Modelling neural probabilistic computation using vector symbolic architectures.

Distributed vector representations are a key bridging point between connectionist and symbolic representations in cognition. It is unclear how uncertainty should be modelled in systems using such representations. In this paper we discuss how bundles of symbols in certain Vector Symbolic Architectures (VSAs) can be understood as defining an object that has a relationship to a probability distribution, and how statements in VSAs can be understood as being analogous to probabilistic statements.

Evidentiary basis of the first regulatory qualification of a digital primary efficacy endpoint.

Stride velocity 95th centile (SV95C) is a wearable-derived endpoint representing the 5% fastest strides taken during everyday living. In July 2023, SV95C received European Medicines Agency (EMA) qualification for use as a primary endpoint in trials of patients with Duchenne muscular dystrophy (DMD) aged ≥ 4 years-becoming the first digital endpoint to receive such qualification. We present the data supporting this qualification, providing insights into the evidentiary basis of qualification as a digital clinical outcome assessment.

Healthcare Stakeholder Perspectives on a Value Assessment Approach for Duchenne Muscular Dystrophy Therapies.

Purpose: Traditional value assessment frameworks are challenged in comprehensively assessing the societal value new therapies bring to individuals with rare, progressive, genetic, fatal, neuromuscular diseases such as Duchenne muscular dystrophy (DMD). The objective of this study was to identify how value assessment frameworks may need to be adapted to measure the value to society of DMD therapies.

Patients And Methods: Three stakeholder groups (6 patient advocates, 4 clinicians, 3 health economists; N = 13) participated in semi-structured interviews around the International Society for Pharmacoeconomics and Outcomes Research's Value Flower, which includes elements to consider within value assessments of healthcare technologies.

Efficient Hyperdimensional Computing With Spiking Phasors.

Hyperdimensional (HD) computing (also referred to as vector symbolic architectures, VSAs) offers a method for encoding symbols into vectors, allowing for those symbols to be combined in different ways to form other vectors in the same vector space. The vectors and operators form a compositional algebra, such that composite vectors can be decomposed back to their constituent vectors. Many useful algorithms have implementations in HD computing, such as classification, spatial navigation, language modeling, and logic.