Coding of self and other's future choices in dorsal premotor cortex during social interaction

Representing others’ intentions is central to primate social life. We explored the role of dorsal premotor cortex (PMd) in discriminating between self and others’ behavior while two male rhesus monkeys performed a non-match-to-goal task in a monkey-human paradigm. During each trial, two of four potential targets were randomly presented on the right and left parts of a screen, and the monkey or the human was required to choose the one that did not match the previously chosen target. Each agent had to monitor the other's action in order to select the correct target in that agent's own turn. We report neurons that selectively encoded the future choice of the monkey, the human agent, or both. Our findings suggest that PMd activity shows a high degree of self-other differentiation during face-to-face interactions, leading to an independent representation of what others will do instead of entailing self-centered mental rehearsal or mirror-like activities. Understanding others’ intentions is essential to successful primate social life. Cirillo et al. explore the role of dorsal premotor cortex (PMd) in discriminating between self and others’ behavior while macaques interacted with humans. They show that the majority of neurons encoding the future choice did so selectively for the monkey or the human agent. PMd thus differentiates self from others’ behavior, leading to independent representations of future actions

El niño abusado se convierte en adulto: reflexiones sobre algunos casos tratados

Este artículo es la traducción del titulado “Il bambino abusato diventa adulto”, publicado en el número 91 de la revista Terapia Familiare (noviembre 2009, páginas 161-182). Traducción de Valentina Capecci, Gonzalo del Moral y Miguel Garrido.El autor analiza algunos casos clínicos para reflexionar sobre diferentes resultados que la experiencia del abuso sexual sufrido en la infancia puede tener en la influencia del desarrollo de un sujeto de sexo masculino. Se proponen tres distintas posibilidades que se pueden detectar en la población clínica. La clásica trasformación de víctima a agresor, la persistencia, por el contrario, en la posición de víctima y aquella del espectador relativa a los hermanos varones de víctimas de sexo femenino. Los recursos ofrecidos por el modelo de apego (ofrecido por el progenitor protector, y también por el mismo abusador) en relación a la dimensión del miedo suscitado por el evento traumático juegan un papel determinante en la dirección que puede tomar la evolución del niño abusado.The author analyzes some cases clinicians to reflect on different results than the experience of the sexual abuse suffered in childhood can have on the influence of development of a male subject. Proposed three different possibilities that are they can detect in the clinical population. The classical transformation of victim to aggressor, the persistence, on the contrary, in the position of victim and one the relative to the victims of female male brothers spectator. The resources offered by the attachment (offered by the parent) model (guard, and also by the same abuser) in relation to the dimension of the fear aroused by the traumatic event play a decisive role in the address that can take the evolution of the abused child

Social network data analysis to highlight privacy threats in sharing data

AbstractSocial networks are a vast source of information, and they have been increasing impact on people's daily lives. They permit us to share emotions, passions, and interactions with other people around the world. While enabling people to exhibit their lives, social networks guarantee their privacy. The definitions of privacy requirements and default policies for safeguarding people's data are the most difficult challenges that social networks have to deal with. In this work, we have collected data concerning people who have different social network profiles, aiming to analyse privacy requirements offered by social networks. In particular, we have built a tool exploiting image-recognition techniques to recognise a user from his/her picture, aiming to collect his/her personal data accessible through social networks where s/he has a profile. We have composed a dataset of 5000 users by combining data available from several social networks; we compared social network data mandatory in the registration phases, publicly accessible and those retrieved by our analysis. We aim to analyse the amount of extrapolated data for evaluating privacy threats when users share information on different social networks to help them be aware of these aspects. This work shows how users data on social networks can be retrieved easily by representing a clear privacy violation. Our research aims to improve the user's awareness concerning the spreading and managing of social networks data. To this end, we highlighted all the statistical evaluations made over the gathered data for putting in evidence the privacy issues

Assessment of oppositional defiant disorder and oppositional behavior in children and adolescents with Down syndrome

IntroductionChildren and adolescents with intellectual disability (ID) exhibit higher rates of oppositional defiant disorder (ODD) than typically developing (TD) peers. However, studies focusing on the investigation of ODD prevalence in youth with Down syndrome (DS) are still limited.MethodsThe current study aimed to investigate the prevalence of ODD clinical and subclinical symptoms in a group of 101 youth with DS (63 boys, 38 girls) ranging in age from 6 to 18 years. Moreover, the prevalence of ODD symptoms, as detected by means of three parent-report questionnaires, was compared with that detected by a semi-structured psychopathological interview, namely, the Schedule for Affective Disorders and Schizophrenia for School Aged Children Present and Lifetime (K-SADS) Version Diagnostic and Statistical Manual of Mental Disorders-5 (DSM-5).ResultsWe found that 17% of participants met diagnostic criteria for ODD on the K-SADS, whereas 24% exhibited subclinical symptoms. Results also suggest good specificity of Swanson, Nolan, and Pelham-IV Rating Scale (SNAP-IV), Conners’ Parent Rating Scales Long Version (CPRS) and Child Behavior Checklist (CBCL) in detecting ODD symptoms. The investigation of the agreement in the prevalence rates of clinical and subclinical symptoms of ODD between K-SADS and the parent-report questionnaires indicated CPRS as the parent-report questionnaire with the best agreement with K-SADS.DiscussionThis study provides support for the use of parent-report questionnaires to assess ODD symptoms in children and adolescents with DS by evaluating their levels of agreement with a semi-structured psychopathological interview. In particular, our results suggest that CPRS could be considered a suitable screening tool for ODD clinical and subclinical symptoms in youth with DS

MRI-based radiomics to predict response in locally advanced rectal cancer: comparison of manual and automatic segmentation on external validation in a multicentre study

Background: Pathological complete response after neoadjuvant chemoradiotherapy in locally advanced rectal cancer (LARC) is achieved in 15–30% of cases. Our aim was to implement and externally validate a magnetic resonance imaging (MRI)-based radiomics pipeline to predict response to treatment and to investigate the impact of manual and automatic segmentations on the radiomics models. Methods: Ninety-five patients with stage II/III LARC who underwent multiparametric MRI before chemoradiotherapy and surgical treatment were enrolled from three institutions. Patients were classified as responders if tumour regression grade was 1 or 2 and nonresponders otherwise. Sixty-seven patients composed the construction dataset, while 28 the external validation. Tumour volumes were manually and automatically segmented using a U-net algorithm. Three approaches for feature selection were tested and combined with four machine learning classifiers. Results: Using manual segmentation, the best result reached an accuracy of 68% on the validation set, with sensitivity 60%, specificity 77%, negative predictive value (NPV) 63%, and positive predictive value (PPV) 75%. The automatic segmentation achieved an accuracy of 75% on the validation set, with sensitivity 80%, specificity 69%, and both NPV and PPV 75%. Sensitivity and NPV on the validation set were significantly higher (p = 0.047) for the automatic versus manual segmentation. Conclusion: Our study showed that radiomics models can pave the way to help clinicians in the prediction of tumour response to chemoradiotherapy of LARC and to personalise per-patient treatment. The results from the external validation dataset are promising for further research into radiomics approaches using both manual and automatic segmentations