
A Neural Circuit Framework for Economic Choice This repository contains the code associated with the manuscript: A neural circuit framework for economic choice: from building blocks of valuation to compositionality in multitasking Aldo Battista, Camillo Padoa-Schioppa, and Xiao-Jing Wang bioRxiv (2025) Description This project provides the computational models and simulated data used to investigate the neural circuit mechanisms of value-based decision-making. Code The repository includes two primary Python scripts: network_training.py: This script contains the code to train the recurrent neural network model on the economic choice tasks described in the paper. data_generation.py: This script loads the pre-trained network models and generates the behavioral and neural activity data used for all analyses and figures presented in the paper. Citation If you use this code or data in your research, please cite our paper: [Battista, Aldo, Camillo Padoa-Schioppa, and Xiao-Jing Wang. "A Neural Circuit Framework for Economic Choice: From Building Blocks of Valuation to Compositionality in Multitasking." bioRxiv (2025).]
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
