Anxiety and depressive symptoms and migraine-related outcomes in children and adolescents.

OBJECTIVE: The objective of this study was to explore the longitudinal relationship between anxiety and depressive symptoms and migraine outcomes in children and adolescents. BACKGROUND: Children and adolescents with migraine experience more anxiety and depressive symptoms than their peers without migraine, but it is unknown if these symptoms are associated with differential migraine outcomes. METHODS: In this prospective clinical cohort study, children and adolescents aged 8.0-18.0 years with migraine completed headache questionnaires and validated measures of anxiety and depressive symptoms (Patient-Reported Outcomes Measurement Information System) at an initial consultation and at their first follow-up visit with a neurologist. Changes in monthly headache frequency and changes in migraine-related disability (Pediatric Migraine Disability Assessment) were tracked at each time point. The relationships between these migraine outcomes and anxiety and depressive symptoms were estimated using models controlling for sex, age, headache frequency, and treatment type. RESULTS: There were 123 consenting participants. In models adjusted for age, sex, baseline disability score, and treatment type, baseline anxiety and depressive symptom levels were not significantly associated with change in headache frequency (for anxiety symptoms: ß = -0.05, 95% confidence interval [CI] = -0.268 to 0.166, p = 0.639; for depressive symptoms: ß = 0.14, 95% CI = -0.079 to 0.359, p = 0.209). Similarly, in models adjusted for age, sex, baseline headache frequency, and treatment type, the change in disability was not associated with baseline anxiety (ß = -0.45, 95% CI = -1.69 to 0.78, p = 0.470), nor with baseline depressive symptom scores (ß = 0.16, 95% CI = -1.07 to 1.40, p = 0.796). In post hoc exploratory analyses (N = 84 with anxiety and N = 82 with depressive symptom data at both visits), there were also no significant associations between change in mental health symptoms and change in headache frequency (for anxiety symptoms: ß = -0.084, 95% CI = -0.246 to 0.078, p = 0.306; for depressive symptoms: ß = -0.013, 95% CI = -0.164 to 0.138, p = 0.865). Similarly, the change in disability scores between visits was not related to the change in anxiety (ß = 0.85, 95% CI = -0.095 to 1.78, p = 0.077) nor depressive symptom scores (ß = 0.32, 95% CI = -0.51 to 1.15, p = 0.446). CONCLUSION: Baseline anxiety and depressive symptom levels were not associated with longitudinal migraine outcomes and neither were longitudinal changes in anxiety and depressive symptom levels; this contradicts popular clinical belief that mental health symptoms predict or consistently change in tandem with migraine outcomes.

Anxiety and Depressive Symptoms and Disorders in Children and Adolescents With Migraine: A Systematic Review and Meta-analysis.

Importance: Though it is presumed that children and adolescents with migraine are at risk of internalizing symptoms and disorders, high-level summative evidence to support this clinical belief is lacking. Objective: To determine if there is an association between internalizing symptoms and disorders and migraine in children and adolescents. Data Sources: A librarian-led, peer-reviewed search was performed using MEDLINE, Embase, PsycINFO, and CINAHL databases (inception to March 28, 2022). Study Selection: Case-control, cohort, and cross-sectional studies on the association between internalizing symptoms and disorders and migraine in children and adolescents 18 years or younger were eligible. Data Extraction and Synthesis: Two investigators independently completed abstract and full-text screening, data extraction, and quality appraisal using the Newcastle-Ottawa scales. Studies were pooled with random-effects meta-analyses using standardized mean differences (SMD) or odds ratios (OR) with 95% CIs. Where sufficient data for pooling were unavailable, studies were described qualitatively. Main Outcomes and Measures: The primary outcome was migraine diagnosis; additional outcomes included migraine outcomes and incidence. Associations between these outcomes and internalizing symptoms and disorders were evaluated. Results: The study team screened 4946 studies and included 80 studies in the systematic review. Seventy-four studies reported on the association between internalizing symptoms and disorders and migraine, and 51 studies were amenable to pooling. Meta-analyses comparing children and adolescents with migraine with healthy controls showed: (1) an association between migraine and anxiety symptoms (SMD, 1.13; 95% CI, 0.64-1.63); (2) an association between migraine and depressive symptoms (SMD, 0.67; 95% CI, 0.46-0.87); and (3) significantly higher odds of anxiety disorders (OR, 1.93, 95% CI, 1.49-2.50) and depressive disorders (OR, 2.01, 95% CI, 1.46-2.78) in those with, vs without, migraine. Stratification of results did not reveal differences between clinical vs community/population-based samples and there was no evidence of publication bias. Twenty studies assessing the association between internalizing symptoms or disorders and migraine outcomes (n = 18) or incident migraine (n = 2) were summarized descriptively given significant heterogeneity, with minimal conclusions drawn. Conclusions and Relevance: In this study, children and adolescents with migraine were at higher risk of anxiety and depression symptoms and disorders compared with healthy controls. It may be beneficial to routinely screen children and adolescents with migraine for anxiety and depression in clinical practice. It is unclear whether having anxiety and depressive symptoms or disorders has an affect on migraine outcomes or incidence.

EEG in motion: Using an oddball task to explore motor interference in active skateboarding.

Recent advancements in portable computer devices have opened new avenues in the study of human cognition outside research laboratories. This flexibility in methodology has led to the publication of several electroencephalography studies recording brain responses in real-world scenarios such as cycling and walking outside. In the present study, we tested the classic auditory oddball task while participants moved around an indoor running track using an electric skateboard. This novel approach allows for the study of attention in motion while virtually removing body movement. Using the skateboard auditory oddball paradigm, we found reliable and expected standard-target differences in the P3 and MMN/N2b event-related potentials. We also recorded baseline electroencephalography activity and found that, compared to this baseline, alpha power is attenuated in frontal and parietal regions during skateboarding. In order to explore the influence of motor interference in cognitive resources during skateboarding, we compared participants' preferred riding stance (baseline level of riding difficulty) versus their non-preferred stance (increased level of riding difficulty). We found that an increase in riding difficulty did not modulate the P3 and tonic alpha amplitude during skateboard motion. These results suggest that increases in motor demands might not lead to reductions in cognitive resources as shown in previous literature.

Predicting stroke severity with a 3-min recording from the Muse portable EEG system for rapid diagnosis of stroke.

In this study, we demonstrated the use of low-cost portable electroencephalography (EEG) as a method for prehospital stroke diagnosis. We used a portable EEG system to record data from 25 participants, 16 had acute ischemic stroke events, and compared the results to age-matched controls that included stroke mimics. Delta/alpha ratio (DAR), (delta + theta)/(alpha + beta) ratio (DBATR) and pairwise-derived Brain Symmetry Index (pdBSI) were investigated, as well as head movement using the on-board accelerometer and gyroscope. We then used machine learning to distinguish between different subgroups. DAR and DBATR increased in ischemic stroke patients with increasing stroke severity (p = 0.0021, partial η2 = 0.293; p = 0.01, partial η2 = 0.234). Also, pdBSI decreased in low frequencies and increased in high frequencies in patients who had a stroke (p = 0.036, partial η2 = 0.177). Using classification trees, we were able to distinguish moderate to severe stroke patients and from minor stroke and controls, with a 63% sensitivity, 86% specificity and accuracy of 76%. There are significant differences in DAR, DBATR, and pdBSI between patients with ischemic stroke when compared to controls, and these effects scale with severity. We have shown the utility of a low-cost portable EEG system to aid in patient triage and diagnosis as an early detection tool.

A ride in the park: Cycling in different outdoor environments modulates the auditory evoked potentials.

In this study, we investigated the effect of environmental sounds on ERPs during an auditory task, by having participants perform the same dual task in two different outdoor environments. Participants performed an auditory oddball task while cycling outside both in a quiet park and near a noisy roadway. While biking near the roadway, an increased N1 amplitude was observed when evoked by both standard and target tones. This may be due to attentional processes of enhancing sound processing in the noisier environment. No behavioural differences were found. Future directions include investigating auditory ERPs in more realistic studies outside of laboratory.

The ecological cocktail party: Measuring brain activity during an auditory oddball task with background noise.

Most experiments using EEG recordings take place in highly isolated and restricted environments, limiting their applicability to real-life scenarios. New technologies for mobile EEG are changing this by allowing EEG recording to take place outside of the laboratory. However, before results from experiments performed outside the laboratory can be fully understood, the effects of ecological stimuli on brain activity during cognitive tasks must be examined. In this experiment, participants performed an auditory oddball task while also listening to concurrent background noises of silence, white noise, and outdoor ecological sounds, as well as a condition in which the tones themselves were at a low volume. We found a significantly increased N1 and decreased P2 when participants performed the task with outdoor sounds and white noise in the background, with the largest differences in the outdoor sound condition. This modulation in the N1 and P2 replicates what we have previously found outside while people rode bicycles. No behavioral differences were found in response to the target tones. We interpret these modulations in early ERPs as indicative of sensory filtering of background sounds and that ecologically valid sounds require more filtering than simple synthetic sounds. Our results reveal that much of what we understand about the brain will need to be updated as cognitive neuroscience research begins to step outside of the lab.

Taking off the training wheels: Measuring auditory P3 during outdoor cycling using an active wet EEG system.

Mobile EEG allows the investigation of brain activity in increasingly complex environments. In this study, EEG equipment was adapted for use and transportation in a backpack while cycling. Participants performed an auditory oddball task while cycling outside and sitting in an isolated chamber inside the lab. Cycling increased EEG noise and marginally diminished alpha amplitude. However, this increased noise did not influence the ability to measure reliable event related potentials (ERP). The P3 was similar in topography, and morphology when outside on the bike, with a lower amplitude in the outside cycling condition. There was only a minor decrease in the statistical power to measure reliable ERP effects. Unexpectedly, when biking outside significantly decreased P2 and increased N1 amplitude were observed when evoked by both standards and targets compared with sitting in the lab. This may be due to attentional processes filtering the overlapping sounds between the tones used and similar environmental frequencies. This study established methods for mobile recording of ERP signals. Future directions include investigating auditory P2 filtering inside the laboratory.

Two-Layered and Stretchable e-Textile Patches for Wearable Healthcare Electronics.

Wearable healthcare systems require skin-adhering electrodes that allow maximal comfort for patients as well as an electronics system to enable signal processing and transmittance. Textile-based electronics, known as "e-textiles," is a platform technology that allows comfort for patients. Here, two-layered e-textile patches are designed by controlled permeation of Ag-particle/fluoropolymer composite ink into a porous textile. The permeated ink forms a cladding onto the nanofibers in the textile substrate, which is beneficial for mechanical and electrical properties of the e-textile. The printed e-textile features conductivity of ≈3200 S cm-1 , whereas 1000 cycles of 30% uniaxial stretching causes the resistance to increase only by a factor of ≈5, which is acceptable in many applications. Controlling over the penetration depth enables a two-layer design of the e-textile, where the sensing electrodes and the conducting traces are printed in the opposite sides of the substrate. The formation of vertical interconnected access is remarkably simple as an injection from a syringe. With the custom-developed electronic circuits, a surface electromyography system with wireless data transmission is demonstrated. Furthermore, the dry e-textile patch collects electroencephalography with comparable signal quality to commercial gel electrodes. It is anticipated that the two-layered e-textiles will be effective in healthcare and sports applications.

Increasing the mobility of EEG data collection using a Latte Panda computer.

BACKGROUND: Electroencephalography (EEG) experiments often require several computers to ensure accurate stimulus presentation and data collection. However, this requirement can make it more difficult to perform such experiments in mobile settings within, or outside, the laboratory. NEW METHOD: Computer miniaturisation and increasing processing power allow for EEG experiments to become more portable. Our goal is to show that a Latte Panda, a small Windows 10 computer, can be used to accurately collect EEG data in a similar manner to a laptop. Using a stationary bike, we also suggest that the Latte Panda will allow for more portable EEG experiments. RESULTS: Significant and reliable MMN and P3 responses, event-related potentials (ERPs) typically associated with auditory oddball tasks, were observed and were consistent when using either the laptop or Latte Panda for EEG data collection. Similar MMN and P3 ERPs were also measured in the sitting and stationary biking conditions while using a Latte Panda for data collection. COMPARISON WITH EXISTING METHOD: Data recorded by the Latte Panda computer produced comparable and equally reliable results to the laptop. As well, similar ERPs during sitting and biking would suggest that EEG experiments can be conducted in more mobile situations despite the increased noise and artifacts associated with muscle movement. CONCLUSIONS: Our results show that the Latte Panda is a low-cost, more portable alternative to a laptop computer for recording EEG data. Such a device will further allow for more portable and mobile EEG experimentation in a wider variety of environments.

Transitioning EEG experiments away from the laboratory using a Raspberry Pi 2.

BACKGROUND: Electroencephalography (EEG) experiments are typically performed in controlled laboratory settings to minimise noise and produce reliable measurements. These controlled conditions also reduce the applicability of the obtained results to more varied environments and may limit their relevance to everyday situations. NEW METHOD: Advances in computer portability may increase the mobility and applicability of EEG results while decreasing costs. In this experiment we show that stimulus presentation using a Raspberry Pi 2 computer provides a low cost, reliable alternative to a traditional desktop PC in the administration of EEG experimental tasks. RESULTS: Significant and reliable MMN and P3 activity, typical event-related potentials (ERPs) associated with an auditory oddball paradigm, were measured while experiments were administered using the Raspberry Pi 2. While latency differences in ERP triggering were observed between systems, these differences reduced power only marginally, likely due to the reduced processing power of the Raspberry Pi 2. COMPARISON WITH EXISTING METHOD: An auditory oddball task administered using the Raspberry Pi 2 produced similar ERPs to those derived from a desktop PC in a laboratory setting. Despite temporal differences and slight increases in trials needed for similar statistical power, the Raspberry Pi 2 can be used to design and present auditory experiments comparable to a PC. RESULTS: Our results show that the Raspberry Pi 2 is a low cost alternative to the desktop PC when administering EEG experiments and, due to its small size and low power consumption, will enable mobile EEG experiments unconstrained by a traditional laboratory setting.