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Background: Attachment theory represents one of the most important references for the study of the development of an individual throughout their life cycle and provides the clinician with a profound key for the purposes of understanding the suffering that underlies severe psychopathologies such as eating disorders. As such, we conducted a cross-sectional study with a mixed-methods analysis on a sample of 32 young women with anorexia nervosa (AN); this study was embedded in the utilized theoretical framework with the following aims: 1. to evaluate the state of mind (SoM) in relation to adult attachment, assuming a prevalence of the dismissing (DS) SoM and 2. to analyze the linguistic attachment profile emerging from the transcripts of the AAIs. Methods: Interviews were transcribed verbatim, coded, and analyzed using the linguistic inquiry and word count (LIWC) method. Results: The results were observed to be consistent with the referenced literature. The prevalence of a DS SoM (68.75%) is observed in the study sample, whereas the results of the lexical analysis of the stories deviate from expectations. Notably, the lexical results indicate the coexistence of the dismissing and entangled aspects at the representational level. Conclusions: The study results suggest a high level of specificity in the emotional functioning of patients with AN, with a focusing on a pervasive control of emotions that is well illustrated by the avoidant/ambivalent (A/C) strategy described in Crittenden’s dynamic–maturational model. These findings and considerations have important implications for clinical work and treatment, which we believe must be structured on the basis of starting from a reappraisal of emotional content.

Although sensory processing is pivotal to nearly every theory of emotion, the evaluation of the visual input as ‘emotional’ (e.g. a smile as signalling happiness) has been traditionally assumed to take place in supramodal ‘limbic’ brain regions. Accordingly, subcortical structures of ancient evolutionary origin that receive direct input from the retina, such as the superior colliculus (SC), are traditionally conceptualized as passive relay centres. However, mounting evidence suggests that the SC is endowed with the necessary infrastructure and computational capabilities for the innate recognition and initial categorization of emotionally salient features from retinal information. Here, we built a neurobiologically inspired convolutional deep neural network (DNN) model that approximates physiological, anatomical and connectional properties of the retino-collicular circuit. This enabled us to characterize and isolate the initial computations and discriminations that the DNN model of the SC can perform on facial expressions, based uniquely on the information it directly receives from the virtual retina. Trained to discriminate facial expressions of basic emotions, our model matches human error patterns and above chance, yet suboptimal, classification accuracy analogous to that reported in patients with V1 damage, who rely on retino-collicular pathways for non-conscious vision of emotional attributes. When presented with gratings of different spatial frequencies and orientations never ‘seen’ before, the SC model exhibits spontaneous tuning to low spatial frequencies and reduced orientation discrimination, as can be expected from the prevalence of the magnocellular (M) over parvocellular (P) projections. Likewise, face manipulation that biases processing towards the M or P pathway affects expression recognition in the SC model accordingly, an effect that dovetails with variations of activity in the human SC purposely measured with ultra-high field functional magnetic res

We effortlessly sort people into different racial groups from their visual appearance and implicitly generate racial bias affecting cognition and behavior. As these mental activities provide the proximate mechanisms for social behaviours, it becomes essential to understand the neural activity underlying differences between own-race and other-race visual categorization. Yet intrinsic limitations of individual neuroimaging studies, owing to reduced sample size, inclusion of multiple races, and interactions between races in the participants and in the displayed visual stimuli, dampens generalizability of results. In the present meta-analytic study, we applied multimodal techniques to partly overcome these hurdles, and we investigated the entire functional neuroimaging literature on race categorization, therefore including more than 2000 Black, White and Asian participants. Our data-driven approach shows that own- and other-race visual categorization involves partly segregated neural networks, with distinct connectivity and functional profiles, and defined hierarchical organization. Categorization of own-race mainly engages areas related to cognitive components of empathy and mentalizing, such as the medial prefrontal cortex and the inferior frontal gyrus. These areas are functionally co-activated with cortical structures involved in auto-biographical memories and social knowledge. Conversely, other-race categorization recruits areas implicated in, and functionally connected with, visuo-attentive processing, like the fusiform gyrus and the inferior parietal lobule, and areas engaged in affective functions, like the amygdala. These results contribute to a better definition of the neural networks involved in the visual parcelling of social categories based on race, and help to situate these processes within a common neural space.