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Recorded neural data from: Nonlinear feedback modulation contributes to the optimization of flexible decision-making

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DataONE2025-09-30 更新2025-10-04 收录
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Neural activity in the primate brain correlates with both sensory evaluation and action selection aspects of decision-making. However, the intricate interaction between these distinct neural processes and their impact on decision behaviors remains unexplored. Here, we examined the interplay of these decision processes in the posterior parietal cortex (PPC) when monkeys performed a flexible decision task. We found that the PPC activity related to monkeys’ abstract decisions about visual stimuli was nonlinearly modulated by monkeys’ following saccade choices directed outside each neuron’s response field. Recurrent neural network modeling suggested that the feedback connections, which matched the learned stimulus-response associations during the task, might mediate such feedback modulation. Further analysis on network dynamics revealed that selectivity-specific feedback connectivity intensified the attractor basins of population activity underlying saccade choices, thereby increasing the r..., , # Recorded neural data from: Nonlinear feedback modulation contributes to the optimization of flexible decision-making This dataset contains the recorded single-neuron data from two macaque monkeys on a reaction-time version of the flexible visual-motion discrimination (FVMD) task. This dataset is used in the study [https://doi.org/10.7554/eLife.96402.2](https://doi.org/10.7554/eLife.96402.2). #### Description of the data and file structure Files are stored in MATLAB (.mat) format #### File Naming Each file contains neural recording data from one session of motion discrimination experiments. The files are named according to: `MONKEY_DM_CO_YYYYMMDD_SESSION.mat` Where: * **MONKEY**: Subject identifier * \"Bootsy\": First monkey subject * \"Meceo\": Second monkey subject * **DM**: Motion discrimination task * **CO**: Coherence task variant * **YYYYMMDD**: Recording date (Year-Month-Day) * **SESSION**: Session number for that day For example, `Bootsy_DM_CO_20180502_2.mat` indicates...,
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2025-10-01
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