Impact of COVID-19 pandemic in the activity of a Therapeutic Apheresis unit in Italy.

INTRODUCTION: The recent Coronavirus Disease 2019 (COVID-19) outbreak has led to profound and rapid changes in the Italian and Veneto Region Healthcare System. This context also includes the quick reorganization which the Apheresis Unit (AU) of the Padova University Hospital, i.e. the Regional Reference Center for Therapeutic Apheresis (TA), had to face. MATERIAL AND METHODS: The study retrospectively evaluated the TA activity (procedures performed, patients treated and consultations) during the COVID-19 pandemic, from March to April 2020, comparing the activity in the same time period in 2018 and 2019. RESULTS: In the period analyzed, a significant reduction in both the total number of procedures performed and of patients treated, respectively by 17 % and 16 % for the procedures and by 19 % and 20 % for patients treated compared to the same period of 2018 and 2019, respectively, was observed. A concomitant reduction in requests for TA consultation for new patients (both outpatients and inpatients) was observed, equal to 32 % and 21 % compared to 2018 and 2019, respectively. CONCLUSION: Many reasons determined the observed reduction in the TA activity during the recent COVID-19 outbreak. The AU itself was quickly reorganized in terms of location and supplies to allow for the appropriate COVID-19 patients care. Many non urgent cases, after multidisciplinary discussion between Clinicians and Apheresis Specialists, were deferred, maintaining close phone and e-mail contact with patients.

Karyotype-phenotype correlation in partial trisomies of the short arm of chromosome 6: a family case report and review of the literature.

The first child (proband) of nonconsanguineous Caucasian parents underwent genetic investigation because she was affected with congenital choanal atresia, heart defects and kidney hyposplasia with mild transient renal insufficiency. The direct DNA sequencing after PCR of the CHD7 gene, which is thought to be responsible for approximately 60-70% of the cases of CHARGE syndrome/association, found no mutations. The cytogenetic analysis (standard GTG banding karyotype) revealed the presence of extrachromosomal material on 10q. The chromosome analysis was completed with array CGH (30 kb resolution), MLPA and FISH, which allowed the identification of three 6p regions (6p.25.3p23 × 3): 2 of these regions are normally located on chromosome 6, and the third region is translocated to the long arm of chromosome 10. The same chromosomal rearrangement was subsequently found in the father, who was affected with congenital ptosis and progressive hearing loss, and in the proband's sister, the second child, who presented at birth with choanal atresia and congenital heart defects. The mutated karyotypes, which were directly inherited, are thought to be responsible for a variable phenotype, including craniofacial dysmorphisms, choanal atresia, congenital ptosis, sensorineural hearing loss, heart defects, developmental delay, and renal dysfunction. Nevertheless, to achieve a complete audiological assessment of the father, he underwent further investigation that revealed an increased level of the coagulation factor XIII (300% increased activity), fluctuating levels of fibrin D-dimer degradation products (from 296 to 1,587 ng/ml) and a homoplasmic mitochondrial DNA mutation: T961G in the MTRNR1 (12S rRNA) gene. He was made a candidate for cochlear implantation. Preoperative high-resolution computed tomography and magnetic resonance imaging of the temporal bone revealed the presence of an Arnold-Chiari malformation type I. To the best of our knowledge, this study is the second report on partial 6p trisomy that involves the 10q terminal region. Furthermore, we report the first case of documented Arnold-Chiari malformation type I and increased factor XIII activity associated with 6p trisomy. We present a comprehensive report of the familial cases and an exhaustive literature review.

Decellularized normal and cancer tissues as tools for cancer research.

Today it is widely accepted that molecular mechanisms triggering cancer initiate with a genetic modification. However, a genetic alteration providing the aberrant clone with a growing advantage over neighboring cells is not sufficient to develop cancer. Currently, tumors are considered a heterogeneous population of cells and an extracellular matrix (ECM) that make up a characteristic microenvironment. Interactions between tumor cells and cancer microenvironment define cancer progression and therapeutic response. To investigate and clarify the role of ECM in the regulation of cancer cell behavior and response to therapy, the decellularization of ECM, a widely used technique in tissue engineering, has been recently employed to develop 3D culture model of disease. In this review, we briefly explore the different components of healthy and pathological ECM and the methods to obtain and characterize the ECM from native bioptic tissue. Finally, we highlight the most relevant applications of ECM in translational cancer research strategies: decellularized ECM, ECM-hydrogel and 3D bioprinting.

A novel approach to measure brain-to-brain spatial and temporal alignment during positive empathy.

Empathy is defined as the ability to vicariously experience others' suffering (vicarious pain) or feeling their joy (vicarious reward). While most neuroimaging studies have focused on vicarious pain and describe similar neural responses during the observed and the personal negative affective involvement, only initial evidence has been reported for the neural responses to others' rewards and positive empathy. Here, we propose a novel approach, based on the simultaneous recording of multi-subject EEG signals and exploiting the wavelet coherence decomposition to measure the temporal alignment between ERPs in a dyad of interacting subjects. We used the Third-Party Punishment (TPP) paradigm to elicit the personal and vicarious experiences. During a positive experience, we observed the simultaneous presence in both agents of the Late Positive Potential (LPP), an ERP component related to emotion processing, as well as the existence of an inter-subject ERPs synchronization in the related time window. Moreover, the amplitude of the LPP synchronization was modulated by the presence of a human-agent. Finally, the localized brain circuits subtending the ERP-synchronization correspond to key-regions of personal and vicarious reward. Our findings suggest that the temporal and spatial ERPs alignment might be a novel and direct proxy measure of empathy.

Patient-Clinician Brain Response During Clinical Encounter and Pain Treatment.

The patient-clinician relationship is known to significantly affect the pain experience, as empathy, mutual trust and therapeutic alliance can significantly modulate pain perception and influence clinical therapy outcomes. The aim of the present study was to use an EEG hyperscanning setup to identify brain and behavioral mechanisms supporting the patient-clinician relationship while this clinical dyad is engaged in a therapeutic interaction. Our previous study applied fMRI hyperscanning to investigate whether brain concordance is linked with analgesia experienced by a patient while undergoing treatment by the clinician. In this current hyperscanning project we investigated similar outcomes for the patient-clinician dyad exploiting the high temporal resolution of EEG and the possibility to acquire the signals while patients and clinicians were present in the same room and engaged in a face-to-face interaction under an experimentally-controlled therapeutic context. Advanced source localization methods allowed for integration of spatial and spectral information in order to assess brain correlates of therapeutic alliance and pain perception in different clinical interaction contexts. Preliminary results showed that both behavioral and brain responses across the patient-clinician dyad were significantly affected by the interaction style.Clinical Relevance- The context of a clinical intervention can significantly impact the treatment of chronic pain. Effective therapeutic alliance, based on empathy, mutual trust, and warmth can improve treatment adherence and clinical outcomes. A deeper scientific understanding of the brain and behavioral mechanisms underlying an optimal patient-clinician interaction may lead to improved quality of clinical care and physician training, as well as better understanding of the social aspects of the biopsychosocial model mediating analgesia in chronic pain patients.

Signal informatics as an advanced integrative concept in the framework of medical informatics. New trends demonstrated by examples derived from neuroscience.

OBJECTIVES: The main objective is to show current topics and future trends in the field of medical signal processing which are derived from current research concepts. Signal processing as an integrative concept within the scope of medical informatics is demonstrated. METHODS: For all examples time-variant multivariate autoregressive models were used. Based on this modeling, the concept of Granger causality in terms of the time-variant Granger causality index and the time-variant partial directed coherence was realized to investigate directed information transfer between different brain regions. RESULTS: Signal informatics encompasses several diverse domains including: processing steps, methodologies, levels and subject fields, and applications. Five trends can be recognized and in order to illustrate these trends, three analysis strategies derived from current neuroscientific studies are presented. These examples comprise high-dimensional fMRI and EEG data. In the first example, the quantification of time-variant-directed information transfer between activated brain regions on the basis of fast-fMRI data is introduced and discussed. The second example deals with the investigation of differences in word processing between dyslexic and normal reading children. Different dynamic neural networks of the directed information transfer are identified on the basis of event-related potentials. The third example shows time-variant cortical connectivity networks derived from a source model. CONCLUSIONS: These examples strongly emphasize the integrative nature of signal informatics, encompassing processing steps, methodologies, levels and subject fields, and applications.

The Optimal Setting for Multilayer Modularity Optimization in Multilayer Brain Networks.

Community detection plays a key role in the study of brain networks, as mechanisms of modular integration and segregation are known to characterize the brain functioning. Moreover, brain networks are intrinsically multilayer: they can vary across time, frequency, subjects, conditions, and meaning, according to different definitions of connectivity. Several algorithms for the multilayer community detection were defined to identify communities in time-varying networks. The most used one is based on the optimization of a multilayer formulation of the modularity, in which two parameters linked to the spatial (γ) and temporal (ω) resolution of the uncovered communities can be set. While the effect of different γ-values has been largely explored, which ω-values are most suitable to different purposes and conditions is still an open issue. In this work, we test the algorithm performances under different values of ω by means of ad hoc implemented benchmark graphs that cover a wide range of conditions. Results provide a guide to the choice of the ω-values according to the network features. Finally, we show an application of the algorithm to real functional brain networks estimated from electro-encephalographic (EEG) signals collected at rest with closed and open eyes. The application to real data agrees with the results of the simulation study and confirms the conclusion drawn from it.

Tracking the time-varying cortical connectivity patterns by adaptive multivariate estimators.

The directed transfer function (DTF) and the partial directed coherence (PDC) are frequency-domain estimators that are able to describe interactions between cortical areas in terms of the concept of Granger causality. However, the classical estimation of these methods is based on the multivariate autoregressive modelling (MVAR) of time series, which requires the stationarity of the signals. In this way, transient pathways of information transfer remains hidden. The objective of this study is to test a time-varying multivariate method for the estimation of rapidly changing connectivity relationships between cortical areas of the human brain, based on DTF/PDC and on the use of adaptive MVAR modelling (AMVAR) and to apply it to a set of real high resolution EEG data. This approach will allow the observation of rapidly changing influences between the cortical areas during the execution of a task. The simulation results indicated that time-varying DTF and PDC are able to estimate correctly the imposed connectivity patterns under reasonable operative conditions of signal-to-noise ratio (SNR) ad number of trials. An SNR of five and a number of trials of at least 20 provide a good accuracy in the estimation. After testing the method by the simulation study, we provide an application to the cortical estimations obtained from high resolution EEG data recorded from a group of healthy subject during a combined foot-lips movement and present the time-varying connectivity patterns resulting from the application of both DTF and PDC. Two different cortical networks were detected with the proposed methods, one constant across the task and the other evolving during the preparation of the joint movement.

Multiple-Brain Connectivity During Third Party Punishment: an EEG Hyperscanning Study.

Compassion is a particular form of empathic reaction to harm that befalls others and is accompanied by a desire to alleviate their suffering. This altruistic behavior is often manifested through altruistic punishment, wherein individuals penalize a deprecated human's actions, even if they are directed toward strangers. By adopting a dual approach, we provide empirical evidence that compassion is a multifaceted prosocial behavior and can predict altruistic punishment. In particular, in this multiple-brain connectivity study in an EEG hyperscanning setting, compassion was examined during real-time social interactions in a third-party punishment (TPP) experiment. We observed that specific connectivity patterns were linked to behavioral and psychological intra- and interpersonal factors. Thus, our results suggest that an ecological approach based on simultaneous dual-scanning and multiple-brain connectivity is suitable for analyzing complex social phenomena.

Speech perception in noise by young sequential bilingual children.

The objective of this study was to ascertain the effects of competitive noise on second language perception skills of sequentially bilingual children and to compare the results with those relating to matched monolingual peers. Fifteen bilingual immigrant children (aged 6-10 years) (BL) learning through their second language (L2), which was Italian, were matched with 15 peers who only spoke Italian (IO). All immigrant children had arrived in Italy and were exposed to L2 after their 4th year of life. The speech-to-noise ratio (SNR) needed to obtain 50% intelligibility - the speech reception threshold (SRT) - for Italian words was measured against the Italian version of ICRA noise, using an adaptive method. Moreover, presentation of phrases against a contralateral continuous discourse (informational masking) was carried out to exclude possible biases due to differences in memory, attention, or other central auditory processing disorders between groups. The SNR was -2.7 dB (SD 1.7; range: -5.5 to + 0.9) for the BL group and -5.3 dB (SD 2.3; range: -8.8 to -0.9) for the IO group (p < 0.01). With contralateral continuous discourse presentation the SNR were -32.8 dB (SD 2.4; range: -36.1 to -28.2) for the BL group and -27.8 dB (SD 2.1; range: -31.7 to -24.1) for the OI group (p < 0.01). Even sequential bilingual individuals exposed to L2 at 4 years old had worse speech perception in noise than their matched IO peers. On the other hand, the BL group demonstrated superior divided attention skills in tests with competitive contralateral discourse (p < 0.01).

EEG source estimation accuracy in presence of simulated cortical lesions.

Methods to reconstruct the neuroelectrical activity in the brain source space can be used to improve the spatial resolution of scalp-recorded EEG and to estimate the locations of electrical sources in the brain. This procedure can improve the investigation of the functional organization of the human brain, exploiting the high temporal resolution of EEG to follow the temporal dynamics of information processing. As for today, the uncertainties about the effects of inhomogeneities due to brain lesions preclude the adoption of EEG functional mapping on patients with lesioned brain. The aim of this work is to quantify the accuracy of a distributed source localization method in recovering extended sources of activated cortex when cortical lesions of different dimensions are introduced in simulated data. For this purpose, EEG source-distributed activity estimated from real data was modified including silent lesion areas. Then, for each simulated lesion, forward and inverse calculations were carried out to localize the produced scalp activity and the reconstructed cortical activity. Finally, the error induced in the reconstruction by the presence of the lesion was computed and analyzed in relation to the number of electrodes and to the size of the simulated lesion. Results returned values of global error in the whole cortex and of error in the non-lesioned area which are strongly dependent on the number of recorded scalp sensors, as they increase when a lower spatial sampling is performed on the scalp (64 versus 32 EEG channels). For increasing spatial sampling frequencies, the accuracy of the source reconstruction improves and even the presence of small lesions induces significantly higher error levels with respect to the lesion-free condition.

Brain connectivity networks at the basis of human attention components: An EEG study.

The Attention Network Task (ANT) was developed to disentangle the three components of attention identified in the Posner's theoretical model (alerting, orienting and executive control) and to measure the corresponding behavioral efficiency. Several fMRI studies have already provided evidences on the anatomical separability and interdependency of these three networks, and EEG studies have also unveiled the associated brain rhythms. What is still missing is a characterization of the brain circuits subtending the attentional components in terms of directed relationships between the brain areas and their frequency content. Here, we want to exploit the high temporal resolution of the EEG, improving its spatial resolution by means of advanced source localization methods, and to integrate the resulting information by a directed connectivity analysis. The results showed in the present study demonstrate the possibility to associate a specific directed brain circuit to each attention component and to identify synthetic indices able to selectively describe their neurophysiological, spatial and spectral properties.

Community detection: Comparison among clustering algorithms and application to EEG-based brain networks.

Community structure is a feature of complex networks that can be crucial for the understanding of their internal organization. This is particularly true for brain networks, as the brain functioning is thought to be based on a modular organization. In the last decades, many clustering algorithms were developed with the aim to identify communities in networks of different nature. However, there is still no agreement about which one is the most reliable, and to test and compare these algorithms under a variety of conditions would be beneficial to potential users. In this study, we performed a comparative analysis between six different clustering algorithms, analyzing their performances on a ground-truth consisting of simulated networks with properties spanning a wide range of conditions. Results show the effect of factors like the noise level, the number of clusters, the network dimension and density on the performances of the algorithms and provide some guidelines about the use of the more appropriate algorithm according to the different conditions. The best performances under a wide range of conditions were obtained by Louvain and Leicht & Newman algorithms, while Ronhovde and Infomap proved to be more appropriate in very noisy conditions. Finally, as a proof of concept, we applied the algorithms under exam to brain functional connectivity networks obtained from EEG signals recorded during a sustained movement of the right hand, obtaining a clustering of scalp electrodes which agrees with the results of the simulation study conducted.

Transcranial cerebellar direct current stimulation: Effects on brain resting state oscillatory and network activity.

Transcranial cerebellar direct current stimulation (tcDCS) can offer new insights into the cerebellar function and disorders, by modulating noninvasively the activity of cerebellar networks. Taking into account the functional interplay between the cerebellum and the cerebral cortex, we addressed the effects of unilateral tcDCS (active electrode positioned over the right cerebellar hemisphere) on the electroencephalographic (EEG) oscillatory activity and on the cortical network organization at resting state. Effects on spectral (de)synchronizations and functional connectivity after anodal and cathodal stimulation were assessed with respect to a sham condition. A lateralized synchronization over the sensorimotor area in gamma band, as well as an increase of the network segregation in sensory-motor rhythms and a higher communication between hemispheres in gamma band, were detected after anodal stimulation. The same measures after cathodal tcDCS returned responses similar to the sham condition.

A new software tool for 3D motion analyses of the musculo-skeletal system.

BACKGROUND: Many clinical and biomechanical research studies, particularly in orthopaedics, nowadays involve forms of movement analysis. Gait analysis, video-fluoroscopy of joint replacement, pre-operative planning, surgical navigation, and standard radiostereometry would require tools for easy access to three-dimensional graphical representations of rigid segment motion. Relevant data from this variety of sources need to be organised in structured forms. Registration, integration, and synchronisation of segment position data are additional necessities. With this aim, the present work exploits the features of a software tool recently developed within a EU-funded project ('Multimod') in a series of different research studies. METHODS: Standard and advanced gait analysis on a normal subject, in vivo fluoroscopy-based three-dimensional motion of a replaced knee joint, patellar and ligament tracking on a knee specimen by a surgical navigation system, stem-to-femur migration pattern on a patient operated on total hip replacement, were analysed with standard techniques and all represented by this innovative software tool. Segment pose data were eventually obtained from these different techniques, and were successfully imported and organised in a hierarchical tree within the tool. FINDINGS: Skeletal bony segments, prosthesis component models and ligament links were registered successfully to corresponding marker position data for effective three-dimensional animations. These were shown in various combinations, in different views, from different perspectives, according to possible specific research interests. INTERPRETATION: Bioengineering and medical professionals would be much facilitated in the interpretation of the motion analysis measurements necessary in their research fields, and would benefit therefore from this software tool.

Cochlear implantation in post-lingually deafened adults and elderly patients: analysis of audiometric and speech perception outcomes during the first year of use.

The aim of this study was to analyse audiometric and speech perception outcomes after cochlear implantation (CI) in adult and elderly patients in the first year post-CI activation. We evaluated 42 subjects who underwent CI at the Otorhinolaryngological Clinic of Padua Hospital. The subjects enrolled were post-lingually deafened patients who were unilaterally implanted for bilateral, severe-to-profound hearing loss. The overall sample was divided into three groups according to the age at the time of implantation: group A (35-49 years), group B (50-64 years) and group C (≥ 65 years). The subjects were assessed, both before and after surgery (at months 1, 3, 6 and 12), using pure tone audiometry, speech audiometry and speech perception tests and the CAP questionnaire. Statistical analysis of outcomes was using a Student's t-test for paired data. In all study groups a significant improvement was demonstrated in auditory performance examinations post-CI compared to the pre-operative scores. All subjects in all age groups obtained significant improvements in PTA scores before surgery and post-CI activation. Comparison of PTA values among the three age groups did not reveal any significant difference. Considerable improvement was obtained even in the speech audiometry thresholds in all groups at follow-up, with no significant differences between groups. The speech perception examination and CAP questionnaire showed good progress in all study groups, although younger patients tended to achieve more complex categories than older ones. In conclusion, CI is an effective treatment for severe-to-profound hearing loss with no significant differences in auditory performances between older and younger CI recipients. Even if somewhat slower, subjects older than 65 reached good performance and therefore are good candidates for a cochlear implant.

Cochlear implant and inflammation reaction: Safety study of a new steroid-eluting electrode.

Dexamethasone is a common anti-inflammatory agent added to cochlear implants to reduce hearing loss due to electrode insertion trauma. We evaluated the safety of eluting silicone rods containing 10% dexamethasone in a Guinea pig model. Animals were implanted with a dexamethasone eluting silicone electrode (DER) or with a non-eluting electrode (NER). The control group only underwent a cochleostomy (CS). Prior to implantation and during the two weeks following implantation, the hearing status of the animals was assessed by means of Compound Action Potentials (CAPs) with an electrode placed near the round window. Two weeks after implantation, the mean click threshold shifts were 1 dB ± 10 dB in the DER group, 10 dB ± 10 dB in the NER group and -4 dB ± 10 dB in the control group. After two weeks the bullae of each animal were extracted to verify the presence of macrophages, the percent of tissue growth in the scala tympani and the tissue sealing around cochleostomy. Silicone electrodes samples were also explanted and examined for bacterial infection. Neither bacterial infection nor enhanced number of macrophages were observed. A limited, but not significant, tissue growth was found in the scala tympani between the experimental and the control group. The data suggest that, in the Guinea pig model, the use of DER is apparently safe as an anti-inflammatory slow-release additive to the cochlear implant.

Measuring the agreement between brain connectivity networks.

Investigating the level of similarity between two brain networks, resulting from measures of effective connectivity in the brain, can be of interest from many respects. In this study, we propose and test the idea to borrow measures of association used in machine learning to provide a measure of similarity between the structure of (un-weighted) brain connectivity networks. The measures here explored are the accuracy, Cohen's Kappa (K) and Area Under Curve (AUC). We implemented two simulation studies, reproducing two contexts of application that can be particularly interesting for practical applications, namely: i) in methodological studies, performed on surrogate data, aiming at comparing the estimated network with the corresponding ground-truth network; ii) in applications to real data, when it is necessary to compare the structure of a network obtained in a specific subject with a reference (e.g. a baseline condition or normative data). In the simulations, the level of similarity between two networks was manipulated through different factors. We then investigated the effect of such manipulations on the measures of association. Results showed how the three parameters modulated their values according to the level of similarity between the two networks. In particular, the AUC provided the better performances in terms of its capability to synthetize the similarity between two networks, showing high dynamic and sensitivity.

Interfacing brain with computer to improve communication and rehabilitation after brain damage.

Communication and control of the external environment can be provided via brain-computer interfaces (BCIs) to replace a lost function in persons with severe diseases and little or no chance of recovery of motor abilities (ie, amyotrophic lateral sclerosis, brainstem stroke). BCIs allow to intentionally modulate brain activity, to train specific brain functions, and to control prosthetic devices, and thus, this technology can also improve the outcome of rehabilitation programs in persons who have suffered from a central nervous system injury (ie, stroke leading to motor or cognitive impairment). Overall, the BCI researcher is challenged to interact with people with severe disabilities and professionals in the field of neurorehabilitation. This implies a deep understanding of the disabled condition on the one hand, and it requires extensive knowledge on the physiology and function of the human brain on the other. For these reasons, a multidisciplinary approach and the continuous involvement of BCI users in the design, development, and testing of new systems are desirable. In this chapter, we will focus on noninvasive EEG-based systems and their clinical applications, highlighting crucial issues to foster BCI translation outside laboratories to eventually become a technology usable in real-life realm.

Assessing cortical functional connectivity by linear inverse estimation and directed transfer function: simulations and application to real data.

OBJECTIVE: To test a technique called Directed Transfer Function (DTF) for the estimation of human cortical connectivity, by means of simulation study and human study, using high resolution EEG recordings related to finger movements. METHODS: The method of the Directed Transfer Function (DTF) is a frequency-domain approach, based on a multivariate autoregressive modeling of time series and on the concept of Granger causality. Since the spreading of the potential from the cortex to the sensors makes it difficult to infer the relation between the spatial patterns on the sensor space and those on the cortical sites, we propose the use of the DTF method on cortical signals estimated from high resolution EEG recordings, which exhibit a higher spatial resolution than conventional cerebral electromagnetic measures. The simulation study was followed by an analysis of variance (ANOVA) of the results obtained for different levels of Signal to Noise Ratio (SNR) and temporal length, as they have been systematically imposed on simulated signals. The whole methodology was then applied to high resolution EEG data recorded during a visually paced finger movement. RESULTS: The statistical analysis performed returns that during simulations, DTF is able to estimate correctly the imposed connectivity patterns under reasonable operative conditions, i.e. when data exhibit a SNR of at least 3 and a length of at least 75 s of non-consecutive recordings at 64 Hz of sampling rate, equivalent, more generally, to 4800 data samples. CONCLUSIONS: Functional connectivity patterns of cortical activity can be effectively estimated under general conditions met in any practical EEG recordings, by combining high resolution EEG techniques, linear inverse estimation and the DTF method. SIGNIFICANCE: The estimation of cortical connectivity can be performed not only with hemodynamic measurements, by using functional MRI recordings, but also with modern EEG recordings treated with advanced computational techniques.