7 research outputs found

    Representation of foreseeable choice outcomes in orbitofrontal cortex triplet-wise interactions.

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    Shared neuronal variability has been shown to modulate cognitive processing. However, the relationship between shared variability and behavioral performance is heterogeneous and complex in frontal areas such as the orbitofrontal cortex (OFC). Mounting evidence shows that single-units in OFC encode a detailed cognitive map of task-space events, but the existence of a robust neuronal ensemble coding for the predictability of choice outcome is less established. Here, we hypothesize that the coding of foreseeable outcomes is potentially unclear from the analysis of units activity and their pairwise correlations. However, this code might be established more conclusively when higher-order neuronal interactions are mapped to the choice outcome. As a case study, we investigated the trial-to-trial shared variability of neuronal ensemble activity during a two-choice interval-discrimination task in rodent OFC, specifically designed such that a lose-switch strategy is optimal by repeating the rewarded stimulus in the upcoming trial. Results show that correlations among triplets are higher during correct choices with respect to incorrect ones, and that this is sustained during the entire trial. This effect is not observed for pairwise nor for higher than third-order correlations. This scenario is compatible with constellations of up to three interacting units assembled during trials in which the task is performed correctly. More interestingly, a state-space spanned by such constellations shows that only correct outcome states that can be successfully predicted are robust over 100 trials of the task, and thus they can be accurately decoded. However, both incorrect and unpredictable outcome representations were unstable and thus non-decodeable, due to spurious negative correlations. Our results suggest that predictability of successful outcomes, and hence the optimal behavioral strategy, can be mapped out in OFC ensemble states reliable over trials of the task, and revealed by sufficiency complex neuronal interactions

    On the Potential of Neuroeconomics: A Critical (but Hopeful) Appraisal

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    This paper evaluates the prospects for the emerging field of neuroeconomics to shed light on traditional positive and normative economic questions. It argues that the potential for meaningful contributions, though often misunderstood and frequently overstated, is nevertheless present.

    Discovering Causal Relations and Equations from Data

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    Physics is a field of science that has traditionally used the scientific method to answer questions about why natural phenomena occur and to make testable models that explain the phenomena. Discovering equations, laws and principles that are invariant, robust and causal explanations of the world has been fundamental in physical sciences throughout the centuries. Discoveries emerge from observing the world and, when possible, performing interventional studies in the system under study. With the advent of big data and the use of data-driven methods, causal and equation discovery fields have grown and made progress in computer science, physics, statistics, philosophy, and many applied fields. All these domains are intertwined and can be used to discover causal relations, physical laws, and equations from observational data. This paper reviews the concepts, methods, and relevant works on causal and equation discovery in the broad field of Physics and outlines the most important challenges and promising future lines of research. We also provide a taxonomy for observational causal and equation discovery, point out connections, and showcase a complete set of case studies in Earth and climate sciences, fluid dynamics and mechanics, and the neurosciences. This review demonstrates that discovering fundamental laws and causal relations by observing natural phenomena is being revolutionised with the efficient exploitation of observational data, modern machine learning algorithms and the interaction with domain knowledge. Exciting times are ahead with many challenges and opportunities to improve our understanding of complex systems.Comment: 137 page

    RNA, the Epicenter of Genetic Information

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    The origin story and emergence of molecular biology is muddled. The early triumphs in bacterial genetics and the complexity of animal and plant genomes complicate an intricate history. This book documents the many advances, as well as the prejudices and founder fallacies. It highlights the premature relegation of RNA to simply an intermediate between gene and protein, the underestimation of the amount of information required to program the development of multicellular organisms, and the dawning realization that RNA is the cornerstone of cell biology, development, brain function and probably evolution itself. Key personalities, their hubris as well as prescient predictions are richly illustrated with quotes, archival material, photographs, diagrams and references to bring the people, ideas and discoveries to life, from the conceptual cradles of molecular biology to the current revolution in the understanding of genetic information. Key Features Documents the confused early history of DNA, RNA and proteins - a transformative history of molecular biology like no other. Integrates the influences of biochemistry and genetics on the landscape of molecular biology. Chronicles the important discoveries, preconceptions and misconceptions that retarded or misdirected progress. Highlights major pioneers and contributors to molecular biology, with a focus on RNA and noncoding DNA. Summarizes the mounting evidence for the central roles of non-protein-coding RNA in cell and developmental biology. Provides a thought-provoking retrospective and forward-looking perspective for advanced students and professional researchers

    CONECTAREA ÎNTREPRINDERII LA MEDIUL PRODUCTIV MODERN

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    Managementul, marketingul, calitatea resurselor de intrare, sistemul informatic si cel informational pot fi perfectionate însa viitorul performant al productiei este asigurat de transformarile (schimbarile) tehnologice, a caror infuzie modifica parametrii finali ai modelului productiv-economic. Mediul exterior întreprinderii poate fi a) stabil (evolutii „linistite”, adaptabilitate facila, b) instabil (cu frecvente modificari în componentele sale sau c) turbulent (ostil întreprinderii).mediul productiv modern; modelul productiv-economic
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