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Background Deception is present in all walks of life, from social interactions to matters of homeland security. Nevertheless, reliable indicators of deceptive behavior in real‐life scenarios remain elusive. Methods By integrating electrophysiological and communicative approaches, we demonstrate a new and objective detection approach to identify participant‐specific indicators of deceptive behavior in an interactive scenario of a two‐person deception task. We recorded participants' facial muscle activity using novel dry screen‐printed electrode arrays and applied machine‐learning algorithms to identify lies based on brief facial responses. Results With an average accuracy of 73%, we identified two groups of participants: Those who revealed their lies by activating their cheek muscles and those who activated their eyebrows. We found that the participants lied more often with time, with some switching their telltale muscle groups. Moreover, while the automated classifier, reported here, outperformed untrained human detectors, their performance was correlated, suggesting reliance on shared features. Conclusions Our findings demonstrate the feasibility of using wearable electrode arrays in detecting human lies in a social setting and set the stage for future research on individual differences in deception expression., What classifies lying from truth‐telling behavior? The current study adopts a physiological‐social approach, combining state‐of‐the‐art techniques from electrical and neuro‐engineering (nanotechnology‐based skin printed electrodes for measuring electromyography), computer science (machine‐learning algorithms), and cognitive psychology (deception task) to automatically and objectively characterize different deceptive behaviors based on “giveaway” signs of facial expressions.

Purpose To provide a biophysical basis to estimate the effect of cytoplasmic flow in neurons, and assess their contribution to the drop in the Apparent Diffusion Coefficient (ADC) in a nerve tissue following extreme conditions, such as brain injury and epileptic seizures. Methods Three mechanisms are treated using the relevant physics of hydrodynamics and electrostatics: cargo induced streaming, electroosmosis, and membrane swelling. Results We begin by discussing the lack of experimental evidence on the necessary velocities required to influence the Magnetic Resonance (MR) experiments. This is followed by demonstrating that cargo induced streaming, a widely known phenomenon in plant cells, has a minor effect on the ADC in neurons. Subsequently, we suggest and analyze two additional mechanisms that may induce fluid displacement in neurons, and are related to the electrical activity: electroosmosis and membrane swelling. Conclusion Although these mechanisms may induce interesting fluid displacements, these cannot explain the significant drop in the ADC. We conclude by outlining the criteria that any future mechanism should meet to have an influence on standard diffusion-MR measurements. Magn Reson Med, 2016. © 2016 International Society for Magnetic Resonance in Medicine

Objective Human facial muscle activation underlies highly sophisticated signaling mechanisms that are critically important for healthy physiological function. Accordingly, the necessity to analyze facial muscle activation at high-resolution and in a non-invasive manner is important for the diagnosis and treatment of many medical conditions. However, current clinical examination methods are neither precise nor quantitative. Approach Wearable, multi-channel surface electromyography can provide a solution to this yet unmet challenge. Here, we present the design and testing of a customized surface electromyography electrode array for facial muscle mapping. Main results Muscle activation maps were derived from repeated voluntary facial muscle activations. A customized independent component analysis algorithm and a clustering algorithm were developed to identify consistent building block activation patterns within and between participants. Finally, focusing on spontaneous smile analysis and relying on the building block mapping, we classified muscle activation sources, revealing a consistent intra-subject activation and an inter-subject variability. Significance The herein described approach can be readily used for automated and objective mapping of facial expressions in general and in the assessment of normal and abnormal smiling in particular.

Human facial expressions are a complex capacity, carrying important psychological and neurological information. Facial expressions typically involve the co-activation of several muscles; they vary between individuals, between voluntary versus spontaneous expressions, and depend strongly on personal interpretation. Accordingly, while high-resolution recording of muscle activation in a non-laboratory setting offers exciting opportunities, it remains a major challenge. This paper describes a wearable and non-invasive method for objective mapping of facial muscle activation and demonstrates its application in a natural setting. We focus on muscle activation associated with “enjoyment”, “social” and “masked” smiles; three categories with distinct social meanings. We use an innovative, dry, soft electrode array designed specifically for facial surface electromyography recording, a customized independent component analysis algorithm, and a short training procedure to achieve the desired mapping. First, identification of the orbicularis oculi and the levator labii superioris was demonstrated from voluntary expressions. Second, the zygomaticus major was identified from voluntary and spontaneous Duchenne and non-Duchenne smiles. Finally, using a wireless device in an unmodified work environment revealed expressions of diverse emotions in face-to-face interaction. Our high-resolution and crosstalk-free mapping, along with excellent user-convenience, opens new opportunities in gaming, virtual-reality, bio-feedback and objective psychological and neurological assessment.

Facial surface electromyography (sEMG) is a powerful tool for objective evaluation of human facial expressions and was accordingly suggested in recent years for a wide range of psychological and neurological assessment applications. Owing to technical challenges, in particular the cumbersome gelled electrodes, the use of facial sEMG was so far limited. Using innovative facial temporary tattoos optimized specifically for facial applications, we demonstrate the use of sEMG as a platform for robust identification of facial muscle activation. In particular, differentiation between diverse facial muscles is demonstrated. We also demonstrate a wireless version of the system. The potential use of the presented technology for user-experience monitoring and objective psychological and neurological evaluations is discussed.

Objective Circadian and sleep dysfunction have long been symptomatic hallmarks of a variety of devastating neurodegenerative conditions. The gold standard for sleep monitoring is overnight sleep in a polysomnography (PSG) laboratory. However, this method has several limitations such as availability, cost and being labour-intensive. In recent years there has been a heightened interest in home-based sleep monitoring via wearable sensors. Our objective was to demonstrate the use of printed electrode technology as a novel platform for sleep monitoring. Approach Printed electrode arrays offer exciting opportunities in the realm of wearable electrophysiology. In particular, soft electrodes can conform neatly to the wearer's skin, allowing user convenience and stable recordings. As such, soft skin-adhesive non-gel-based electrodes offer a unique opportunity to combine electroencephalography (EEG), electromyography (EMG), electrooculography (EOG) and facial EMG capabilities to capture neural and motor functions in comfortable non-laboratory settings. In this investigation temporary-tattoo dry electrode system for sleep staging analysis was designed, implemented and tested. Main results EMG, EOG and EEG were successfully recorded using a wireless system. Stable recordings were achieved both at a hospital environment and a home setting. Sleep monitoring during a 6 h session shows clear differentiation of sleep stages. Significance The new system has great potential in monitoring sleep disorders in the home environment. Specifically, it may allow the identification of disorders associated with neurological disorders such as rapid eye movement (REM) sleep behavior disorder.

Electromyography is a non-invasive method widely used to map muscle activation. For decades, it was commonly accepted that dry metallic electrodes establish poor electrode-skin contact, making them impractical for skin electromyography applications. Gelled electrodes are therefore the standard in electromyography with their use confined, almost entirely, to laboratory settings. Here we present novel dry electrodes, exhibiting outstanding electromyography recording along with excellent user comfort. The electrodes were realized using screen-printing of carbon ink on a soft support. The conformity of the electrodes helps establish direct contact with the skin, making the use of a gel superfluous. Plasma polymerized 3,4-ethylenedioxythiophene was used to enhance the impedance of the electrodes. Cyclic voltammetry measurements revealed an increase in electrode capacitance by a factor of up to 100 in wet conditions. Impedance measurements show a reduction factor of 10 in electrode impedance on human skin. The suitability of the electrodes for long-term electromyography recordings from the hand and from the face is demonstrated. The presented electrodes are ideally-suited for many applications, such as brain-machine interfacing, muscle diagnostics, post-injury rehabilitation, and gaming.

Objective: In view of the fact that cancer patterns in patients with Parkinson disease (PD) differ from the general population, we aimed to verify whether patients with PD with LRRK2 mutations have an increased risk for particular cancer types. Methods: In this cross-sectional study, eligible consenting Jewish patients with PD were genotyped for the predominant LRRK2 G2019S mutation. Oncologic data were obtained by personal interview and reviewing patients9 files. Stepwise logistic regression was applied to model the probability of cancer occurrence in carriers vs noncarriers. Results: Overall, 79/490 (16.1%) genotyped patients carried the G2019S mutation. Seventy-seven (16%) were diagnosed with cancer; of those, 67 (14%) with a non-skin cancer. Eighteen (23%) carriers vs 49 (12%) noncarriers had a non-skin cancer ( p = 0.01, odds ratio [OR] = 2.18, 95% confidence interval [CI] 1.19–3.99). A significant ethnicity effect was noted ( p = 0.045, OR = 1.84, 95% CI 1.02–3.34). Among Ashkenazi patients, age and LRRK2 emerged as significant using stepwise logistic regression including age, gender, and LRRK2 status as explanatory variables. The OR for LRRK2 mutation carriers adjusted for age was 3.38 (95% CI 1.64–6.97, p = 0.0009). Conclusions: Ashkenazi Jewish patients with PD who harbor the G2019S LRRK2 mutation are more likely to have a concomitant non-skin cancer than noncarriers.

Objective: To assess whether Parkinson disease (PD) genes are somatically mutated in cutaneous melanoma (CM) tissue, because CM occurs in patients with PD at higher rates than in the general population and PD is more common than expected in CM cohorts. Methods: We cross-referenced somatic mutations in metastatic CM detected by whole-exome sequencing with the 15 known PD ( PARK ) genes. We computed the empirical distribution of the sum of mutations in each gene (Smut) and of the number of tissue samples in which a given gene was mutated at least once (SSampl) for each of the analyzable genes, determined the 90th and 95th percentiles of the empirical distributions of these sums, and verified the location of PARK genes in these distributions. Identical analyses were applied to adenocarcinoma of lung (ADENOCA-LUNG) and squamous cell carcinoma of lung (SQUAMCA-LUNG). We also analyzed the distribution of the number of mutated PARK genes in CM samples vs the 2 lung cancers. Results: Somatic CM mutation analysis (n = 246) detected 315,914 mutations in 18,758 genes. Somatic CM mutations were found in 14 of 15 PARK genes. Forty-eight percent of CM samples carried ≥1 PARK mutation and 25% carried multiple PARK mutations. PARK8 mutations occurred above the 95th percentile of the empirical distribution for SMut and SSampl. Significantly more CM samples harbored multiple PARK gene mutations compared with SQUAMCA-LUNG ( p = 0.0026) and with ADENOCA-LUNG ( p Conclusions: The overrepresentation of somatic PARK mutations in CM suggests shared dysregulated pathways for CM and PD.