RESUMEN
Research on infodemics, i.e., the rapid spread of (mis)information related to a hazardous event, such as the COVID-19 pandemic, requires integrating a multiplicity of scientific disciplines. The dynamics emerging from infodemics have the potential to generate complex behavioral patterns. To react appropriately, it is of ultimate importance for the fields of Business and Economics to understand these dynamics. In the short run, they might lead to an adaptation in household spending or to a shift in buying behavior towards online providers. In the long run, changes in investments, consumer behavior, and markets are to be expected. We argue that the dynamics emerge from complex interactions among multiple factors, such as information and misinformation accessible to individuals and the formation and revision of beliefs. (Mis)information accessible to individuals is, amongst others, affected by algorithms specifically designed to provide personalized information, while automated fact-checking algorithms can help reduce the amount of circulating misinformation. The formation and revision of individual (and probably false) beliefs and individual fact-checking and interpretation of information are heavily affected by linguistic patterns inherent to information during pandemics and infodemics and further factors, such as affect, intuition, and motives. We argue that, to get a deep(er) understanding of the dynamics emerging from infodemics, the fields of Business and Economics should integrate the perspectives of Computer Science and Information Systems, (Computational) Linguistics, and Cognitive Science into the wider context of economic systems (e.g., organizations, markets or industries) and propose a way to do so. As research on infodemics is a strongly interdisciplinary field and the integration of the above-mentioned disciplines is a first step towards a holistic approach, we conclude with a call to action which should encourage researchers to collaborate across scientific disciplines and unfold collective creativity, which will substantially advance research on infodemics.
RESUMEN
Modern electron microscopy (EM) such as fine-scale transmission EM, focused ion beam scanning EM, and EM tomography have enormously improved our knowledge about the synaptic organization of the normal, developmental, and pathologically altered brain. In contrast to various animal species, comparably little is known about these structures in the human brain. Non-epileptic neocortical access tissue from epilepsy surgery was used to generate quantitative 3D models of synapses. Beside the overall geometry, the number, size, and shape of active zones and of the three functionally defined pools of synaptic vesicles representing morphological correlates for synaptic transmission and plasticity were quantified. EM tomography further allowed new insights in the morphological organization and size of the functionally defined readily releasable pool. Beside similarities, human synaptic boutons, although comparably small (approximately 5 µm), differed substantially in several structural parameters, such as the shape and size of active zones, which were on average 2 to 3-fold larger than in experimental animals. The total pool of synaptic vesicles exceeded that in experimental animals by approximately 2 to 3-fold, in particular the readily releasable and recycling pool by approximately 2 to 5-fold, although these pools seemed to be layer-specifically organized. Taken together, synaptic boutons in the human temporal lobe neocortex represent unique entities perfectly adapted to the "job" they have to fulfill in the circuitry in which they are embedded. Furthermore, the quantitative 3D models of synaptic boutons are useful to explain and even predict the functional properties of synaptic connections in the human neocortex.