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TermX is an open-source knowledge management and sharing platform, including a terminology server, a Wiki, a model designer, a transformation editor, and tools for authoring and publishing. The core development goals of TermX were to enhance the semantic interoperability of software and systems, particularly within the healthcare sector, by improving access to terminology, simplifying the design of data models, optimising the efficiency of data transformations across various data models, and developing implementation guides through an intuitive web interface. TermX aims to guarantee open and standardised access to published terminology, data models and schemas, ensuring semantic interoperability following the FHIR standard or other standards or agreements.

A central question in behavioural neuroscience is how different rewards modulate learning. While the role of monetary rewards is well-studied in decision-making research, the influence of abstract rewards like music remains poorly understood. This study investigated the dissociable effects of these two reward types on decision making. Forty participants completed two decision-making tasks, each characterised by probabilistic associations between stimuli and rewards, with probabilities changing over time to reflect environmental volatility. In each task, choices were reinforced either by monetary outcomes (win/lose) or by the endings of musical melodies (consonant/dissonant). We applied the Hierarchical Gaussian Filter, a validated hierarchical Bayesian framework, to model learning under these two conditions. Bayesian statistics provided evidence for similar learning patterns across both reward types, suggesting individuals’ similar adaptability. However, within the musical task, individual preferences for consonance over dissonance explained some aspects of learning. Specifically, correlation analyses indicated that participants more tolerant of dissonance behaved more stochastically in their belief-to-response mappings and were less likely to choose the response associated with the current prediction for a consonant ending, driven by higher volatility estimates. By contrast, participants averse to dissonance showed increased tonic volatility, leading to larger updates in reward tendency beliefs.