Applying machine learning EEG signal classification to emotion‑related brain anticipatory activity

Machine learning approaches have been fruitfully applied to several neurophysiological signal classification problems. Considering the relevance of emotion in human cognition and behaviour, an important application of machine learning has been found in the field of emotion identification based on neurophysiological activity. Nonetheless, there is high variability in results in the literature depending on the neuronal activity measurement, the signal features and the classifier type. The present work aims to provide new methodological insight into machine learning applied to emotion identification based on electrophysiological brain activity. For this reason, we analysed previously recorded EEG activity measured while emotional stimuli, high and low arousal (auditory and visual) were provided to a group of healthy participants. Our target signal to classify was the pre-stimulus onset brain activity. Classification performance of three different classifiers (linear discriminant analysis, support vector machine and k-nearest neighbour) was compared using both spectral and temporal features. Furthermore, we also contrasted the classifiers' performance with static and dynamic (time evolving) features. The results show a clear increase in classification accuracy with temporal dynamic features. In particular, the support vector machine classifiers with temporal features showed the best accuracy (63.8 %) in classifying high vs low arousal auditory stimuli

Applying machine learning EEG signal classification to emotion related brain anticipatory activity

Machine learning approaches have been fruitfully applied to several neurophysiological signal classification problems. Considering the relevance of emotion in human cognition and behaviour, an important application of machine learning has been found in the field of emotion identification based on neurophysiological activity. Nonetheless, there is high variability in results in the literature depending on the neuronal activity measurement, the signal features and the classifier type. The present work aims to provide new methodological insight into machine learning applied to emotion identification based on electrophysiological brain activity. For this reason, we analysed previously recorded EEG activity measured while emotional stimuli, high and low arousal (auditory and visual) were provided to a group of healthy participants. Our target signal to classify was the pre-stimulus onset brain activity. Classification performance of three different classifiers (LDA, SVM and kNN) was compared using both spectral and temporal features. Furthermore, we also contrasted the performance of static and dynamic (time evolving) approaches. The best static feature-classifier combination was the SVM with spectral features (51.8%), followed by LDA with spectral features (51.4%) and kNN with temporal features (51%). The best dynamic feature‑classifier combination was the SVM with temporal features (63.8%), followed by kNN with temporal features (63.70%) and LDA with temporal features (63.68%). The results show a clear increase in classification accuracy with temporal dynamic features

A Pyrazolo[3,4-d]pyrimidine compound inhibits Fyn phosphorylation and induces apoptosis in natural killer cell leukemia

Natural killer (NK) cell neoplasms are characterized by clonal proliferation of cytotoxic NK cells. Since there is no standard treatment to date, new therapeutic options are needed, especially for NK aggressive tumors. Fyn tyrosine kinase has a key role in different biological processes, such as cell growth and differentiation, being also involved in the pathogenesis of hematologic malignancies. Our previous studies led us to identify 4c pyrazolo[3,4-d]pyrimidine compound capable of inhibiting Fyn activation and inducing apoptosis in different cancer cell lines. Here we investigated the presence of Fyn and the effect of its inhibitor in NK malignant cells. Firstly, we showed Fyn over-expression in NK leukemic cells compared to peripheral blood mononuclear cells from healthy donors. Subsequently, we demonstrated that 4c treatment reduced cell viability, induced caspase 3-mediate apoptosis and cell cycle arrest in NK cells. Moreover, by inhibiting Fyn phosphorylation, 4c compound reduced Akt and P70 S6 kinase activation and changed the expression of genes involved in cell death and survival in NK cells. Our study demonstrated that Fyn is involved in the pathogenesis of NK leukemia and that it could represent a potential target for this neoplasm. Moreover, we proved that Fyn inhibitor pyrazolo[3,4-d]pyrimidine compound, could be a started point to develop new therapeutic agents

The Opa1-Dependent Mitochondrial Cristae Remodeling Pathway Controls Atrophic, Apoptotic and Ischemic Tissue Damage

SummaryMitochondrial morphological and ultrastructural changes occur during apoptosis and autophagy, but whether they are relevant in vivo for tissue response to damage is unclear. Here we investigate the role of the optic atrophy 1 (OPA1)-dependent cristae remodeling pathway in vivo and provide evidence that it regulates the response of multiple tissues to apoptotic, necrotic, and atrophic stimuli. Genetic inhibition of the cristae remodeling pathway in vivo does not affect development, but protects mice from denervation-induced muscular atrophy, ischemic heart and brain damage, as well as hepatocellular apoptosis. Mechanistically, OPA1-dependent mitochondrial cristae stabilization increases mitochondrial respiratory efficiency and blunts mitochondrial dysfunction, cytochrome c release, and reactive oxygen species production. Our results indicate that the OPA1-dependent cristae remodeling pathway is a fundamental, targetable determinant of tissue damage in vivo

Excellent outcomes of 2G-TKI therapy after imatinib failure in chronic phase CML patients

Second-generation tyrosine kinase inhibitors (2G-TKIs) dasatinib and nilotinib produced historical rates of about 50% complete cytogenetic response (CCyR) and about 40% major molecular response (MMR) in chronic myeloid leukaemia (CML) patients failing imatinib. Direct comparisons between dasatinib and nilotinib are lacking, and few studies addressed the dynamics of deep molecular response (DMR) in a "real-life" setting. We retrospectively analyzed 163 patients receiving dasatinib (n= 95) or nilotinib (n= 68) as second-line therapy after imatinib. The two cohorts were comparable for disease's characteristics, although there was a higher rate of dasatinib use in imatinib-resistant and of nilotinib in intolerant patients. Overall, 75% patients not in CCyR and 60% patients not in MMR at 2G-TKI start attained this response. DMR was achieved by 61 patients (37.4%), with estimated rate of stable DMR at 5 years of 24%. After a median follow-up of 48 months, 60% of patients persisted on their second-line treatment. Rates and kinetics of cytogenetic and molecular responses, progression-free and overall survival were similar for dasatinib and nilotinib. In a "real-life" setting, dasatinib and nilotinib resulted equally effective and safe after imatinib failure, determining high rates of CCyR and MMR, and a significant chance of stable DMR, a prerequisite for treatment discontinuation

Mammal responses to global changes in human activity vary by trophic group and landscape

Wildlife must adapt to human presence to survive in the Anthropocene, so it is critical to understand species responses to humans in different contexts. We used camera trapping as a lens to view mammal responses to changes in human activity during the COVID-19 pandemic. Across 163 species sampled in 102 projects around the world, changes in the amount and timing of animal activity varied widely. Under higher human activity, mammals were less active in undeveloped areas but unexpectedly more active in developed areas while exhibiting greater nocturnality. Carnivores were most sensitive, showing the strongest decreases in activity and greatest increases in nocturnality. Wildlife managers must consider how habituation and uneven sensitivity across species may cause fundamental differences in human–wildlife interactions along gradients of human influence.Peer reviewe

Comparison of Slides and Video Clips as Different Methods for Inducing Emotions: An Electroencephalographic Alpha Modulation Study

Films, compared with emotional static pictures, represent true-to-life dynamic stimuli that are both ecological and effective in inducing an emotional response given the involvement of multimodal stimulation (i.e., visual and auditory systems). We hypothesized that a direct comparison between the two methods would have shown greater efficacy of movies, compared to standardized slides, in eliciting emotions at both subjective and neurophysiological levels. To this end, we compared these two methods of emotional stimulation in a group of 40 young adults (20 females). Electroencephalographic (EEG) Alpha rhythm (8–12 Hz) was recorded from 64 scalp sites while participants watched (in counterbalanced order across participants) two separate blocks of 45 slides and 45 clips. Each block included three groups of 15 validated stimuli classified as Erotic, Neutral and Fear content. Greater self-perceived arousal was found after the presentation of Fear and Erotic video clips compared with the same slide categories. sLORETA analysis showed a different lateralization pattern: slides induced decreased Alpha power (greater activation) in the left secondary visual area (Brodmann Area, BA, 18) to Erotic and Fear compared with the Neutral stimuli. Instead, video clips elicited reduced Alpha in the homologous right secondary visual area (BA 18) again to both Erotic and Fear contents compared with Neutral ones. Comparison of emotional stimuli showed smaller Alpha power to Erotic than to Fear stimuli in the left precuneus/posterior cingulate cortex (BA 7/31) for the slide condition, and in the left superior parietal lobule (BA 7) for the clip condition. This result matched the parallel analysis of the overlapped Mu rhythm (corresponding to the upper Alpha band) and can be interpreted as Mu/Alpha EEG suppression elicited by greater motor action tendency to Erotic (approach motivation) compared to Fear (withdrawal motivation) stimuli. Correlation analysis found lower Alpha in the left middle temporal gyrus (BA 21) associated with greater pleasantness to Erotic slides (r38 = –0.62, p = 0.009), whereas lower Alpha in the right supramarginal/angular gyrus (BA 40/39) was associated with greater pleasantness to Neutral clips (r38 = –0.69, p = 0.012). Results point to stronger emotion elicitation of movies vs. slides, but also to a specific involvement of the two hemispheres during emotional processing of slides vs. video clips, with a shift from the left to the right associative visual areas

Does Psychophysiological Predictive Anticipatory Activity Predict Real or Future Probable Events?

Background: The possibility of predicting random future events before any sensory clues by using human physiology as a dependent variable has been supported by the meta- analysis of Mossbridge et al. (2012)1 and recent \ufb01ndings by Tressoldi et al. (2011 and 2013) and Mossbridge et al. (2014) de\ufb01ned this phenomenon predictive anticipatory activity (PAA). Aim of the study: From a theoretical point of view, one interesting question is whether PAA is related to the effective, real future presentation of these stimuli or whether it is related only to the probability of their presentation. Methods: This hypothesis was tested with four experiments, two using heart rate and two using pupil dilation as dependent variables. Results: In all four experiments, both a neutral stimulus and a potentially threatening stimulus were predicted 7\u201310% above chance, independently from whether the predicted threatening stimulus was presented or not. Conclusion: These \ufb01ndings are discussed with reference to the \u201cgrandfather paradox,\u201d and some candidate explanations for this phenomena are presented