ArticleNeuroinformatics2022
A Computational Neural Model for Mapping Degenerate Neural Architectures.
Article in Neuroinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Neural Predictors of Fear Depend on the Situation.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
- Fear-related psychophysiological patterns are situation and individual dependent: A Bayesian model comparison approach.Emotion (Washington, D.C.) · 2024Article
- Improving the study of brain-behavior relationships by revisiting basic assumptions.Trends in cognitive sciences · 2023Review
- Predictive processing models and affective neuroscience.Neuroscience and biobehavioral reviews · 2021Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Degeneracy in biological systems refers to a many-to-one mapping between physical structures and their functional (including psychological) outcomes. Despite the ubiquity of the phenomenon, traditional analytical tools for modeling degeneracy in neuroscience are extremely limited. In this study, we generated synthetic datasets to describe three situations of degeneracy in fMRI data to demonstrate the limitations of the current univariate approach. We describe a novel computational approach for the analysis referred to as neural topographic factor analysis (NTFA). NTFA is designed to capture variations in neural activity across task conditions and participants. The advantage of this discovery-oriented approach is to reveal whether and how experimental trials and participants cluster into task conditions and participant groups. We applied NTFA on simulated data, revealing the appropriate degeneracy assumption in all three situations and demonstrating NTFA's utility in uncovering degeneracy. Lastly, we discussed the importance of testing degeneracy in fMRI data and the implications of applying NTFA to do so.
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Registered trials
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