ArticlePLoS computational biology2021
Excitatory-inhibitory tone shapes decision strategies in a hierarchical neural network model of multi-attribute choice.
Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 24 citations in OpenAlex.
- Attention and learning strategies reveal distinct dimensions of psychiatric diseases.Research square · 2026Article
- Contributions of Attention to Learning in Multidimensional Reward Environments.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Broadscale dampening of uncertainty adjustment in the aging brain.Nature communications · 2024Article
- Measuring excitation-inhibition balance through spectral components of local field potentials.bioRxiv : the preprint server for biology · 2024Article
- The competition dynamics of approach and avoidance motivations following interpersonal transgression.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- The impact of the human thalamus on brain-wide information processing.Nature reviews. Neuroscience · 2023Review
- Relating local connectivity and global dynamics in recurrent excitatory-inhibitory networks.PLoS computational biology · 2023Article
- Orbitofrontal cortex contributes to the comparison of values underlying economic choices.Nature communications · 2022Article
- Article
- Article
- Thalamocortical excitability modulation guides human perception under uncertainty.Nature communications · 2021Article
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Authors and funding
4 authors at 2 institutions in 1 country.
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Abstract
We are constantly faced with decisions between alternatives defined by multiple attributes, necessitating an evaluation and integration of different information sources. Time-varying signals in multiple brain areas are implicated in decision-making; but we lack a rigorous biophysical description of how basic circuit properties, such as excitatory-inhibitory (E/I) tone and cascading nonlinearities, shape attribute processing and choice behavior. Furthermore, how such properties govern choice performance under varying levels of environmental uncertainty is unknown. We investigated two-attribute, two-alternative decision-making in a dynamical, cascading nonlinear neural network with three layers: an input layer encoding choice alternative attribute values; an intermediate layer of modules processing separate attributes; and a final layer producing the decision. Depending on intermediate layer E/I tone, the network displays distinct regimes characterized by linear (I), convex (II) or concave (III) choice indifference curves. In regimes I and II, each option's attribute information is additively integrated. In regime III, time-varying nonlinear operations amplify the separation between offer distributions by selectively attending to the attribute with the larger differences in input values. At low environmental uncertainty, a linear combination most consistently selects higher valued alternatives. However, at high environmental uncertainty, regime III is more likely than a linear operation to select alternatives with higher value. Furthermore, there are conditions where readout from the intermediate layer could be experimentally indistinguishable from the final layer. Finally, these principles are used to examine multi-attribute decisions in systems with reduced inhibitory tone, leading to predictions of different choice patterns and overall performance between those with restrictions on inhibitory tone and neurotypicals.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.