A Neuro-computational Account of Arbitration between Choice Imitation and Goal Emulation during Human Observational Learning

When individuals learn from observing the behavior of others, they deploy at least two distinct strategies. Choice imitation involves repeating other agents’ previous actions, whereas emulation proceeds from inferring their goals and intentions. Despite the prevalence of observational learning in humans and other social animals, a fundamental question remains unaddressed: how does the brain decide which strategy to use in a given situation? In two fMRI studies (the second a pre-registered replication of the first), we identify a neuro-computational mechanism underlying arbitration between choice imitation and goal emulation. Computational modeling, combined with a behavioral task that dissociated the two strategies, revealed that control over behavior was adaptively and dynamically weighted toward the most reliable strategy. Emulation reliability, the model’s arbitration signal, was represented in the ventrolateral prefrontal cortex, temporoparietal junction, and rostral cingulate cortex. Our replicated findings illuminate the computations by which the brain decides to imitate or emulate others

A Review of Energy Models. No. 3 (Special Issue on Soviet Models)

The experience of the USSR in the field of energy systems development modeling reveals certain patterns and principles that influence the structure and use of energy models, principally: -- The need to use mainly optimization models since, for planning purposes, optimal solutions must be found; -- The need to coordinate individual models in order to obtain the country's objectives; -- The existing organizational structure of planning which must be taken into account; -- The dependence of models on time aspects of planning (annual, 5-year, 15-year); -- The elaboration of corresponding methods for providing necessary input data. This has required the development of a special concept for optimizing energy systems development with the use of mathematical models. It is based on consideration of the energy industries of the country as complex with a hierarchical structure of energy systems of various territorial and branch levels. At the same time, the differentiation of aims at different times during the planning period have been taken into account. This concept is given here in its existing state (it is continuously developed and perfected) for better understanding of the energy models described. In particular, we show the role of the system of models for optimization of the energy supply system as a whole, and that of more detailed branch models (oil, gas, coal, electricity production systems). For optimal energy strategy evaluation, the most important models are those used on the highest levels of the energy systems hierarchy, i.e. the general (aggregate) energy systems of the country and of economic regions, and branch energy systems. Only these models are described here; models used on lower levels for solving some technical problems are far more diverse and numerous, and it is impossible to consider them all in a single review

A Review of Energy Models No.4 - July 1978

This review is the fourth in the IIASA series A REVIEW OF ENERGY MODELS (RR-74-10, No. 1 of May 1974 as revised in September 1976; RR-75-30, No. 2 of July 1975; and RR-77-13, No. 3, Special Issue of Soviet Models), which aims at wider diffusion of energy modeling work in progress at other institutions. Fourteen models are described in this issue and again classified in terms of substance and geographical applicability with further subdivision into groups corresponding to model user requirements: the majority of the models focus on the energy problem; they are mostly national ones involving either one or several kinds of fuel; six other models, both international and national, combine energy and overall economic aspects; they may be of particular interest for a more global consideration of energy problems

Neuro-computational account of arbitration between imitation and emulation during human observational learning

In observational learning (OL), organisms learn from observing the behavior of others. There are at least two distinct strategies for OL. Imitation involves learning to repeat the previous actions of other agents, while in emulation, learning proceeds from inferring the goals and intentions of others. While putative neural correlates for these forms of learning have been identified, a fundamental question remains unaddressed: how does the brain decides which strategy to use in a given situation? Here we developed a novel computational model in which arbitration between the strategies is determined by the predictive reliability, such that control over behavior is adaptively weighted toward the strategy with the most reliable prediction. To test the theory, we designed a novel behavioral task in which our experimental manipulations produced dissociable effects on the reliability of the two strategies. Participants performed this task while undergoing fMRI in two independent studies (the second a pre-registered replication of the first). Behavior manifested patterns consistent with both emulation and imitation and flexibly changed between the two strategies as expected from the theory. Computational modelling revealed that behavior was best described by an arbitration model, in which the reliability of the emulation strategy determined the relative weights allocated to behavior for each strategy. Emulation reliability - the model's arbitration signal - was encoded in the ventrolateral prefrontal cortex, temporoparietal junction and rostral cingulate cortex. Being replicated across two fMRI studies, these findings suggest a neuro-computational mechanism for allocating control between emulation and imitation during observational learning

Influence of Topological Edge States on the Properties of Al/Bi2Se3/Al Hybrid Josephson Devices

In superconductor-topological insulator-superconductor hybrid junctions, the barrier edge states are expected to be protected against backscattering, to generate unconventional proximity effects, and, possibly, to signal the presence of Majorana fermions. The standards of proximity modes for these types of structures have to be settled for a neat identification of possible new entities. Through a systematic and complete set of measurements of the Josephson properties we find evidence of ballistic transport in coplanar Al-Bi2Se3-Al junctions that we attribute to a coherent transport through the topological edge state. The shunting effect of the bulk only influences the normal transport. This behavior, which can be considered to some extent universal, is fairly independent of the specific features of superconducting electrodes. A comparative study of Shubnikov - de Haas oscillations and Scanning Tunneling Spectroscopy gave an experimental signature compatible with a two dimensional electron transport channel with a Dirac dispersion relation. A reduction of the size of the Bi2Se3 flakes to the nanoscale is an unavoidable step to drive Josephson junctions in the proper regime to detect possible distinctive features of Majorana fermions.Comment: 11 pages, 14 figure