The Impact of Math Anxiety on Working Memory:A Cortical Activations and Cortical Functional Connectivity EEG Study

Mathematical anxiety (MA) is defined as a feeling of tension, apprehension, or fear that interferes with mathematical performance in various daily or academic situations. Cognitive consequences of MA have been studied a lot and revealed that MA seriously affects solving the complex problem due to the corruption of working memory (WM). The corruption of WM caused by MA is well documented in behavioral level, but the involved neurophysiological processes have not been properly addressed, despite the recent attention drawn on the neural basis of MA. This is the second part of our study that intents to investigate the neurophysiological aspects of MA and its implications to WM. In the first study, we saw how MA affects the early stages of numeric stimuli processes as the WM indirectly using event-related potentials in scalp electroencephalographic (EEG) signals. This paper goes one step further to investigate the cortical activations, obtained by the multichannel EEG recordings as well as the cortical functional networks in three WM tasks with increasing difficulty. Our results indicate that the high-math anxious (HMA) group activated more areas linked with negative emotions, pain, and fear, while the low-math anxious (LMA) group activated regions related to the encoding and retrieval processes of the WM. Functional connectivity analysis also reveals that the LMAs' brain has got more structured cortical networks with increased connectivity in areas related to WM, such as the frontal cortex, while the HMAs' brain has a more diffused and unstructured network, superimposing the evidence that the structured processes of WM are corrupted

Math anxiety:brain cortical network changes in anticipation of doing mathematics

Following our previous work regarding the involvement of math anxiety (MA) in math-oriented tasks, this study tries to explore the differences in the cerebral networks' topology between self-reported low math-anxious (LMA) and high math-anxious (HMA) individuals, during the anticipation phase prior to a mathematical related experiment. For this reason, multichannel EEG recordings were adopted, while the solution of the inverse problem was applied in a generic head model, in order to obtain the cortical signals. The cortical networks have been computed for each band separately, using the magnitude square coherence metric. The main graph theoretical parameters, showed differences in segregation and integration in almost all EEG bands of the HMAs in comparison to LMAs, indicative of a great influence of the anticipatory anxiety prior to mathematical performance

A Systematic Review of Investigations into Functional Brain Connectivity Following Spinal Cord Injury

Background: Complete or incomplete spinal cord injury (SCI) results in varying degree of motor, sensory and autonomic impairment. Long-lasting, often irreversible disability results from disconnection of efferent and afferent pathways. How does this disconnection affect brain function is not so clear. Changes in brain organization and structure have been associated with SCI and have been extensively studied and reviewed. Yet, our knowledge regarding brain connectivity changes following SCI is overall lacking. Methods: In this study we conduct a systematic review of articles regarding investigations of functional brain networks following SCI, searching on PubMed, Scopus and ScienceDirect according to PRISMA-P 2015 statement standards. Results: Changes in brain connectivity have been shown even during the early stages of the chronic condition and correlate with the degree of neurological impairment. Connectivity changes appear as dynamic post-injury procedures. Sensorimotor networks of patients and healthy individuals share similar patterns but new functional interactions have been identified as unique to SCI networks. Conclusions: Large-scale, multi-modal, longitudinal studies on SCI patients are needed to understand how brain network reorganization is established and progresses through the course of the condition. The expected insight holds clinical relevance in preventing maladaptive plasticity after SCI through individualized neurorehabilitation, as well as the design of connectivity-based brain-computer interfaces and assistive technologies for SCI patients

Does combined training of biofeedback and neurofeedback affect smoking status, behavior, and longitudinal brain plasticity?

Introduction: Investigations of biofeedback (BF) and neurofeedback (NF) training for nicotine addiction have been long documented to lead to positive gains in smoking status, behavior and to changes in brain activity. We aimed to: (a) evaluate a multi-visit combined BF/NF intervention as an alternative smoking cessation approach, (b) validate training-induced feedback learning, and (c) document effects on resting-state functional connectivity networks (rsFCN); considering gender and degree of nicotine dependence in a longitudinal design.Methods: We analyzed clinical, behavioral, and electrophysiological data from 17 smokers who completed five BF and 20 NF sessions and three evaluation stages. Possible neuroplastic effects were explored comparing whole-brain rsFCN by phase-lag index (PLI) for different brain rhythms. PLI connections with significant change across time were investigated according to different resting-state networks (RSNs).Results: Improvements in smoking status were observed as exhaled carbon monoxide levels, Total Oxidative Stress, and Fageström scores decreased while Vitamin E levels increased across time. BF/NF promoted gains in anxiety, self-esteem, and several aspects of cognitive performance. BF learning in temperature enhancement was observed within sessions. NF learning in theta/alpha ratio increase was achieved across baselines and within sessions. PLI network connections significantly changed across time mainly between or within visual, default mode and frontoparietal networks in theta and alpha rhythms, while beta band RSNs mostly changed significantly after BF sessions.Discussion: Combined BF/NF training positively affects the clinical and behavioral status of smokers, displays benefit in smoking harm reduction, plays a neuroprotective role, leads to learning effects and to positive reorganization of RSNs across time.Clinical Trial Registration:https://clinicaltrials.gov/ct2/show/NCT02991781

Neuroscientific investigation of the role of neurofeedback in addiction

Smoking constitutes a leading cause of morbidity and premature death constituting a global health challenge. Although, pharmacological and behavioral approaches comprise the mainstay of smoking cessation interventions, the efficacy and safety of pharmacotherapy is not demonstrated for some populations. Investigations of biofeedback (BF) and neurofeedback (NF) training for nicotine addiction have been long documented to lead to positive gains in smoking status, aspects of behavior and to changes in brain activity. In this thesis, we aimed to a) evaluate a multi-visit combined BF/NF intervention as an alternative smoking cessation approach, b) assess the impact of intervention on various behavioral components and c) explore effects on resting-state functional connectivity networks (rsFCN), considering gender and degree of nicotine dependence in a longitudinal design. A systematic narrative synthesis of peer-reviewed controlled and uncontrolled BF and/or NF studies focusing on smoking was performed according to PRISMA guidelines. Moreover, we analyzed clinical, behavioral, and electrophysiological data from smokers who fulfilled the inclusion criteria of our study. We have performed two separate analyses. In the first one, data from 27 smokers who complete 5 sessions of BF training were analyzed. We focused on possible alterations in default mode network (DMN) connectivity as it is affected by both stress and smoking addiction. Eighteen custom-defined ROIs representing important nodes of the DMN were selected in order to proceed to computation of connectivity. Analysis was performed through eConnectome toolbox using Directed Transfer Function metric (DTF) with surrogate significance testing as a connectivity measure. In the second one, data from 17 participants of the same pool who completed 5 BF and 20 NF sessions, and three evaluation stages were evaluated. Possible neuroplastic effects were explored comparing whole-brain rsFCN by phase-lag index (PLI) for different brain rhythms across time. PLI connections with significant change across time were investigated according to different resting-state networks (RSNs). In both analyses, smoking, clinical and behavioral status of the participants was evaluated across time. Based on the existing literature, smoking prior to training was found to affect BF outcomes while individualized EEG NF training holds promise for modulating craving-related response minimizing the required number of sessions. Real-time fMRI NF studies concluded that nicotine-dependent individuals could modulate craving-related brain responses. Transfer of this learned self-regulation skill to behavior was shown. Focusing on DMN connectivity modulation after BF training, a significant increase of information flow from right ventrolateral prefrontal cortex and right temporal pole cortex towards other DMN components was observed. Although, biofeedback training did not alter smoking status, the degree of nicotine dependence and the presence of psychiatric symptoms were significantly improved. Assessing the overall combined intervention, we observed improvement in smoking status, anxiety, self-esteem, and several aspects of cognitive performance. BF learning in temperature enhancement was observed within sessions. NF learning in theta/alpha ratio increase was achieved across baselines and within sessions. PLI network connections significantly changed across time mainly between or within visual, default mode and frontoparietal networks in theta and alpha rhythms, while beta band RSNs mostly changed significantly after the BF sessions. Combined BF/NF training positively affects the clinical and behavioral status of smokers, displays benefit in smoking harm reduction, plays a neuroprotective role, leads to learning effects and to positive reorganization of RSNs across time. Based on the results, combined BF/NF training could be an important complementary tool to standard smoking cessation care. However, BF and NF training should address remaining issues on specificity and scientific validity, target diverse demographics, and produce robust reproducible methodologies and clinical guidelines for relevant health care providers.Το κάπνισμα αποτελεί μια σημαντική αιτία νοσηρότητας και πρόωρης θνησιμότητας συνιστώντας μια παγκόσμια πρόκληση για την υγεία. Αν και οι φαρμακολογικές και συμπεριφορικές προσεγγίσεις αποτελούν τις κύριες παρεμβάσεις για τη διακοπή του καπνίσματος, η αποτελεσματικότητα και η ασφάλεια της φαρμακοθεραπείας δεν έχει αποδειχθεί για ορισμένους πληθυσμούς. Η διερεύνηση του ρόλου της βιοανάδρασης (BF) και νευροανάδρασης (NF) στην αντιμετώπιση της εξάρτησης από τη νικοτίνη έχει καταδείξει ότι οι παραπάνω προσεγγίσεις μπορούν να οδηγήσουν σε βελτίωση του καπνιστικού προφίλ, πτυχών της συμπεριφοράς και μεταβολές στη δραστηριότητα του εγκεφάλου. Με την παρούσα διατριβή, στοχεύουμε: α) στην αξιολόγηση της συνδυαστικής εκπαίδευσης BF/NF ως μια εναλλακτική προσέγγιση για τη διακοπή του καπνίσματος, β) στη μελέτη των επιδράσεων αυτής σε διαφορετικούς συμπεριφορικούς δείκτες και γ) στη διερεύνηση μεταβολών στη λειτουργική συνδεσιμότητα δικτύων σε κατάσταση ηρεμίας λαμβάνοντας υπόψη το φύλο και το βαθμό εξάρτησης, ακολουθώντας ένα σχεδιασμό διαχρονικής μελέτης. Πραγματοποιήσαμε μια συστηματική αφηγητική σύνθεση της βιβλιογραφίας ακολουθώντας τις κατευθυντήριες οδηγίες PRISMA. Στην εν λόγω συστηματική ανασκόπηση λάβαμε υπόψη ελεγχόμενες και μη ελεγχόμενες μελέτες που εξέταζαν το ρόλο της βιοανάδρασης και/ή νευροανάδρασης στο κάπνισμα. Επιπλέον, αναλύσαμε κλινικά, συμπεριφορικά και ηλεκτροφυσιολογικά δεδομένα καπνιστών που ικανοποιούν τα κριτήρια ένταξης της μελέτης. Πραγματοποιήσαμε δυο ξεχωριστές αναλύσεις. Στην πρώτη, αναλύσαμε δεδομένα από 27 άτομα που πραγματοποίησαν 5 συνεδρίες βιοανάδρασης εστιάζοντας στις πιθανές μεταβολές λειτουργικής συνδεσιμότητας στο δίκτυο default mode (DMN). Η συνδεσιμότητα στο παραπάνω δίκτυο έχει δειχθεί ότι επηρεάζεται τόσο από το στρες όσο και το κάπνισμα. Έτσι, υπολογίσαμε τη συνδεσιμότητα του δικτύου χρησιμοποιώντας 18 περιοχές ενδιαφέροντος που αντιπροσώπευαν σημαντικούς κόμβους του DMN. Η ανάλυση πραγματοποιήθηκε με τη βοήθεια του εργαλείου eConnectome εφαρμόζοντας ως μέτρο συνδεσιμότητας τη μετρική Directed Transfer Function (DTF) με παράλληλο στατιστικό έλεγχο υποκατάστατων δεδομένων (surrogates). Στη δεύτερη ανάλυση αξιολογήσαμε δεδομένα από 17 συμμετέχοντες που ολοκλήρωσαν όλες τις διαδικασίες της παρέμβασης, 5 συνεδρίες βιοανάδρασης, 20 συνεδρίες νευροανάδρασης και τρεις φάσεις αξιολόγησης. Οι πιθανές νευροπλαστικές μεταβολές διερευνήθηκαν συγκρίνοντας τη συνολική συνδεσιμότητα του εγκεφάλου σε διαφορετικούς ρυθμούς εφαρμόζοντας ως μέτρο συνδεσιμότητας τη μετρική phase-lag index (PLI). Οι συνδέσεις που παρουσίασαν σημαντικές μεταβολές κατά μήκος του χρόνου διερευνήθηκαν σύμφωνα με διαφορετικά δίκτυα που ενεργοποιούνται σε κατάσταση ηρεμίας (RSNs). Το καπνιστικό, κλινικό και συμπεριφορικό προφίλ των συμμετεχόντων εκτιμήθηκε στις διάφορες φάσεις αξιολόγησης και στις δυο αναλύσεις. Με βάση την υπάρχουσα βιβλιογραφία το κάπνισμα πριν την εκπαίδευση επηρεάζει τα αποτελέσματα της εκπαίδευσης βιοανάδρασης ενώ η εξατομικευμένη εκπαίδευση νευροανάδρασης φαίνεται ότι τροποποιεί τις αποκρίσεις που σχετίζονται με τη λαχτάρα ενώ παράλληλα μειώνει τον απαιτούμενο αριθμό συνεδριών. Οι μελέτες που εξετάζουν την εκπαίδευση νευροανάδρασης που βασίζεται στη λειτουργική απεικόνιση μαγνητικού συντονισμού πραγματικού χρόνου έχουν δείξει ότι η εν λόγω προσέγγιση μπορεί να τροποποιήσει τις αποκρίσεις του εγκεφάλου που σχετίζονται με τη λαχτάρα. Επίσης, έχει παρατηρηθεί μεταφορά αυτής της μαθημένης δεξιότητας στη συμπεριφορά. Εστιάζοντας στη διαμόρφωση της συνδεσιμότητας του DMN έπειτα από την εκπαίδευση βιοανάδρασης, εντοπίσαμε μια αύξηση στη ροή πληροφορίας από το δεξί μεσοκοιλιακό προμετωπιαίο φλοιό (vlPFC) και το δεξί πόλο του κροταφικού φλοιού (TPC) προς τις άλλες συνιστώσες του DMN. Αν και η εκπαίδευση βιοανάδρασης δε μετέβαλε το καπνιστικό προφίλ των συμμετεχόντων παρατηρήθηκε σημαντική βελτίωση στο βαθμό εξάρτησης από τη νικοτίνη και στη παρουσία ψυχιατρικών συμπτωμάτων. Αξιολογώντας συνολικά τη συνδυαστική εκπαίδευση παρατηρήσαμε βελτίωση στο καπνιστικό προφίλ, στην αγχώδη συμπτωματολογία, την αυτοεκτίμηση καθώς και σε μερικές πτυχές της γνωστικής επίδοσης. Επιπρόσθετα, επισημάναμε την εγκαθίδρυση μάθησης έπειτα από την εκπαίδευση βιοανάδρασης εντός των συνεδριών ενώ κατά την εκπαίδευση νευροανάδρασης σημειώθηκε μάθηση τόσο εντός όσο και μεταξύ των συνεδριών. Οι συνδέσεις των PLI δικτύων που διαφοροποιήθηκαν κατά μήκος του χρόνου εντοπίστηκαν κυρίως μεταξύ ή εντός του οπτικού, του DMN και του προσθιοβρεγματικού δικτύου στο θήτα και άλφα ρυθμό ενώ διαφοροποίηση στα δίκτυα του βήτα ρυθμού σημειώθηκε κυρίως μετά την εκπαίδευση βιοανάδρασης. Η συνδυαστική εκπαίδευση βιοανάδρασης και νευροανάδρασης φαίνεται ότι επηρέασε θετικά την κλινική και συμπεριφορική κατάσταση των καπνιστών ενώ παράλληλα καταδείχθηκαν σημαντικά οφέλη στη μείωση της βλάβης που προκαλείται από το κάπνισμα. Επιπλέον, δείξαμε ότι μπορεί να διαδραματίσει ένα νευροπροστατευτικό ρόλο και να οδηγήσει σε εγκαθίδρυση επαγόμενης μάθησης από την εκπαίδευση που εφαρμόσαμε αλλά και σε θετική αναδιοργάνωση των δικτύων κατά μήκος του χρόνου. Με βάση τα ευρήματα της εν λόγω διατριβής, το πρωτόκολλο που εξετάστηκε θα μπορούσε να διαδραματίσει ένα σημαντικό επικουρικό ρόλο στις συνήθεις πρακτικές διακοπής του καπνίσματος. Ωστόσο, αναφορικά με την εκπαίδευση βιοανάδρασης και νευροανάδρασης, είναι σημαντικό να αντιμετωπιστούν ορισμένα μεθοδολογικά ζητήματα που αφορούν στην ειδικότητα και την επιστημονική εγκυρότητα, να εφαρμοστούν σε πληθυσμούς με ποικίλα δημογραφικά χαρακτηριστικά, να δημιουργηθούν ισχυρές και αναπαραγώγιμες μεθοδολογίες καθώς και να διαμορφωθούν κλινικές κατευθυντήριες οδηγίες για τους σχετικούς ειδικούς υγείας

Functional Brain Connectivity during Multiple Motor Imagery Tasks in Spinal Cord Injury

Reciprocal communication of the central and peripheral nervous systems is compromised during spinal cord injury due to neurotrauma of ascending and descending pathways. Changes in brain organization after spinal cord injury have been associated with differences in prognosis. Changes in functional connectivity may also serve as injury biomarkers. Most studies on functional connectivity have focused on chronic complete injury or resting-state condition. In our study, ten right-handed patients with incomplete spinal cord injury and ten age- and gender-matched healthy controls performed multiple visual motor imagery tasks of upper extremities and walking under high-resolution electroencephalography recording. Directed transfer function was used to study connectivity at the cortical source space between sensorimotor nodes. Chronic disruption of reciprocal communication in incomplete injury could result in permanent significant decrease of connectivity in a subset of the sensorimotor network, regardless of positive or negative neurological outcome. Cingulate motor areas consistently contributed the larger outflow (right) and received the higher inflow (left) among all nodes, across all motor imagery categories, in both groups. Injured subjects had higher outflow from left cingulate than healthy subjects and higher inflow in right cingulate than healthy subjects. Alpha networks were less dense, showing less integration and more segregation than beta networks. Spinal cord injury patients showed signs of increased local processing as adaptive mechanism. This trial is registered with NCT02443558

Wireless Brain-Robot Interface: User Perception and Performance Assessment of Spinal Cord Injury Patients

Patients suffering from life-changing disability due to Spinal Cord Injury (SCI) increasingly benefit from assistive robotics technology. The field of brain-computer interfaces (BCIs) has started to develop mature assistive applications for those patients. Nonetheless, noninvasive BCIs still lack accurate control of external devices along several degrees of freedom (DoFs). Unobtrusiveness, portability, and simplicity should not be sacrificed in favor of complex performance and user acceptance should be a key aim among future technological directions. In our study 10 subjects with SCI (one complete) and 10 healthy controls were recruited. In a single session they operated two anthropomorphic 8-DoF robotic arms via wireless commercial BCI, using kinesthetic motor imagery to perform 32 different upper extremity movements. Training skill and BCI control performance were analyzed with regard to demographics, neurological condition, independence, imagery capacity, psychometric evaluation, and user perception. Healthy controls, SCI subgroup with positive neurological outcome, and SCI subgroup with cervical injuries performed better in BCI control. User perception of the robot did not differ between SCI and healthy groups. SCI subgroup with negative outcome rated Anthropomorphism higher. Multi-DoF robotics control is possible by patients through commercial wireless BCI. Multiple sessions and tailored BCI algorithms are needed to improve performance

Information System for Symptom Diagnosis and Improvement of Attention Deficit Hyperactivity Disorder: Protocol for a Nonrandomized Controlled Pilot Study

BackgroundAttention deficit hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders during childhood; however, the diagnosis procedure remains challenging, as it is nonstandardized, multiparametric, and highly dependent on subjective evaluation of the perceived behavior. ObjectiveTo address the challenges of existing procedures for ADHD diagnosis, the ADHD360 project aims to develop a platform for (1) early detection of ADHD by assessing the user’s likelihood of having ADHD characteristics and (2) providing complementary training for ADHD management. MethodsA 2-phase nonrandomized controlled pilot study was designed to evaluate the ADHD360 platform, including ADHD and non-ADHD participants aged 7 to 16 years. At the first stage, an initial neuropsychological evaluation along with an interaction with the serious game developed (“Pizza on Time”) for approximately 30-45 minutes is performed. Subsequently, a 2-week behavior monitoring of the participants through the mADHD360 app is planned after a telephone conversation between the participants’ parents and the psychologist, where the existence of any behaviors characteristic of ADHD that affect daily functioning is assessed. Once behavior monitoring is complete, the research team invites the participants to the second stage, where they play the game for a mean duration of 10 weeks (2 times per week). Once the serious game is finished, a second round of behavior monitoring is performed following the same procedures as the initial one. During the study, gameplay data were collected and preprocessed. The protocol of the pilot trials was initially designed for in-person participation, but after the COVID-19 outbreak, it was adjusted for remote participation. State-of-the-art machine learning (ML) algorithms were used to analyze labeled gameplay data aiming to detect discriminative gameplay patterns among the 2 groups (ADHD and non-ADHD) and estimate a player’s likelihood of having ADHD characteristics. A schema including a train-test splitting with a 75:25 split ratio, k-fold cross-validation with k=3, an ML pipeline, and data evaluation were designed. ResultsA total of 43 participants were recruited for this study, where 18 were diagnosed with ADHD and the remaining 25 were controls. Initial neuropsychological assessment confirmed that the participants in the ADHD group showed a deviation from the participants without ADHD characteristics. A preliminary analysis of collected data consisting of 30 gameplay sessions showed that the trained ML models achieve high performance (ie, accuracy up to 0.85) in correctly predicting the users’ labels (ADHD or non-ADHD) from their gameplay session on the ADHD360 platform. ConclusionsADHD360 is characterized by its notable capacity to discriminate player gameplay behavior as either ADHD or non-ADHD. Therefore, the ADHD360 platform could be a valuable complementary tool for early ADHD detection. Trial RegistrationClinicalTrials.gov NCT04362982; https://clinicaltrials.gov/ct2/show/NCT04362982 International Registered Report Identifier (IRRID)RR1-10.2196/4018