted two functional components with latencies and topographical scalp distributions similar to the PNwm. Our results imply that the PNwm represents a new electrophysiological index for working memory load in humans.

Towards the utilization of EEG as a brain imaging tool.

Recent advances in signal analysis have engendered EEG with the status of a true brain mapping and brain imaging method capable of providing spatio-temporal information regarding brain (dys)function. Because of the increasing interest in the temporal dynamics of brain networks, and because of the straightforward compatibility of the EEG with other brain imaging techniques, EEG is increasingly used in the neuroimaging community. However, the full capability of EEG is highly underestimated. Many combined EEG-fMRI studies use the EEG only as a spike-counter or an oscilloscope. Many cognitive and clinical EEG studies use the EEG still in its traditional way and analyze grapho-elements at certain electrodes and latencies. We here show that this way of using the EEG is not only dangerous because it leads to misinterpretations, but it is also largely ignoring the spatial aspects of the signals. In fact, EEG primarily measures the electric potential field at the scalp surface in the same way as MEG measures the magnetic field. By properly sampling and correctly analyzing this electric field, EEG can provide reliable information about the neuronal activity in the brain and the temporal dynamics of this activity in the millisecond range. This review explains some of these analysis methods and illustrates their potential in clinical and experimental applications.

L'hémisphérotomie péri-insulaire: technique chirurgicale, monitoring EEG intraopératoire et résultats sur le contrôle de l'épilepsie [Periinsular hemispherotomy: surgical technique, intraoperative EEG monitoring and results on seizure outcome]

Peri-insular hemispherotomy is a surgical technique used in the treatment of drug-resistant epilepsy of hemispheric origin. It is based on the exposure of insula and semi-circular sulci, providing access to the lateral ventricle through a supra- and infra-insular window. From inside the ventricle, a parasagittal callosotomy is performed. The basal and medial portion of the frontal lobe is isolated. Projections to the anterior commissure are interrupted at the time of amygdala resection. The hippocampal tail and fimbria-fornix are disrupted posteriorly. We report our experience of 18 cases treated with this approach. More than half of them presented with congenital epilepsy. Neuronavigation was useful in precisely determining the center and extent of the craniotomy, as well as the direction of tractotomies and callosotomy, allowing minimal exposure and blood loss. Intra-operative monitoring by scalp EEG on the contralateral hemisphere was used to follow the progression of the number of interictal spikes during the disconnection procedure. Approximately 90% of patients were in Engel's Class I. We observed one case who presented with transient postoperative neurological deterioration probably due to CSF overdrainage and documented one case of incomplete disconnection in a patient presenting with hemimegalencephaly who needed a second operation. We observed a good correlation between a significant decrease in the number of spikes at the end of the procedure and seizure outcome. Peri-insular hemispherotomy provides a functional disconnection of the hemisphere with minimal resection of cerebral tissue. It is an efficient technique with a low complication rate. Intra-operative EEG monitoring might be used as a predictive factor of completeness of the disconnection and consequently, seizure outcome.

Simultaneous EEG-fMRI at ultra-high field: Artifact prevention and safety assessment.

The simultaneous recording of scalp electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) can provide unique insights into the dynamics of human brain function, and the increased functional sensitivity offered by ultra-high field fMRI opens exciting perspectives for the future of this multimodal approach. However, simultaneous recordings are susceptible to various types of artifacts, many of which scale with magnetic field strength and can seriously compromise both EEG and fMRI data quality in recordings above 3T. The aim of the present study was to implement and characterize an optimized setup for simultaneous EEG-fMRI in humans at 7T. The effects of EEG cable length and geometry for signal transmission between the cap and amplifiers were assessed in a phantom model, with specific attention to noise contributions from the MR scanner coldheads. Cable shortening (down to 12cm from cap to amplifiers) and bundling effectively reduced environment noise by up to 84% in average power and 91% in inter-channel power variability. Subject safety was assessed and confirmed via numerical simulations of RF power distribution and temperature measurements on a phantom model, building on the limited existing literature at ultra-high field. MRI data degradation effects due to the EEG system were characterized via B0 and B1(+) field mapping on a human volunteer, demonstrating important, although not prohibitive, B1 disruption effects. With the optimized setup, simultaneous EEG-fMRI acquisitions were performed on 5 healthy volunteers undergoing two visual paradigms: an eyes-open/eyes-closed task, and a visual evoked potential (VEP) paradigm using reversing-checkerboard stimulation. EEG data exhibited clear occipital alpha modulation and average VEPs, respectively, with concomitant BOLD signal changes. On a single-trial level, alpha power variations could be observed with relative confidence on all trials; VEP detection was more limited, although statistically significant responses could be detected in more than 50% of trials for every subject. Overall, we conclude that the proposed setup is well suited for simultaneous EEG-fMRI at 7T.

A temporal hierarchy for conspecific vocalization discrimination in humans.

Introduction: Discrimination of species-specific vocalizations is fundamental for survival and social interactions. Its unique behavioral relevance has encouraged the identification of circumscribed brain regions exhibiting selective responses (Belin et al., 2004), while the role of network dynamics has received less attention. Those studies that have examined the brain dynamics of vocalization discrimination leave unresolved the timing and the inter-relationship between general categorization, attention, and speech-related processes (Levy et al., 2001, 2003; Charest et al., 2009). Given these discrepancies and the presence of several confounding factors, electrical neuroimaging analyses were applied to auditory evoked-potential (AEPs) to acoustically and psychophysically controlled non-verbal human and animal vocalizations. This revealed which region(s) exhibit voice-sensitive responses and in which sequence. Methods: Subjects (N=10) performed a living vs. man-made 'oddball' auditory discrimination task, such that on a given block of trials 'target' stimuli occurred 10% of the time. Stimuli were complex, meaningful sounds of 500ms duration. There were 120 different sound files in total, 60 of which represented sounds of living objects and 60 man-made objects. The stimuli that were the focus of the present investigation were restricted to those of living objects within blocks where no response was required. These stimuli were further sorted between human non-verbal vocalizations and animal vocalizations. They were also controlled in terms of their spectrograms and formant distributions. Continuous 64-channel EEG was acquired through Neuroscan Synamps referenced to the nose, band-pass filtered 0.05-200Hz, and digitized at 1000Hz. Peri-stimulus epochs of continuous EEG (-100ms to 900ms) were visually inspected for artifacts, 40Hz low-passed filtered and baseline corrected using the pre-stimulus period . Averages were computed from each subject separately. AEPs in response to animal and human vocalizations were analyzed with respect to differences of Global Field Power (GFP) and with respect to changes of the voltage configurations at the scalp (reviewed in Murray et al., 2008). The former provides a measure of the strength of the electric field irrespective of topographic differences; the latter identifies changes in spatial configurations of the underlying sources independently of the response strength. In addition, we utilized the local auto-regressive average distributed linear inverse solution (LAURA; Grave de Peralta Menendez et al., 2001) to visualize and statistically contrast the likely underlying sources of effects identified in the preceding analysis steps. Results: We found differential activity in response to human vocalizations over three periods in the post-stimulus interval, and this response was always stronger than that to animal vocalizations. The first differential response (169-219ms) was a consequence of a modulation in strength of a common brain network localized into the right superior temporal sulcus (STS; Brodmann's Area (BA) 22) and extending into the superior temporal gyrus (STG; BA 41). A second difference (291-357ms) also followed from strength modulations of a common network with statistical differences localized to the left inferior precentral and prefrontal gyrus (BA 6/45). These two first strength modulations correlated (Spearman's rho(8)=0.770; p=0.009) indicative of functional coupling between temporally segregated stages of vocalization discrimination. A third difference (389-667ms) followed from strength and topographic modulations and was localized to the left superior frontal gyrus (BA10) although this third difference did not reach our spatial criterion of 12 continuous voxels. Conclusions: We show that voice discrimination unfolds over multiple temporal stages, involving a wide network of brain regions. The initial stages of vocalization discrimination are based on modulations in response strength within a common brain network with no evidence for a voice-selective module. The latency of this effect parallels that of face discrimination (Bentin et al., 2007), supporting the possibility that voice and face processes can mutually inform one another. Putative underlying sources (localized in the right STS; BA 22) are consistent with prior hemodynamic imaging evidence in humans (Belin et al., 2004). Our effect over the 291-357ms post-stimulus period overlaps the 'voice-specific-response' reported by Levy et al. (Levy et al., 2001) and the estimated underlying sources (left BA6/45) were in agreement with previous findings in humans (Fecteau et al., 2005). These results challenge the idea that circumscribed and selective areas subserve con-specific vocalization processing.

Comparison of early cortical networks in efficient and inefficient visual search: an event-related potential study.

Functional magnetic resonance imaging studies have indicated that efficient feature search (FS) and inefficient conjunction search (CS) activate partially distinct frontoparietal cortical networks. However, it remains a matter of debate whether the differences in these networks reflect differences in the early processing during FS and CS. In addition, the relationship between the differences in the networks and spatial shifts of attention also remains unknown. We examined these issues by applying a spatio-temporal analysis method to high-resolution visual event-related potentials (ERPs) and investigated how spatio-temporal activation patterns differ for FS and CS tasks. Within the first 450 msec after stimulus onset, scalp potential distributions (ERP maps) revealed 7 different electric field configurations for each search task. Configuration changes occurred simultaneously in the two tasks, suggesting that contributing processes were not significantly delayed in one task compared to the other. Despite this high spatial and temporal correlation, two ERP maps (120-190 and 250-300 msec) differed between the FS and CS. Lateralized distributions were observed only in the ERP map at 250-300 msec for the FS. This distribution corresponds to that previously described as the N2pc component (a negativity in the time range of the N2 complex over posterior electrodes of the hemisphere contralateral to the target hemifield), which has been associated with the focusing of attention onto potential target items in the search display. Thus, our results indicate that the cortical networks involved in feature and conjunction searching partially differ as early as 120 msec after stimulus onset and that the differences between the networks employed during the early stages of FS and CS are not necessarily caused by spatial attention shifts.

Decoding decisions in healthy subjects and auditory discrimination in comatose patients through single-trial topographic EEG analyses

Neuroimaging studies analyzing neurophysiological signals are typically based on comparing averages of peri-stimulus epochs across experimental conditions. This approach can however be problematic in the case of high-level cognitive tasks, where response variability across trials is expected to be high and in cases where subjects cannot be considered part of a group. The main goal of this thesis has been to address this issue by developing a novel approach for analyzing electroencephalography (EEG) responses at the single-trial level. This approach takes advantage of the spatial distribution of the electric field on the scalp (topography) and exploits repetitions across trials for quantifying the degree of discrimination between experimental conditions through a classification scheme. In the first part of this thesis, I developed and validated this new method (Tzovara et al., 2012a,b). Its general applicability was demonstrated with three separate datasets, two in the visual modality and one in the auditory. This development allowed then to target two new lines of research, one in basic and one in clinical neuroscience, which represent the second and third part of this thesis respectively. For the second part of this thesis (Tzovara et al., 2012c), I employed the developed method for assessing the timing of exploratory decision-making. Using single-trial topographic EEG activity during presentation of a choice's payoff, I could predict the subjects' subsequent decisions. This prediction was due to a topographic difference which appeared on average at ~516ms after the presentation of payoff and was subject-specific. These results exploit for the first time the temporal correlates of individual subjects' decisions and additionally show that the underlying neural generators start differentiating their responses already ~880ms before the button press. Finally, in the third part of this project, I focused on a clinical study with the goal of assessing the degree of intact neural functions in comatose patients. Auditory EEG responses were assessed through a classical mismatch negativity paradigm, during the very early phase of coma, which is currently under-investigated. By taking advantage of the decoding method developed in the first part of the thesis, I could quantify the degree of auditory discrimination at the single patient level (Tzovara et al., in press). Our results showed for the first time that even patients who do not survive the coma can discriminate sounds at the neural level, during the first hours after coma onset. Importantly, an improvement in auditory discrimination during the first 48hours of coma was predictive of awakening and survival, with 100% positive predictive value. - L'analyse des signaux électrophysiologiques en neuroimagerie se base typiquement sur la comparaison des réponses neurophysiologiques à différentes conditions expérimentales qui sont moyennées après plusieurs répétitions d'une tâche. Pourtant, cette approche peut être problématique dans le cas des fonctions cognitives de haut niveau, où la variabilité des réponses entre les essais peut être très élevéeou dans le cas où des sujets individuels ne peuvent pas être considérés comme partie d'un groupe. Le but principal de cette thèse est d'investiguer cette problématique en développant une nouvelle approche pour l'analyse des réponses d'électroencephalographie (EEG) au niveau de chaque essai. Cette approche se base sur la modélisation de la distribution du champ électrique sur le crâne (topographie) et profite des répétitions parmi les essais afin de quantifier, à l'aide d'un schéma de classification, le degré de discrimination entre des conditions expérimentales. Dans la première partie de cette thèse, j'ai développé et validé cette nouvelle méthode (Tzovara et al., 2012a,b). Son applicabilité générale a été démontrée avec trois ensembles de données, deux dans le domaine visuel et un dans l'auditif. Ce développement a permis de cibler deux nouvelles lignes de recherche, la première dans le domaine des neurosciences cognitives et l'autre dans le domaine des neurosciences cliniques, représentant respectivement la deuxième et troisième partie de ce projet. En particulier, pour la partie cognitive, j'ai appliqué cette méthode pour évaluer l'information temporelle de la prise des décisions (Tzovara et al., 2012c). En se basant sur l'activité topographique de l'EEG au niveau de chaque essai pendant la présentation de la récompense liée à un choix, on a pu prédire les décisions suivantes des sujets (en termes d'exploration/exploitation). Cette prédiction s'appuie sur une différence topographique qui apparaît en moyenne ~516ms après la présentation de la récompense. Ces résultats exploitent pour la première fois, les corrélés temporels des décisions au niveau de chaque sujet séparément et montrent que les générateurs neuronaux de ces décisions commencent à différentier leurs réponses déjà depuis ~880ms avant que les sujets appuient sur le bouton. Finalement, pour la dernière partie de ce projet, je me suis focalisée sur une étude Clinique afin d'évaluer le degré des fonctions neuronales intactes chez les patients comateux. Des réponses EEG auditives ont été examinées avec un paradigme classique de mismatch negativity, pendant la phase précoce du coma qui est actuellement sous-investiguée. En utilisant la méthode de décodage développée dans la première partie de la thèse, j'ai pu quantifier le degré de discrimination auditive au niveau de chaque patient (Tzovara et al., in press). Nos résultats montrent pour la première fois que même des patients comateux qui ne vont pas survivre peuvent discriminer des sons au niveau neuronal, lors de la phase aigue du coma. De plus, une amélioration dans la discrimination auditive pendant les premières 48heures du coma a été observée seulement chez des patients qui se sont réveillés par la suite (100% de valeur prédictive pour un réveil).

Updated survival data of the phase iii clinical trial of novottf-100a versus best standard chemotherapy for recurrent glioblastoma

NovoTTF-100A (TTF) is a portable device delivering low-intensity, intermediate-frequency, alternating electric fields using noninvasive, disposable scalp electrodes. TTF interferes with tumor cell division, and it has been approved by the US Food and Drug Administration (FDA) for the treatment of recurrent glioblastoma (rGBM) based on data from a phase III trial. This presentation describes the updated survival data 2 years after completing recruitment. Adults with rGBM (KPS ≥ 70) were randomized (stratified by surgery and center) to either continuous TTF (20-24 h/day, 7 days/week) or efficacious chemotherapy based on best physician choice (BPC). The primary endpoint was overall survival (OS), and secondary endpoints were PFS6, 1-year survival, and QOL. Patients were randomized (28 US and European centers) to either TTF alone (n ¼ 120) or BPC (n ¼ 117). Patient characteristics were balanced, median age was 54 years (range, 23-80 years), and median KPS was 80 (range, 50-100). One quarter of the patients had debulking surgery, and over half of the patients were at their second or later recurrence. OS in the intent-to-treat (ITT) population was equivalent in TTF versus BPC patients (median OS, 6.6vs. 6.0 months; n ¼ 237; p ¼ 0.26; HR ¼ 0.86). With a median follow-up of 33.6 months, long-term survival in the TTF group was higher than that in the BPC group at 2, 3, and 4 years of follow-up (9.3% vs. 6.6%; 8.4% vs. 1.4%; 8.4% vs. 0.0%, respectively). Analysis of patients who received at least one treatment course demonstrated a survival benefit for TTF patients compared to BPC patients (median OS, 7.8 vs. 6.0 months; n ¼ 93 vs. n ¼ 117; p ¼ 0.012; HR ¼ 0.69). In this group, 1-year survival was 28% vs. 20%, and PFS6 was 26.2% vs. 15.2% (p ¼ 0.034). TTF, a noninvasive, novel cancer treatment modality shows significant therapeutic efficacy with promising long-term survival results. The impact of TTF was more pronounced when comparing only patients who received the minimal treatment course. A large-scale phase III trial in newly diagnosed GBM is ongoing.

Event-related potential analyses via single-subject topographic classification.

Introduction: Responses to external stimuli are typically investigated by averaging peri-stimulus electroencephalography (EEG) epochs in order to derive event-related potentials (ERPs) across the electrode montage, under the assumption that signals that are related to the external stimulus are fixed in time across trials. We demonstrate the applicability of a single-trial model based on patterns of scalp topographies (De Lucia et al, 2007) that can be used for ERP analysis at the single-subject level. The model is able to classify new trials (or groups of trials) with minimal a priori hypotheses, using information derived from a training dataset. The features used for the classification (the topography of responses and their latency) can be neurophysiologically interpreted, because a difference in scalp topography indicates a different configuration of brain generators. An above chance classification accuracy on test datasets implicitly demonstrates the suitability of this model for EEG data. Methods: The data analyzed in this study were acquired from two separate visual evoked potential (VEP) experiments. The first entailed passive presentation of checkerboard stimuli to each of the four visual quadrants (hereafter, "Checkerboard Experiment") (Plomp et al, submitted). The second entailed active discrimination of novel versus repeated line drawings of common objects (hereafter, "Priming Experiment") (Murray et al, 2004). Four subjects per experiment were analyzed, using approx. 200 trials per experimental condition. These trials were randomly separated in training (90%) and testing (10%) datasets in 10 independent shuffles. In order to perform the ERP analysis we estimated the statistical distribution of voltage topographies by a Mixture of Gaussians (MofGs), which reduces our original dataset to a small number of representative voltage topographies. We then evaluated statistically the degree of presence of these template maps across trials and whether and when this was different across experimental conditions. Based on these differences, single-trials or sets of a few single-trials were classified as belonging to one or the other experimental condition. Classification performance was assessed using the Receiver Operating Characteristic (ROC) curve. Results: For the Checkerboard Experiment contrasts entailed left vs. right visual field presentations for upper and lower quadrants, separately. The average posterior probabilities, indicating the presence of the computed template maps in time and across trials revealed significant differences starting at ~60-70 ms post-stimulus. The average ROC curve area across all four subjects was 0.80 and 0.85 for upper and lower quadrants, respectively and was in all cases significantly higher than chance (unpaired t-test, p<0.0001). In the Priming Experiment, we contrasted initial versus repeated presentations of visual object stimuli. Their posterior probabilities revealed significant differences, which started at 250ms post-stimulus onset. The classification accuracy rates with single-trial test data were at chance level. We therefore considered sub-averages based on five single trials. We found that for three out of four subjects' classification rates were significantly above chance level (unpaired t-test, p<0.0001). Conclusions: The main advantage of the present approach is that it is based on topographic features that are readily interpretable along neurophysiologic lines. As these maps were previously normalized by the overall strength of the field potential on the scalp, a change in their presence across trials and between conditions forcibly reflects a change in the underlying generator configurations. The temporal periods of statistical difference between conditions were estimated for each training dataset for ten shuffles of the data. Across the ten shuffles and in both experiments, we observed a high level of consistency in the temporal periods over which the two conditions differed. With this method we are able to analyze ERPs at the single-subject level providing a novel tool to compare normal electrophysiological responses versus single cases that cannot be considered part of any cohort of subjects. This aspect promises to have a strong impact on both basic and clinical research.

Positive EtG findings in hair as a result of a cosmetic treatment.

In a case of a driving ability assessment, hair analysis for ethyl glucuronide (EtG) was requested by the authorities. The person concerned denied alcohol consumption and did not present any clinical sign of alcoholism. However, EtG was found in concentrations of up to 910pg/mg in hair from different sampling dates suggesting an excessive drinking behavior. The person declared to use a hair lotion on a regularly base. To evaluate a possible effect of the hair lotion, prospective blood and urine controls as well as hair sampling of scalp and pubic hair were performed. The traditional clinical biomarkers of ethanol consumption, CDT and GGT, were inconspicuous in three blood samples taken. EtG was not detected in all collected urine samples. The hair lotion was transmitted to our laboratory. The ethanol concentration in this lotion was determined with 35g/L. The EtG immunoassay gave a positive result indicating EtG, which could be confirmed by GC-MS/MS-NCI. In a follow-up experiment the lotion was applied to the hair of a volunteer over a period of six weeks. After this treatment, EtG could be measured in the hair at a concentration of 72pg/mg suggesting chronic and excessive alcohol consumption. Overnight incubation of EtG free hair in the lotion yielded an EtG concentration of 140pg/mg. In the present case, the positive EtG hair findings could be interpreted as the result of an EtG containing hair care product. To our knowledge, the existence of such a product has not yet been reported, and it is exceptionally unusual to find EtG in cosmetics. Therefore, external sources for hair contamination should always be taken into account when unusual cosmetic treatment is mentioned. In those cases, it is recommended to analyze the hair product for a possible contamination with EtG. The analysis of body hair can help to reveal problems occurring from cosmetic treatment of head hair. As a consequence, the assessment of drinking behavior should be based on more than one diagnostic parameter.

Abnormal cortical network activation in human amnesia: A high-resolution evoked potential study.

Little is known about how human amnesia affects the activation of cortical networks during memory processing. In this study, we recorded high-density evoked potentials in 12 healthy control subjects and 11 amnesic patients with various types of brain damage affecting the medial temporal lobes, diencephalic structures, or both. Subjects performed a continuous recognition task composed of meaningful designs. Using whole-scalp spatiotemporal mapping techniques, we found that, during the first 200 ms following picture presentation, map configuration of amnesics and controls were indistinguishable. Beyond this period, processing significantly differed. Between 200 and 350 ms, amnesic patients expressed different topographical maps than controls in response to new and repeated pictures. From 350 to 550 ms, healthy subjects showed modulation of the same maps in response to new and repeated items. In amnesics, by contrast, presentation of repeated items induced different maps, indicating distinct cortical processing of new and old information. The study indicates that cortical mechanisms underlying memory formation and re-activation in amnesia fundamentally differ from normal memory processing.

Effect of Emotion and Personality on Deviation from Purely Rational Decision-Making

Human decision-making has consistently demonstrated deviation from "pure" rationality. Emotions are a primary driver of human actions and the current study investigates how perceived emotions and personality traits may affect decision-making during the Ultimatum Game (UG). We manipulated emotions by showing images with emotional connotation while participants decided how to split money with a second player. Event-related potentials (ERPs) from scalp electrodes were recorded during the whole decision-making process. We observed significant differences in the activity of central and frontal areas when participants offered money with respect to when they accepted or rejected an offer. We found that participants were more likely to offer a higher amount of money when making their decision in association with negative emotions. Furthermore, participants were more likely to accept offers when making their decision in association with positive emotions. Honest, conscientious, and introverted participants were more likely to accept offers. Our results suggest that factors others than a rational strategy may predict economic decision-making in the UG.

Self-paced Movement Intention Detection from Human Brain Signals: Invasive and Non-invasive EEG

Neural signatures of humans' movement intention can be exploited by future neuroprosthesis. We propose a method for detecting self-paced upper limb movement intention from brain signals acquired with both invasive and noninvasive methods. In the first study with scalp electroencephalograph (EEG) signals from healthy controls, we report single trial detection of movement intention using movement related potentials (MRPs) in a frequency range between 0.1 to 1 Hz. Movement intention can be detected above chance level (p<0.05) on average 460 ms before the movement onset with low detection rate during the on-movement intention period. Using intracranial EEG (iEEG) from one epileptic subject, we detect movement intention as early as 1500 ms before movement onset with accuracy above 90% using electrodes implanted in the bilateral supplementary motor area (SMA). The coherent results obtained with non-invasive and invasive method and its generalization capabilities across different days of recording, strengthened the theory that self-paced movement intention can be detected before movement initiation for the advancement in robot-assisted neurorehabilitation.

Proposition: Limbic encephalitis may represent limbic status epilepticus. A review of clinical and EEG characteristics.

Limbic encephalitis (LE) with waxing and waning neuropsychiatric manifestations including behavioral, personality, psychiatric, and memory changes can evolve over days to months. Many features of LE show remarkable overlap with the characteristics of mesial-temporal (limbic) status epilepticus (MTLSE or LSE). With LE, these prolonged impaired states are assumed not to be due to ongoing epileptic activity or MTLSE, because scalp EEGs usually show no epileptiform spike-wave activity; cycling behavioral and motor changes are attributed to LE; there may be little immediate improvement with antiepileptic drugs (AEDs); and of course, implanted electrodes are rarely used. Conversely, it is known that in pre-surgical patients with refractory limbic epilepsy, implanted electrodes have revealed limbic seizures that cannot be seen at the scalp. This paper assembles a chain of inferences to advance the proposition that refractory LE might represent LSE more often than is thought, and that implanted electrodes should be considered in some cases. We present two cases that suggest that LE was also LSE, one of which warranted implanted electrodes (case 1).