Metabolomic biomarkers for (R, S)-ketamine and (S)-ketamine in treatment-resistant depression and healthy controls: A systematic review.

BACKGROUND: Ketamine is increasingly used for treatment-resistant depression (TRD) while its mechanism of action is still being investigated. In this systematic review, we appraise the current evidence of metabolomic biomarkers for racemic ketamine and esketamine in patients with TRD and healthy controls (HCs). METHODS: A comprehensive search of several databases (Ovid MEDLINE®, Embase, and Epub Ahead of Print) was performed from each database's inception to June 29, 2022, in any language, was conducted. We included studies wherein the metabolomic biomarkers for racemic ketamine or esketamine were investigated in TRD or HCs. Our main outcomes were to examine changes in metabolites among patients treated with ketamine/esketamine and explore the association with response to ketamine/esketamine. RESULTS: A total of 1859 abstracts were screened of which 11 were included for full-text review. Of these, a total of five articles were included (N = 147), including three RCTs (n = 129) and two open-label trials (n = 18). All studies used racemic ketamine; one study additionally used esketamine. The included studies evaluated patients with treatment-resistant bipolar depression (n = 22), unipolar depression (n = 91), and HCs (n = 34). The included studies reported alteration in several metabolites including acylcarnitines, lipids, kynurenine (KYN), and arginine with ketamine in TRD. Studies suggest the involvement of energy metabolism, KYN, and arginine pathways. In HCs, acetylcarnitine decreased post-infusion, whereas inconsistent findings were observed after the ketamine infusion in TRD patients. CONCLUSIONS: This systematic review provides preliminary evidence that ketamine may cause changes in several important pathways involved in energy metabolism and inflammation. Larger and more rigorous studies are needed.

High and low frequency anterior nucleus of thalamus deep brain stimulation: Impact on memory and mood in five patients with treatment resistant temporal lobe epilepsy.

High frequency anterior nucleus of the thalamus deep brain stimulation (ANT DBS) is an established therapy for treatment resistant focal epilepsies. Although high frequency-ANT DBS is well tolerated, patients are rarely seizure free and the efficacy of other DBS parameters and their impact on comorbidities of epilepsy such as depression and memory dysfunction remain unclear. The purpose of this study was to assess the impact of low vs high frequency ANT DBS on verbal memory and self-reported anxiety and depression symptoms. Five patients with treatment resistant temporal lobe epilepsy were implanted with an investigational brain stimulation and sensing device capable of ANT DBS and ambulatory intracranial electroencephalographic (iEEG) monitoring, enabling long-term detection of electrographic seizures. While patients received therapeutic high frequency (100 and 145 Hz continuous and cycling) and low frequency (2 and 7 Hz continuous) stimulation, they completed weekly free recall verbal memory tasks and thrice weekly self-reports of anxiety and depression symptom severity. Mixed effects models were then used to evaluate associations between memory scores, anxiety and depression self-reports, seizure counts, and stimulation frequency. Memory score was significantly associated with stimulation frequency, with higher free recall verbal memory scores during low frequency ANT DBS. Self-reported anxiety and depression symptom severity was not significantly associated with stimulation frequency. These findings suggest the choice of ANT DBS stimulation parameter may impact patients' cognitive function, independently of its impact on seizure rates.

Spatiotemporal Rhythmic Seizure Sources Can be Imaged by means of Biophysically Constrained Deep Neural Networks.

Noninvasive dynamic brain imaging of neural oscillations provides valuable insights into both physiological and pathological brain states. Yet, challenges remain due to the ill-posed nature of the problem and high complexity of the solution space, which can be alleviated by advanced computational models. Here, we investigated the capability of a novel deep learning-based source imaging framework (DeepSIF) for imaging ictal activities from high-density electroencephalogram (EEG) recordings in drug-resistant focal epilepsy patients. The neural mass model of ictal oscillations was adopted to generate synthetic training data with spatio-temporal-spectra features similar to ictal dynamics. We rigorously validated the trained DeepSIF model using computer simulations and in a cohort of 33 drug-resistant focal epilepsy patients. The DeepSIF ictal source imaging was compared with interictal source imaging and three conventional imaging methods as benchmark comparisons. Our findings show that the trained DeepSIF model outperforms other methods in estimating the spatial and temporal information of ictal sources. It achieves a high spatial specificity of 96% and a low spatial dispersion of 3.80 ± 5.74 mm when compared to the resection region. The noninvasive source imaging results also demonstrate good coverage of seizure-onset-zone (SOZ), with an average distance of 10.89 ± 10.14 mm (from the SOZ to the reconstruction). These promising results suggest that DeepSIF has significant potential for advancing noninvasive imaging of ictal activities in patients with focal epilepsy. By providing valuable insights into the spatiotemporal dynamics of seizure activity, DeepSIF promises to help guide clinical decisions and improve treatment outcomes for epilepsy patients.

An Update on the Efficacy of Single and Serial Intravenous Ketamine Infusions and Esketamine for Bipolar Depression: A Systematic Review and Meta-Analysis.

Ketamine has shown rapid antidepressant and anti-suicidal effects in treatment-resistant depression (TRD) with single and serial intravenous (IV) infusions, but the effectiveness for depressive episodes of bipolar disorder is less clear. We conducted an updated systematic review and meta-analysis to appraise the current evidence on the efficacy and tolerability of ketamine/esketamine in bipolar depression. A search was conducted to identify randomized controlled trials (RCTs) and non-randomized studies examining single or multiple infusions of ketamine or esketamine treatments. A total of 2657 articles were screened; 11 studies were included in the systematic review of which 7 studies were included in the meta-analysis (five non-randomized, N = 159; two RCTs, N = 33) with a mean age of 42.58 ± 13.1 years and 54.5% females. Pooled analysis from two RCTs showed a significant improvement in depression symptoms measured with MADRS after receiving a single infusion of ketamine (1-day WMD = -11.07; and 2 days WMD = -12.03). Non-randomized studies showed significant response (53%, p < 0.001) and remission rates (38%, p < 0.001) at the study endpoint. The response (54% vs. 55%) and remission (30% vs. 40%) rates for single versus serial ketamine infusion studies were similar. The affective switch rate in the included studies approximated 2.4%. Esketamine data for bipolar depression are limited, based on non-randomized, small sample-sized studies. Further studies with larger sample sizes are required to strengthen the evidence.

Correction: Joseph et al. Efficacy of Ketamine with and without Lamotrigine in Treatment-Resistant Depression: A Preliminary Report. Pharmaceuticals 2023, 16, 1164.

In the original publication [...].

Efficacy of Ketamine with and without Lamotrigine in Treatment-Resistant Depression: A Preliminary Report.

Intravenous (IV) ketamine and FDA-approved intranasal (IN) esketamine are increasingly used for treatment-resistant depression (TRD). Preliminary studies have suggested a synergistic effect of ketamine and lamotrigine, although the data are inconclusive. Herein, we report the response to serial ketamine/esketamine treatment among patients with TRD with or without lamotrigine therapy. In this historical cohort study, we included adult patients with TRD who received serial IV racemic ketamine (0.5 mg/kg over 40-100 min) or IN esketamine (56/84 mg) treatments. A change in depressive symptoms was assessed using the 16-item Quick Inventory of Depressive Symptomatology self-report (QIDS-SR) scale. There were no significant differences in response or remission rates among the patients on or not on lamotrigine during the ketamine/esketamine treatments. For a percent change in the QIDS-SR from baseline, no interaction was found between the lamotrigine groups and treatment number (p = 0.70), nor the overall effect of the group (p = 0.38). There was a trend towards lower dissociation (based on the CADSS score) among current lamotrigine users, especially in patients who received IV ketamine. A major limitation is the limited number of patients taking lamotrigine (n = 13). This preliminary study provides insufficient evidence that continuing lamotrigine therapy attenuates the antidepressant effect of repeated ketamine/esketamine; however, there seems to be a signal toward attenuating dissociation with lamotrigine in patients receiving serial ketamine treatments. Further observational studies or randomized controlled trials are needed to replicate these findings.

Efficacy and Safety of Clonidine in the Treatment of Acute Mania in Bipolar Disorder: A Systematic Review.

Clonidine, an alpha-2 adrenergic agonist, has been proposed as an antimanic agent that acts by reducing noradrenergic transmission. We conducted a systematic review to examine the efficacy and safety of clonidine for acute mania/hypomania. A comprehensive literature search was performed to identify randomized controlled trials (RCT) and non-randomized studies investigating the efficacy and safety of monotherapy/adjuvant treatment with clonidine for acute mania/hypomania in patients with bipolar disorder (BD). Nine studies (n = 222) met our inclusion criteria, including five RCTs (n = 159) and four non-randomized studies (n = 63). Non-randomized studies showed clonidine to help reduce symptoms of mania. However, data from placebo controlled RCTs were inconsistent. One RCT showed adjuvant clonidine as superior to placebo, whereas another RCT reported that clonidine was not better than placebo. In individual RCTs, lithium and valproate offered better antimanic effects compared to clonidine. Studies reported hypotension, depression, and somnolence as common adverse effects. Significant differences in study design and sample size contributed to high heterogeneity. This systematic review suggests low-grade evidence for clonidine as an adjuvant treatment for acute mania with mood stabilizers and inconclusive efficacy as monotherapy, warranting further well-designed RCTs.

Seizure occurrence is linked to multiday cycles in diverse physiological signals.

OBJECTIVE: The factors that influence seizure timing are poorly understood, and seizure unpredictability remains a major cause of disability. Work in chronobiology has shown that cyclical physiological phenomena are ubiquitous, with daily and multiday cycles evident in immune, endocrine, metabolic, neurological, and cardiovascular function. Additionally, work with chronic brain recordings has identified that seizure risk is linked to daily and multiday cycles in brain activity. Here, we provide the first characterization of the relationships between the cyclical modulation of a diverse set of physiological signals, brain activity, and seizure timing. METHODS: In this cohort study, 14 subjects underwent chronic ambulatory monitoring with a multimodal wrist-worn sensor (recording heart rate, accelerometry, electrodermal activity, and temperature) and an implanted responsive neurostimulation system (recording interictal epileptiform abnormalities and electrographic seizures). Wavelet and filter-Hilbert spectral analyses characterized circadian and multiday cycles in brain and wearable recordings. Circular statistics assessed electrographic seizure timing and cycles in physiology. RESULTS: Ten subjects met inclusion criteria. The mean recording duration was 232 days. Seven subjects had reliable electroencephalographic seizure detections (mean = 76 seizures). Multiday cycles were present in all wearable device signals across all subjects. Seizure timing was phase locked to multiday cycles in five (temperature), four (heart rate, phasic electrodermal activity), and three (accelerometry, heart rate variability, tonic electrodermal activity) subjects. Notably, after regression of behavioral covariates from heart rate, six of seven subjects had seizure phase locking to the residual heart rate signal. SIGNIFICANCE: Seizure timing is associated with daily and multiday cycles in multiple physiological processes. Chronic multimodal wearable device recordings can situate rare paroxysmal events, like seizures, within a broader chronobiology context of the individual. Wearable devices may advance the understanding of factors that influence seizure risk and enable personalized time-varying approaches to epilepsy care.

Long-Term Lithium Therapy and Thyroid Disorders in Bipolar Disorder: A Historical Cohort Study.

Lithium has been a cornerstone treatment for bipolar disorder (BD). Despite descriptions in the literature regarding associations between long-term lithium therapy (LTLT) and development of a thyroid disorder (overt/subclinical hypo/hyperthyroidism, thyroid nodule, and goiter) in BD, factors such as time to onset of thyroid abnormalities and impact on clinical outcomes in the course of illness have not been fully characterized. In this study we aimed to compare clinical characteristics of adult BD patients with and without thyroid disorders who were on LTLT. We aimed to identify the incidence of thyroid disorders in patients with BD on LTLT and response to lithium between patients with and without thyroid disorders in BD. The Cox proportional model was used to find the median time to the development of a thyroid disorder. Our results showed that up to 32% of patients with BD on LTLT developed a thyroid disorder, of which 79% developed hypothyroidism, which was corrected with thyroid hormone replacement. We did not find significant differences in lithium response between patients with or without thyroid disorders in BD. Findings from this study suggest that patients with BD and comorbid thyroid disorders when adequately treated have a response to lithium similar to patients with BD and no thyroid disorders.

Real-World Clinical Practice Among Patients With Bipolar Disorder and Chronic Kidney Disease on Long-term Lithium Therapy.

PURPOSE: Long-term lithium therapy (LTLT) has been associated with chronic kidney disease (CKD). We investigated changes in clinical characteristics, pharmacotherapeutic treatments for medical/psychiatric disorders, and outcomes among patients with bipolar disorder (BD) and CKD on LTLT in a 2-year mirror-image study design. METHODS: Adult BD patients on LTLT for ≥1 year who enrolled in the Mayo Clinic Bipolar Disorder Biobank and developed CKD (stage 3) were included, and our study was approved by the Mayo Clinic Institutional Review Board. The primary outcome was the time to the first mood episode after CKD diagnosis among the lithium (Li) continuers and discontinuers. Cox proportional hazards models were used to estimate the time to the first mood episode. We tested for differences in other medication changes between the Li continuers and discontinuers group using Mantel-Haenszel χ2 tests (linear associations). RESULTS: Of 38 BD patients who developed CKD, 18 (47%) discontinued Li, and the remainder continued (n = 20). The median age of the cohort was 56 years (interquartile range [IQR], 48-67 years), 63.2% were female, and 97.4% were White. As compared with continuers, discontinuers had more psychotropic medication trials (6 [IQR, 4-6] vs 3 [IQR, 2-5], P = 0.02), a higher rate of 1 or more mood episodes (61% vs 10%, P = 0.002), and a higher risk of a mood episode after CKD diagnoses (Hazard Ratio, 8.38; 95% confidence interval, 1.85-38.0 [log-rank P = 0.001]]. CONCLUSIONS: Bipolar disorder patients on LTLT who discontinued Li had a higher risk for relapse and a shorter time to the first mood episode, suggesting a need for more thorough discussion before Li discontinuation after the CKD diagnosis.

Data quality evaluation in wearable monitoring.

Wearable recordings of neurophysiological signals captured from the wrist offer enormous potential for seizure monitoring. Yet, data quality remains one of the most challenging factors that impact data reliability. We suggest a combined data quality assessment tool for the evaluation of multimodal wearable data. We analyzed data from patients with epilepsy from four epilepsy centers. Patients wore wristbands recording accelerometry, electrodermal activity, blood volume pulse, and skin temperature. We calculated data completeness and assessed the time the device was worn (on-body), and modality-specific signal quality scores. We included 37,166 h from 632 patients in the inpatient and 90,776 h from 39 patients in the outpatient setting. All modalities were affected by artifacts. Data loss was higher when using data streaming (up to 49% among inpatient cohorts, averaged across respective recordings) as compared to onboard device recording and storage (up to 9%). On-body scores, estimating the percentage of time a device was worn on the body, were consistently high across cohorts (more than 80%). Signal quality of some modalities, based on established indices, was higher at night than during the day. A uniformly reported data quality and multimodal signal quality index is feasible, makes study results more comparable, and contributes to the development of devices and evaluation routines necessary for seizure monitoring.

Quantitative analysis of visually reviewed normal scalp EEG predicts seizure freedom following anterior temporal lobectomy.

OBJECTIVE: Anterior temporal lobectomy (ATL) is a widely performed and successful intervention for drug-resistant temporal lobe epilepsy (TLE). However, up to one third of patients experience seizure recurrence within 1 year after ATL. Despite the extensive literature on presurgical electroencephalography (EEG) and magnetic resonance imaging (MRI) abnormalities to prognosticate seizure freedom following ATL, the value of quantitative analysis of visually reviewed normal interictal EEG in such prognostication remains unclear. In this retrospective multicenter study, we investigate whether machine learning analysis of normal interictal scalp EEG studies can inform the prediction of postoperative seizure freedom outcomes in patients who have undergone ATL. METHODS: We analyzed normal presurgical scalp EEG recordings from 41 Mayo Clinic (MC) and 23 Cleveland Clinic (CC) patients. We used an unbiased automated algorithm to extract eyes closed awake epochs from scalp EEG studies that were free of any epileptiform activity and then extracted spectral EEG features representing (a) spectral power and (b) interhemispheric spectral coherence in frequencies between 1 and 25 Hz across several brain regions. We analyzed the differences between the seizure-free and non-seizure-free patients and employed a Naïve Bayes classifier using multiple spectral features to predict surgery outcomes. We trained the classifier using a leave-one-patient-out cross-validation scheme within the MC data set and then tested using the out-of-sample CC data set. Finally, we compared the predictive performance of normal scalp EEG-derived features against MRI abnormalities. RESULTS: We found that several spectral power and coherence features showed significant differences correlated with surgical outcomes and that they were most pronounced in the 10-25 Hz range. The Naïve Bayes classification based on those features predicted 1-year seizure freedom following ATL with area under the curve (AUC) values of 0.78 and 0.76 for the MC and CC data sets, respectively. Subsequent analyses revealed that (a) interhemispheric spectral coherence features in the 10-25 Hz range provided better predictability than other combinations and (b) normal scalp EEG-derived features provided superior and potentially distinct predictive value when compared with MRI abnormalities (>10% higher F1 score). SIGNIFICANCE: These results support that quantitative analysis of even a normal presurgical scalp EEG may help prognosticate seizure freedom following ATL in patients with drug-resistant TLE. Although the mechanism for this result is not known, the scalp EEG spectral and coherence properties predicting seizure freedom may represent activity arising from the neocortex or the networks responsible for temporal lobe seizure generation within vs outside the margins of an ATL.

The role of base excision repair in major depressive disorder and bipolar disorder.

BACKGROUND: In vivo and in vitro studies suggest that inflammation and oxidative damage may contribute to the pathogenesis of major depressive disorder (MDD) and bipolar disorder (BD). Imbalance between DNA damage and repair is an emerging research area examining pathophysiological mechanisms of these major mood disorders. This systematic review sought to review DNA repair enzymes, with emphasis on the base excision repair (BER), in mood disorders. METHODS: We conducted a comprehensive literature search of Ovid MEDLINE® Epub Ahead of Print, Ovid MEDLINE® In-Process & Other Non-Indexed Citations, Ovid MEDLINE® Daily, EMBASE (1947), and PsycINFO for studies investigating the alterations in base excision repair in patients with MDD or BD. RESULTS: A total of 1364 records were identified. 1352 records remained after duplicates were removed. 24 records were selected for full-text screening and a remaining 12 articles were included in the qualitative synthesis. SNPs (single nucleotide polymorphisms) of several BER genes have been shown to be associated with MDD and BD. However, it was difficult to draw conclusions from BER gene expression studies due to conflicting findings and the small number of studies. LIMITATIONS: All studies were correlational so it was not possible to draw conclusions regarding causality. CONCLUSION: Future studies comparing DNA repair during the manic or depressive episode to remission will give us a better insight regarding the role of DNA repair in mood disorders. These alterations might be utilized as diagnostic and prognostic biomarkers as well as measuring treatment response.

Intracranial electrophysiological recordings from the human brain during memory tasks with pupillometry.

Data comprise intracranial EEG (iEEG) brain activity represented by stereo EEG (sEEG) signals, recorded from over 100 electrode channels implanted in any one patient across various brain regions. The iEEG signals were recorded in epilepsy patients (N = 10) undergoing invasive monitoring and localization of seizures when they were performing a battery of four memory tasks lasting approx. 1 hour in total. Gaze tracking on the task computer screen with estimating the pupil size was also recorded together with behavioral performance. Each dataset comes from one patient with anatomical localization of each electrode contact. Metadata contains labels for the recording channels with behavioral events marked from all tasks, including timing of correct and incorrect vocalization of the remembered stimuli. The iEEG and the pupillometric signals are saved in BIDS data structure to facilitate efficient data sharing and analysis.

Augmentation strategies for treatment resistant major depression: A systematic review and network meta-analysis.

OBJECTIVE: To compare the efficacy and discontinuation of augmentation agents in adult patients with treatment-resistant depression (TRD). We conducted a systematic review and network meta-analyses (NMA) to combine direct and indirect comparisons of augmentation agents. METHODS: We included randomized controlled trials comparing one active drug with another or with placebo following a treatment course up to 24 weeks. Nineteen agents were included: stimulants, atypical antipsychotics, thyroid hormones, antidepressants, and mood stabilizers. Data for response/remission and all-cause discontinuation rates were analyzed. We estimated effect-size by relative risk using pairwise and NMA with random-effects model. RESULTS: A total of 65 studies (N = 12,415) with 19 augmentation agents were included in the NMA. Our findings from the NMA for response rates, compared to placebo, were significant for: liothyronine, nortriptyline, aripiprazole, brexpiprazole, quetiapine, lithium, modafinil, olanzapine (fluoxetine), cariprazine, and lisdexamfetamine. For remission rates, compared to placebo, were significant for: thyroid hormone(T4), aripiprazole, brexpiprazole, risperidone, quetiapine, and olanzapine (fluoxetine). Compared to placebo, ziprasidone, mirtazapine, and cariprazine had statistically significant higher discontinuation rates. Overall, 24% studies were rated as having low risk of bias (RoB), 63% had moderate RoB and 13% had high RoB. LIMITATIONS: Heterogeneity in TRD definitions, variable trial duration and methodological clinical design of older studies and small number of trials per comparisons. CONCLUSIONS: This NMA suggests a superiority of the regulatory approved adjunctive atypical antipsychotics, thyroid hormones, dopamine compounds (modafinil and lisdexamfetamine) and lithium. Acceptability was lower with ziprasidone, mirtazapine, and cariprazine. Further research and head-to-head studies should be considered to strengthen the best available options for TRD.

Ambulatory seizure forecasting with a wrist-worn device using long-short term memory deep learning.

The ability to forecast seizures minutes to hours in advance of an event has been verified using invasive EEG devices, but has not been previously demonstrated using noninvasive wearable devices over long durations in an ambulatory setting. In this study we developed a seizure forecasting system with a long short-term memory (LSTM) recurrent neural network (RNN) algorithm, using a noninvasive wrist-worn research-grade physiological sensor device, and tested the system in patients with epilepsy in the field, with concurrent invasive EEG confirmation of seizures via an implanted recording device. The system achieved forecasting performance significantly better than a random predictor for 5 of 6 patients studied, with mean AUC-ROC of 0.80 (range 0.72-0.92). These results provide the first clear evidence that direct seizure forecasts are possible using wearable devices in the ambulatory setting for many patients with epilepsy.

Improving the prediction of epilepsy surgery outcomes using basic scalp EEG findings.

OBJECTIVE: This study aims to evaluate the role of scalp electroencephalography (EEG; ictal and interictal patterns) in predicting resective epilepsy surgery outcomes. We use the data to further develop a nomogram to predict seizure freedom. METHODS: We retrospectively reviewed the scalp EEG findings and clinical data of patients who underwent surgical resection at three epilepsy centers. Using both EEG and clinical variables categorized into 13 isolated candidate predictors and 6 interaction terms, we built a multivariable Cox proportional hazards model to predict seizure freedom 2 years after surgery. Harrell's step-down procedure was used to sequentially eliminate the least-informative variables from the model until the change in the concordance index (c-index) with variable removal was less than 0.01. We created a separate model using only clinical variables. Discrimination of the two models was compared to evaluate the role of scalp EEG in seizure-freedom prediction. RESULTS: Four hundred seventy patient records were analyzed. Following internal validation, the full Clinical + EEG model achieved an optimism-corrected c-index of 0.65, whereas the c-index of the model without EEG data was 0.59. The presence of focal to bilateral tonic-clonic seizures (FBTCS), high preoperative seizure frequency, absence of hippocampal sclerosis, and presence of nonlocalizable seizures predicted worse outcome. The presence of FBTCS had the largest impact for predicting outcome. The analysis of the models' interactions showed that in patients with unilateral interictal epileptiform discharges (IEDs), temporal lobe surgery cases had a better outcome. In cases with bilateral IEDs, abnormal magnetic resonance imaging (MRI) predicted worse outcomes, and in cases without IEDs, patients with extratemporal epilepsy and abnormal MRI had better outcomes. SIGNIFICANCE: This study highlights the value of scalp EEG, particularly the significance of IEDs, in predicting surgical outcome. The nomogram delivers an individualized prediction of postoperative outcome, and provides a unique assessment of the relationship between the outcome and preoperative findings.

Wearable devices for seizure detection: Practical experiences and recommendations from the Wearables for Epilepsy And Research (WEAR) International Study Group.

The Wearables for Epilepsy And Research (WEAR) International Study Group identified a set of methodology standards to guide research on wearable devices for seizure detection. We formed an international consortium of experts from clinical research, engineering, computer science, and data analytics at the beginning of 2020. The study protocols and practical experience acquired during the development of wearable research studies were discussed and analyzed during bi-weekly virtual meetings to highlight commonalities, strengths, and weaknesses, and to formulate recommendations. Seven major essential components of the experimental design were identified, and recommendations were formulated about: (1) description of study aims, (2) policies and agreements, (3) study population, (4) data collection and technical infrastructure, (5) devices, (6) reporting results, and (7) data sharing. Introducing a framework of methodology standards promotes optimal, accurate, and consistent data collection. It also guarantees that studies are generalizable and comparable, and that results can be replicated, validated, and shared.