Minimum clinical utility standards for wearable seizure detectors: A simulation study.

OBJECTIVE: Epilepsy management employs self-reported seizure diaries, despite evidence of seizure underreporting. Wearable and implantable seizure detection devices are now becoming more widely available. There are no clear guidelines about what levels of accuracy are sufficient. This study aimed to simulate clinical use cases and identify the necessary level of accuracy for each. METHODS: Using a realistic seizure simulator (CHOCOLATES), a ground truth was produced, which was then sampled to generate signals from simulated seizure detectors of various capabilities. Five use cases were evaluated: (1) randomized clinical trials (RCTs), (2) medication adjustment in clinic, (3) injury prevention, (4) sudden unexpected death in epilepsy (SUDEP) prevention, and (5) treatment of seizure clusters. We considered sensitivity (0%-100%), false alarm rate (FAR; 0-2/day), and device type (external wearable vs. implant) in each scenario. RESULTS: The RCT case was efficient for a wide range of wearable parameters, though implantable devices were preferred. Lower accuracy wearables resulted in subtle changes in the distribution of patients enrolled in RCTs, and therefore higher sensitivity and lower FAR values were preferred. In the clinic case, a wide range of sensitivity, FAR, and device type yielded similar results. For injury prevention, SUDEP prevention, and seizure cluster treatment, each scenario required high sensitivity and yet was minimally influenced by FAR. SIGNIFICANCE: The choice of use case is paramount in determining acceptable accuracy levels for a wearable seizure detection device. We offer simulation results for determining and verifying utility for specific use case and specific wearable parameters.

Artificial intelligence-enhanced epileptic seizure detection by wearables.

OBJECTIVE: Wrist- or ankle-worn devices are less intrusive than the widely used electroencephalographic (EEG) systems for monitoring epileptic seizures. Using custom-developed deep-learning seizure detection models, we demonstrate the detection of a broad range of seizure types by wearable signals. METHODS: Patients admitted to the epilepsy monitoring unit were enrolled and asked to wear wearable sensors on either wrists or ankles. We collected patients' electrodermal activity, accelerometry (ACC), and photoplethysmography, from which blood volume pulse (BVP) is derived. Board-certified epileptologists determined seizure onset, offset, and types using video and EEG recordings per the International League Against Epilepsy 2017 classification. We applied three neural network models-a convolutional neural network (CNN) and a CNN-long short-term memory (LSTM)-based generalized detection model and an autoencoder-based personalized detection model-to the raw time-series sensor data to detect seizures and utilized performance measures, including sensitivity, false positive rate (the number of false alarms divided by the total number of nonseizure segments), number of false alarms per day, and detection delay. We applied a 10-fold patientwise cross-validation scheme to the multisignal biosensor data and evaluated model performance on 28 seizure types. RESULTS: We analyzed 166 patients (47.6% female, median age = 10.0 years) and 900 seizures (13 254 h of sensor data) for 28 seizure types. With a CNN-LSTM-based seizure detection model, ACC, BVP, and their fusion performed better than chance; ACC and BVP data fusion reached the best detection performance of 83.9% sensitivity and 35.3% false positive rate. Nineteen of 28 seizure types could be detected by at least one data modality with area under receiver operating characteristic curve > .8 performance. SIGNIFICANCE: Results from this in-hospital study contribute to a paradigm shift in epilepsy care that entails noninvasive seizure detection, provides time-sensitive and accurate data on additional clinical seizure types, and proposes a novel combination of an out-of-the-box monitoring algorithm with an individualized person-oriented seizure detection approach.

Wearable device assessments of antiseizure medication effects on diurnal patterns of electrodermal activity, heart rate, and heart rate variability.

Patient-generated health data provide a great opportunity for more detailed ambulatory monitoring and more personalized treatments in many diseases. In epilepsy, robust diagnostics applicable to the ambulatory setting are needed as diagnosis and treatment decisions in current clinical practice are primarily reliant on patient self-reports, which are often inaccurate. Recent work using wearable devices has focused on methods to detect and forecast epileptic seizures. Whether wearable device signals may also contain information about the effect of antiseizure medications (ASMs), which may ultimately help to better monitor their efficacy, has not been evaluated yet. Here we systematically investigated the effect of ASMs on different data modalities (electrodermal activity, EDA, heart rate, HR, and heart rate variability, HRV) simultaneously recorded by a wearable device in 48 patients with epilepsy over several days in the epilepsy long-term monitoring unit at a tertiary hospital. All signals exhibited characteristic diurnal variations. HRV, but not HR or EDA-based metrics, were reduced by ASMs. By assessing multiple signals related to the autonomic nervous system simultaneously, our results provide novel insights into the effects of ASMs on the sympathetic and parasympathetic interplay in the setting of epilepsy and indicate the potential of easy-to-wear wearable devices for monitoring ASM action. Future work using longer data may investigate these metrics on multidien cycles and their utility for detecting seizures, assessing seizure risk, or informing treatment interventions.

Twenty-four-hour patterns in electrodermal activity recordings of patients with and without epileptic seizures.

OBJECTIVE: Daytime and nighttime patterns affect the dynamic modulation of brain and body functions and influence the autonomic nervous system response to seizures. Therefore, we aimed to evaluate 24-hour patterns of electrodermal activity (EDA) in patients with and without seizures. METHODS: We included pediatric patients with (a) seizures (SZ), including focal impaired awareness seizures (FIAS) or generalized tonic-clonic seizures (GTCS), (b) no seizures and normal electroencephalography (NEEG), or (c) no seizures but epileptiform activity in the EEG (EA) during vEEG monitoring. Patients wore a device that continuously recorded EDA and temperature (TEMP). EDA levels, EDA spectral power, and TEMP levels were analyzed. To investigate 24-hour patterns, we performed a nonlinear mixed-effects model analysis. Relative mean pre-ictal (-30 min to seizure onset) and post-ictal (I: 30 min after seizure offset; II: 30 to 60 min after seizure offset) values were compared for SZ subgroups. RESULTS: We included 119 patients (40 SZ, 17 NEEG, 62 EA). EDA level and power group-specific models (SZ, NEEG, EA) (h = 1; P < .01) were superior to the all-patient cohort model. Fifty-nine seizures were analyzed. Pre-ictal EDA values were lower than respective 24-hour modulated SZ group values. Post hoc comparisons following the period-by-seizure type interaction (EDA level: χ2  = 18.50; P < .001, and power: χ2  = 6.73; P = .035) revealed that EDA levels were higher in the post-ictal period I for FIAS and GTCS and in post-ictal period II for GTCS only compared to the pre-ictal period. SIGNIFICANCE: Continuously monitored EDA shows a pattern of change over 24 hours. Curve amplitudes in patients with recorded seizures were lower as compared to patients who did not exhibit seizures during the recording period. Sympathetic skin responses were greater and more prolonged in GTCS compared to FIAS. EDA recordings from wearable devices offer a noninvasive tool to continuously monitor sympathetic activity with potential applications for seizure detection, prediction, and potentially sudden unexpected death in epilepsy (SUDEP) risk estimation.

Seizure detection using wearable sensors and machine learning: Setting a benchmark.

OBJECTIVE: Tracking seizures is crucial for epilepsy monitoring and treatment evaluation. Current epilepsy care relies on caretaker seizure diaries, but clinical seizure monitoring may miss seizures. Wearable devices may be better tolerated and more suitable for long-term ambulatory monitoring. This study evaluates the seizure detection performance of custom-developed machine learning (ML) algorithms across a broad spectrum of epileptic seizures utilizing wrist- and ankle-worn multisignal biosensors. METHODS: We enrolled patients admitted to the epilepsy monitoring unit and asked them to wear a wearable sensor on either their wrists or ankles. The sensor recorded body temperature, electrodermal activity, accelerometry (ACC), and photoplethysmography, which provides blood volume pulse (BVP). We used electroencephalographic seizure onset and offset as determined by a board-certified epileptologist as a standard comparison. We trained and validated ML for two different algorithms: Algorithm 1, ML methods for developing seizure type-specific detection models for nine individual seizure types; and Algorithm 2, ML methods for building general seizure type-agnostic detection, lumping together all seizure types. RESULTS: We included 94 patients (57.4% female, median age = 9.9 years) and 548 epileptic seizures (11 066 h of sensor data) for a total of 930 seizures and nine seizure types. Algorithm 1 detected eight of nine seizure types better than chance (area under the receiver operating characteristic curve [AUC-ROC] = .648-.976). Algorithm 2 detected all nine seizure types better than chance (AUC-ROC = .642-.995); a fusion of ACC and BVP modalities achieved the best AUC-ROC (.752) when combining all seizure types together. SIGNIFICANCE: Automatic seizure detection using ML from multimodal wearable sensor data is feasible across a broad spectrum of epileptic seizures. Preliminary results show better than chance seizure detection. The next steps include validation of our results in larger datasets, evaluation of the detection utility tool for additional clinical seizure types, and integration of additional clinical information.

Learning to play golf for elderly people with subjective memory complaints: feasibility of a single-blinded randomized pilot trial.

BACKGROUND: Subjective Memory Complaints (SMC) in elderly people due to preclinical Alzheimer's Disease may be associated with dysregulation of the Kynurenine Pathway (KP), with an increase in neurotoxic metabolites that affect cognition. Golf is a challenging sport with high demands on motor, sensory, and cognitive abilities, which might bear the potential to attenuate the pathological changes of preclinical AD. This trial investigated the feasibility of learning to play golf for elderly with cognitive problems and its effects on cognitive functions and the KP. METHODS: In a 22-week single-blinded randomized controlled trial, elderly people with SMC were allocated to the golf (n = 25, 180 min training/week) or control group (n = 21). Primary outcomes were feasibility (golf exam, adherence, adverse events) and general cognitive function (Alzheimer's Disease Assessment Scale). Secondary outcomes include specific cognitive functions (Response Inhibition, Corsi Block Tapping Test, Trail Making Test), KP metabolites and physical performance (6-Minute-Walk-Test). Baseline-adjusted Analysis-of-Covariance was conducted for each outcome. RESULTS: 42 participants were analyzed. All participants that underwent the golf exam after the intervention passed it (20/23). Attendance rate of the golf intervention was 75 %. No adverse events or drop-outs related to the intervention occurred. A significant time*group interaction (p = 0.012, F = 7.050, Cohen's d = 0.89) was found for correct responses on the Response Inhibition task, but not for ADAS-Cog. Moreover, a significant time*group interaction for Quinolinic acid to Tryptophan ratios (p = 0.022, F = 5.769, Cohen's d = 0.84) in favor of the golf group was observed. An uncorrected negative correlation between attendance rate and delta Quinolinic acid to Kynurenic acid ratios in the golf group (p = 0.039, r=-0.443) was found as well. CONCLUSIONS: The findings indicate that learning golf is feasible and safe for elderly people with cognitive problems. Preliminary results suggest positive effects on attention and the KP. To explore the whole potential of golfing and its effect on cognitive decline, a larger cohort should be studied over a longer period with higher cardiovascular demands. TRIAL REGISTRATION: The trial was retrospectively registered (2nd July 2018) at the German Clinical Trials Register ( DRKS00014921 ).

Generalized tonic-clonic seizures are accompanied by changes of interrelations within the autonomic nervous system.

PURPOSE: A seizure is a strong central stimulus that affects multiple subsystems of the autonomic nervous system (ANS), and results in different interactions across ANS modalities. Here, we aimed to evaluate whether multimodal peripheral ANS measures demonstrate interactions before and after seizures as compared to controls to provide the basis for seizure detection and forecasting based on peripheral ANS signals. METHODS: Continuous electrodermal activity (EDA), heart rate (HR), peripheral body temperature (TEMP), and respiratory rate (RR) calculated based on blood volume pulse were acquired by a wireless multi-sensor device. We selected 45 min of preictal and 60 min of postictal data and time-matched segments for controls. Data were analyzed over 15-min windows. For unimodal analysis, mean values over each time window were calculated for all modalities and analyzed by Friedman's two-way analysis of variance. RESULTS: Twenty-one children with recorded generalized tonic-clonic seizures (GTCS), and 21 age- and gender-matched controls were included. Unimodal results revealed no significant effect for RR and TEMP, but EDA (p = 0.002) and HR (p < 0.001) were elevated 0-15 min after seizures. The averaged bimodal correlation across all pairs of modalities changed for 15-min windows in patients with seizures. The highest correlations were observed immediately before (0.85) and the lowest correlation immediately after seizures. Overall, average correlations for controls were higher. SIGNIFICANCE: Multimodal ANS changes related to GTCS occur within and across autonomic nervous system modalities. While unimodal changes were most prominent during postictal segments, bimodal correlations increased before seizures and decreased postictally. This offers a promising avenue for further research on seizure detection, and potentially risk assessment for seizure recurrence and sudden unexplained death in epilepsy.

Effects of force level and task difficulty on force control performance in elderly people.

As the proportion of people over 60 years of age rises continuously in westernized societies, it becomes increasingly important to better understand aging processes and how to maintain independence in old age. Fine motor tasks are essential in daily living and, therefore, necessary to maintain. This paper extends the existing literature on fine motor control by manipulating the difficulty of a force maintenance task to characterize performance optima for elderly. Thirty-seven elderly (M = 68.00, SD = 4.65) performed a force control task at dynamically varying force levels, i.e. randomly changing every 3 s between 10%, 20%, and 30% of the individual's maximum voluntary contraction (MVC). This task was performed alone or with one or two additional tasks to increase task difficulty. The force control characteristics accuracy, variability, and complexity were analyzed. Lowest variability was observed at 20%. Accuracy and complexity increased with increasing force level. Overall, increased task difficulty had a negative impact on task performance. Results support the assumption, that attention control has a major impact on force control performance in elderly people. We assume different parameters to have their optimum at different force levels, which remain comparably stable when additional tasks are performed. The study contributes to a better understanding of how force control is affected in real-life situations when it is performed simultaneously to other cognitive and sensory active and passive tasks.

Multimodal approach towards understanding the changes in the autonomic nervous system induced by an ultramarathon.

Purpose: Running an ultramarathon can be considered as a multifaceted, intense stressor inducing changes within the autonomic nervous system (ANS). The aim of this study was to examine changes within and across ANS modalities in response to an ultramarathon.Methods: Thirteen runners (44.3 ± 5.9 years) completed a 65 km run. Electrodermal activity (EDA), heart rate (HR), and skin temperature measured at wrist (Temp), were recorded before and after running. Three-minute intervals were analysed. Mean values were compared by t-tests for dependent samples. Joint principal component analysis-canonical correlation analysis (PCA-CCA) and multiset CCA techniques were employed to measure the interactions between either any two or among all modalities.Results: HR (p < 0.01) and EDA (p < 0.01) increased, while Temp decreased (p < 0.01). PCA-CCA revealed one significant component (p < 0.05) for each modality pair in pre and post measures. Component strength increased from pre (mean = 0.73) to post (mean = 0.92) test. Multiset CCA supported the assumption of increasing strength of correlations across modalities.Conclusion: Ultramarathon, an intense physical stressor, increases correlations across modalities pointing towards a reorganization of central ANS control to restore dynamic balance after physical load. This characterization of ANS-states might offer new avenues for training control.

Peripheral multimodal monitoring of ANS changes related to epilepsy.

The goal of this study was to evaluate and summarize the current literature on multimodal changes of the autonomic nervous system (ANS) in people with epilepsy (PWE). We included studies reporting ANS measures of at least two modalities and with a minimum of one group of people with epilepsy. We screened two hundred eighty-three abstracts and sixty-six full texts, of which twenty-two met our inclusion criteria. Eleven studies reported ictal and interictal cardiac and respiratory changes. Three studies investigated the correlation between cardiac and respiratory markers, whereby two found no correlation and one showed a relation. Six studies evaluated electrodermal and cardiac parameters and showed effects on both ANS subsystems that jointly indicate a shift toward increased sympathetic activity for people with epilepsy during rest and during activity. Two studies assessed three modalities and reveal epilepsy-related alterations within the ANS. In summary, there is a growing interest in multimodal monitoring approaches, such as combining at least two ANS modalities, to describe epilepsy-related changes in ANS activity and to test for the potential to use ANS markers for seizure detection and prediction. Most studies report multiple unimodal analyses while only few studies analyzed multimodal patterns. Patterns of changes depend on the type of epilepsy and differ on an individual level; therefore, a multimodal approach might offer an approach to more individualized monitoring and, ultimately, management.

Explaining Individual Differences in Fine Motor Performance and Learning in Older Adults: The Contribution of Muscle Strength and Cardiovascular Fitness.

It remains controversial whether aging influences motor learning and whether physiological factors, such as local strength or fitness, are associated with fine motor performance and learning in older adults (OA). OA (n = 51) and young adults (YA, n = 31) performed a short-term motor learning session using a precision grip force modulation task. The rate of improvement of OA compared with YA was steeper with respect to performance variability and temporal precision. Both age groups showed positive transfer during an unpracticed variant of the force modulation task. Local muscle strength (pinch and grip strength) and high cardiovascular fitness positively predicted fine motor performance, whereas initial performance, muscle strength, and motor fitness (heterogeneous motor test battery) negatively predicted rate of improvement. Analyses indicated potentials, but also limits of plasticity for OA.

Dynamical signatures of isometric force control as a function of age, expertise, and task constraints.

From the conceptual and methodological framework of the dynamical systems approach, force control results from complex interactions of various subsystems yielding observable behavioral fluctuations, which comprise both deterministic (predictable) and stochastic (noise-like) dynamical components. Here, we investigated these components contributing to the observed variability in force control in groups of participants differing in age and expertise level. To this aim, young (18-25 yr) as well as late middle-aged (55-65 yr) novices and experts (precision mechanics) performed a force maintenance and a force modulation task. Results showed that whereas the amplitude of force variability did not differ across groups in the maintenance tasks, in the modulation task it was higher for late middle-aged novices than for experts and higher for both these groups than for young participants. Within both tasks and for all groups, stochastic fluctuations were lowest where the deterministic influence was smallest. However, although all groups showed similar dynamics underlying force control in the maintenance task, a group effect was found for deterministic and stochastic fluctuations in the modulation task. The latter findings imply that both components were involved in the observed group differences in the variability of force fluctuations in the modulation task. These findings suggest that between groups the general characteristics of the dynamics do not differ in either task and that force control is more affected by age than by expertise. However, expertise seems to counteract some of the age effects.NEW & NOTEWORTHY Stochastic and deterministic dynamical components contribute to force production. Dynamical signatures differ between force maintenance and cyclic force modulation tasks but hardly between age and expertise groups. Differences in both stochastic and deterministic components are associated with group differences in behavioral variability, and observed behavioral variability is more strongly task dependent than person dependent.

Lifespan development of the bilateral deficit in a simple reaction time task.

Performing an action at a maximum speed or with a maximum strength simultaneously with two limbs leads to a lower performance than the sum of unimanual performances. This phenomenon is known as bilateral deficit. There is some evidence that the bilateral deficit changes over the lifespan, in a way that children and older adults show lower deficits than young adults. Inverse developmental changes of childrens' and older adults' brain structures connecting both hemispheres, i.e., the corpus callosum, might importantly contribute to this phenomenon. The seemingly similar developments have been observed with different experimental protocols in the different age groups, respectively. To test for similarities and differences in changes of the bilateral deficit at critical periods of the lifespan development of bimanual actions, children, young adults, and older adults performed a simple reaction time task uni- and bimanually. Reaction times and the resulting bilateral deficit, as well as reaction time variability were analyzed. As expected, reaction times were different for the young adults between the uni- and the bimanual task. Children and older adults performed both conditions with similar reaction times. However, a difference in the direction of the %bilateral deficit occurred between the two age groups. The findings demonstrated an absence of the bilateral deficit for children, but not for younger and older adults.

Age-related changes in force control under different task contexts.

We investigated age-related differences in motor behavior under different task contexts of isometric force control. The tasks involved rapid force production and force maintenance, either separately or in combination. For the combined context, we used Fitts-like tasks, in which we scaled either the force level (D manipulation, i.e., manipulation of the amplitude of the force to be produced) or the tolerance range (W manipulation, i.e., manipulation of the target width in which force is allowed to fluctuate). We studied two age groups and analyzed mainly variables that quantify behavioral variability (SD), information processing (signal-to-noise ratio and efficiency functions), and age-related slowing (slowing ratio). For rapid force control, age-related differences were more pronounced when preplanned processes were primarily involved, that is, in the rapid force production and Fitts-D manipulation tasks. Further, older adults were comparable to the younger adults in terms of end-point variability at the cost of being slower and more variable in timing. For force maintenance control, requiring mainly online control, age-related differences were the most visible in the stabilized phase of Fitts-D manipulation, followed by Fitts-W manipulation for SD, and then the force maintenance task. In sum, our findings reveal an age-related reorganization of how preplanned and online control processes are combined under different force control contexts. Indeed, both behavioral slowing and the overreliance on online control processes seem to be dependent on the task. In this respect, beyond the study of force control, we show the interest of investigating age effects using functionally different tasks.

Effects of task and age on the magnitude and structure of force fluctuations: insights into underlying neuro-behavioral processes.

BACKGROUND: The present study aimed at characterizing the effects of increasing (relative) force level and aging on isometric force control. To achieve this objective and to infer changes in the underlying control mechanisms, measures of information transmission, as well as magnitude and time-frequency structure of behavioral variability were applied to force-time-series. RESULTS: Older adults were found to be weaker, more variable, and less efficient than young participants. As a function of force level, efficiency followed an inverted-U shape in both groups, suggesting a similar organization of the force control system. The time-frequency structure of force output fluctuations was only significantly affected by task conditions. Specifically, a narrower spectral distribution with more long-range correlations and an inverted-U pattern of complexity changes were observed with increasing force level. Although not significant older participants displayed on average a less complex behavior for low and intermediate force levels. The changes in force signal's regularity presented a strong dependence on time-scales, which significantly interacted with age and condition. An inverted-U profile was only observed for the time-scale relevant to the sensorimotor control process. However, in both groups the peak was not aligned with the optimum of efficiency. CONCLUSION: Our results support the view that behavioral variability, in terms of magnitude and structure, has a functional meaning and affords non-invasive markers of the adaptations of the sensorimotor control system to various constraints. The measures of efficiency and variability ought to be considered as complementary since they convey specific information on the organization of control processes. The reported weak age effect on variability and complexity measures suggests that the behavioral expression of the loss of complexity hypothesis is not as straightforward as conventionally admitted. However, group differences did not completely vanish, which suggests that age differences can be more or less apparent depending on task properties and whether difficulty is scaled in relative or absolute terms.

Effects of age and expertise on tactile learning in humans.

Repetitive tactile stimulation is a well-established tool for inducing somatosensory cortical plasticity and changes in tactile perception. Previous studies have suggested that baseline performance determines the amount of stimulation-induced learning differently in specific populations. Older adults with lower baseline performance than young adults, but also experts, with higher baseline performance than non-experts of the same age, have been found to profit most from such interventions. This begs the question of how age-related and expertise-related differences in tactile learning are reflected in neurophysiological correlates. In two experiments, we investigated how tactile learning depends on age (experiment 1) and expertise (experiment 2). We assessed tactile spatial and temporal discrimination accuracy and event-related potentials (ERPs) in 57 persons of different age and expertise groups before and after a 30-min tactile stimulation intervention. The intervention increased accuracy in temporal (found in experiment 1) and spatial (found in experiment 2) discrimination. Experts improved more than non-experts in spatial discrimination. Lower baseline performance was associated with higher learning gain in experts and non-experts. After the intervention, P300 latencies were reduced in young adults and amplitudes were increased in late middle-aged adults in the temporal discrimination task. Experts showed a steeper P300 parietal-to-frontal gradient after the stimulation. We demonstrated that tactile stimulation partially reverses the age-related decline in late middle-aged adults and increases processing speed in young adults. We further showed that learning gain depends on baseline performance in both non-experts and experts. In experts, however, the upper limit for learning seems to be shifted to a higher level.

Ultradian rhythms in accelerometric and autonomic data vary based on seizure occurrence in paediatric epilepsy patients.

Ultradian rhythms are physiological oscillations that resonate with period lengths shorter than 24 hours. This study examined the expression of ultradian rhythms in patients with epilepsy, a disease defined by an enduring seizure risk that may vary cyclically. Using a wearable device, we recorded heart rate, body temperature, electrodermal activity and limb accelerometry in patients admitted to the paediatric epilepsy monitoring unit. In our case-control design, we included recordings from 29 patients with tonic-clonic seizures and 29 non-seizing controls. We spectrally decomposed each signal to identify cycle lengths of interest and compared average spectral power- and period-related markers between groups. Additionally, we related seizure occurrence to the phase of ultradian rhythm in patients with recorded seizures. We observed prominent 2- and 4-hour-long ultradian rhythms of accelerometry, as well as 4-hour-long oscillations in heart rate. Patients with seizures displayed a higher peak power in the 2-hour accelerometry rhythm (U = 287, P = 0.038) and a period-lengthened 4-hour heart rate rhythm (U = 291.5, P = 0.037). Those that seized also displayed greater mean rhythmic electrodermal activity (U = 261; P = 0.013). Most seizures occurred during the falling-to-trough quarter phase of accelerometric rhythms (13 out of 27, χ2 = 8.41, P = 0.038). Fluctuations in seizure risk or the occurrence of seizures may interrelate with ultradian rhythms of movement and autonomic function. Longitudinal assessments of ultradian patterns in larger patient samples may enable us to understand how such rhythms may improve the temporal precision of seizure forecasting models.

Age-related differences in finger force control are characterized by reduced force production.

It has been repeatedly shown that precise finger force control declines with age. The tasks and evaluation parameters used to reveal age-related differences vary between studies. In order to examine effects of task characteristics, young adults (18-25 years) and late middle-aged adults (55-65 years) performed precision grip tasks with varying speed and force requirements. Different outcome variables were used to evaluate age-related differences. Age-related differences were confirmed for performance accuracy (TWR) and variability (relative root mean square error, rRMSE). The task characteristics, however, influenced accuracy and variability in both age groups: Force modulation performance at higher speed was poorer than at lower speed and at fixed force levels than at force levels adjusted to the individual maximum forces. This effect tended to be stronger for older participants for the rRMSE. A curve fit confirmed the age-related differences for both spatial force tracking parameters (amplitude and intercept) and for one temporal parameter (phase shift), but not for the temporal parameter frequency. Additionally, matching the timing parameters of the sine wave seemed to be more important than matching the spatial parameters in both young adults and late middle-aged adults. However, the effect was stronger for the group of late middle-aged, even though maximum voluntary contraction was not significantly different between groups. Our data indicate that changes in the processing of fine motor control tasks with increasing age are caused by difficulties of late middle-aged adults to produce a predefined amount of force in a short time.

Effects of age and fine motor expertise on the bilateral deficit in force initiation.

Performance of a task carried out with two hands separately is better than the performance of the same task done with both hands at the same time. This so-called bilateral deficit may be reduced or counteracted by long-term practice. Little is known about age-related changes. We examined age- and expertise-related differences in the bilateral deficit in force initiation. Participants performed static and dynamic force modulation tasks either with the right and left hand separately or both hands simultaneously. In order to examine age-related differences, we compared novices of fine motor control (service employees) from three age groups, covering the working age (young n = 13, early middle-aged n = 10 and late middle-aged n = 12). To assess the influence of expertise, we considered precision mechanics as experts in fine motor control. To ensure the acquisition of expertise, only early middle-aged (n = 10) and late middle-aged (n = 14) experts were recruited. Regardless of the task, bimanual force initiation was slower than unimanual force initiation. This bilateral deficit was (1) more pronounced in the static than in the dynamic task, (2) higher in early and late middle-aged than in younger novices, and (3) lower in experts as compared to novices. Based on our results, we assume both interhemispheric inhibition and division of attention to contribute to the bilateral deficit and the expertise- and age-related differences, respectively. The results are promising for the possibility to overcome constraints of bilateral hand movements by long-term practice.

EEG Biomarkers of Repository Corticotropin Injection Treatment.

PURPOSE: Hypsarrhythmia is one of the major diagnostic and treatment response criteria in infantile spasms (IS). The clinical and electrophysiological effect of repository corticotropin injection treatment on IS was evaluated using electrophysiological biomarkers. METHODS: Consecutive infants (<24 months) treated with repository corticotropin injection for IS were included in this retrospective descriptive study. Inclusion criteria were (1) clinical IS diagnosis, (2) repository corticotropin injection treatment, and (3) consecutive EEG recordings before and after repository corticotropin injection treatment. Patients with tuberous sclerosis complex were excluded. Response to treatment was defined as freedom from IS for at least 7 consecutive days during the treatment and resolution of hypsarrhythmia. The authors defined "relapse" as the recurrence of seizures after an initial response. Electrophysiological biomarker assessment included evaluation of semiautomatic spike counting algorithm, delta power, and delta coherence calculation during non-REM sleep EEG. RESULTS: One hundred fifty patients (83 males; 55%; median age of IS onset: 5.9 months) with complete data were included, including 101 responders (67%, 71 with sustained response, and 30 relapses). Fifty patients (33%) with complete EEG data also underwent advanced EEG analysis. Baseline delta coherence was higher in sustained responders than in nonresponders or patients who relapsed. Greater decreases in semiautomatic spike counting algorithm, delta power, and delta coherence were found in sustained responders compared with nonresponders or patients who relapsed. CONCLUSIONS: Repository corticotropin injection treatment was associated with a 67% response rate in patients with IS. Computational biomarkers beyond hypsarrhythmia may provide additional information during IS treatment, such as early determination of treatment response and outcome assessment.