EEG connectivity in functional brain networks supporting visuomotor integration processes in dominant and non-dominant hand movements.

OBJECTIVE: This study explores the changes in the organization of functional brain networks induced by performing a visuomotor integration task, as revealed by noninvasive spontaneous electroencephalographic traces (EEG). APPROACH: EEG data were acquired during the execution of the Nine Hole Peg Test (NHPT) with the dominant and non-dominant hands in a group of 44 right-handed volunteers. Both spectral analysis and phase-based connectivity analysis were performed in the Theta (ϑ), Mu (µ) and Beta (ß) bands. Graph Theoretical Analysis (GTA) was also performed to investigate the topological reorganization induced by motor task execution. MAIN RESULTS: Spectral analysis revealed an increase of frontoparietal ϑ power and a spatially diffused reduction of µ and ß contribution, regardless of the hand used. GTA showed a significant increase in network integration induced by movement with the dominant limb compared to baseline in the ϑ band. The µ and ß bands were associated with a reduction in network integration during the NHPT. In the µ rhythm, this result was more evident for the right-hand movement, while in the ß band, results did not show dependence on the laterality. Finally, correlation analysis highlighted an association between frequency-specific topology measures and task performance for both hands. SIGNIFICANCE: Our results show that functional brain networks reorganize during visually guided movements in a frequency-dependent manner, differently depending on the hand used (dominant/non dominant).

Assessing cardiovascular stress based on heart rate variability in female shift workers: a multiscale-multifractal analysis approach.

Introduction: Sleep-wake cycle disruption caused by shift work may lead to cardiovascular stress, which is observed as an alteration in the behavior of heart rate variability (HRV). In particular, HRV exhibits complex patterns over different time scales that help to understand the regulatory mechanisms of the autonomic nervous system, and changes in the fractality of HRV may be associated with pathological conditions, including cardiovascular disease, diabetes, or even psychological stress. The main purpose of this study is to evaluate the multifractal-multiscale structure of HRV during sleep in healthy shift and non-shift workers to identify conditions of cardiovascular stress that may be associated with shift work. Methods: The whole-sleep HRV signal was analyzed from female participants: eleven healthy shift workers and seven non-shift workers. The HRV signal was decomposed into intrinsic mode functions (IMFs) using the empirical mode decomposition method, and then the IMFs were analyzed using the multiscale-multifractal detrended fluctuation analysis (MMF-DFA) method. The MMF-DFA was applied to estimate the self-similarity coefficients, α(q, τ), considering moment orders (q) between -5 and +5 and scales (τ) between 8 and 2,048 s. Additionally, to describe the multifractality at each τ in a simple way, a multifractal index, MFI(τ), was computed. Results: Compared to non-shift workers, shift workers presented an increase in the scaling exponent, α(q, τ), at short scales (τ < 64 s) with q < 0 in the high-frequency component (IMF1, 0.15-0.4 Hz) and low-frequency components (IMF2-IMF3, 0.04-0.15 Hz), and with q> 0 in the very low frequencies (IMF4, < 0.04 Hz). In addition, at large scales (τ> 1,024 s), a decrease in α(q, τ) was observed in IMF3, suggesting an alteration in the multifractal dynamic. MFI(τ) showed an increase at small scales and a decrease at large scales in IMFs of shift workers. Conclusion: This study helps to recognize the multifractality of HRV during sleep, beyond simply looking at indices based on means and variances. This analysis helps to identify that shift workers show alterations in fractal properties, mainly on short scales. These findings suggest a disturbance in the autonomic nervous system induced by the cardiovascular stress of shift work.

Early sleep after action observation plus motor imagery improves gait and balance abilities in older adults.

Action observation plus motor imagery (AOMI) is a rehabilitative approach to improve gait and balance performance. However, limited benefits have been reported in older adults. Early sleep after motor practice represents a strategy to enhance the consolidation of trained skills. Here, we investigated the effects of AOMI followed by early sleep on gait and balance performance in older adults. Forty-five older adults (mean age: 70.4 ± 5.2 years) were randomized into three groups performing a 3-week training. Specifically, AOMI-sleep and AOMI-control groups underwent observation and motor imagery of gait and balance tasks between 8:00 and 10:00 p.m. or between 8:00 and 10:00 a.m. respectively, whereas Control group observed landscape video-clips. Participants were assessed for gait performance, static and dynamic balance and fear of falling before and after training and at 1-month follow-up. The results revealed that early sleep after AOMI training sessions improved gait and balance abilities in older adults compared to AOMI-control and Control groups. Furthermore, these benefits were retained at 1-month after the training end. These findings suggested that early sleep after AOMI may represent a safe and easy-applicable intervention to minimize the functional decay in older adults.

Entropy and fractal analysis of brain-related neurophysiological signals in Alzheimer's and Parkinson's disease.

Brain-related neuronal recordings, such as local field potential, electroencephalogram and magnetoencephalogram, offer the opportunity to study the complexity of the human brain at different spatial and temporal scales. The complex properties of neuronal signals are intrinsically related to the concept of 'scale-free' behavior and irregular dynamic, which cannot be fully described through standard linear methods, but can be measured by nonlinear indexes. A remarkable application of these analysis methods on electrophysiological recordings is the deep comprehension of the pathophysiology of neurodegenerative diseases, that has been shown to be associated to changes in brain activity complexity. In particular, a decrease of global complexity has been associated to Alzheimer's disease, while a local increase of brain signals complexity characterizes Parkinson's disease. Despite the recent proliferation of studies using fractal and entropy-based analysis, the application of these techniques is still far from clinical practice, due to the lack of an agreement about their correct estimation and a conclusive and shared interpretation. Along with the aim of helping towards the realization of a multidisciplinary audience to approach nonlinear methods based on the concepts of fractality and irregularity, this survey describes the implementation and proper employment of the mostly known and applied indexes in the context of Alzheimer's and Parkinson's diseases.

Modeling Electric Fields in Transcutaneous Spinal Direct Current Stimulation: A Clinical Perspective.

Clinical findings suggest that transcutaneous spinal direct current stimulation (tsDCS) can modulate ascending sensitive, descending corticospinal, and segmental pathways in the spinal cord (SC). However, several aspects of the stimulation have not been completely understood, and realistic computational models based on MRI are the gold standard to predict the interaction between tsDCS-induced electric fields and anatomy. Here, we review the electric fields distribution in the SC during tsDCS as predicted by MRI-based realistic models, compare such knowledge with clinical findings, and define the role of computational knowledge in optimizing tsDCS protocols. tsDCS-induced electric fields are predicted to be safe and induce both transient and neuroplastic changes. This could support the possibility to explore new clinical applications, such as spinal cord injury. For the most applied protocol (2-3 mA for 20-30 min, active electrode over T10-T12 and the reference on the right shoulder), similar electric field intensities are generated in both ventral and dorsal horns of the SC at the same height. This was confirmed by human studies, in which both motor and sensitive effects were found. Lastly, electric fields are strongly dependent on anatomy and electrodes' placement. Regardless of the montage, inter-individual hotspots of higher values of electric fields were predicted, which could change when the subjects move from a position to another (e.g., from the supine to the lateral position). These characteristics underlines the need for individualized and patient-tailored MRI-based computational models to optimize the stimulation protocol. A detailed modeling approach of the electric field distribution might contribute to optimizing stimulation protocols, tailoring electrodes' configuration, intensities, and duration to the clinical outcome.

Environmental effects on brain functional networks in a juvenile twin population.

The brain's intrinsic organization into large-scale functional networks, the resting state networks (RSN), shows complex inter-individual variability, consolidated during development. Nevertheless, the role of gene and environment on developmental brain functional connectivity (FC) remains largely unknown. Twin design represents an optimal platform to shed light on these effects acting on RSN characteristics. In this study, we applied statistical twin methods to resting-state functional magnetic resonance imaging (rs-fMRI) scans from 50 young twin pairs (aged 10-30 years) to preliminarily explore developmental determinants of brain FC. Multi-scale FC features were extracted and tested for applicability of classical ACE and ADE twin designs. Epistatic genetic effects were also assessed. In our sample, genetic and environmental effects on the brain functional connections largely varied between brain regions and FC features, showing good consistency at multiple spatial scales. Although we found selective contributions of common environment on temporo-occipital connections and of genetics on frontotemporal connections, the unique environment showed a predominant effect on FC link- and node-level features. Despite the lack of accurate genetic modeling, our preliminary results showed complex relationships between genes, environment, and functional brain connections during development. A predominant role of the unique environment on multi-scale RSN characteristics was suggested, which needs replications on independent samples. Future investigations should especially focus on nonadditive genetic effects, which remain largely unexplored.

Early sleep after action observation and motor imagery training boosts improvements in manual dexterity.

The systematic observation and imagination of actions promotes acquisition of motor skills. Furthermore, studies demonstrated that early sleep after practice enhances motor learning through an offline stabilization process. Here, we investigated behavioral effects and neurodynamical correlates of early sleep after action observation and motor imagery training (AO + MI-training) on motor learning in terms of manual dexterity. Forty-five healthy participants were randomized into three groups receiving a 3 week intervention consisting of AO + MI-training immediately before sleeping or AO + MI-training at least 12 h before sleeping or a control stimulation. AO + MI-training implied the observation and motor imagery of transitive manual dexterity tasks, whereas the control stimulation consisted of landscape video-clips observation. Manual dexterity was assessed using functional tests, kinematic and neurophysiological outcomes before and after the training and at 1-month follow-up. AO + MI-training improved manual dexterity, but subjects performing AO + MI-training followed by early sleep had significantly larger improvements than those undergoing the same training at least 12 h before sleeping. Behavioral findings were supported by neurodynamical correlates during motor performance and additional sleep-dependent benefits were also detected at 1 month follow-up. These findings introduce a new approach to enhance the acquisition of new motor skills or facilitate recovery in patients with motor impairments.

Magnetic susceptibility as a 1-year predictor of outcome in familial cerebral cavernous malformations: a pilot study.

OBJECTIVES: To test whether quantitative susceptibility mapping (QSM) of cerebral cavernous malformations (CCMs) assessed at baseline may predict the presence or absence of haemorrhagic signs at 1-year follow-up. METHODS: Familial CCM patients were enrolled in the longitudinal multicentre study Treat-CCM. The 3-T MRI scan allowed performing a semi-automatic segmentation of CCMs and computing the maximum susceptibility in each segmented CCM (QSMmax) at baseline. CCMs were classified as haemorrhagic and non-haemorrhagic at baseline and then subclassified according to the 1-year (t1) evolution. Between-group differences were tested, and the diagnostic accuracy of QSMmax in predicting the presence or absence of haemorrhagic signs in CCMs was calculated with ROC analyses. RESULTS: Thirty-three patients were included in the analysis, and a total of 1126 CCMs were segmented. QSMmax was higher in haemorrhagic CCMs than in non-haemorrhagic CCMs (p < 0.001). In haemorrhagic CCMs at baseline, the accuracy of QSMmax in differentiating CCMs that were still haemorrhagic from CCMs that recovered from haemorrhage at t1 calculated as area under the curve (AUC) was 0.78 with sensitivity 62.69%, specificity 82.35%, positive predictive value (PPV) 93.3% and negative predictive value (NPV) 35.9% (QSMmax cut-off ≥ 1462.95 ppb). In non-haemorrhagic CCMs at baseline, AUC was 0.91 in differentiating CCMs that bled at t1 from stable CCMs with sensitivity 100%, specificity 81.9%, PPV 5.1%, and NPV 100% (QSMmax cut-off ≥ 776.29 ppb). CONCLUSIONS: The QSMmax in CCMs at baseline showed high accuracy in predicting the presence or absence of haemorrhagic signs at 1-year follow-up. Further effort is required to test the role of QSM in follow-up assessment and therapeutic trials in multicentre CCM studies. KEY POINTS: • QSM in semi-automatically segmented CCM was feasible. • The maximum magnetic susceptibility in a single CCM at baseline may predict the presence or absence of haemorrhagic signs at 1-year follow-up. • Multicentric studies are needed to enforce the role of QSM in predicting the CCMs' haemorrhagic evolution in patients affected by familial and sporadic forms.

Quantitative susceptibility mapping of the normal-appearing white matter as a potential new marker of disability progression in multiple sclerosis.

OBJECTIVES: To investigate the normal-appearing white matter (NAWM) susceptibility in a cohort of newly diagnosed multiple sclerosis (MS) patients and to evaluate possible correlations between NAWM susceptibility and disability progression. METHODS: Fifty-nine patients with a diagnosis of MS (n = 53) or clinically isolated syndrome (CIS) (n = 6) were recruited and followed up. All participants underwent neurological examination, blood sampling for serum neurofilament light chain (sNfL) level assessment, lumbar puncture for the quantification of cerebrospinal fluid (CSF) ß-amyloid1-42 (Aß) levels, and brain MRI. T2-weighted scans were used to quantify white matter (WM) lesion loads. For each scan, we derived the NAWM volume fraction and the WM lesion volume fraction. Quantitative susceptibility mapping (QSM) of the NAWM was calculated using the susceptibility tensor imaging (STI) suite. Susceptibility maps were computed with the STAR algorithm. RESULTS: Primary progressive patients (n = 9) showed a higher mean susceptibility value in the NAWM than relapsing-remitting (n = 44) and CIS (n = 6) (p = 0.01 and p = 0.02). Patients with a higher susceptibility in the NAWM showed increased sNfL concentration (ρ = 0.38, p = 0.004) and lower CSF Aß levels (ρ = -0.34, p = 0.009). Mean NAWM susceptibility turned out to be a predictor of the expanded disability status scale (EDSS) worsening at follow-up (ß = 0.41, t = 2.66, p = 0.01) and of the MS severity scale (MSSS) (ß = 0.38, t = 2.43, p = 0.019). CONCLUSIONS: QSM in the NAWM seems to predict the EDSS increment over time. This finding might provide evidence on the role of QSM in identifying patients with an increased risk of early disability progression. KEY POINTS: • NAWM-QSM is higher in PPMS patients than in RRMS. • NAWM-QSM seems to be a predictor of EDSS worsening over time. • Patients with higher NAWM-QSM show increased sNfL concentration and lower CSF Aß levels.

Kinematic evaluation and reliability assessment of the Nine Hole Peg Test for manual dexterity.

BACKGROUND: The Nine Hole Peg Test (NHPT) is one of the most frequently used tools to assess manual dexterity. However, no kinematic parameters are provided to describe the quality of the motor performance, since time is the only score. PURPOSE: To investigate test-retest and intra-rater reliability, correlation with clinical test score, and discriminant validity of kinematic indexes during NHPT. STUDY DESIGN: A clinical measurement study. METHODS: Twenty-five healthy right-handed volunteers performed the NHPT. An experienced physiotherapist administered two sessions at a 6-hour interval with two trials for dominant and non-dominant upper limbs. An optoelectronic system was used to detect NHPT performance, which was divided into nine consecutive peg-grasp, peg-transfer, peg-in-hole, hand-return phases, and one final removing phase. Outcome measures were total and single phases times, normalized jerk, mean, peak and time-to-peak of velocity, curvature index during peg-grasp and hand-return phases, and trunk 3D displacement. The statistical analysis included Intraclass Correlation Coefficients (ICCs) for test-retest and intra-rater reliability, Pearson's coefficients for correlation with the NHPT score, and paired t-tests for discriminant validity. RESULTS: Test-retest reliability was excellent for trunk rotation (ICC: 0.91) and good to moderate for the other indexes (ICCs: 0.89-0.61). Intra-rater reliability was excellent for total and removing times (ICCs: 0.91 and 0.94) and good to moderate for the other indexes (ICCs: 0.84-0.66), except for trunk inclination (ICC: 0.37). NHPT phases, normalized jerk, mean velocity, peak of velocity, time-to-peak and curvature index correlated with total time (r-score: 0.8-0.3). NHPT phases and most kinematic indexes discriminated the dominant from non-dominant upper limb, with the greatest effect size for normalized jerk during hand-return (d = 1.16). CONCLUSIONS: Kinematic indexes during NHPT can be considered for manual dexterity assessment. These indexes may allow for the detection of kinematic changes responsible for NHPT score variations in healthy subjects or patients with upper limb impairments.

Electric Fields Induced in the Brain by Transcranial Electric Stimulation: A Review of In Vivo Recordings.

Transcranial electrical stimulation (tES) techniques, such as direct current stimulation (tDCS) and transcranial alternating current stimulation (tACS), cause neurophysiological and behavioral modifications as responses to the electric field are induced in the brain. Estimations of such electric fields are based mainly on computational studies, and in vivo measurements have been used to expand the current knowledge. Here, we review the current tDCS- and tACS-induced electric fields estimations as they are recorded in humans and non-human primates using intracerebral electrodes. Direct currents and alternating currents were applied with heterogeneous protocols, and the recording procedures were characterized by a tentative methodology. However, for the clinical stimulation protocols, an injected current seems to reach the brain, even at deep structures. The stimulation parameters (e.g., intensity, frequency and phase), the electrodes' positions and personal anatomy determine whether the intensities might be high enough to affect both neuronal and non-neuronal cell activity, also deep brain structures.

Multi-Scale Evaluation of Sleep Quality Based on Motion Signal from Unobtrusive Device.

Sleep disorders are a growing threat nowadays as they are linked to neurological, cardiovascular and metabolic diseases. The gold standard methodology for sleep study is polysomnography (PSG), an intrusive and onerous technique that can disrupt normal routines. In this perspective, m-Health technologies offer an unobtrusive and rapid solution for home monitoring. We developed a multi-scale method based on motion signal extracted from an unobtrusive device to evaluate sleep behavior. Data used in this study were collected during two different acquisition campaigns by using a Pressure Bed Sensor (PBS). The first one was carried out with 22 subjects for sleep problems, and the second one comprises 11 healthy shift workers. All underwent full PSG and PBS recordings. The algorithm consists of extracting sleep quality and fragmentation indexes correlating to clinical metrics. In particular, the method classifies sleep windows of 1-s of the motion signal into: displacement (DI), quiet sleep (QS), disrupted sleep (DS) and absence from the bed (ABS). QS proved to be positively correlated (0.72±0.014) to Sleep Efficiency (SE) and DS/DI positively correlated (0.85±0.007) to the Apnea-Hypopnea Index (AHI). The work proved to be potentially helpful in the early investigation of sleep in the home environment. The minimized intrusiveness of the device together with a low complexity and good performance might provide valuable indications for the home monitoring of sleep disorders and for subjects' awareness.

Automatic Identification of Failure in Hip Replacement: An Artificial Intelligence Approach.

Background: Total hip arthroplasty (THA) follow-up is conventionally conducted with serial X-ray imaging in order to ensure the early identification of implant failure. The purpose of this study is to develop an automated radiographic failure detection system. Methods: 630 patients with THA were included in the study, two thirds of which needed total or partial revision for prosthetic loosening. The analysis is based on one antero-posterior and one lateral radiographic view obtained from each patient during routine post-surgery follow-up. After pre-processing for proper standardization, images were analyzed through a convolutional neural network (the DenseNet169 network), aiming to predict prosthesis failure. The entire dataset was divided in three subsets: training, validation, and test. These contained transfer learning and fine-tuning algorithms, based on the training dataset, and were implemented to adapt the DenseNet169 network to the specific data and clinical problem. Results: After the training procedures, in the test set, the classification accuracy was 0.97, the sensitivity 0.97, the specificity 0.97, and the ROC AUC was 0.99. Only five images were incorrectly classified. Seventy-four images were classified as failed, and eighty as non-failed with a probability >0.999. Conclusion: The proposed deep learning procedure can detect the loosening of the hip prosthesis with a very high degree of precision.

Respiratory Sinus Arrhythmia (RSA) stress response in preschool age varies by serotonin transporter polymorphism (5-HTTLPR): A preliminary report.

The serotonin transporter promoter region polymorphism (5-HTTLPR) has been implicated in stress regulation, with increased stress reactivity often being found in carriers of the low-expressing short (S) allele. Nevertheless, the role of the 5-HTTLPR in influencing parasympathetic stress reactivity, as indexed by Respiratory Sinus Arrhythmia (RSA), is still unknown. This study examined, for the first time, whether the 5-HTTLPR was associated with variations in RSA response to maternal separation in a sample of 69 healthy 5-year-old children. Preschoolers' RSA was measured during an age-adapted version of the Strange Situation Procedure (SSP). The 5-HTTLPR polymorphism was tested as a predictor of RSA dynamic response to the SSP through multilevel models. A significant interaction between 5-HTTLPR and SSP episodes was found. In particular, whereas a significant decrease in RSA levels was observed during the stranger episode in the whole sample, S allele carriers showed a significant decrease in RSA levels from the stranger episode to the first separation episode, followed by an increase for the rest of the procedure. Albeit preliminary, data support the view that the 5-HTTLPR may contribute to individual differences in RSA stress reactivity from preschool age.

Information Retrieval from Photoplethysmographic Sensors: A Comprehensive Comparison of Practical Interpolation and Breath-Extraction Techniques at Different Sampling Rates.

The increasingly widespread diffusion of wearable devices makes possible the continuous monitoring of vital signs, such as heart rate (HR), heart rate variability (HRV), and breath signal. However, these devices usually do not record the "gold-standard" signals, namely the electrocardiography (ECG) and respiratory activity, but a single photoplethysmographic (PPG) signal, which can be exploited to estimate HR and respiratory activity. In addition, these devices employ low sampling rates to limit power consumption. Hence, proper methods should be adopted to compensate for the resulting increased discretization error, while diverse breath-extraction algorithms may be differently sensitive to PPG sampling rate. Here, we assessed the efficacy of parabola interpolation, cubic-spline, and linear regression methods to improve the accuracy of the inter-beat intervals (IBIs) extracted from PPG sampled at decreasing rates from 64 to 8 Hz. PPG-derived IBIs and HRV indices were compared with those extracted from a standard ECG. In addition, breath signals extracted from PPG using three different techniques were compared with the gold-standard signal from a thoracic belt. Signals were recorded from eight healthy volunteers during an experimental protocol comprising sitting and standing postures and a controlled respiration task. Parabola and cubic-spline interpolation significantly increased IBIs accuracy at 32, 16, and 8 Hz sampling rates. Concerning breath signal extraction, the method holding higher accuracy was based on PPG bandpass filtering. Our results support the efficacy of parabola and spline interpolations to improve the accuracy of the IBIs obtained from low-sampling rate PPG signals, and also indicate a robust method for breath signal extraction.

Association of Superficial White Matter Alterations with Cerebrospinal Fluid Biomarkers and Cognitive Decline in Neurodegenerative Dementia.

BACKGROUND: Superficial white matter (SWM) alterations correlated with cognitive decline have been described in Alzheimer's disease (AD). OBJECTIVE: The study aims to extend the investigation of the SWM alterations to AD and non-AD neurodegenerative dementia (ND) and explore the relationship with cerebrospinal fluid (CSF) biomarkers and clinical data. METHODS: From a database of 323 suspected dementia cases, we retrospectively recruited 55 ND with abnormal amyloid-ß42 (AD) and 38 ND with normal amyloid-ß42 (non-AD) and collected clinical data, CSF biomarkers, and magnetic resonance images. Ten healthy controls (HC) were recruited for imaging and Mini-Mental State Examination (MMSE). Diffusion tensor imaging (DTI) measurements were performed in the lobar SWM regions and Kruskal Wallis tests were used for among-group comparison. Spearman's correlation tests were performed between DTI measures, CSF biomarkers, and clinical data. RESULTS: AD and non-AD showed significant differences in the DTI measures across the SWM compared to HC. Significant differences between AD and non-AD were detected in the left parietal lobe. DTI measures correlated with amyloid-ß42 and MMSE diffusely in the SWM, less extensively with total-tau and phosphorylated tau, and with disease duration in the parietal lobe bilaterally. CONCLUSION: Widespread SWM alterations occur in both AD and non-AD ND and AD shows appreciably more severe alterations in the parietal SWM. Notably, the alterations in the SWM are strongly linked not only to the cognitive decline but also to the diagnostic CSF biomarkers. Further studies are encouraged to evaluate the DTI measures in the SWM as in vivo non-invasive biomarkers in the preclinical phase.

Assessing stress variations in children during the strange situation procedure: comparison of three widely used respiratory sinus arrhythmia estimation methods.

Objective.The respiratory sinus arrhythmia (RSA) is a well-known marker of vagal activity that can be exploited to measure stress changes. RSA is usually estimated from heart rate variability (HRV). This study aims to compare the RSA obtained with three widely adopted methods showing their strengths and potential pitfalls.Approach.The three methods are tested on 69 healthy preschoolers undergoing a stressful protocol, the strange situation procedure (SSP). We compare the RSA estimated by the Porges method, the univariate autoregressive (AR) spectral analysis of the HRV signal, and the bivariate AR spectral analysis of HRV and respirogram signals. We examine RSA differences detected across the SSP episodes and correlation between the estimates provided by each method.Main results.The Porges and the bivariate AR approaches both detected significant differences (i.e. stress variations) in the RSA measured across the SSP. However, the latter method showed higher sensitivity to stress changes induced by the procedure, with the mean RSA variation between baseline and first separation from the mother (the most stressful condition) being significantly different among methods: Porges, -17.5%; univariate AR, -18.3%; bivariate AR, -23.7%. Moreover, the performances of the Porges algorithm were found strictly dependent on the applied preprocessing.Significance.Our findings confirm the bivariate AR analysis of the HRV and respiratory signals as a robust stress assessment tool that does not require any population-specific preprocessing of the signals and warn about using RSA estimates that neglect breath information in more natural experiments, such as those involving children, in which respiratory frequency changes are extremely likely.

Effective Connectivity During Rest and Music Listening: An EEG Study on Parkinson's Disease.

Music-based interventions seem to enhance motor, sensory and cognitive functions in Parkinson's disease (PD), but the underlying action mechanisms are still largely unknown. This electroencephalography (EEG) study aimed to investigate the effective connectivity patterns characterizing PD in the resting state and during music listening. EEG recordings were obtained from fourteen non-demented PD patients and 12 healthy controls, at rest and while listening to three music tracks. Theta- and alpha-band power spectral density and multivariate partial directed coherence were computed. Power and connectivity measures were compared between patients and controls in the four conditions and in music vs. rest. Compared to controls, patients showed enhanced theta-band power and slightly enhanced alpha-band power, but markedly reduced theta- and alpha-band interactions among EEG channels, especially concerning the information received by the right central channel. EEG power differences were partially reduced by music listening, which induced power increases in controls but not in patients. Connectivity differences were slightly compensated by music, whose effects largely depended on the track. In PD, music enhanced the frontotemporal inter-hemispheric communication. Our findings suggest that PD is characterized by enhanced activity but reduced information flow within the EEG network, being only partially normalized by music. Nevertheless, music capability to facilitate inter-hemispheric communication might underlie its beneficial effects on PD pathophysiology and should be further investigated.

Increase in endogenous glucose production with SGLT2 inhibition is attenuated in individuals who underwent kidney transplantation and bilateral native nephrectomy.

AIMS/HYPOTHESIS: The glucosuria induced by sodium-glucose cotransporter 2 (SGLT2) inhibition stimulates endogenous (hepatic) glucose production (EGP), blunting the decline in HbA1c. We hypothesised that, in response to glucosuria, a renal signal is generated and stimulates EGP. To examine the effect of acute administration of SGLT2 inhibitors on EGP, we studied non-diabetic individuals who had undergone renal transplant with and without removal of native kidneys. METHODS: This was a parallel, randomised, double-blind, placebo-controlled, single-centre study, designed to evaluate the effect of a single dose of dapagliflozin or placebo on EGP determined by stable-tracer technique. We recruited non-diabetic individuals who were 30-65 years old, with a BMI of 25-35 kg/m2 and stable body weight (±2 kg) over the preceding 3 months, and HbA1c <42 mmol/mol (6.0%). Participants had undergone renal transplant with and without removal of native kidneys and were on a stable dose of immunosuppressive medications. Participants received a single dose of dapagliflozin 10 mg or placebo on two separate days, at a 5- to 14-day interval, according to randomisation performed by our hospital pharmacy, which provided dapagliflozin and matching placebo, packaged in bulk bottles that were sequentially numbered. Both participants and investigators were blinded to group assignment. RESULTS: Twenty non-diabetic renal transplant patients (ten with residual native kidneys, ten with bilateral nephrectomy) participated in the study. Dapagliflozin induced greater glucosuria in individuals with residual native kidneys vs nephrectomised individuals (8.6 ± 1.1 vs 5.5 ± 0.5 g/6 h; p = 0.02; data not shown). During the 6 h study period, plasma glucose decreased only slightly and similarly in both groups, with no difference compared with placebo (data not shown). Following administration of placebo, there was a progressive time-related decline in EGP that was similar in both nephrectomised individuals and individuals with residual native kidneys. Following dapagliflozin administration, EGP declined in both groups, but the differences between the decrement in EGP with dapagliflozin and placebo in the group with bilateral nephrectomy (Δ = 1.11 ± 0.72 µmol min-1 kg-1) was significantly lower (p = 0.03) than in the residual native kidney group (Δ = 2.56 ± 0.33 µmol min-1 kg-1). In the population treated with dapagliflozin, urinary glucose excretion was correlated with EGP (r = 0.34, p < 0.05). Plasma insulin, C-peptide, glucagon, prehepatic insulin:glucagon ratio, lactate, alanine and pyruvate concentrations were similar following placebo and dapagliflozin treatment. ß-Hydroxybutyrate increased with dapagliflozin treatment in the residual native kidney group, while a small increase was observed only at 360 min in the nephrectomy group. Plasma adrenaline (epinephrine) did not change after dapagliflozin and placebo treatment in either group. Following dapagliflozin administration, plasma noradrenaline (norepinephrine) increased slightly in the residual native kidney group and decreased in the nephrectomy group. CONCLUSIONS/INTERPRETATION: In nephrectomised individuals, the hepatic compensatory response to acute SGLT2 inhibitor-induced glucosuria was attenuated, as compared with individuals with residual native kidneys, suggesting that SGLT2 inhibitor-mediated stimulation of hepatic glucose production via efferent renal nerves occurs in an attempt to compensate for the urinary glucose loss (i.e. a renal-hepatic axis). TRIAL REGISTRATION: ClinicalTrials.gov NCT03168295 FUNDING: This protocol was supported by Qatar National Research Fund (QNRF) Award No. NPRP 8-311-3-062 and NIH grant DK024092-38. Graphical abstract.

Bicoherence Interpretation in EEG Requires Signal to Noise Ratio Quantification: An Application to Sensorimotor Rhythms.

OBJECTIVE: In the electroencephalogram (EEG) the quadratic phase coupling (QPC) phenomenon indicates the presence of non-linear interactions among brain rhythms that could affect the interpretation of their physiological meaning. We propose the use of the bicoherence as a QPC quantification method to understand the nature of brain rhythm interplay. METHODS: We firstly provide a simulation study to show under which condition of signal to noise ratio (SNR) the bicoherence is a reliable QPC quantifier and how to interpret the results. Secondly, in the light of the simulation results, we applied the bicoherence analysis to real EEG data acquired on thirteen volunteers during a cue-paced reaching motor task to quantify coupling and decoupling between mu and beta rhythms. An inter-trial averaging procedure was adopted in order to allow the correct calculation of the bicoherence during a motor task. RESULTS: Simulations demonstrated that SNR has a strong impact on the correct quantification of bicoherence and that a reliable detection of QPC is possible when the SNR is favorable (>-5 dB). Results from EEG data demonstrated a QPC between mu and beta rhythms during the resting state and its fading during movement planning and execution, providing valuable information for the interpretation of their dynamics. CONCLUSION: The bicoherence was proven to be an effective tool for the investigation of coupling between the sensorimotor rhythms during all the phases of a motor task. This was assessed in relation to the physiological changing of the SNR characterizing the frequency components of interest.