Asynchronous behavioral and neurophysiological changes in word production in the adult lifespan.

Behavioral and brain-related changes in word production have been claimed to predominantly occur after 70 years of age. Most studies investigating age-related changes in adulthood only compared young to older adults, failing to determine whether neural processes underlying word production change at an earlier age than observed in behavior. This study aims to fill this gap by investigating whether changes in neurophysiological processes underlying word production are aligned with behavioral changes. Behavior and the electrophysiological event-related potential patterns of word production were assessed during a picture naming task in 95 participants across five adult lifespan age groups (ranging from 16 to 80 years old). While behavioral performance decreased starting from 70 years of age, significant neurophysiological changes were present at the age of 40 years old, in a time window (between 150 and 220 ms) likely associated with lexical-semantic processes underlying referential word production. These results show that neurophysiological modifications precede the behavioral changes in language production; they can be interpreted in line with the suggestion that the lexical-semantic reorganization in mid-adulthood influences the maintenance of language skills longer than for other cognitive functions.

Antiseizure medication ≤48 hours portends better prognosis in new-onset epilepsy.

BACKGROUND: Several studies found that patients with new-onset epilepsy (NOE) have higher seizure recurrence rates if they presented already prior seizures. These observations suggest that timing of antiseizure medication (ASM) is crucial and should be offered immediately after the first seizure. Here, we wanted to assess whether immediate ASM is associated with improved outcome. METHODS: Single-center study of 1010 patients (≥16 years) who presented with a possible first seizure in the emergency department between 1 March 2010 and 1 March 2017. A comprehensive workup was launched upon arrival, including routine electroencephalography (EEG), brain computed tomography/magnetic resonance imaging, long-term overnight EEG and specialized consultations. We followed patients for 5 years comparing the relapse rate in patients treated within 48 h to those with treatment >48 h. RESULTS: A total of 487 patients were diagnosed with NOE. Of the 416 patients (162 female, age: 54.6 ± 21.1 years) for whom the treatment start could be retrieved, 80% (333/416) were treated within 48 h. The recurrence rate after immediate treatment (32%; 107/333) was significantly lower than in patients treated later (56.6%; 47/83; p < 0.001). For patients for whom a complete 5-year-follow-up was available (N = 297, 123 female), those treated ≤48 h (N = 228; 76.8%) had a significantly higher chance of remaining seizure-free compared with patients treated later (N = 69; 23.2%; p < 0.001). CONCLUSIONS: In this retrospective study, immediate ASM therapy (i.e., within 48 h) was associated with better prognosis up to 5 years after the index event. Prospective studies are required to determine the value of immediate workup and drug therapy in NOE patients.

Added value of advanced workup after the first seizure: A 7-year cohort study.

OBJECTIVE: This study was undertaken to establish whether advanced workup including long-term electroencephalography (LT-EEG) and brain magnetic resonance imaging (MRI) provides an additional yield for the diagnosis of new onset epilepsy (NOE) in patients presenting with a first seizure event (FSE). METHODS: In this population-based study, all adult (≥16 years) patients presenting with FSE in the emergency department (ED) between March 1, 2010 and March 1, 2017 were assessed. Patients with obvious nonepileptic or acute symptomatic seizures were excluded. Routine EEG, LT-EEG, brain computed tomography (CT), and brain MRI were performed as part of the initial workup. These examinations' sensitivity and specificity were calculated on the basis of the final diagnosis after 2 years, along with the added value of advanced workup (MRI and LT-EEG) over routine workup (routine EEG and CT). RESULTS: Of the 1010 patients presenting with FSE in the ED, a definite diagnosis of NOE was obtained for 501 patients (49.6%). Sensitivity of LT-EEG was higher than that of routine EEG (54.39% vs. 25.5%, p < .001). Similarly, sensitivity of MRI was higher than that of CT (67.98% vs. 54.72%, p = .009). Brain MRI showed epileptogenic lesions in an additional 32% compared to brain CT. If only MRI and LT-EEG were considered, five would have been incorrectly diagnosed as nonepileptic (5/100, 5%) compared to patients with routine EEG and MRI (25/100, 25%, p = .0001). In patients with all four examinations, advanced workup provided an overall additional yield of 50% compared to routine workup. SIGNIFICANCE: Our results demonstrate the remarkable added value of the advanced workup launched already in the ED for the diagnosis of NOE versus nonepileptic causes of seizure mimickers. Our findings suggest the benefit of first-seizure tracks or even units with overnight EEG, similar to stroke units, activated upon admission in the ED.

The temporal dynamics of the Stroop effect from childhood to young and older adulthood.

The processes involved in the Stroop task/effect are thought to involve conflict detection and resolution stages. Little is known about the evolution of these two components over the lifespan. It is well admitted that children and older adults tend to show longer response latencies than young adults. The present study aims at clarifying the rational of such changes from childhood to adulthood and in aging by comparing the impacted cognitive processes across age groups. More precisely, the aim was to clarify if all processes take more time to be executed, hence implying that longer latencies rely mainly on processing speed or if an additional process lengthens the resolution of the conflict in children and/or older adults. To this aim we recorded brain electrical activity using EEG in school-age children, young and older adults while they performed a classic verbal Stroop task. The signal was decomposed in microstate brain networks, and age groups and conditions were compared. Behavioral results evolved following an inverted U-shaped curve. In children, different brain states from the ones observed in adults were highlighted, both in the conflict detection and resolution time-windows. Longer latencies in the incongruent condition were mainly attributed to an overly increased duration of the microstates involved in the conflict resolution time window. In aging, the same microstate maps were reported for both young and older adult groups. The differences in performances between groups could be explained by a disproportionally long conflict detection phase, even compressing the latest stage of response articulation. These results tend to favor a specific immaturity of the brain networks involved coupled with a slowing of the processes in children, while cognitive decline could be mostly explained by a general slowing.

Diagnosis of Epilepsy with Functional Connectivity in EEG after a Suspected First Seizure.

Epilepsy is regarded as a structural and functional network disorder, affecting around 50 million people worldwide. A correct disease diagnosis can lead to quicker medical action, preventing adverse effects. This paper reports the design of a classifier for epilepsy diagnosis in patients after a first ictal episode, using electroencephalogram (EEG) recordings. The dataset consists of resting-state EEG from 629 patients, of which 504 were retained for the study. The patient's cohort exists out of 291 patients with epilepsy and 213 patients with other pathologies. The data were split into two sets: 80% training set and 20% test set. The extracted features from EEG included functional connectivity measures, graph measures, band powers and brain asymmetry ratios. Feature reduction was performed, and the models were trained using Machine Learning (ML) techniques. The models' evaluation was performed with the area under the receiver operating characteristic curve (AUC). When focusing specifically on focal lesional epileptic patients, better results were obtained. This classification task was optimized using a 5-fold cross-validation, where SVM using PCA for feature reduction achieved an AUC of 0.730 ± 0.030. In the test set, the same model achieved 0.649 of AUC. The verified decrease is justified by the considerable diversity of pathologies in the cohort. An analysis of the selected features across tested models shows that functional connectivity and its graph measures have the most considerable predictive power, along with full-spectrum frequency-based features. To conclude, the proposed algorithms, with some refinement, can be of added value for doctors diagnosing epilepsy from EEG recordings after a suspected first seizure.

Changes of interictal epileptiform discharges during medication withdrawal and seizures: A scalp EEG marker of epileptogenicity.

Objective: To determine the influence of antiseizure medication (ASM) withdrawal on interictal epileptogenic discharges (IEDs) in scalp-EEG and seizure propensity. Methods: We included 35 adult unifocal epilepsy patients admitted for presurgical evaluation in the EEG and Epilepsy Unit of Geneva between 2016 and 2020, monitored for at least 5 days. ASM was individually tapered down, and automated IED detection was performed using Epilog PreOp (Epilog NV, Belgium, Ghent). We compared spike rate per hour (SR) at day 1 when patients were on full medication (baseline) with SR at the day with the lowest dose of medication. To determine possible peri-ictal changes of SR, we compared SR 8 h before and after a seizure with the SR at the same time of the baseline day. Results: Our results showed a significant increase in spiking activity in the day of lowest drug load if compared to spike rate at day on full medication (p < 0.001). The total amount of spikes during 24 h correlated significantly with seizure occurrence (p < 0.0001). We also revealed significant increase in peri-ictal SR, in particular 2-4 h preceding a seizure (p = 0.05) extending up to 3 h after the seizure (p = 0.03) with a short decrease just before seizure occurrence. Conclusions: Our results suggest that SR increases with medication withdrawal and particularly before and after seizures. There is a complex pattern of increase and decrease around seizure onset which explains divergent results in previous studies. Significance: Precise spike counting at similar circadian periods for a patient could help to determine the risk of seizure occurrence in a personalized fashion.

Acute symptomatic seizures and hippocampal sclerosis: the major contributor for post-stroke epilepsy?

OBJECTIVE: Hippocampal sclerosis (HS) is a prominent biomarker of epilepsy. If acquired later in life, it usually occurs in the context of degenerative or acute inflammatory-infectious disease. Conversely, acute symptomatic seizures (ASS) are considered a risk factor for developing post-stroke epilepsy, but other factors remain unrecognized. Here, we hypothesize that silent hippocampal injury contributes to the development of post-stroke epilepsy. METHODS: We performed a retrospective observational study of patients hospitalized between 1/2007 and 12/2018 with an acute stroke in the Stroke Center of the Geneva University Hospital. Patients were included if they had a documented normal hippocampal complex at onset and a control MRI at ≥ 2 year interval without new lesion in the meantime. RESULTS: 162 patients fulfilled our inclusion criteria. ASS during the first week (p < 0.0001) and epileptiform abnormalities in electroencephalography (EEG; p = 0.02) were more frequently associated with the development of epilepsy. Hemorrhagic stroke was strongly associated to both ASS and future focal epilepsy (p = 0.00097). Three patients (1.8%) developed hippocampal sclerosis ipsilateral to the cerebrovascular event between 2 and 5 years, all with ASS and hemorrhagic stroke. INTERPRETATION: ASS and epileptiform EEG abnormalities are strong predictors of post-stroke epilepsy. HS develops in a minority of patients after hemorrhagic lesions, leading to focal epilepsy. Prospective studies are required, including follow-up with EEG and if characterized by epileptiform discharges, with MRI, to determine the true frequency of HS and to better understand predictors of post-stroke epilepsy (AAS, stroke type, and HS), and their impact on stroke recovery.

Attentional Reorientation and Inhibition Adjustment in a Verbal Stroop Task: A Lifespan Approach to Interference and Sequential Congruency Effect.

Several parameters influence the interference effect elicited in a Stroop task, especially contextual information. Contextual effects in the Stroop paradigms are known as the Gratton or Sequential congruency effect (SCE). This research aims at isolating two processes contributing to the SCE in a Stroop paradigm, namely attentional reorientation from the color to the word and vice-versa, as well as inhibition (engagement/disengagement from one trial to the next one). To this end, in Study 1 subprocesses of the SCE were isolated. Specifically, attentional reorientation and inhibition were segregated by submitting young adults to a discrete verbal Stroop task including neutral trials. In Study 2, the same procedure was applied to 124 participants aged from 10 to 80 years old to analyze how interference, SCE, and the aforementioned decomposition of attention and inhibition change across the lifespan. In both studies, the Gratton effect was only partially replicated, while both attentional reorientation and inhibition effects were observed, supporting the idea that these two processes contribute to SCE on top of conflict monitoring and of other processes highlighted in different theories (contingency learning, feature integration, and repetition expectancy). Finally, the classical age-related evolution was replicated in Study 2 on raw interference scores, but no age effect was observed when processing speed was taken into account, nor on the isolated attentional reorientation and inhibition processes, which is in line with the hypothesis of stability of the inhibition processes over age.

Learning to trust a face: The time course of brain activation during a money game.

Evidence shows that human faces can rapidly produce impressions of trust or distrust on the basis of their facial features. However, trust is also built through repeated interactions in which an opposite party acts positively towards the subject in a consistent way. The dynamics of cortical activation of this form of interactively-experienced trust is unclear. The current study therefore investigated the electrophysiological response to trust/distrust, arising through interactions in an investment game. Using an ERP paradigm, participants took part in a money game in which they chose to entrust different amounts to fictitious players. Some of these players were associated with the higher probability of a positive outcome (trustworthy behaviour), others were associated with a higher negative outcome (untrustworthy behaviour), and yet others were neutral. Over the course of the game, a strong central positivity emerged between 450 and 650 ms for trustworthy faces, compared to both neutral and untrustworthy players. This time period thus reflects the window during which the trustworthiness of a face is processed, when based on prior interaction. In addition, by evidencing ERP modifications for trustworthy faces alone, these findings suggest that the "default mode" of processing is initially biased towards distrust.