Learning and representation of hierarchical concepts in hippocampus and prefrontal cortex

A key aspect of conceptual knowledge is that it can be flexibly applied at different levels of abstraction, implying a hierarchical organization. It is yet unclear how this hierarchical structure is acquired and represented in the brain. Here we investigate the computations underlying the acquisition and representation of the hierarchical structure of conceptual knowledge in the hippocampal-prefrontal system of 32 human participants (22 females). We assessed the hierarchical nature of learning during a novel tree-like categorization task via computational model comparisons. The winning model allowed to extract and quantify estimates for accumulation and updating of hierarchical compared with single-feature-based concepts from behavior. We find that mPFC tracks accumulation of hierarchical conceptual knowledge over time, and mPFC and hippocampus both support trial-to-trial updating. As a function of those learning parameters, mPFC and hippocampus further show connectivity changes to rostro-lateral PFC, which ultimately represented the hierarchical structure of the concept in the final stages of learning. Our results suggest that mPFC and hippocampus support the integration of accumulated evidence and instantaneous updates into hierarchical concept representations in rostro-lateral PFC.SIGNIFICANCE STATEMENT A hallmark of human cognition is the flexible use of conceptual knowledge at different levels of abstraction, ranging from a coarse category level to a fine-grained subcategory level. While previous work probed the representational geometry of long-term category knowledge, it is unclear how this hierarchical structure inherent to conceptual knowledge is acquired and represented. By combining a novel hierarchical concept learning task with computational modeling of categorization behavior and concurrent fMRI, we differentiate the roles of key concept learning regions in hippocampus and PFC in learning computations and the representation of a hierarchical category structure

A Stochastic Description of Dictyostelium Chemotaxis

Chemotaxis, the directed motion of a cell toward a chemical source, plays a key role in many essential biological processes. Here, we derive a statistical model that quantitatively describes the chemotactic motion of eukaryotic cells in a chemical gradient. Our model is based on observations of the chemotactic motion of the social ameba Dictyostelium discoideum, a model organism for eukaryotic chemotaxis. A large number of cell trajectories in stationary, linear chemoattractant gradients is measured, using microfluidic tools in combination with automated cell tracking. We describe the directional motion as the interplay between deterministic and stochastic contributions based on a Langevin equation. The functional form of this equation is directly extracted from experimental data by angle-resolved conditional averages. It contains quadratic deterministic damping and multiplicative noise. In the presence of an external gradient, the deterministic part shows a clear angular dependence that takes the form of a force pointing in gradient direction. With increasing gradient steepness, this force passes through a maximum that coincides with maxima in both speed and directionality of the cells. The stochastic part, on the other hand, does not depend on the orientation of the directional cue and remains independent of the gradient magnitude. Numerical simulations of our probabilistic model yield quantitative agreement with the experimental distribution functions. Thus our model captures well the dynamics of chemotactic cells and can serve to quantify differences and similarities of different chemotactic eukaryotes. Finally, on the basis of our model, we can characterize the heterogeneity within a population of chemotactic cells

The hippocampus maps concept space, not feature space

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Rôle des vétérinaires dans la production du vaccin antivariolique en Belgique

Soon after the discovery of the smallpox vaccine by Edward Jenner in 1798, Guillaume De Manet, a physician from Ghent, used it in Belgium to protect his patients against smallpox. Unfortunately, this was only an isolated case and we have to wait until 1865 for doctor Warlomont of Brussels to import from France a heifer inoculated by the Italian vaccinal strain, which was perfected by Negri. The private institute founded by Warlomont became Belgian state property as early as 1868 and the institute was transferred at the Veterinary School of Cureghem in 1882 under the name of «Office vaccinogène central de l'Etat». For personal reasons, Warlomont refused the directorship of the new institute and this responsibility felt to Professor Degive, then in charge of the «Clinique des grands animaux». Warlomont did not disclose his production method of the vaccine and Degive had to create new techniques. When the School of Cureghem established itself in its new buildings in 1909-10, a special and totally isolated wing was built for the «Office vaccinogène» according to the norms established by Degive. It worked until 1965, when the Office was transferred in the rooms of the «Institut d'Hygiène et d'Epidémiologie». Since 1882, the production of the smallpox vaccine has continually been under the responsibility of veterinary surgeons. The directors of the «Office vaccinogène» were successively: Alphonse Degive, Guillaume Antoine, Charles Van Goidsenhoven, Fernand Schoenaers and Louis Bugyaki