Identifying control ensembles for information processing within the cortico-basal ganglia-thalamic circuit
Catalina Vich1,2, Matthew Clapp3,4, Jonathan E Rubin4,5
1Dept. de Matemàtiques i Informàtica, Universitat de les Illes Balears, Palma, Spain.
Plos Computational Biology
|June 23, 2022
Summary
Mammals flexibly adjust decision-making strategies under uncertainty. This study reveals three key cortico-basal ganglia-thalamic network control ensembles influencing decision speed, evidence requirements, and choice commitment.
Area of Science:
- Neuroscience
- Computational Neuroscience
- Decision Science
Background:
- Mammalian decision-making under uncertainty involves flexible strategy adoption.
- The cortico-basal ganglia-thalamic (CBGT) network is crucial for decision-making.
- CBGT network complexity hinders understanding of specific population roles in evidence accumulation.
Purpose of the Study:
- To explore how CBGT network properties influence decision-making parameters.
- To map variations in CBGT network properties to a normative drift diffusion model (DDM).
- To identify control ensembles within the CBGT network that shape decision policies.
Main Methods:
- Applied a strategic sampling approach using Latin hypercube sampling.
- Investigated variations in CBGT subpopulation firing rates and synaptic weights.
- Utilized canonical correlation analysis to link network properties to DDM parameters.
Main Results:
- Identified three low-dimensional control ensembles within the CBGT network.
- Responsiveness is linked to corticothalamic and direct pathway activity.
- Pliancy relates to indirect pathway activity; choice relates to pathway differences across action channels.
Conclusions:
- Specific CBGT network elements critically tune evidence accumulation and behavioral output.
- Mechanistic predictions are provided for the roles of CBGT network components in decision-making.
- Understanding these ensembles offers insights into flexible decision-making under uncertainty.
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