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RADIOGRAFII Un studiu recent examinează felul în care se raportează oamenii la moarte, în funcţie de credinţă ( Jong J. et al, The religious correlates of death anxiety: a systematic review and meta-analysis, 2017). Religia a fost, prin urmare, creată de oameni ca un mecanism de coping în faţa morţii – mecanism de apărare necesar şi izvorât din conflictul prezent la specia umană între instinctele de apărare puternice, similare cu ale oricăror fiinţe vii care fug din faţa unui pericol, şi conştiinţa faptului că absolut toată lumea moare, a murit şi va muri. Nu avem nicio dovadă a vieţii de apoi, avem doar mărturii ale pacienţilor în stop cardiac sau în comă al căror creier mai era încă irigat şi avem speranţa (atei sau credincioşi) că poate, totuşi, mintea noastră, ideile şi tot ceea ce am trăit ar putea să mai existe, cumva, după moarte. Dar dacă credem cu tărie în ceva doar pentru că ne dorim să fie aşa şi pentru că sună bine nu facem ca acel lucru să fie adevărat.

The paper reviews the existing literature relating to the recognition and evaluation of human capital by providing a short overview of it. Presently, accounting regulations allow for inconsistencies in the recognition and evaluation of human capital, and for this reason many dilemmas and controversies have arisen regarding this topic. The purpose of this review is to provide evidence and alternatives developed in the literature in order to help both the academic and practical environments in learning about valorization and understanding human capital.

Predictive processing (PP) stands as a predominant theoretical framework in neuroscience. While some efforts have been made to frame PP within a cognitive domain‐general network perspective, suggesting the existence of a “prediction network,” these studies have primarily focused on specific cognitive domains or functions. The question of whether a domain‐general predictive network that encompasses all well‐established cognitive domains exists remains unanswered. The present meta‐analysis aims to address this gap by testing the hypothesis that PP relies on a large‐scale network spanning across cognitive domains, supporting PP as a unified account toward a more integrated approach to neuroscience. The Activation Likelihood Estimation meta‐analytic approach was employed, along with Meta‐Analytic Connectivity Mapping, conjunction analysis, and behavioral decoding techniques. The analyses focused on prediction incongruency and prediction congruency, two conditions likely reflective of core phenomena of PP. Additionally, the analysis focused on a prediction phenomena‐independent dimension, regardless of prediction incongruency and congruency. These analyses were first applied to each cognitive domain considered (cognitive control, attention, motor, language, social cognition). Then, all cognitive domains were collapsed into a single, cross‐domain dimension, encompassing a total of 252 experiments. Results pertaining to prediction incongruency rely on a defined network across cognitive domains, while prediction congruency results exhibited less overall activation and slightly more variability across cognitive domains. The converging patterns of activation across prediction phenomena and cognitive domains highlight the role of several brain hubs unfolding within an organized large‐scale network (Dynamic Prediction Network), mainly encompassing bilateral insula, frontal gyri, claustrum, parietal lobules, and temporal gyri. Additionally, the crucial role played at a cross‐domain, multimodal level by the anterior insula, as evidenced by the conjunction and Meta‐Analytic Connectivity Mapping analyses, places it as the major hub of the Dynamic Prediction Network. Results support the hypothesis that PP relies on a domain‐general, large‐scale network within whose regions PP units are likely to operate, depending on the context and environmental demands. The wide array of regions within the Dynamic Prediction Network seamlessly integrate context‐ and stimulus‐dependent predictive computations, thereby contributing to the adaptive updating of the brain's models of the inner and external world. Predictive processing units operate within a cognitive domain‐general network encompassing bilateral insula, frontal gyri, claustrum, parietal lobules, and temporal gyri. The role played at a cross‐domain, multimodal level by the anterior insula, as evidenced by the conjunction and Meta‐Analytic Connectivity Mapping analyses, places it as the major hub of the Dynamic Prediction Network.

•A multimodal semantic control network was delineated with formal meta-analyses.•Semantic control recruits inferior and medial frontal and posterior temporal cortex.•A large extent of posterior temporal cortex was implicated and no parietal regions.•Semantic control is left-lateralised but regions show differential lateralisation.•The semantic control regions were situated in the context of the wider semantic network. Semantic control, the ability to selectively access and manipulate meaningful information on the basis of context demands, is a critical component of semantic cognition. The precise neural correlates of semantic control are disputed, with particular debate surrounding parietal involvement, the spatial extent of the posterior temporal contribution and network lateralisation. Here semantic control is revisited, utilising improved analysis techniques and a decade of additional data to refine our understanding of the network. A meta-analysis of 925 peaks over 126 contrasts illuminated a left-focused network consisting of inferior frontal gyrus, posterior middle temporal gyrus, posterior inferior temporal gyrus and dorsomedial prefrontal cortex. This extended the temporal region implicated, and found no parietal involvement. Although left-lateralised overall, relative lateralisation varied across the implicated regions. Supporting analyses confirmed the multimodal nature of the semantic control network and situated it within the wider set of regions implicated in semantic cognition.