Functional neuroanatomy of cognitive impairment in multiple sclerosis is currently still a challenge. During the progression of the disease, several cognitive mechanisms deteriorate thus diminishing the patient’s quality of life. A primary objective in the cognitive assessment of multiple sclerosis (MS) patients is to find reliable measures utilizing diverse neuroimaging techniques. Moreover, especially relevant in the clinical environment is finding technical approaches that could be applied to individual participants and not only for group analysis. A 64-channel electroencephalographic recording (EEG) was made with thirty participants divided into three groups of equivalent size (N = 10)  and moderate-EDSS (4–6)). Correlation analysis was applied to multiple measures: behavior, neuropsychological tests  and the Symbol Digit Modality Test (SDMT)), Expanded Disability Status Scale (EDSS), even-related potential (P3) and event-related desynchronization (ERD) parameters and the correlation scores between individual participant’s P3/ERD maps and the healthy grand average P3/ERDmaps. Statistical analysis showed that diverse parameters exhibited significant correlations. A remarkable correlation was the moderate score found between SDMT and EDSS . However, the strongest correlation was between the value of integrated measures  and EDSS . In regard to correlations for grand average maps between groups, the P3 component exhibited a lower score according to a more deteriorated condition (higher EDSS). In contrast, ERD maps remained stable with an increase of EDSS. Lastly, a Z-transformation of individual values of all variables included in the study exhibited heterogeneity in cognitive alterations in the multiple sclerosis participants. Understanding the functional and anatomical changes related to cognitive impairment in multiple sclerosis is currently still a challenge. The relatively stochastic localization of lesions in multiple sclerosis (MS) causes complex patterns of cognitive impairment mainly related to slowed cognitive processing speed and episodic memory decline as well as to executive function, verbal fluency and visuospatial analysis . ConsideOne possibility for studying the functional alterations of brain activity associated with cognitive impairment is through cognitive tasks . As a result of this application, diverse behavior variables (reaction time and accuracy) and physiological activity ) can be measured. Diverse approaches can be used in the analysis of the EEG signal: time domain ) or frequency domain ). In the particular case of multiple sclerosis, both approaches have evidenced alterations related to cognitive impairment. For instance, the P3 component  has shown that amplitude could be decreased in MS patients , 5, 6, 7With regard to the frequency domain, one possible technique is the ERD (event-related desynchronization) that was described by Pfurtscheller and Aranibar  and alloOn the other hand, disability in MS is usually assessed by EDSS  . The EDSFor this to be done, not only behavioral parameters  but also neuroimaging techniques will be necessary to understand the functional neuroanatomy of cognitive impairment in MS. Indeed, some recent studies have evinced that some EEG parameters  could be highly correlated to the EDSS score  and withOne of the main goals of the present study is to measure alterations in diverse behavioral and EEG parameters  in two different samples of patients (low and moderate EDSS scores) compared to a healthy sample. A cognitive task  will be used because of its reliability in all of these measures as has been previously tested , 24. It A second main goal is to look for statistically significant correlations between different types of variables  and disability of the MS patient assessed by EDSS. With this aim, we tried to identify neurophysiological parameters that are part of the mechanisms related to the cognitive impairment manifested by MS patients.We hypothesized that a more severely disabled condition in MS patients will show diverse cognitive alterations such as delays in reaction times, or changes in latency, amplitude and topography of P3 and ERD between healthy and patient groups. Another prediction is that correlation analyses will show a moderate correlation between EDSS and SDMT or the PASAT test as has been described in previous studies. However, we expect that a combination of diverse behavioral and neurophysiological parameters could correlate even better with EDSS score.Lastly, and as a more general hypothesis, we expect that the moderate-EDSS group will show a larger number of alterations in diverse parameters (Z-scores >1) than that of the low-EDSS group, indicating a more severe cognitive impairment. At the same time, the full set of individual patients will provide evidence of a complex landscape of alterations in all experimental parameters, indicating diverse cognitive status.Thirty participants were divided evenly into three groups. Two pathological groups were defined by the disability of patients measured through EDSS  .Previous to the ERP study, neuropsychological testing of the patients was provided by well-trained neuropsychologists blinded to the study goals. Diverse cognitive processes such as attention, concentration and speed of information processing were measured through the Paced Auditory Serial Addition Test, 3 seconds (PASAT-3s) , 29, andEEG parameters were recorded using a visual oddball paradigm that consisted of the discrimination of uncommon visual stimuli in a sequence of frequent stimuli. A total of 200 trials were used: 50 were target and 150 standard stimuli displayed in a pseudorandom presentation. The target stimulus was a rectangle with a checkerboard pattern comprising red and white squares. The standard (frequent) stimulus was equivalent in size with the same pattern but with black and white squares. Both stimuli were shown in the same position in the center of the screen. A fixation point was present when no stimuli were displayed to prevent changes in eye position during the experiment. The screen was located 70 centimeters from the participant's eyes, and the size of both stimuli was 7.98 of visual angle on the X axis and 9.42 on the Y axis. Both stimuli were presented for 500 milliseconds (ms), and the stimulus onset asynchrony (SOA) was 1.5 seconds during which the participant could respond. The participants were required to press the mouse button with the right index finger when a target stimulus appeared but to ignore the standard stimulus. At the end of the experimental session, reaction time and accuracy percentage were calculated.The EEG signal was recorded from 64 electrodes mounted in an elastic cap (Electro-cap) according to the International 10–20 system . All eleAn automatic rejection protocol was applied, and limits to exclude trials were set as ±75 μV that reject ocular movements performed during the experiment, as well as large muscle activity . Lastly, averages  were calculated for the target stimulus and for each participant. As recommended by Polich , all of BrainVision Analyzer Software was used to calculate amplitude, latency and topographical maps for both P3 and ERD modulations. The latency and amplitude values of the P3 component were calculated in the electrode that showed the maximum amplitude for each participant. The criterion to identify the P3 component was to select the maximum positivity from electrodes of a matrix of 6 x 7  in this were expAlpha event-related desynchronization (ERD) was obtained from the EEG signal applying the following protocol: 1) filtering in the 8–13 Hz band, 2) rectifying  and 3) averaging , 36. LatStatistical analyses were performed with SPSS v20 software. Considering the limited number of cases for each group (N = 10), a nonparametric test  was conducted to determine potential differences in the behavioral and neurophysiological variables . In all cases, pairwise comparisons were performed with a Bonferroni correction for multiple comparisons. Adjusted p-values are presented in the results section. The transformation of all parameters into a z-score was calculated using the following formula: Z = /standard deviation. Mean and standard calculations were obtained from the healthy group.To analyze the correlations between EDSS and all behavioral and EEG parameters (ERD and P3 latencies and map scores), Pearson’s product-moment r was employed. Neuropsychological data were only correlated with other measures for patient groups. Data from both patient groups were combined to perform the correlation analyses.In addition, we defined two variables termed “map scores” (for P3 and ERD) that were calculated as the correlation score between the voltage from the scalp electrodes (matrix 6x7 referred to above) for each patient and the corresponding voltage values of the grand average P3/ERD maps from the ten healthy controls. These two new variables were also included in the variables that were correlated to the EDSS score. Finally, we calculated the mean of a combined measure of three z-scores from three variables  and termed it as “Z3”.As a general consensus, p<0.05 was considered statistically significant. However, as recommended by Kileny & Kripal , a new lA Kruskal-Wallis test was conducted to determine whether there were differences in the reaction time between the experimental groups: "healthy control" (n = 10), "low-EDSS" (n = 10), and "moderate-EDSS" (n = 10). The median (Mdn) RT values were significantly different between the different levels of experimental groups, χ2(2) = 6,265, p = .043. The post hoc analysis indicated statistically significant differences in the RT values between the healthy control group  and the moderate-EDSS group  (p = .038). There were no significant differences between the other comparisons. The faster value corresponded to the healthy control group (418 ± 72.32 milliseconds (ms)), followed by the low-EDSS group (457 ± 69.19 ms) and finally the longer value belonged to the moderate-EDSS group (494 ± 66.40 ms) . AccuracPotential differences among the three groups  in the ERD latency were examined using a Kruskal-Wallis test. The median ERD latency values were significantly different between the different levels of experimental groups, χ2(2) = 10,095, p = .006. The post hoc analysis indicated statistically significant differences in the ERD values between the healthy control group  and the moderate-EDSS group  (p = .005) . There wThe Kruskal-Wallis test did not show significant differences among the groups for the P3 latency. Despite the lack of significant differences, healthy (371 ± 58.70 ms) and low-EDSS (363 ± 48.99 ms) groups were faster in their P3 latency compared to the moderate-EDSS group (478 ± 123.03 ms) . In the After the analyses, only three correlations showed a statistically significant value (p<0.002): SDMT vs EDSS ; SDMT vs Z3,  and EDSS vs Z3  see . A statiIn the correlation analyses for P3 maps between groups, the healthy and low-moderate group exhibited a good score , but a lower score was found when the comparison was made between healthy and moderate-EDSS groups . In the case of ERD maps, correlation scores between healthy and patient groups were in both cases at an excellent level . Amplitudes for P3 and ERD were not included in these analyses due to the absence of significant differences across the three groups.The reaction time showed a significant difference between the healthy control and moderate-EDSS groups. This difference was based on the slower responses for the moderate-EDSS group. This result suggests progressive deterioration in cognitive processing indexed by a behavioral variable in the moderate-EDSS group and an intermediate status for the low-EDSS group. It is necessary to note that the differences in reaction time were not a product of compensation for lower accuracy (speed-accuracy tradeoff) because there were no significant differences for the accuracy variable between groups.Finally, transformation of the reaction time variable in z-scores for each participant revealed that the moderate-EDSS group has a higher number of individuals with more than 1 (5) and three cases for low-EDSS. This result suggests that the reaction time in an oddball visual task can provide relative evidence of progressive cognitive deterioration in RRMS patients.The Pearson’s product-moment r between EDSS and reaction time exhibited a poor correlation score for these variables , indicating that behavior by itself is not very representative of disability progression. Moreover, it is necessary to mention that the healthy group also showed one individual with a z-score higher than one, indicating the possibility of false positives with this variable. In any case, it is necessary to remark that changes in the reaction time for MS groups could also be due to motor impairment and not only sensory and central cognitive impairments. Moreover, a global EDSS score could hide a potential motor impairment in an MS sample. Future studies considering subscores and peripheral and central motor evaluations would be required to confirm this possibility.The main result for neuropsychological variables is that the low-EDSS group was almost totally unimpaired as assessed by the SDMT and PASAT tests and considering normative scores by Sepulcre et al. . Five ofStatistical analysis of alpha ERD latency evinced that the moderate-EDSS group showed a significant delay compared to the healthy and low-EDSS groups. This result is in line with other described spectral alterations in MS patients. Leocani et al. showed dIn the individual alpha ERD maps,diverse results were remarkable for this parameter. First, some patients exhibited low correlation scores for their individual maps compared to the grand average map of the healthy group. Considering that the grand average maps for ERD between groups reached excellent scores (r>0.9), low correlation scores support previous studies in which it was noted that the grand averaging can hide individual particularities , 24. SecA remarkable result regarding the topography of alpha ERD is that, despite the reliable distribution in grand average maps between groups, individual analyses revealed that a more frontal and sometimes lateralized distribution of ERD modulation is present in the low-EDSS patients compared to that of the healthy grand average. This result is in line with previous studies where a more widespread anterior topography was found in fatigued patients . HoweverIn the case of the P3 component, no significant differences were identified for the latency parameter. A correlation between EDSS and P3 latency has been observed in previous studies . HoweverThe amplitude variable also exhibited a decrease  in the moderate-EDSS group compared to that of the healthy group and low-EDSS groups. Some studies have described similar decrement in P3 amplitude and have suggested that lack of attentional resources could be behind this modulation , 6. AnotThe third parameter for the P3 component (topography) showed in the grand average maps that the correlation score was diminishing in line with the progression of disease status. A lower P3 map score suggests higher disability. This result supports previous studies in which spontaneous fluctuation topography was related with EDSS  or in a Although no individual P3 latency was higher than z>1 for low-EDSS patients, some topography maps in this group exhibited a low P3 map score (4 out 10). This result suggests that P3 latency is probably a highly specific parameter for assessing the cognitive course in MS patients; however, changes in the topographical distribution could suggest that neural generators are affected in their orientation  even before cognitive impairment is visible by other P3 parameters (latency and amplitude).In other correlation analyses, P3 latency exhibited a moderate score with EDSS . However, the higher score was found for Z3  , suggesting that the combination of all of these parameters related with cognitive processing correlate at an acceptable level with the disability status (EDSS) in these patients.The general pattern that is represented in the current data is that several parameters related with cognitive processing  are altered at a more advanced phase of disability of MS patients (moderate-EDSS group). However, individual analyses reflect that, in the low-EDSS phase of the disease, diverse cognitive measures could be altered and provide,with just a few cognitive variables, a complex picture of possible compensatory mechanisms or cognitive processes that are not yet altered but will be once reaching moderate-EDSS status. Indeed, it is possible to find dissociation between behavioral parameters (reaction time) and EEG parameters (P3 and ERD latency) in individual patients who support previous studies in healthy participants .It is necessary to note that the healthy grand average map is valid for a specific cognitive task  and thatFuture research using different approaches to group vs individual analyses, and other research that uses machine learning to find hidden patterns in the cognitive status and evolution , 44 are In conclusion, the present study supports the idea of a moderate correlation between disability assessed by EDSS and alterations in diverse parameters related to cognitive processing. Interestingly, a general pattern is observed with no changes in the P3 latency/amplitude in the early phases of the disease but with an altered topography (even more for moderate-EDSS) with regard to the healthy grand average map. Alpha ERD latency is also affected in moderate-EDSS patients but without changes in topography between groups. However, based on the individual analyses, a complex landscape of diverse alterations in cognitive elements and their chronology may be present in the progression of MS. Further research with a higher number of samples and diverse forms of MS are necessary to enhance our knowledge regarding the functional neuroanatomy basis of cognitive impairment in MS.


State Visual Evoked Potentials (SSVEPs) arise from a resonance phenomenon in the visual cortex that is produced by a repetitive visual stimulus. SSVEPs have long been considered a steady-state response resulting from purely oscillatory components phase locked with the stimulation source, matching the stimulation frequency and its harmonics. Here we explore the dynamical character of the SSVEP response by proposing a novel non-stationary methodology for SSVEP detection based on an ensemble of Echo State Networks (ESN). The performance of this dynamical approach is compared to stationary canonical correlation analysis (CCA) for the detection of 6 visual stimulation frequencies ranging from 12 to 22 Hz. ESN-based methodology outperformed CCA, achieving an average information transfer rate of 47 bits/minute when simulating a BCI system of 6 degrees of freedom. However, for some subjects and stimulation frequencies the detection accuracy of CCA exceeds that of ESN. The comparison suggests that each methodology captures different features of the SSVEP response: while CCA captures purely stationary patterns, the ESN-based approach presented here is capable of detecting the non-stationary nature of the SSVEP. Steady-state visual evoked potentials (SSVEPs) are a neural phenomenon that appears when neural oscillatory activity, mainly in the primary visual cortex, synchronizes to a repetitive visual light source. It can be measured in the EEG as oscillatory components that match the stimulation frequency and/or its harmonics . SpecifiSSVEPs have proved to be useful for many paradigms in cognitive and clinical neuroscience . For exaNs degrees of freedom employs Ns independent light sources flickering at different frequencies. Each light source is associated then to a particular action of the BCI system: when the user wants the system to perform a specific action, he\she shall gaze at its associated light source.Recent years have also witnessed an increased interest in the use of steady state visual evoked potentials (SSVEPs) in brain computer interface (BCI) systems ,13. SSVEMany techniques are used for SSVEP characterization , among tThe brain is a complex, dynamical system that generates non-stationary high dimensional EEG patterns . This coThis paper is structured as follows. In section 2 we provide an overview of reservoir computing. We present the new methodology based on ESN in section 3 and introduce CCA. In section 4 we describe our experimental protocol, and in section 5 we provide results for both stationary and dynamical approaches. We conclude with a discussion of the results in section 6.Artificial neural networks have been extensively used for the analysis of stationary problems in computational intelligence. These architectures are well understood due to their feed-forward structure and non-dynamical nature. It is in general not possible to detect temporal dynamics using feedforward structures. A possible temporal generalization strategy is to add recurrent connections, which allow the system to encode time-dependent information by providing the network with memory and transforming it into a dynamical system , 21. DynSince the early 1980s, a wide variety of approaches for adaptive learning in networks with recurrent connections have been proposed . TraininIn previous works we have demonstrated that among other dynamics ESNs can detect chaotic synchronization variations within temporal series . ReservoK input units, N internal units, and L output units. Input, internal and output connection weights are defined respectively by the connection weight matrices Win, W and Wout. RNNs are characterized by having cyclic paths of connections defined by the back-projection weight matrix Wback. Input (Win), internal (W) and back-propagation weights (Wback) matrices conform the dynamical reservoir (DR) and are randomly constructed. The weight matrix W is characterized by its spectral radius, defined as the largest absolute eigenvalue of the weight matrix. The spectral radius is closely connected with the intrinsic dynamical timescale of the reservoir, and is therefore a key ESN training parameter. A small spectral radius leads to a faster RNN response.The global structure of an RNN is depicted in For the ESN principle to work, the reservoir must fulfill the echo state property (ESP). The ESP holds if the current state of the network, which is running for an infinite time, is uniquely determined by the history of the input and the teacher-forced output . The echo state property has proved to be linked with the characteristics of the reservoir, with the input signals and with the input and back-propagation weights , 38, 39.Other key training parameters in RC are the input scaling and the model size . The modWhen constructing an ESN the first step is thus the random dynamical reservoir (DR) construction for the selected global parameterization. Its role is to provide temporal context and work as a nonlinear expansion of the input. The DR random and feedback connections guarantee different dynamics or states to echo within the reservoir. The larger the reservoir is, the richer its dynamics. That is why the number of units in ESNs is larger compared to other recurrent neural network architectures. During the training process the input signal may provoke dynamics that follow certain trajectories within the randomly constructed DR. ESNs training is a supervised machine learning problem in which for a training input and target output, the output weights of the RNN linearly combine these trajectories to minimize the error between the network output and the desired target. Output weights can be calculated using any linear regression algorithm.X, Y and their linear transformation w and v that maximize the correlation between X and Y such that when the multidimensional variables are transformed, the corresponding coordinates are maximally correlated [Canonical correlation analysis  is emplorrelated :ρ=maxE[fi is evaluated by computing the canonical correlation between the EEG sequence under evaluation (X) and a reference signal (Y), constructed as a set of sine-cosine series at the stimulation frequency and its Nh harmonics of duration equal to that of the EEG sequence:The SSVEP response is characterized by oscillations in the visual cortex matching the stimulation frequency and its harmonics. The performance of a given stimulation frequency ρi) is calculated for all N stimulation frequencies (fi) under test. The stimulation frequency delivering the largest canonical correlation (ρ) is selected as responsible of eliciting the visual response [The maximal canonical correlation , i = 1,2,3…Ne). The SSVEP temporal response at fi for the harmonic K is computed by filtering the raw EEG using a narrow band-pass FIR filter with its central frequency at K∙fi. The ensemble temporal response . As will be explained in following sections, the optimal number of internal units, spectral radius, and input scaling factor has been selected by using three-fold cross validation exhaustive search. The temporal decomposition of SSVEP components coming from each electrode  have been configured to have as many input nodes as there are EEG electrodes that measure the visual evoked response  elicited the visual response during a stimulation trial. To achieve this, the ESN-based architecture has been designed as an ensemble of N ESNs, where each ESN has been trained for each stimulation frequency fi. The SSVEP response at each frequency  through a diffusing panel of 100 squared centimeters. Neuroelectric’s regulatory department acting as ethics committee stated that this experimental campaign was exempt from ethical review. The electroencephalographic recordings were performed on healthy adults. Neither the recording technique, nor the experimental protocol deemed to entail any danger or discomfort for the participants. Participant’s enrolled were professionals working in the field of neuroscience, who were fully aware of the recording technique and protocol. Consequently only oral informed consent was only required. Participants invited to take part in this study received detailed information of the experimental procedure before the session. This explanation was provided by the technician in charge of performing the recording. They were informed that 1) they will undertake periodic visual stimulation, 2) EEG sensors will be placed on their head and conductive gel inserted between the sensors and the scalp in order to ensure adequate contact, 3) a remote possibility of a mild headache and\or skin irritation, 4) that the study aimed to analyze alterations in brain patterns induced by a visual stimulation, and 5) they could quit the experiment at any time if they so desire. They had the opportunity to ask the technician to clarify anything they did not understand or would like to know more about. Participants confirmed they had understood the explanations, and that they voluntarily engage in the study. The researcher responsible of performing the experiment documented this consent in a signed document in which for each participant the date, time and location where the experiment took place were recorded. In this document the researcher declared to have properly informed the participant and that he/she voluntarily agreed to take part in this study.Five Caucasian male volunteers S1 to S5 with average age 33.6 years, and ages ranging from 29 to 46, participated in six recording sessions each, where oscillatory visual stimuli were presented at six different frequencies Ns = 15 stimulation trials (duration randomly ranging from 4 to 5 seconds), where the visual stimulus was presented, were followed by the same number of non-stimulation trials (duration randomly ranging from 5 to 8 seconds) with no visual stimulation. One stimulation source placed on the right of the subject presented the stimulation frequency under evaluation, while another source on the left presented a frequency randomly selected among the other frequencies used in the experiment. The goal of this montage was to simulate background interferences as in brain computer interfaces applications. Stimulation sources were separated by approximately 25 cm.Each session consisted of one recording per stimulation frequency. In each recording, The user was comfortably seated at one-meter distance from the stimulation sources and was instructed to look at the stimulation source placed on his right when hearing a beep sound (played one second before the stimulation started). EEG was acquired using Neuroelectrics Enobio, a wearable, wireless electrophysiology sensor system for the recording of EEG, at a sampling rate of 250Hz and from three channels placed in O1, Oz and O2, according to the 10–20 system . The eleThe goal of the performance evaluation is to compare how well the SSVEP response is detected using stationary and dynamical approaches. Using previously presented ESN and CCA based methods, the stimulation frequency among the 6 under evaluation  responsible for eliciting the evoked potential at each trial is assessed. The performance will be estimated for observation windows ranging from 0.5 to 4 seconds in terms of detection accuracy and information transfer rate (ITR) .Ne = 3 input nodes and one output node. Input nodes are fed with the filtered signals coming from O1, Oz and O2. The activation function of the network nodes is set to a hyperbolic tangent. Least-mean-square error minimization between the network output and the target output has been used to compute output weights. A washout duration of 250 samples has been applied. The optimal number of internal units, spectral radius and input scaling has been calculated through exhaustive search. The detection accuracy calculated over 4-second observation windows and a 0.5-second baseline has been assessed for every combination of internal units , spectral radius (from 0 to 1 in steps of 0.1) and input scaling factor . A total of 462 combinations were attempted.ESN networks have been configured to have Data is split into a training and a test set. The training set consists of the first 10 stimulation sequences, while the test set contains the remaining 5. The training set is used to calculate the optimal ESN parameterization, whereas the test set is used to evaluate the performance of the final model parameters. Parameter optimization was done based on 5 times 2-fold-cross validation (5 x 2-FCV). The cross-validation process was repeated 5 times in order minimize the effect introduced by the random dynamical reservoir initialization. In this process, the training set is partitioned in two non-overlapping folds for independently calculating the readout connections of the ESN and assessing the model under evaluation performance. Each fold is formed by 5 sequences of a stimulation trial (duration randomly ranging from 4 to 5 seconds), where the visual stimulus was presented, followed by a non-stimulation trial (duration randomly ranging from 5 to 8 seconds). The average fold duration was therefore 55 seconds (13750 samples).Parameter optimization was done through grid search for every possible combination of the spectral radius, input scaling and network size values. In each stimulation sequence under evaluation, the frequency maximizing the difference between the average ESN output in the 4-second observation window and the average ESN output in a 0.5-second baseline measured right before the stimulation trial is selected as responsible of eliciting the visual evoked response. A spectral radius of 0.5, 250 internal units and 0.05 input scaling factor delivered the best average classification accuracy across subjects (66%).Final results were calculated for the parameters that delivered the best average classification accuracy in Section 5.1.1, namely a spectral radius of 0.5, 250 internal units and 0.05 input scaling factor, that are applied to SSVEP detection in 0.5, 1, 1.5, 2, 2.5, 3, 3.5, and 4-second observation windows using a baseline of 0.5 seconds. The test set as described in Section 5.1.1, consisting of the 5 stimulation sequences not used for the ESN global parameters search, is employed to evaluate the ESN detection performance at each observation window. The average of five independent iterations has been calculated in order to reduce the effect produced by the random dynamical reservoir construction. Recordings have been band-pass filtered using a finite impulse response filter with 250 coefficients and high and low cut-off frequencies set to 1 and 45 Hz, respectively. The filtering aims to reduce the influence of high amplitude low-frequency components caused by motion artifacts and bad electrode-skin contact, as well as removing power line-noise interferences. After filtering, stimulation sequences have been extracted and split into shorter observation windows starting at the beginning of the visual stimulation. Maximal canonical correlation has been calculated for each stimulation frequency and its second harmonic. Canonical correlation performance has been evaluated on the test set used to assess the performance of the final ESN model.The data shows an important amount of subject variability: while some subjects achieve an excellent detection accuracy and ITR (Subject 3 has 100% classification accuracy for a 4-second observation window and a ITR of 75 bits/minute in 1.5-second windows), others deliver poor classification results (Subject 5 has 27% detection accuracy for 4-second observation windows and a maximum ITR of 3 bits/minute).SSVEP is a subject-dependent phenomenon in which a given stimulation frequency has proved to range from excellent to random classification across subjects . Table 2ESN-based methodologies significantly improve the average detection accuracy of subjects 1 and 5, while standard CCA performs better in subject 2 and 4. Both methodologies deliver excellent average classification performance for subject 3. Results show that the ESN-based method significantly improves classification in some stimulation frequencies and subjects compared to CCA  and vice versa (subject 2 stimulation frequency 14 Hz).We have presented a novel SSVEP-detection methodology based on reservoir computing with non-stationary pattern recognition capabilities whose performance has been compared with state of the art SSVEP stationary detection, Canonical Correlation Analysis. In this study the response to 6 visual stimulation frequencies ranging from 10 to 22 Hz is studied in 5 participants. Stationary and dynamical analysis of SSVEP response delivered disparate classification accuracy as displayed in Traditionally brain response to a flickering visual stimulation has been considered steady-state, in which the elicited effect is believed to be unchanging in time. In this scenario CCA can capture this stationary nature by linearly transforming the EEG into a vector space that reproduces the flickering frequency and its harmonics. In contrast, as previously stated in Section 2, Reservoir Computing based approaches can detect dynamical patterns and complex synchronization between EEG channels, and therefore identify the non-stationary nature of the SSVEP. The study of this SSVEP response duality can be used to further understand brain mechanisms in cognitive and clinical neuroscience. Our hypothesis is that SSVEP dynamical response may serve to study alterations in brain patterns linked attention, aging neurodegeneration and psychiatric disorders.The hereby proposed methodology can be also employed by itself or combined with other stationary techniques for the construction of BCI applications. Its detection capabilities proved to be independent from the observation window duration, delivering similar detection accuracy for windows ranging from 0.5 to 4 seconds (from 63% to 68%). In contrast, in CCA detection, performance increases along with window length, starting at random classification for 0.5-second windows and reaching a detection accuracy of 66% in 4-second windows. These results highlight the communication capabilities of the ESN-based method, which achieves an average information transfer rate of 47 bits/minute (with a maximum ITR of 87 bits/minute for Subect 3), that outperforms the average information transfer rate of 13 bits/minute achieved by the CCA method. The methodology proposed here achieves a high communication rate for a BCI system with 6 degrees of freedom, compared to other state of the art applications , 52. How


MERLIN is a novel biosensor that generates a BRET signal with a signal-to-noise ratio that is sufficient to enable sensing the proximity between the mitochondria and the ER without forcing interaction or establishing artificial connections at the MERCs. The contacts between the ER and mitochondria play a key role in cellular functions such as the exchange of lipids and calcium between both organelles, as well as in apoptosis and autophagy signaling. The molecular architecture and spatiotemporal regulation of these distinct contact regions remain obscure and there is a need for new tools that enable tackling these questions. Here, we present a new bioluminescence resonance energy transfer–based biosensor for the quantitative analysis of distances between the ER and mitochondria that we call MERLIN (Mitochondria–ER Length Indicator Nanosensor). The main advantages of MERLIN compared with available alternatives are that it does not rely on the formation of artificial physical links between the two organelles, which could lead to artifacts, and that it allows to study contact site reversibility and dynamics. We show the applicability of MERLIN by characterizing the role of the mitochondrial dynamics machinery on the contacts of this organelle with the ER. Membrane contact sites are distinct, juxtaposed regions between heterotypic membranous organelles that are physically associated via tethers of protein and lipid nature. They play a critical role in inter-organelle communication, including non-vesicular transport of small molecules, such as lipids and ions, as well as signaling and metabolic pathways. During the last decade, our understanding of the functional relevance and architecture of membrane contact sites has improved dramatically and revealed an unanticipated complexity that remains poorly understood .Some of the best characterized membrane contact sites correspond to the domains that mediate the physical interaction between the ER and mitochondria, which are known as mitochondria–ER membrane contacts (MERCs) or mitochondria-associated membranes . They in2+ receptor IP3R in the ER membrane is physically linked to VDAC1 in the mitochondrial outer membrane (MOM) by Grp75 –based biosensor for the analysis of distances between the mitochondria and ER, and therefore, for probing MERCs, which we call MERLIN (Mitochondria–ER Length Indicator Nanosensor). BRET is a variant of the well-established FRET technique that follows the same physical principle of the radiation-free energy transfer between two chromophores with overlapping spectra in close proximity (less than 10 nm). In BRET, however, the donor is the enzyme luciferase which oxidizes a substrate, the bioluminophore , which tThe main advantage of MERLIN, compared with other methods, is that it generates a BRET signal with a signal-to-noise ratio that is sufficient to enable sensing the proximity between the mitochondria and the ER without forcing interaction or establishing artificial connections at the MERCs. Because of this, MERLIN can be used to follow dynamics and reversibility of MERC formation and dissociation, which also sets it apart from other approaches. The two parts of the BRET biosensor are anchored to either the mitochondrial or ER membranes and each contain a protein of the BRET pair, Renilla Luciferase 8 (RLuc), or mVenus. A fully synthetic linker system with lengths between 0- and 24-nm spans the distance between the two organelles. To validate the functionality of MERLIN, we confirmed that MERC disruption by knockdown of PDZD8 was sensed by a decrease in the BRET signal. In addition, the biosensor detected an increase in the proximity of the ER and mitochondria when PDZD8 was overexpressed, when MERCs were forced by expression of a synthetic linker as well as during apoptosis. We demonstrated the applicability of MERLIN to detect dynamic changes in the distance between the mitochondria and ER by quantifying the reversible responses to a number of cellular stresses. We also report the applicability of MERLIN in sensitive cell types such as living neuronal progenitors and neurons. Finally, we used MERLIN to investigate the role of the machinery for mitochondrial dynamics in MERCs. We found that knockdown of mitofusins 1 and 2 (Mfn1 and Mfn2) or dynamin-related protein 1 (Dp1) resulted in a decrease of the BRET signal, underscoring the importance of mitochondrial shape and dynamics for the maintenance of the contact sites. Altogether, MERLIN is a powerful and innovative tool for the investigation of the mitochondria–ER membrane contact sites.To develop a new tool that allows studying the distance between mitochondria and the ER membrane with minimal interference, and therefore, also their contact sites, we developed a BRET-based biosensor with RLuc acting as a donor and mVenus as an acceptor. We generated MERLIN, a modular, genetically encoded system, where each of the two components of the BRET pair was targeted to the MOM or to the ER membrane. MOM targeting was achieved via the C-terminal domain of the Bcl-2 family protein Bcl-xL  . For theTo confirm the correct intracellular targeting of the MERLIN components, all constructs of the biosensor system were expressed in Cos1 cells and visualized by confocal microscopy. As expected, the mVenus and the RLuc constructs, immunostained with an anti-RLuc antibody, co-localized with MitoTracker and GRP78, respectively, indicative of mitochondrial or ER distribution according to their targeting signal .Next, we characterized the effect of the biosensor expression on cell viability by analyzing the release of the apoptotic protein Smac tagged with mCherry, under healthy and apoptotic conditions. Consistent with the nature of the BRET-based MERLIN partners, the overexpression of these constructs did not affect cell viability neither in healthy nor under apoptotic conditions .After verifying their correct localization and negligible effect on cell viability, we carried out a systematic analysis of the biosensor performance using quantitative saturation BRET assays. For these experiments, we used cells co-expressing constant amounts of the donor protein and increasing amounts of the acceptor protein. We calculated the BRET ratio as the acceptor emission relative to the donor emission and corrected by subtracting the background ratio value detected when only RLuc was expressed.To find out the optimal pair of biosensor components that is most sensitive despite the heterogeneity in ER/mitochondria distances, we performed BRET saturation assays for all possible linker combinations. We quantified the BRET signal for BRET pairs coupled to 0-, 6-, 12-, and 24-nm linkers, as well as with donor/acceptor targeted to the ER/mitochondria and vice versa. The quantitative BRET assays showed a saturation curve for all linker lengths, indicating specificity , and S2.As a negative control, we measured BRET saturation curves for biosensor combinations in which the donor and acceptor fragments were spatially separated by targeting them to two different cellular compartments. As expected, cells co-expressing the donor in the ER  and the acceptor either facing the lumen of the ER (mVen-ER5) or localized to the nucleus (mVen-H2B6) showed extremely low BRET ratios .As a positive control for maximum BRET, we prepared constructs in which the donor and acceptor proteins where physically linked, which was achieved by expressing them as a single polypeptide (Rluc-L1-mVen). As expected, cells expressing the construct RLuc-L1-mVen showed much higher BRET signal than all other biosensor combinations tested at the same donor/acceptor ratio . Of noteTo demonstrate the applicability of MERLIN to study mitochondria/ER contact sites, it is important to validate that the sensor responds with significant signal changes under cellular settings that are known to affect MERCs. For this purpose, we analyzed the sensitivity of MERLIN to changes in the levels of PDZD8, a known tether of MERCs , and to Furthermore, previous studies have shown that the contacts between mitochondria and the ER increase under apoptotic conditions . To checTo validate MERLIN using conditions that are known to reduce MERCs, we treated cells with N-acetylcysteine (NAC), a compound that improves mitochondrial function and is accompanied by a decrease in contact sites between the ER and mitochondria. Accordingly, we could detect a significant amount in the BRET signal that was concentration dependent .Finally, we validated MERLIN with an alternative method using EM . We firsAltogether, these experiments confirmed that the MERLIN system is indeed able to detect a tightening or loosening of the contact sites between the mitochondria and ER under a number of perturbations that are known to affect MERCs and demonstrate the validity of the new biosensor.The absence of a physical link between the two components of MERLIN should allow the biosensor to detect dynamic changes in the distance between the ER. To test if this is the case, we treated the cells transiently with several stimuli that have been proposed to modulate MERC formation and disruption and measured the BRET signal over time. For this purpose, we created a MERLIN-containing stable cell line, which exhibits correct organellar distribution and an insignificant effect in cell viability . In coheStudying MERCs in sensitive cell type such as neurons remains challenging because of the problems with phototoxicity in FRET-based biosensors and the difficulties to apply EM. These issues can be overcome by MERLIN, which we used to detect changes in MERCs induced by PDZD8 overexpression in neuronal progenitors and in differentiated neurons . AltogetBRET saturation assays are a perfect technique for high-throughput screenings in multi-well plate formats. However, we also wanted to test if MERLIN was compatible with light microscopy and the quantification of membrane contact sites in single cells . BecauseWe measured the proximity between the ER and mitochondria in experiments of fluorescence lifetime imaging (FLIM)-FRET using cells co-expressing biosensor combinations based on the 6-nm linker and with the donor targeted to the ER or to the mitochondria. We compared the fluorescence lifetime of the donor in these cells with that of cells only expressing the donor or the acceptor as negative controls . As additional positive and negative controls, we measured the donor fluorescence lifetime in cells expressing a donor–acceptor construct (mCer-L0-mVen) and in cells co-expressing spatially separated donor and acceptor (mCer-L1-B33C + A2A-mVen). As shown in The mitochondria–ER interface contains proteins involved not only in the tethering and regulation of MERCs but also proteins responsible for the several biological functions performed at these sites. Although the molecular composition remains enigmatic, the machinery for mitochondrial dynamics has been associated with MERCs . SeveralTo shed light on this issue, we compared the BRET signal of cells expressing MERLIN and knocked down for Mfn1 or Mfn2 with that of control cells without knockdown or with scramble siRNA knockdown as negative control  and S5. In addition to Mfn1 and Mfn2 knockdown, we also tested the effect of siRNA knockdown of the mitochondrial fission protein Drp1 on the proximity between the ER and mitochondria measured with MERLIN. Drp1 has been reported to be recruited at MERCs to mediate mitochondrial division , but a pAltogether, our findings demonstrate the applicability of the MERLIN system to study the association between the ER and mitochondria. Using the biosensor, we show that the machinery involved in mitochondrial fusion and fission affect the contacts between both organelles, which is associated not only to a likely tethering role of mitofusin 2 but also to alterations in the morphology of the mitochondrial network regulated by these proteins.Here, we present MERLIN, a novel modular biosensor system for probing the proximity between the ER and mitochondria, which is based on BRET between RLuc and mVenus targeted to each of the organelle membranes in a complementary manner. The BRET signal depends on the distance between donor and acceptor, which should be within a radius of at most 10 nm for efficient energy transfer. In MERLIN, they are brought together by a modular linker system that can be tuned to span different lengths ranging from 0 to 24 nm, plus the size of the donor/acceptor proteins and that of the membrane anchors. Although the linkers in MERLIN are designed to structure into rigid rods , the shoWe validated the sensitivity of MERLIN to probe changes in the distance between the ER and mitochondria, and thereby sense contact sites, by inducing a number of cellular perturbations that are known to promote concrete alterations in MERCs. We confirmed that overexpression or knockdown of PDZD8, a recently discovered mitochondria/ER tether and core component of MERCs , increasThe most important feature of MERLIN that sets it apart from alternative biosensors currently available  is that A second advantage of MERLIN over other systems, precisely related to the absence of a physical connection between the two sensor components, is that it allows studying reversible processes. This is the formation and dissociation of MERCs and the regulation of their dynamics. Here, we demonstrated the ability of MERLIN to follow the plasticity of MERCs by following the kinetics of BRET changes resulting from transiently treating the cells with stress inducers over time. Our results indicate that cells are able to recover a steady state in the distance between the ER and mitochondria once the stress stimulus is removed.It is important to note that MERLIN is a sensor of proximity, and it is not specific to contact sites. ER and mitochondria that are proximal to each other without any tether will also produce BRET. Nevertheless, because MERCs are characterized by a short separation between the two organelles, they are expected to be the major contributors to the BRET signal. Indeed, in our validation experiments, we demonstrate that MERLIN is a sensitive system capable of probing changes in MERCs. In this sense, the MERLIN system provides information related to the total juxtaposed area between the mitochondria and ER, but not about the number, size, or dynamics of individual contact sites. Along the same lines, the BRET sensor is not specific for different type of MERCs and cannot differentiate if the contacts have distinct molecular compositions.Using BRET as output signal has the advantage that no donor illumination is required, which avoids problems of phototoxicity and cross talk with the acceptor excitation and emission. The BRET signal is robust and, unlike with FEMP, no addition of rapamycin to maximize the signal by artificial mitochondria/ER juxtaposition is needed . As a reMitochondrial morphology and the machinery regulating have been reported to affect MERCs . Mfn2, wTo conclude, here, we present MERLIN, a novel proximity sensor for the distances between the ER and mitochondria, which is sensitive to alterations induced by genetic or pharmacological treatments. The main advantages of MERLIN compared with current alternatives are that it does not rely on any physical connection between the two organelles and that it can be used to study reversibility of MERCs. This modular biosensor approach could be easily extended to probe other inter-organelle contact sites by exchanging the targeting signals of the complementary components and selecting the optimal linker length. MERLIN opens the possibility to implemented inter-organelle proximity sensors in in vivo models such as mice because bioluminescence detection has been well established in these systems. Finally, we demonstrate the applicability of MERLIN by examining the role of the machinery for mitochondrial dynamics on the juxtaposition between the ER and mitochondria.Commercial antibodies used in this study were anti-Grp78 (Abcam), anti-RLuc (Abcam), anti-Mfn1 , anti-Mfn2 , anti-Drp1 (BD Bioscience), anti-PDZD8 , and anti-β-actin .pcDNA3.1(-) (Invitrogen) served as general targeting vector for all constructs. TOPO-TA cloning was performed into the plasmid pCR2.1-TOPO (Invitrogen). Restriction enzymes NheI and BamHI were used for the insertion of the constructs into the pcDNA3.1(-) vector and restriction enzymes XbaI and EcoRI for the insertion of the linker sequence (Eurofins-MWG). All constructs for expression using Sindbis virus were synthetized in pSinRep5 (Thermo Fisher Scientific). Restriction enzymes Mlu1 and StuI were used for the insertion of the constructs into the SR5 vector. The plasmids mVen-ER-5 (#56611) and mVen-H2B-6 (#56615) and cDNA of PDZD8 (#105005) and mTagBFP2 (#105011) were purchased from Addgene. Smac-mCherry was a gift from Dr Stephen Tait (University of Glasgow) and the components of the BRET pair were a gift from Dr Peter McCormick (University of Surrey).Cos1, HCT116, and HCT116 cells containing MERLIN were maintained in DMEM (Invitrogen) and McCoy’s5A (modified) medium (Sigma-Aldrich), respectively, and supplemented with 10% FBS (Invitrogen) and 1% penicillin/streptomycin (Invitrogen). Cells were transfected with Lipofectamine 2000 (Thermo Fisher Scientific) at 60–80% confluence.5 cells/well and 96-well plates at 6 × 104 cells/well. Neurons were maintained under 5% CO2 at 37°C in Neurobasal medium (Gibco) supplemented with B27 (Gibco), FBS (Gibco), and GlutaMAX (Gibco) until 7 days in vitro (DIV), after which the medium was replaced with the Neurobasal medium supplemented only with B27. To avoid excessive glial proliferation, neurons were treated with the antimitotic cytosine arabinoside  after incubation for 7 DIV. Viral infection was performed in DIV21 neurons during 24–48 h.Primary neurons in culture were prepared from E18 Sprague Dawley rat hippocampi as described by Midbrain dopaminergic neurons were generated with a protocol adapted from 2. Subsequently, the samples were blocked with 3% BSA in PBST (45 min at RT) and incubated with primary antibodies (1:100 in PBST with 3% BSA) for 1 h at RT. Next, the samples were washed with PBS, incubated with appropriate secondary antibody (1:200 in PBST) for 1 h at RT, and washed with PBST. In the cell viability experiments, the cells were grown as described above and transfected with Smac-mCherry and MERLIN (Smac/donor/acceptor in a 2:1:3 ratio). If required, the cells were treated with 1 μM staurosporine (STS) for 4 h at 37°C and 5% CO2. In hypoxia experiments, redox was measured upon BODIPY  addition for 30 min at 37°C and 5% CO2, in the presence/absence of 25 nM Monoethanolamin in HCT116 cells. Image acquisition was made with a Zeiss LSM 710 ConfoCor3 microscope (Carl Zeiss) equipped with a temperature and CO2 controller using a C-Apochromat ×40 NA 1.2 water immersion objective (Zeiss) and Leica SP8 microscope with ×63 NA 1.5 oil immersion objective (Leica Microsystems GmBH). Excitation light came from argon ion (488 nm) or HeNe  lasers. Images were processed and analyzed with ImageJ.Cos1 or HCT116 cells were grown on glass coverslips and transfected with MERLIN constructs for 16 h. For immunostaining, the cells were fixed at RT for 15 min with 4% paraformaldehyde and permeabilized by incubation with 0.25% Triton X-100 in PBS (PBST) for 10 min. If needed, before cell fixation, mitochondria were stained with 200 nM MitoTracker Red (Life Technologies) for 30 min at 37°C and 5% COHCT116 cells were transfected with Rluc-B33C and Scal-mVenus for 16 h as described above and diluted up to individual colonies. Next, G418:McCoy’s5A (modified) medium (Sigma-Aldrich)  selection was carried out during 2–3 wk. Finally, we isolated single clones using the colony cylinders and checked for MERLIN presence and targeting by immunoblotting and by measuring the BRET signal.Sindbis virus was produced as described by 2. Then, BRET measurements were carried out and subsequently the media was removed and substituted by fresh media. The cells were then incubated for 4–16 h to allow for recovery and subsequently subjected to BRET analysis. NAC treatment was prolonged for 10 d by exchanging the media every 48 h.In BRET assays, the cells were seeded in a white 96-well plate  and transfected with MERLIN for 16 h or infected with MERLIN for 48 h. The cells were washed with PBS, incubated with 5 μM coelenterazine h (Promega) in PBS for 5 min in the dark and BRET measurements were carried out in a Tecan Infinite M200 plate reader at RT. If necessary, the cells were transfected with PDZD8:MERLIN or ST:MERLIN at equimolar concentrations. BRET signal was calculated as acceptor emission relative to donor emission and corrected by subtracting the background ratio value detected when RLuc is expressed alone. In the assay for characterization of MERC plasticity, HCT116 cells were transfected with MERLIN as described above. Next, the cells were treated with 15 μM Taxol, STS 1 μM, 50 nM bortezomib, 25 nM Monoethanolamin (hypoxia), 25 nM tunicamycin, or deprived of FBS (starvation) for 4 h at 37°C with 5% of COThe cells were seeded on Matrigel (Corning)-coated glass coverslips and cultivated for 2 d before transfection and drug treatment. After washing and fixation with 2.5% glutaraldehyde (Sigma-Aldrich) in 20 mM Hepes buffer (pH 7.4) for 2 h at 37°C, the cells were washed with buffer, post-fixed in 2% osmium tetroxide, dehydrated, and embedded in epoxide resin  as described previously . UltrathProtein samples (50–200 μg protein) were separated by discontinuous 8.5–15% acrylamide SDS–PAGE and electrotransferred to a polyvinylidene fluoride membrane  using a semi-dry Turbo-blot apparatus (Bio-Rad). The membrane was blocked at RT for 1 h and probed at 4°C overnight with the appropriate primary antibody. After washing with 1× TBST, the HRP-conjugated secondary antibody was added in 5% milk and incubated for 1 h at RT. The membrane was washed with 1× TBST and developed with ECL .The cells were transfected with siRNA at a concentration of 2–10 nM for 48–72 h with Lipofectamine 2000 (Invitrogen) according to the manufacturer’s recommendation. Scramble siRNA used as a control in silencing experiments was purchased by Dharmacon (D-001810-01-20). Specific siRNA for knocking down Mfn1 (J-010670-12-0002), Mfn2 (J-012961-05-0002), Drp1 has a customized sequence (GGAGCCAGCUAGAUAUUAAUU), and PDZD8 (L-018369-02-0005) were purchased from Dharmacon. After transfection, BRET measurements were carried out as described above. PDZD8 signal was quantified and normalized to the actin signal by ImageJ.FLIM-FRET measurements were performed using a Leica TCS SP8 confocal microscope (Leica Microsystems GmBH) equipped with a FLIM unit (PicoQuant GmbH). For excitation (ex) and emission (em) of fluorescent proteins, the following laser settings were used: mCerulean3 at ex458 and em465–505 nm; mVenus at ex514 and em520–560 nm. FLIM data derive from three different biological replicates and measurements of 10 cells each replicate.


We assessed whether informing female sex workers about the availability of HIV self-testing at clinics in Kenya using text messages would increase HIV testing rates. We selected a sample of 2196 female sex workers registered in an electronic health record system who were irregular HIV testers and randomized them to be sent a text message announcing the availability of (1) HIV self-test kits sent three times (intervention), (2) general HIV testing sent three times (enhanced standard of care [SOC]), or (3) general HIV testing sent one time . Participants in the intervention arm were significantly more likely to test for HIV during 2-month follow-up compared to those in the enhanced SOC . There was no difference in HIV testing between those in the enhanced SOC and the traditional SOC arms. Announcing the availability of HIV self-testing via text message increased HIV testing among this high-risk group. Worldwide, HIV prevalence among sex workers is estimated to be as much as 12 times that of the general population . The HIVHIV self-testing may increase HIV testing rates among key populations such as sex workers. A number of studies have found that bringing HIV self-testing to potential users can increase HIV testing rates, including in studies in which pregnant women distributed self-test kits to their main partners in Kenya  and UganWe conducted a randomized controlled trial among female sex workers in Kenya who were irregular HIV testers to assess whether announcing the availability of HIV self-test kits in a clinic system in Kenya via text message would bring more female sex workers to the participating clinics for HIV testing compared to the standard of care text message reminder about HIV testing in general.The study was conducted in eight roadside wellness clinics in Kenya run by the North Star Alliance. The North Star Alliance is an organization providing primary and secondary health services to hard-to-reach populations, including sex workers and truck drivers, through its 36 clinics located at major transit hubs across Africa. In 2015, the North Star Alliance provided services to 253,227 client-visits, of which 18% included HIV testing . When a At every client encounter in a North Star Alliance clinic, HIV testing is offered and the test used is a blood-based (finger-prick) provider-administered test. HIV testing by clients at North Star clinics is tracked in the electronic health record system and a few times a year a text message reminder is sent to those clients who do not have a record of having tested for HIV in the previous 3 months. The message for clients in East Africa reads “North Star Alliance East Africa would wish to kindly remind you to visit any of our roadside wellness centres for HIV testing. Your health, our priority.”For this study, we selected a sample of female sex workers registered in the North Star Alliance electronic health record system who: (1) had no indication that they were HIV-positive, (2) resided in Kenya, (3) had a valid mobile phone number listed, (4) had fewer than four HIV tests recorded in the system in the past 12 months (indicating that they were not following the recommendation to test every 3 months for four tests per year ), and  Those randomized to the enhanced SOC arm received the SOC message reminding clients to come to a clinic for HIV testing (described above under Standard of Care), sent three times, one week apart, first in Kiswahili, then in English and then again in Kiswahili.Traditional Standard of Care  Those randomized to the traditional SOC arm received the SOC message one time sent simultaneously in both Kiswahili and English.The eligible individuals in our samples who did not communicate their desire to opt out of the evaluation were randomized to one of three study arms.Our primary outcome of interest was the comparison of HIV testing rates over a 2-month period following the initial text message about HIV testing between the intervention and enhanced SOC arms. We calculated sample size assuming the enhanced SOC would achieve 48% testing rate , and found that in order to detect a risk ratio (RR) of 1.2 (odds ratio [OR] 1.4) at 80% power and 95% confidence level, we would need a sample of about 750 female sex workers in each study arm. Therefore, we set our target sample size to 750 in each of the two study arms of primary interest, the intervention and enhanced SOC, and determined the randomization ratio after selecting the eligible sample in order to achieve this goal, which ended-up being 1:1:0.93 for the intervention, enhanced SOC, and SOC arms respectively.Study participants who presented at any North Star Alliance clinic in the SOC arms  were offered only the standard provider-administered blood-based HIV test, which is offered to all North Star Alliance clinic attendees. Participants from the intervention arm who presented at a North Star Alliance clinic in Kenya were given a brief demonstration of the self-testing kit and then offered a choice among: (1) the standard provider-administered blood-based HIV test; (2) the self-administered oral HIV test for use in the clinic with provider supervision; or (3) the self-administered oral HIV test kit for home use. Study arm was identified by the clinic receptionist by looking-up the client’s mobile phone number on an Excel spreadsheet listing the numbers of those in the intervention arm. The counselor was informed when an intervention client came in so she would be given a demonstration of the self-test kit and then offered the testing choices. Those in all study arms who visited a North Star Alliance clinic outside of Kenya would be offered the SOC test only, as those clinics did not have self-test kits. In addition, if someone not in the intervention arm came to a Kenyan clinic and specifically requested a self-test kit, presumably having heard about it from someone in the intervention arm, they were given the self-test so as not to miss an HIV testing opportunity. The HIV testing procedures were as follows:Those who accepted the standard provider-administered blood-based test underwent the standard pre- and post-test counseling and testing process.Those who chose the self-test for supervised use in the clinic received the standard pre-test counseling and then were given an OraQuick HIV self-test kit  which haThose who chose to take a self-test kit for use outside of the clinic  were given pre-test counseling in the clinic and then instructed to use their test within 3 days and to call or send a text message after using the test to receive a call-back for post-test counseling and any necessary referrals. Participants who failed to contact the clinic staff within 3 days after obtaining a test kit were called to inquire about the use of the test kit and provided counseling and referrals if needed. Clients were also told that they could call or send a text at any time while self-testing should they have any questions or concerns. As with in-clinic self-testing, clients were encouraged to disclose their test results during post-test counseling, but whether or not they did so was the client’s choice and if she did not disclose, the counselor was to provide information about both HIV test outcome scenarios.For this study, we relied on data from two sources: (1) the North Star Alliance electronic health record system which documented HIV testing and which test was used (provider-administered test or self-test), and (2) administrative data collected at the clinics in a password-protected Excel spreadsheet for tracking the number of self-test kits used to order resupplies when needed and for tracking time since a client took a self-test kit for home use to ascertain when to contact the client if they failed to call for post-test counseling.The study procedures were approved by the City University of New York Institutional Review Board, the Kenya Medical Research Institute Ethics Committee, and the University of KwaZulu-Natal Biomedical Research Ethics Committee.We described the sample in terms of the basic demographic characteristics  overall and by study arm and assessed the statistical significance of any differences by study arm using a Chi square test for categorical variables and a Kruskal–Wallis test for numeric variables. We then conducted logistic regression analysis to compare HIV testing during the 2-month follow-up period among clients in the intervention arm versus those in the enhanced SOC arm (primary comparison) as well as among those in the enhanced SOC versus those in the traditional SOC arms (secondary comparison) to look at the impact of the content of the text message  and of the number of text messages (3 vs. 1) on HIV testing, respectively. We also used logistic regression to look at differences in clinic contact for any reason  between the groups to see if the text message brought more clients to the clinic even if some chose not to test. Finally, we looked at whether the differences in HIV testing by study arm were modified by HIV testing history (whether the client had an HIV test at a North Star Alliance clinic in the past year) and, for those in the intervention arm, we describe the HIV testing choices made.We found some discrepancies between the electronic health record data and the clinic administrative records that were kept on self-testers in the number of people who self-tested for HIV in the intervention arm. Specifically, there were 38 female sex workers whose data in the electronic health record system did not indicate an HIV test but the clinics listed them as having self-tested. This might occur for a number of reasons, such as the counselor forgot to enter the data in the online health record system, or entered it but the internet connection was disrupted while the data were being sent to the server, or the data were entered after we downloaded the data for these analyses. The data were downloaded from the health record system 2 months after completing follow-up. Because of this discrepancy, we first analyzed the data including these 38 female sex workers as not having tested  because we did not have similar administrative data on HIV testing from the clinics for those in the SOC arms. Differential data cleaning could bias the results and incorrectly elevate the association between the intervention and HIV testing and we felt it best to err on the conservative side knowing that we might have bias toward the null. However, we also ran the analysis recoding those 38 female sex workers as having tested, as indicated in the administrative clinic records, to see if it changed our results substantively; while the strength of the effect increased as would be expected, the conclusions regarding the significance of the associations remained unchanged in all comparisons. In addition, after the study began, two participants in the intervention arm disclosed that they were HIV-positive to clinic staff when offered HIV testing. There was no indication in the electronic heath record system of their HIV-positive status. We included these two individuals in the intervention arm for analysis to maintain the randomization, despite the fact that it would bias our findings toward the null.On February 13, 2017, we selected the sample of 2364 female sex worker clients from the electronic health record system who met the eligibility criteria. We deleted duplicate phone numbers from the sample, leaving us with a sample of 2349 female sex workers to whom we sent the first consent text message, after which 116 female sex workers contacted us to opt out and 15 phone numbers were returned as invalid. A week later we sent the second consent text message, after which an additional 22 female sex workers contacted us to opt out. On March 2, 2017, the remaining 2196 female sex workers were randomized to the intervention (n = 750), enhanced SOC (n = 750) or traditional SOC (n = 696) arms and the first study text messages were sent according to their study arm. The text messages were sent two more times, 1 week apart for those in the intervention and enhanced SOC arms . Overall, 64.7% had not had an HIV test in the past year, and among those who had tested in the past year, the mean time since testing was 6.3 months. There were no significant differences in these characteristics by study arm Table .Table 1DForty-six (6.1%) participants in the enhanced SOC arm and 81 (10.8%) in the intervention arm tested for HIV during the 2-month follow-up period. Those in the intervention arm had 1.9 times greater odds of HIV testing compared to those in the enhanced SOC arm, which was statistically significant (p = 0.001). If we include the additional 38 female sex workers who had an indication of HIV self-testing in the administrative clinic records but not in the electronic health record system, the odds ratio increases to 2.9 (p < 0.001). (Table Seventy participants (9.3%) in the enhanced SOC arm and 105 (14.0%) in the intervention arm had some form of clinic contact or service during the 2-month follow-up. Those in the intervention arm had 1.6 times greater odds of clinic contact compared to those in the enhanced SOC arm, which was statistically significant (p = 0.005). If we include the additional 38 female sex workers who had an indication of HIV self-testing in the administrative clinic records but not in the electronic health record system as having had clinic contact, the odds ratio increases to 2.0 (p < 0.001)  participants in the traditional SOC arm compared to 46 (6.1%) in the enhanced SOC arm tested for HIV over the 2-month follow-up period, giving an odds ratio of 1.0 (p = 0.972). There was also no difference in clinic contact between the two arms  , 71 (59.7%) chose to self-test. One person took two HIV self-test kits from two different clinics, so the number of self-test kits used was 72. Of those, 52 (72.2%) self-tested in the clinic with supervision and 20 (27.8%) were taken for home use.Of the 20 test kits taken for home use, in 5 (25.0%) cases participants called while testing with questions, in 3 (15.0%) cases participants called after testing for posttest counseling, and in 7 cases (35.0%) participants called both while testing with questions and after for counseling. Five (25.0%) female sex workers did not call at all, and the counselor had to call them for posttest counseling. It took one attempt to reach three of these participants who did not call, two attempts for one participant and five attempts for the remaining participant. Five female sex workers tested HIV-positive during the study, all of whom were in the intervention arm (data not shown).HIV testing at baseline was very low in this sample of female sex workers, with only 35.3% having had an HIV test in the past year. This was in part by design as the goal of the study was to look at the impact of HIV self-testing among irregular testers and not following the recommendation of testing every 3 months was an eligibility criterion. Testing rates during study follow-up were also low, at about 6% in both the enhanced and traditional SOC arms, suggesting that we have not been able to reach this group with traditional HIV testing options. Advertising self-test kits increased the HIV testing rate to 10.6% for an OR of 1.9 when using the health record data alone and 2.9 times when including the clinic record data.Our findings that offering HIV self-testing increases HIV testing uptake are similar to those found in other trials. The impact of HIV self-testing on testing rates has ranged from a RR of 1.1–2.1, depending on the study design and population –9. Thus,Our use of text messaging in this study to announce the availability of a new HIV testing option is an important, low-cost innovation which could be useful as countries roll out self-testing in various venues. HIV self-testing was initiated in Kenya in May 2017, about one month after our study ended, with plans to make it available at public and private clinics and in pharmacies for a cost of about $8 US . Text meDespite the success of our intervention, the percent testing even with the self-testing intervention remained alarmingly low (10.8% in the intervention arm). Clearly offering self-testing at North Star Alliance clinics is only a partial solution to the low HIV testing rates among some female sex workers; other mechanisms will also be needed to increase testing rates in this high-risk group. One possible barrier may be the distribution mechanism. Distributing test-kits through clinics may not reach those who are unable to access or feel uncomfortable going to clinics. Although everyone in our study had received services from the North Star Alliance clinic system at least once in the past, as indicated by their registration in the health record system, some may have gotten those services via outreach instead of visiting a clinic. Other studies have looked at alternate distribution mechanisms for getting self-test kits to people, including pregnant women bringing self-test kits to male partners , 5, doorAmong those in the intervention arm who were offered HIV testing choices, there was a range in which test participants selected. While the majority chose to self-test 59.7%), the SOC test was chosen by a fair number of participants. Furthermore, of those who opted to self-test, about two-thirds chose to self-test in the clinic with supervision while the others chose to take a test kit for home use. This suggests that people vary in their preferences around HIV testing and offering choices may be key to maximizing HIV-testing rates as it increases the chance that an acceptable option will be available. The self-testing study among truck drivers in Kenya found similarly varied choices , 9, 16, .7%, the The OraQuick HIV self-test kit used in this study has slightly lower sensitivity (probability that someone HIV-infected tests HIV-positive = 91.7%), but higher specificity (probability that someone not HIV-infected tests HIV-negative = 99.9%)  comparedThere are a number of limitations to this study that should be considered in interpreting study findings. First, as previously mentioned, our text message was not very detailed and many receiving it may not have understood what it meant. This may have limited the number of participants who came to the clinics for the self-test and weakened the impact of the intervention. Second, our method of selection of eligible participants via the North Star Alliance health record system might have led us to include some who were not eligible and to exclude some who were eligible due to data errors in the system. The inclusion of duplicate phone numbers in the system as well as the missing HIV-testing data on 38 female sex workers who self-tested indicates a fairly high level of delayed data entry or error in the system. It is also possible that some participants in our sample had recently tested or been diagnosed with HIV in a non-North Star clinic prior to the study and should have been excluded or tested for HIV during follow-up at a non-North Star clinic and were therefore misclassified in our data. We did, in fact, find two participants who did not have an HIV-positive status indication in the health record system, but when they came to the clinic and were offered HIV testing, disclosed to clinic staff that they were HIV-positive. These errors should all be non-differential by study arm, on average, and bias our results toward the null. Furthermore, the self-test kits were only available at clinics located in Kenya, which may have hampered access for some who traveled outside of Kenya. However, prior to randomization, the clinic most recently visited was located in Kenya for all participants Table , so thisWe found that sending text messages announcing the availability of HIV self-test kits at North Star Alliance clinics in Kenya increased HIV testing rates among a sample of female sex workers who were inconsistent HIV testers. However, a number of issues need to be considered in designing clinic-based programs that include self-testing. First and foremost, oral self-testing should be thought of as complementary to existing services rather than replacing them. Many of the participants in our study chose the existing SOC HIV test when given a choice, but for others, self-testing was an attractive alternative, in that more people came to the clinic to test when learning about the availability of self-test kits. Thus, testing choices may be the key to maximizing HIV testing rates. Implementing an HIV self-testing program not only requires HTC counselor training and consideration of how self-testing fits into the current service model , but also design of appropriate information and counseling resources for clients. As we learned in this study, questions do arise during the testing process, so clients need to have some way to have their questions answered. For those with smart phones, the online video  may help


Background: Gaming disorder (GD) has been shown to co-occur with attention deficit hyperactivity disorder (ADHD), yet few studies to date have investigated their longitudinal associations.Method: The sample included 5,067 young Swiss men (mean age was 20 years at wave 1 and 25 years at wave 3). Measures were the Game Addiction Scale and the Adult ADHD Self-Report Scale (6-item screener). Longitudinal associations were tested using autoregressive cross-lagged models for binary measures of GD and ADHD, as well as continuous measures for GD score and ADHD subscales of inattention and hyperactivity.Results: ADHD at age 20 increased the risk for GD at age 25 . GD at age 20 also increased the risk for ADHD at wave 3 . Only the ADHD inattention subscale showed a bidirectional longitudinal relationship with the GD score , whereas associations between the hyperactivity subscale and GD were not significant.Discussion: GD had bidirectional longitudinal associations with ADHD, in that ADHD increased the risk for GD and GD increased the risk for ADHD, and they may reinforce each other. These associations may be linked more to the inattention ADHD component than to the hyperactivity ADHD component. Individuals with ADHD or GD should be screened for the other disorder, and preventive measures for GD should be evaluated in individuals with ADHD. Video gaming is a widespread activity among young men. Although gaming is an unproblematic leisure activity like many others for most people , it doesADHD is classified as a neurodevelopmental disorder. It is characterised by two components: inattention  and hyperactivity  . PrevaleThere has been relatively little research about the link between GD and ADHD. This is partly because before the DSM-5 included internet GD as a condition for further study, in 2013, internet GD was often studied together with internet addiction, and only afterwards as an independent condition . In a reRegarding associations with ADHD's inattention and hyperactivity subscales, another recent study reported that attention problems  in adolescents predicted internet GD 1 year later . A crossSeveral theories have been proposed for the link between ADHD and GD. For example, the “optimal stimulation model” proposes that individuals with ADHD have a higher threshold for reaching an agreeable level of arousal, and the rapid visual and acoustical stimulations in computer games requiring fast motor responses may be one way to reach this level . AnotherMost explanations and research have focussed on how ADHD leads to GD, although some explanations for a relationship in the other direction have also been proposed. Notably, ADHD symptoms may make gaming more attractive, whereas increased gaming may, in turn, exacerbate ADHD symptoms “by providing an activity that continuously reinforces the exact disinhibition, quick responsiveness, need for immediate reward, and inattention that are areas of concern” . A studyThis study aimed to re-examine the association between GD and ADHD in a longitudinal sample of young Swiss men. We first investigated whether our data confirmed cross-sectional associations between GD and ADHD and the ADHD subscales of inattention and hyperactivity. In a second step, we tested the longitudinal associations between GD and ADHD using an autoregressive cross-lagged (ARCL) model. The model examined whether ADHD at age 20 was associated with GD at age 25, whether GD at age 20 was associated with ADHD at 25, or whether there were bidirectional associations between GD and ADHD. We also tested GD for longitudinal associations with ADHD's inattention and hyperactivity subscales. In a third step, we tested whether participants with ADHD and GD at wave 1 (at about 20 years old) had worse outcomes with both of those disorders at wave 3 (about 25 years old) than participants with GD only or ADHD only, as well as several other outcomes potentially associated with ADHD or GD, namely major depression, mental health, life satisfaction, and poor performance at work or school.www.c-surf.ch). This study follows a large sample of young Swiss men recruited in their late adolescence to their adulthood, with measurement points at the age of about 20, 21, and 25 years, with more measurement waves being in planning. The main aim of the study is to evaluate patterns, trajectories, and associated risk or protective factors of substance use and non-substance related behaviours in these young men , during the recruitment procedure for military service. These procedures are mandatory for all young Swiss men at about the age of 20, therefore the sampling at this occasion has the advantage of covering most of young men of that cohort. Responses to questionnaires were independent of army procedures as individuals responded privately at home and confidentiality from the army was ensured. Participants could choose between paper questionnaires per mail or online questionnaires which were accessible by a link sent per e-mail. A total of 13,237 of young men have been asked to participate in the study, and 7,556 finally gave their written consent to participate in the study, of which 5,987 returned the baseline questionnaire (wave 1) and 5,516 returned the second follow-up questionnaire (wave 3) between April 2016 and March 2018. To increase response rates, participants who did not answer the questionnaire after standard reminders were encouraged by trained interviewers via phone calls to participate .The present study includes all 5,125 (85.6% retention rate) participants who responded to the baseline and second follow-up questionnaires. Of those, 58 (1.1%) participants with missing values for GD or ADHD in waves 1 or 3 were excluded, leaving 5,067 participants included in our present analysis. Participants received vouchers (50 CHF per questionnaire) as compensation for their efforts. Data from wave 2 were not used  because the measure for ADHD was only included in waves 1 and 3. The research protocol was approved by the Human Research Ethics Committee of the Canton Vaud (Protocol No. 15/07).never) to 4 (very often), and participants who responded to at least three items with a score of at least 2 (sometimes) were defined as presenting GD, as suggested by Lemmens and Valkenburg . This was done, because at the time when the questionnaire for wave 1 was developed, it was thought that lots of games involve internet activities, and that GD may be impossible without spending time in the internet (online games). After the DSM-5  was measured using the Game Addiction Scale (GAS) , which wlkenburg . Additiohe DSM-5 , releaseTable 2). Response options were on a five-point Likert-type scale ranging from 0 (never) to 4 (very often). For building a binary measure of ADHD, items were dichotomised—at least 2 (sometimes) for the first three items and at least 3 (often) for the last three items—and ADHD was defined as the presence of at least 4 symptoms as suggested by the authors of the scale  was measured using the six-item screener version of the Adult ADHD Self-Report Scale (ASRS-v1.1)  developehe scale . For anaAlcohol use disorder  was measured using 12 items for the 11 DSM-5 criteria , 36, 37 never) to 4 , a measure of the frequency of cannabis use ranging from 1 (monthly or less often) to 4 (four or more times per week), and one item with two response options, 0 (smoking cannabis for fun) or 4 (smoking cannabis out of habit). A cut-off of 8 out of 40 possible points was used to define cannabis use disorder. Cronbach's Alpha for the cannabis use disorder scale was 0.894 in wave 1 and 0.906 in wave 3.Cannabis use disorder (last 12 months) was measured using the revised version of the Cannabis Use Disorder Identification Test . Prevalence of ADHD increased from 5.7% in wave 1 to 7.6% in wave 3 [McNemar test p < 0.001]. Cross-sectionally, ADHD was more frequent in participants with GD than without GD, in both waves, with an Odds Ratio (OR) of 3.21  for wave 1 and 2.56  for wave 3. SUDs were not significantly associated with GD in wave 1, yet SUDs were significantly more frequent in participants with GD than without GD in wave 3. Accordingly, adjusting for SUDs only marginally changed the association between ADHD and GD in wave 1, but reduced this association in wave 3 (from OR = 2.56 to OR = 2.08). The mean scores of each of the six ADHD items were higher in participants with GD at waves 1 and 3, although this was not significantly higher for the second item of the ADHD hyperactivity subscale  to the coefficient for GD at wave 1 on ADHD at wave 3 . Adjustments for SUD had only a minor impact on the cross-lagged paths .Participants with GD at wave 1 were more likely to show ADHD at wave 3, and participants with ADHD at wave 1 were more likely to show GD at wave 3 . The ADHD hyperactivity subscale showed no significant longitudinal associations with GD score .As regards longitudinal associations between ADHD subscale scores and GD score, the ARCL including the GD score and the ADHD inattention and hyperactivity subscales only showed significant  and attention deficit hyperactivity disorder (ADHD) in a longitudinal sample of young Swiss men. At both measurement points, GD was considerably more frequent  among participants with ADHD than among those without ADHD. Similarly, ADHD was more frequent among participants with GD than those without GD. These findings are well in line with existing studies showing cross-sectional associations between GD and ADHD  Several theories have been proposed concerning the mechanisms underlying associations between ADHD and gaming. Notably, gaming may optimally stimulate individuals with ADHD by providing an exciting activity with immediate rewards: it may therefore be a way to cope with the symptoms of ADHD. However, because gaming provides exactly what individuals with ADHD may prefer, frequent exposure to such a potent stimulus may in turn reinforce ADHD symptoms  and leadA further finding was that the inattention and hyperactivity subscales of ADHD also showed significant cross-sectional associations with GD. However, if jointly entered in a regression model, only inattention remained significant, indicating that the link between ADHD and GD may be mainly accounted for by this variable. Similarly, the ARCL model using both the continuous ADHD subscales and the GD score showed that the link between ADHD and GD (in both directions) was dominated by the inattention subscale, with longitudinal associations for the hyperactivity subscale being non-significant (and even slightly negative). This finding is consistent with those from an earlier cross-sectionall study  of 205 aThe present study tested whether individuals with GD and ADHD at age 20 had worse outcomes at age 25 than individuals with only GD or only ADHD. Our results indicate that GD might have been more persistent  among individuals who also had ADHD at age 20 than among those with only GD at age 20, however, the coefficient in our study was just below significance after adjustment for SUD, indicating that other factors besides ADHD may also influence the persistence of GD. This is in line with similar evidence from the field of SUDs showing that ADHD may have a negative impact on the courses of those disorders, i.e., individuals with ADHD may become addicted more easily and have lower remission rates . The preAt age 25, participants with both ADHD and GD at age 20 had the worst outcomes on all the other scales measured—SF-12 mental health scale scores, major depression scores, life satisfaction, and poor performance at work or school. Participants who only had ADHD at age 20 had the second-worst outcomes. Participants who only had GD at age 20 had somewhat better outcomes at age 25 than those with only ADHD at age 20. Participants who had neither ADHD nor GD at age 20 had the best other outcomes. However, the differences in other outcomes between participants with GD and ADHD at age 20 and those with only ADHD were relatively small and only significant for major depression scores. However, there were relatively few cases with both GD and ADHD at wave 1.Nevertheless, our results provide evidence that individuals with GD and ADHD may have worse outcomes than individuals who only have GD or who only have ADHD. They also suggest that GD is more than just a symptom or correlate of ADHD, as it is associated with worse outcomes even in individuals with ADHD. GD should therefore be considered as a potentially serious condition, and individuals with comorbid ADHD and GD may require special consideration.Our sample consisted only of young Swiss men of a restricted age range. Thus, our results may not be generalizable to other populations. Overall, although coefficients for longitudinal associations between GD and ADHD were significant, they were relatively small. However, they remained relatively unchanged, even when adjusted for potentially confounding variables like SUDs. The instrument used for measuring GD differed somewhat between waves 1 and 3, as the Game Addiction Scale was extended in waves 1 and 2 to assess internet addiction too. This was partly corrected by setting the instrument's score to 0 for participants who played video games less than weekly. Overall, small differences in prevalence rates were in the expected direction , and consistent results indicated that the impact of the differences in wording between the instruments was small. For space reasons, we used the short, six-item screener version of the Adult ADHD Self-Report Scale, consisting of only four items for inattention and two for hyperactivity. Further research using longer ADHD scales, allowing for better differentiation of subtypes, is certainly required.The present study adds to existing evidence that GD may be associated with serious negative mental health outcomes by providing evidence that GD and adult ADHD have bidirectional longitudinal associations, i.e., each increases the risk of the other. This also suggests the possibility that the two disorders may reinforce each other, i.e., cause a vicious circle : early ASM analysed the data and wrote the paper. GG and JS designed the study. GG, JS, and VG assisted data analysis and commented on earlier versions of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.