Analysis of Error Potentials generated by a lower limb exoskeleton feedback in a BMI for gait control.

Brain-machine interfaces (BMIs) based on motor imagery (MI) for controlling lower-limb exoskeletons during the gait have been gaining importance in the rehabilitation field. However, these MI-BMI are not as precise as they should. The detection of error related potentials (ErrP) as a self-tune parameter to prevent wrong commands could be an interesting approach to improve their performance. For this reason, in this investigation ErrP elicited by the movement of a lower-limb exoskeleton against subject's will is analyzed in the time, frequency and time-frequency domain and compared with the cases where the exoskeleton is correctly commanded by motor imagery (MI). The results of the ErrP study indicate that there is statistical significative evidence of a difference between the signals in the erroneous events and the success events. Thus, ErrP could be used to increase the accuracy of BMIs which commands exoskeletons.Clinical Relevance- This investigation has the purpose of improving brain-machine interfaces (BMIs) based on motor imagery (MI) by means of the detection of error potentials. This could promote the adoption of robotic exoskeletons commanded by BMIs in rehabilitation therapies.

Transfer Learning with CNN Models for Brain-Machine Interfaces to command lower-limb exoskeletons: A Solution for Limited Data.

This study evaluates the performance of two convolutional neural networks (CNNs) in a brain-machine interface (BMI) based on motor imagery (MI) by using a small dataset collected from five participants wearing a lower-limb exoskeleton. To address the issue of limited data availability, transfer learning was employed by training models on EEG signals from other subjects and subsequently fine-tuning them to specific users. A combination of common spatial patterns (CSP) and linear discriminant analysis (LDA) was used as a benchmark for comparison. The study's primary aim is to examine the potential of CNNs and transfer learning in the development of an automatic neural classification system for a BMI based on MI to command a lower-limb exoskeleton that can be used by individuals without specialized training.Clinical Relevance- BMI can be used in rehabilitation for patients with motor impairment by using mental simulation of movement to activate robotic exoskeletons. This can promote neural plasticity and aid in recovery.

Minimum clinically important differences for the Functioning Assessment Short Test and a battery of neuropsychological tests in bipolar disorders: results from the FACE-BD cohort.

AIMS: Establishing the minimum clinically important difference (MCID) in functioning and cognition is essential to the interpretation of the research and clinical work conducted in bipolar disorders (BD). The present study aimed to estimate the MCID for the Functioning Assessment Short Test (FAST) and a battery of neuropsychological tests in BD. METHODS: Anchor-based and distributive methods were used to estimate the MCID for the FAST and cognition using data from a large, multicentre, observational cohort of individuals with BD. The FAST and cognition were linked with the Clinical Global Impressions Scale-Severity (CGI-S) and Global Assessment of Functioning (GAF) using an equipercentile method. The magnitude of the standard error measurement (s.e.m.) provided another estimate of the MCID. RESULTS: In total, 570 participants were followed for 2 years. Cross-sectional CGI-S and GAF scores were linked to a threshold ⩽7 on the FAST for functional remission. The MCID for the FAST equalled 8- or 9-points change from baseline using the CGI-S and GAF. One s.e.m. on the FAST corresponded to 7.6-points change from baseline. Cognitive variables insufficiently correlated with anchor variables (all ρ <0.3). One s.e.m. for cognitive variables corresponded to a range of 0.45 to 0.93-s.d. change from baseline. CONCLUSIONS: These findings support the value of the estimated MCID for the FAST and cognition and may be a useful tool to evaluate cognitive and functional remediation effects and improve patient functional outcomes in BD. The CGI-S and GAF were inappropriate anchors for cognition. Further studies may use performance-based measures of functioning instead.

The implications of hypersomnia in the context of major depression: Results from a large, international, observational study.

According to the DSM-5, "reduction in the need for sleep" is the only sleep-related criteria for mixed features in depressive episodes. We aimed at studying the prevalence, clinical correlates and the role of hypersomnia in a sample of acutely depressed patients. Secondarily, we factors significantly increasing the odds of hypersomnia were studied. We conducted a post-hoc analysis of the BRIDGE-II-Mix study. Variables were compared between patients with hypersomnia (SLEEP+) and with insomnia (SLEEP-) with standard bivariate tests. A stepwise backward logistic regression model was performed with SLEEP+ as dependent variable. A total of 2514 subjects were dichotomized into SLEEP+ (n = 423, 16.8%) and SLEEP- (n = 2091, 83.2%). SLEEP+ had significant higher rates of obese BMI (p < 0.001), BD diagnosis (p = 0.027), severe BD (p < 0.001), lifetime suicide attempts (p < 0.001), lower age at first depression (p = 0.004) than SLEEP-. Also, SLEEP+ had significantly poorer response to antidepressants (AD) such as (hypo)manic switches, AD resistance, affective lability, or irritability (all 0<0.005). Moreover, SLEEP+ had significantly higher rates of mixed-state specifiers than SLEEP- (all 0 < 0.006). A significant contribution to hypersomnia in our regression model was driven by metabolic-related features, such as "current bulimia" (OR = 4.21) and "overweight/obese BMI (OR = 1.42)". Globally, hypersomnia is associated with poor outcome in acute depression. Hypersomnia is strongly associated with mixed features and bipolarity. Metabolic aspects could influence the expression of hypersomnia, worsening the overall clinical outcome. Along with commonly used screening tools, detection of hypersomnia has potential, costless discriminative validity in the differential diagnosis unipolar and bipolar depression.

Functional neuroimaging in patients presenting with somatoform disorders: A model for investigating persisting symptoms after tick bites and post-treatment Lyme disease syndrome?

Approximately 10% of patients presenting with Lyme disease experience fatigue, musculoskeletal pain, concentration disorders, or short-term memory deficits in the six months following treatment. This entity has been defined as post-Lyme disease syndrome or post-treatment Lyme disease syndrome. The pathophysiology of this syndrome is unknown, but neither persistence of the bacterium nor effectiveness of antibiotics are currently reported in the literature. The French High Council for Public Health (French acronym HCSP) has recently defined a new entity called "persistent polymorphic symptoms after a tick bite" allowing for designing studies to better understand these subjective presentations, for which objective biomarkers are currently lacking. This entity encompasses patients experiencing fatigue and generalized pain in the months following a tick bite and can be associated with several subjective symptoms with major impact on the quality of life. In the field of somatoform disorders, this article reviews functional neuroimaging studies in patients presenting with subjective complaints and discusses potential clinical implications for persisting symptoms after tick bites and post-treatment Lyme disease syndrome.

The relationship between attention deficit hyperactivity disorder, bipolarity and mixed features in major depressive patients: Evidence from the BRIDGE-II-Mix Study.

OBJECTIVE: This study primarily focused on the relationship between comorbid attention deficit-hyperactivity disorder (ADHD), mixed features and bipolarity in major depressive patients. METHODS: The sample comprised 2777 patients with Major Depressive Episode (MDE) enrolled in a multicentre, multinational study originally designed to assess different definitions of mixed depression. Socio-demographic, familial and clinical characteristics were compared in patients with (ADHD + ) and without (ADHD-) comorbid ADHD. RESULTS: Sixty-one patients (2.2%) met criteria for ADHD. ADHD was associated with a higher number of (hypo)manic symptoms during depression. Mixed depression was more represented in ADHD + patients than in ADHD- using both DSM-5 and experimental criteria. Differences were maintained after removing overlapping symptoms between (hypo)mania and ADHD. ADHD in MDE was also associated with a variety of clinical and course features such as onset before the age of 20, first-degree family history of (hypo)mania, past history of antidepressant-induced (hypo)manic switches, higher number of depressive and affective episodes, atypical depressive features, higher rates of bipolarity specifier, psychiatric comorbidities with eating, anxiety and borderline personality disorders. LIMITATIONS: The study was primarily designed to address mixed features in ADHD, with slightly reduced sensitivity to the diagnosis of ADHD. Other possible diagnostic biases due to heterogeneity of participating clinicians. CONCLUSIONS: In a sample of major depressive patients, the comorbid diagnosis of current ADHD is associated with bipolar diathesis, mixed features, multiple psychiatric comorbidity and a more unstable course. Further prospective studies are necessary to confirm the possible mediating role of temperamental mood instability and emotional dysregulation in such a complex clinical presentation.

Effects of an Exoskeleton-Assisted Gait Motor Imagery Training in Functional Brain Connectivity.

Lower-limb exoskeletons have been used in gait rehabilitation to facilitate the restoration of motor skills. These robotics systems could be complemented by Brain-Computer Interfaces (BCIs) to assist or rehabilitate people with walking disabilities. In this preliminary study, electroencephalography-based brain functional connectivity is analyzed during exoskeleton-assisted gait motor imagery (MI) training. Partial Directed Coherence (PDC) analysis was employed to assess the exchange of information flow between EEG signals during gait MI in four healthy subjects, two using an exoskeleton and two without using it. Besides, in order to explore the functional connectivity, an outflow index based on the number of significant directed connectivities revealed by the PDC analysis is proposed. We found that the outflow index increases in the central zone (C2, C3, C4) while decreases in the central-parietal (CP1, CP2) and fronto-central (FC1) zones when the training was assisted by an exoskeleton. The results obtained can be useful to obtain informative features for BCI applications as well as in motor rehabilitation.

[Aripiprazole as dopamine partial agonist model: Basic concepts and clinical impact]. / L'aripiprazole comme modèle d'agoniste dopaminergique partiel : concepts de base et incidence clinique.

Aripiprazole may be viewed as the prototype of third-generation antipsychotics. This concept is based on the notion of D2 partial agonism, whereas all molecules of first-and second generation were D2 antagonists. After reviewing the basic pharmacological notions linked to such concepts, the mechanisms of action of these molecules are addressed, with a particular focus on functional selectivity and biased ligand. One of the essential pharmacological properties of D2 agonists, and particularity aripiprazole, is their ability to not induce D2 supersensitivity as well as to reverse this supersensitivity when it has been induced by D2 antagonists. In clinical practice, this impacts the choice of treatment in first episode psychosis as well as in refractory schizophrenia. Animal research shows that D2 supersensitivity could contribute to worsen addictive trends. The pharmacokinetic incidence of D2 supersensitivity tends to favour the long-acting forms of partial agonists. The notion of partial agonism could finally lead to design fourth-generation antipsychotics, on the basis on research focusing on functional selectivity.

Comparison of different EEG signal analysis techniques for an offline lower limb motor imagery brain-computer interface.

The use of motion assistance devices improves the rehabilitation process of patients that have motor disabilities. In the case these devices are controlled by brain-machine interfaces, the rehabilitation process can be improved due to neuroplasticity. However, in the case of lower limb rehabilitation, the limited accuracy of the control algorithms is a serious difficulty to overcome. In this research, different EEG signal's processing techniques, based on motor imagery, are tested for a brain-computer interface in an offline scenario, in order to detect the limitations of the models previous to its realtime implementation. The results reveal that motor imagery is very dependent on the subject and that Stockwell Transform provides the best accuracy among the models tested.

Novel tDCS montage favors lower limb motor imagery detection.

This work studies a novel transcranial direct current stimulation (tDCS) montage to improve a brain-machine interface (BMI) lower limb motor imagery detection. The tDCS montage is composed by two anodes and one cathode. One anode is located over the motor cortex and the other one over the cerebellum. Ten healthy subjects participated in this experiment. They were randomly separated into two groups: sham, which received a fake stimulation, and active tDCS, which received a real stimulation. Each subject was experimented on five consecutive days. Results pointed out that there was a significant difference $(p < 0 .05)$ in the classification accuracy between the sham and the active tDCS group. On each of the five days of the experiment the active tDCS group achieved better accuracy results than the sham group: 4%, 10%, 10%, 9% and 7% higher respectively.

Offline Lower-Limb Kinematic Decodification by Segments of EEG Signals.

In this work, hip and knee angles were decoded from low frequency EEG components recorded during the execution of two tasks. In order to compare their performance, three decoders based on multiple linear regression (MLR) models were applied under different conditions; which consisted in considering the processed data as a whole or divided into segments. Results suggest that, when the segments are related to specific tasks, the segmentation provides a better performance than applying the decoding method to unsegmented data.

Central nervous system modulates the neuromechanical delay in a broad range for the control of muscle force.

Force is generated by muscle units according to the neural activation sent by motor neurons. The motor unit is therefore the interface between the neural coding of movement and the musculotendinous system. Here we propose a method to accurately measure the latency between an estimate of the neural drive to muscle and force. Furthermore, we systematically investigate this latency, which we refer to as the neuromechanical delay (NMD), as a function of the rate of force generation. In two experimental sessions, eight men performed isometric finger abduction and ankle dorsiflexion sinusoidal contractions at three frequencies and peak-to-peak amplitudes {0.5, 1, and 1.5 Hz; 1, 5, and 10 of maximal force [%maximal voluntary contraction (MVC)]}, with a mean force of 10% MVC. The discharge timings of motor units of the first dorsal interosseous (FDI) and tibialis anterior (TA) muscle were identified by high-density surface EMG decomposition. The neural drive was estimated as the cumulative discharge timings of the identified motor units. The neural drive predicted 80 ± 0.4% of the force fluctuations and consistently anticipated force by 194.6 ± 55 ms (average across conditions and muscles). The NMD decreased nonlinearly with the rate of force generation ( R2 = 0.82 ± 0.07; exponential fitting) with a broad range of values (from 70 to 385 ms) and was 66 ± 0.01 ms shorter for the FDI than TA ( P < 0.001). In conclusion, we provided a method to estimate the delay between the neural control and force generation, and we showed that this delay is muscle-dependent and is modulated within a wide range by the central nervous system. NEW & NOTEWORTHY The motor unit is a neuromechanical interface that converts neural signals into mechanical force with a delay determined by neural and peripheral properties. Classically, this delay has been assessed from the muscle resting level or during electrically elicited contractions. In the present study, we introduce the neuromechanical delay as the latency between the neural drive to muscle and force during variable-force contractions, and we show that it is broadly modulated by the central nervous system.

Secular trends in the age at onset of bipolar I disorder - Support for birth cohort effects from interational, multi-centre clinical observational studies.

OBJECTIVE: To examine any association of birth decade, sex and exposure to alcohol and/or substance use disorders (ASUD) with age at onset (AAO) of bipolar I disorder (BD-I). METHODS: Using data from a representative clinical sample of 3896 BD-I cases recruited from 14 European countries, we examined AAO distributions in individuals born in consecutive birth decades. Cumulative probabilities with Mantel-Cox log-rank tests, pairwise comparisons and Odds Ratios (OR) with 95% confidence intervals (95% CI) were employed to analyze AAO according to birth decade, sex, and presence or absence of an ASUD. RESULTS: In the total sample, median AAO of BD-I decreased from about 41 years for those born in the 1930s to about 26 years for those born in the 1960s. In a sub-sample of 1247 individuals (selected to minimize confounding), AAO significantly decreased for males and females born in each consecutive decade between 1930 and 50 (OR: 0.65; 95% CI: 0.51, 0.81), and for cases with an ASUD as compared to without (OR: 0.77, 95% CI: 0.69, 0.87). The best fitting regression model identified an independent effect for each birth decade and an interaction between ASUD status and sex, with a consistently earlier AAO in males with an ASUD (OR: 0.79: 95% CI: 0.70, 0.91). CONCLUSIONS: In BD-I cases diagnosed according to internationally recognized criteria and recruited to pan-European clinical observational studies, the AAO distributions are compatible with a birth cohort effect. A potentially modifiable risk factor, namely ASUD status, was associated with the observed reduction in AAO, especially in males.

Emotional hyper-reactivity and cardiometabolic risk in remitted bipolar patients: a machine learning approach.

OBJECTIVE: Remitted bipolar disorder (BD) patients frequently present with chronic mood instability and emotional hyper-reactivity, associated with poor psychosocial functioning and low-grade inflammation. We investigated emotional hyper-reactivity as a dimension for characterization of remitted BD patients, and clinical and biological factors for identifying those with and without emotional hyper-reactivity. METHOD: A total of 635 adult remitted BD patients, evaluated in the French Network of Bipolar Expert Centers from 2010-2015, were assessed for emotional reactivity using the Multidimensional Assessment of Thymic States. Machine learning algorithms were used on clinical and biological variables to enhance characterization of patients. RESULTS: After adjustment, patients with emotional hyper-reactivity (n = 306) had significantly higher levels of systolic and diastolic blood pressure (P < 1.0 × 10-8 ), high-sensitivity C-reactive protein (P < 1.0 × 10-8 ), fasting glucose (P < 2.23 × 10-6 ), glycated hemoglobin (P = 0.0008) and suicide attempts (P = 1.4 × 10-8 ). Using models of combined clinical and biological factors for distinguishing BD patients with and without emotional hyper-reactivity, the strongest predictors were: systolic and diastolic blood pressure, fasting glucose, C-reactive protein and number of suicide attempts. This predictive model identified patients with emotional hyper-reactivity with 84.9% accuracy. CONCLUSION: The assessment of emotional hyper-reactivity in remitted BD patients is clinically relevant, particularly for identifying those at higher risk of cardiometabolic dysfunction, chronic inflammation, and suicide.

Quantitative System Pharmacology (QSP): An Integrative Framework for paradigm change in the treatment of the first-episode schizophrenia.

Despite the lack of progress in the curative treatment of mental illness, especially schizophrenia, the accumulation of neuroscience data over the past decade suggests the re-conceptualization of schizophrenia. With the advent of new biomarkers and cognitive tools, new neuroscience technologies such as functional dynamic connectivity and the identification of subtle clinical features; it is now possible to detect early stages at risk or prodromes of a first psychotic episode. Current concepts reconceptualizes schizophrenia as a neurodevelopmental disorder at early onset, with polygenic risk and only symptomatic treatment for positive symptoms at this time. The use of such technologies in the future suggests new diagnostic and therapeutic options. Next steps include new pharmacological perspectives and potential contributions of new technologies such as quantitative system pharmacology brain computational modeling approach.

Sleep quality and emotional reactivity cluster in bipolar disorders and impact on functioning.

OBJECTIVE: Bipolar disorders (BD) are characterized by sleep disturbances and emotional dysregulation both during acute episodes and remission periods. We hypothesized that sleep quality (SQ) and emotional reactivity (ER) defined clusters of patients with no or abnormal SQ and ER and we studied the association with functioning. METHOD: We performed a bi-dimensional cluster analysis using SQ and ER measures in a sample of 533 outpatients patients with BD (in remission or with subsyndromal mood symptoms). Clusters were compared for mood symptoms, sleep profile and functioning. RESULTS: We identified three clusters of patients: C1 (normal ER and SQ, 54%), C2 (hypo-ER and low SQ, 22%) and C3 (hyper-ER and low SQ, 24%). C1 was characterized by minimal mood symptoms, better sleep profile and higher functioning than other clusters. Although highly different for ER, C2 and C3 had similar levels of subsyndromal mood symptoms as assessed using classical mood scales. When exploring sleep domains, C2 showed poor sleep efficiency and a trend for longer sleep latency as compared to C3. Interestingly, alterations in functioning were similar in C2 and C3, with no difference in any of the sub-domains. CONCLUSION: Abnormalities in ER and SQ delineated three clusters of patients with BD and significantly impacted on functioning.

Childhood trauma, dimensions of psychopathology and the clinical expression of bipolar disorders: A pathway analysis.

BACKGROUND: This study aims at testing for paths from childhood abuse to clinical indicators of complexity in bipolar disorder (BD), through dimensions of affective dysregulation, impulsivity and hostility. METHOD: 485 euthymic patients with BD from the FACE-BD cohort were included from 2009 to 2014. We collect clinical indicators of complexity/severity: age and polarity at onset, suicide attempt, rapid cycling and substance misuse. Patients completed questionnaires to assess childhood emotional, sexual and physical abuses, affective lability, affect intensity, impulsivity, motor and attitudinal hostility. RESULTS: The path-analysis demonstrated significant associations between emotional abuse and all the affective/impulsive dimensions (p < 0.001). Sexual abuse was moderately associated with emotion-related dimensions but not with impulsivity nor motor hostility. In turn, affect intensity and attitudinal hostility were associated with high risk for lifetime presence of suicide attempts (p < 0.001), whereas impulsivity was associated with a higher risk of lifetime presence of substance misuse (p < 0.001). No major additional paths were identified when including Emotional and Physical Neglect in the model. CONCLUSIONS: This study provides refinement of the links between early adversity, dimensions of psychopathology and the complexity/severity of BD. Mainly, dimensions of affective dysregulation, impulsivity/hostility partially mediate the links between childhood emotional to suicide attempts and substance misuse in BD.

Electromechanical delay in the tibialis anterior muscle during time-varying ankle dorsiflexion.

We evaluated the electromechanical delay (EMD) for the tibialis anterior (TA) muscle during the performance of time-varying ankle dorsiflexions. Subjects were asked to track a sinusoidal trajectory, for a range of amplitudes and frequencies. Motor unit (MU) action potential trains were identified from surface electromyography (EMG) decomposition and summed to generate the cumulative spike train (CST). CST and the exerted force were cross-correlated to identify the delay between the CST and force, which was considered as an estimate of the EMD. The results showed that the EMD decreased logarithmically with the increase in the slope of the force produced.

Effect on the classification of motor imagery in EEG after applying anodal tDCS with a 4×1 ring montage over the motor cortex.

Transcranial direct stimulation (tDCS) is a technique for modulating brain excitability that has potential to be used in motor neurorehabilitation by enhancing motor activity, such as motor imagery (MI). tDCS effects depend on different factors, like current density and the position of the stimulating electrodes. This study presents preliminary results of the evaluation of the effect of current density on MI performance by measuring right-hand/feet MI accuracy of classification from electroencephalographic (EEG) measurements after anodal tDCS is applied with a 4×1 ring montage over the right-hand or feet motor cortex. Results suggest that there might be an enhancement of feet MI when tDCS is applied over the right-hand motor cortex, but further evaluation is required. If results are confirmed with a larger sample, the montage could be used to optimize feet MI performance and improve the outcome of MI-based brain-computer interfaces, which are used during motor neurorehabilitation.

Aggressiveness in depression: a neglected symptom possibly associated with bipolarity and mixed features.

OBJECTIVE: To evaluate aggressiveness during a major depressive episode (MDE) and its relationship with bipolar disorder (BD) in a post hoc analysis of the BRIDGE-II-MIX study. METHOD: A total of 2811 individuals were enrolled in this multicenter cross-sectional study. MDE patients with (MDE-A, n = 399) and without aggressiveness (MDE-N, n = 2412) were compared through chi-square test or Student's t-test. A stepwise backward logistic regression model was performed. RESULTS: MDE-A group was more frequently associated with BD (P < 0.001), while aggressiveness was negatively correlated with unipolar depression (P < 0.001). At the logistic regression, aggressiveness was associated with the age at first depressive episode (P < 0.001); the severity of mania (P = 0.03); the diagnosis of BD (P = 0.001); comorbid borderline personality disorder (BPD) (P < 0.001) but not substance abuse (P = 0.63); no current psychiatric treatment (P < 0.001); psychotic symptoms (P = 0.007); the marked social/occupational impairment (P = 0.002). The variable most significantly associated with aggressiveness was the presence of DSM-5 mixed features (P < 0.001, OR = 3.815). After the exclusion of BPD, the variable of lifetime suicide attempts became significant (P = 0.013, OR = 1.405). CONCLUSION: Aggressiveness seems to be significantly associated with bipolar spectrum disorders, independently from BPD and substance abuse. Aggressiveness should be considered as a diagnostic criterion for the mixed features specifier and a target of tailored treatment strategy.