Advances in EEG-based functional connectivity approaches to the study of the central nervous system in health and disease

Functional brain connectivity is closely linked to the complex interactions between brain networks. In the last two decades, measures of functional connectivity based on electroencephalogram (EEG) data have proved to be an important tool for neurologists and clinical and non-clinical neuroscientists. Indeed, EEG-based functional connectivity may reveal the neurophysiological processes and networks underlying human cognition and the pathophysiology of neuropsychiatric disorders. This editorial discusses recent advances and future prospects in the study of EEG-based functional connectivity, with a focus on the main methodological approaches to studying brain networks in health and disease

Is ALT control really necessary for routine ART monitoring in resource poor settings?

2006 AIDS Conference in Toront

Are errors detected before they occur? Early error sensations revealed by metacognitive judgments on the timing of error awareness

Errors in choice tasks are not only detected fast and reliably, participants often report that they knew that an error occurred already before a response was produced. These early error sensations stand in contrast with evidence suggesting that the earliest neural correlates of error awareness emerge around 300 ms after erroneous responses. The present study aimed to investigate whether anecdotal evidence for early error sensations can be corroborated in a controlled study in which participants provide metacognitive judgments on the subjective timing of error awareness. In Experiment 1, participants had to report whether they became aware of their errors before or after the response. In Experiment 2, we measured confidence in these metacognitive judgments. Our data show that participants report early error sensations with high confidence in the majority of error trials across paradigms and experiments. These results provide first evidence for early error sensations, informing theories of error awareness

Resting state alpha oscillatory activity is a valid and reliable marker of schizotypy

Schizophrenia is among the most debilitating neuropsychiatric disorders. However, clear neurophysiological markers that would identify at-risk individuals represent still an unknown. The aim of this study was to investigate possible alterations in the resting alpha oscillatory activity in normal population high on schizotypy trait, a physiological condition known to be severely altered in patients with schizophrenia. Direct comparison of resting-state EEG oscillatory activity between Low and High Schizotypy Group (LSG and HSG) has revealed a clear right hemisphere alteration in alpha activity of the HSG. Specifically, HSG shows a significant slowing down of right hemisphere posterior alpha frequency and an altered distribution of its amplitude, with a tendency towards a reduction in the right hemisphere in comparison to LSG. Furthermore, altered and reduced connectivity in the right fronto-parietal network within the alpha range was found in the HSG. Crucially, a trained pattern classifier based on these indices of alpha activity was able to successfully differentiate HSG from LSG on tested participants further confirming the specific importance of right hemispheric alpha activity and intrahemispheric functional connectivity. By combining alpha activity and connectivity measures with a machine learning predictive model optimized in a nested stratified cross-validation loop, current research offers a promising clinical tool able to identify individuals at-risk of developing psychosis (i.e., high schizotypy individuals)

Internal characterization of embankment dams using ground penetrating radar (GPR) and thermographic analysis: A case study of the Medau Zirimilis Dam (Sardinia, Italy)

The stability of embankment dams without an impermeable core depends on the characteristics of the face slab that prevents internal erosion, piping and eventual collapse of the structure. Under a Mediterranean climate, the impermeable asphaltic face slab is subjected to high solar radiation and consequent temperature changes, which can generate the creation of cracks and joints. The Medau Zirimilis Dam, located in the Casteddu River (Sardinia), is an embankment dam that has undergone seepage and continuous repairs in its asphalt face slab. These reparations have been conducted because of the occurrence of cracks and relative movement of different segments of the slab. To evaluate if seepage endangers the integrity of the dam, GPR was used, with different antennas (100, 250 and 500 MHz), along its crest and upstream and downstream faces, and the data were integrated with infrared thermographic images. Although geophysical data do not show structural changes affecting the main dam structure, deformation structures at shallow levels and in particular in the upstream face and along the crest of the dam have been identified. Such deformation affects the road atop the crest, the face slab and underlying levels, resulting in landslides that include material from several meters below the surface. The analysis permitted the identification of the origin of surficial cracks and their effects on the face slab. These sectors, independent of current movement, define the most unstable areas against water level changes that can affect the dam integrity. GPR analysis at the embankments usually has the handicap of high clay content that precludes electromagnetic wave penetration; however, in this case, the obtained resolution and extent of penetration using the different antennas was sufficient, due to the absence of an inner waterproof unit, and permitted the evaluation of the inner structure of the dam and the application of GPR for construction quality surveillance, internal structural characterization and dam monitoring

Feasibility interventional study investigating PAIN in neurorehabilitation through wearabLE SensorS (PAINLESS): a study protocol

Introduction: Millions of people survive injuries to the central or peripheral nervous system for which neurorehabilitation is required. In addition to the physical and cognitive impairments, many neurorehabilitation patients experience pain, often not widely recognised and inadequately treated. This is particularly true for multiple sclerosis (MS) patients, for whom pain is one of the most common symptoms. In clinical practice, pain assessment is usually conducted based on a subjective estimate. This approach can lead to inaccurate evaluations due to the influence of numerous factors, including emotional or cognitive aspects. To date, no objective and simple to use clinical methods allow objective quantification of pain and the diagnostic differentiation between the two main types of pain (nociceptive vs neuropathic). Wearable technologies and artificial intelligence (AI) have the potential to bridge this gap by continuously monitoring patients' health parameters and extracting meaningful information from them. Therefore, we propose to develop a new automatic AI-powered tool to assess pain and its characteristics during neurorehabilitation treatments using physiological signals collected by wearable sensors. Methods and analysis: We aim to recruit 15 participants suffering from MS undergoing physiotherapy treatment. During the study, participants will wear a wristband for three consecutive days and be monitored before and after their physiotherapy sessions. Measurement of traditionally used pain assessment questionnaires and scales (ie, painDETECT, Doleur Neuropathique 4 Questions, EuroQoL-5-dimension-3-level) and physiological signals (photoplethysmography, electrodermal activity, skin temperature, accelerometer data) will be collected. Relevant parameters from physiological signals will be identified, and AI algorithms will be used to develop automatic classification methods. Ethics and dissemination: The study has been approved by the local Ethical Committee (285-2022-SPER-AUSLBO). Participants are required to provide written informed consent. The results will be disseminated through contributions to international conferences and scientific journals, and they will also be included in a doctoral dissertation. Trial registration number: NCT05747040

BCR-ABL1 doubling-times and halving-times may predict CML response to tyrosine kinase inhibitors

In Chronic Myeloid Leukemia (CML), successful treatment requires accurate molecular monitoring to evaluate disease response and provide timely interventions for patients failing to achieve the desired outcomes. We wanted to determine whether measuring BCR-ABL1 mRNA doubling-times (DTs) could distinguish inconsequential rises in the oncogene’s expression from resistance to tyrosine kinase inhibitors (TKIs). Thus, we retrospectively examined BCR-ABL1 evolution in 305 chronic-phase CML patients receiving imatinib mesylate (IM) as a first line treatment. Patients were subdivided in two groups: those with a confirmed rise in BCR-ABL1 transcripts without MR3.0 loss and those failing IM. We found that the DTs of the former patients were significantly longer than those of patients developing IM resistance (57.80 vs. 41.45 days, p = 0.0114). Interestingly, the DT values of individuals failing second-generation (2G) TKIs after developing IM resistance were considerably shorter than those observed at the time of IM failure (27.20 vs. 41.45 days; p = 0.0035). We next wanted to establish if decreases in BCR-ABL1 transcripts would identify subjects likely to obtain deep molecular responses. We therefore analyzed the BCR-ABL1 halving-times (HTs) of a different cohort comprising 174 individuals receiving IM in first line and observed that, regardless of the time point selected for our analyses (6, 12, or 18 months), HTs were significantly shorter in subjects achieving superior molecular responses (p = 0.002 at 6 months; p < 0.001 at 12 months; p = 0.0099 at 18 months). Moreover, 50 patients receiving 2G TKIs as first line therapy and obtaining an MR3.0 (after 6 months; p = 0.003) or an MR4.0 (after 12 months; p = 0.019) displayed significantly shorter HTs than individuals lacking these molecular responses. Our findings suggest that BCR-ABL1 DTs and HTs are reliable tools to, respectively, identify subjects in MR3.0 that are failing their assigned TKI or to recognize patients likely to achieve deep molecular responses that should be considered for treatment discontinuation