Hierarchical Bayesian Model Maps Cognitive Processes to Functional Severity
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Solution Overview
Problem
Current methods struggle to accurately map cognitive processes to functional abilities, particularly in translating latent cognitive processes into continuous measures of functional severity, which is crucial for understanding changes in cognitive and functional abilities in conditions like Alzheimer's disease.
Innovation Solution
The development of hierarchical Bayesian cognitive processing models that incorporate signal detection theory, allowing for the transformation of latent cognitive processes into continuous-valued measures of functional ability, enabling the mapping of cognitive processes to functional severity and predicting recognition memory performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If discrete functional severity measures are used to classify patients, then ease of operation is improved, but measurement precision deteriorates
Solution Approach 1:
The patent transforms the discrete functional severity measure into a continuous measure by changing the parameter representation from categorical stages to continuous cognitive process parameters (discriminability d' and response bias c). This allows for more precise measurement while maintaining clinical interpretability through the mapping function.
Solution Approach 2:
The patent introduces latent cognitive process parameters as intermediaries between observed cognitive task performance and functional severity classification. These intermediate parameters (discriminability and response bias) provide a continuous representation that bridges the gap between discrete clinical stages and underlying cognitive processes.
2Measurement precision
If latent cognitive processes are used to map to functional ability, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent replaces complex mechanical or procedural assessment systems with a statistical modeling approach. Instead of using complex clinical assessment procedures, the system uses hierarchical Bayesian cognitive processing models that can be implemented computationally, substituting mathematical modeling for complex operational procedures.
Solution Approach 2:
The patent changes the parameters from direct functional severity ratings to underlying cognitive process parameters (discriminability d' and response bias c). This parameter transformation simplifies the mapping process by focusing on fundamental cognitive dimensions that can be estimated from standard cognitive task performance.
3Ease of operation
If correlations are computed between cognitive and functional abilities, then ease of operation is improved, but loss of information increases
Solution Approach 1:
The patent introduces latent cognitive process parameters as intermediaries that preserve information about the underlying cognitive mechanisms. Instead of directly correlating observed cognitive scores with functional ratings, the model uses discriminability and response bias as intermediaries that maintain information about the cognitive processes while enabling relationship analysis.
Solution Approach 2:
The patent transforms the analysis from simple correlation of observed variables to analysis of relationships between latent cognitive parameters and functional severity. This parameter transformation preserves information about the cognitive processes by modeling them explicitly rather than using aggregate scores that lose process-specific information.
Data Source
AI summary
Methods, systems, and apparatus, including medium-encoded computer program products, for mapping cognitive to functional ability include receiving data regarding assessments of a cognitive ability and assessments of a functional ability; processing the received data to generate a map of one or more cognitive processes underlying the cognitive ability to a continuous-valued measure of the functional ability; and storing the generated map on a computer-storage medium to be used by a computer device in continuous-valued assessments of the functional ability.