Bioscience Method 2024, Vol.15, No.1, 21-27 http://bioscipublisher.com/index.php/bm 23 Based on the center-out reaching experiments and linear encoding models of neural activity in Figure 3, it can be observed that the top part of the figure displays the total number of neurons for each non-human primate (NHP), while the bottom shows the total number of active (hollow bars) and passive (solid bars) trials. The screen cursor coordinates in the example session represent the end-effector trajectories during the center-out reaching, with colors indicating the target direction. The normalized firing rates of neurons in both active and passive trials are displayed in raster plots, sorted by movement direction. A pairwise comparison of the average firing rates of individual neurons under active and passive conditions was conducted for NHP S (CN) and NHP H (S1). The distribution of single-neuron test explained variance for the baseline linear encoding models was analyzed using task-related and behavioral variables, in both single-variable and multi-variable models. Figure 4 illustrates the task-driven neural network models predicting neural dynamics during active and passive movements. Time-varying neural predictions for active (top) and passive (bottom) movements were tested on sample units in CN and S1, showing a comparison between experimental spike firing rates (black lines) and predictions (colored lines) based on the best-predicting layer of a 12-layer spatial-temporal neural network model. An example distribution analysis of single-neuron explainability across all NHPs and types of movements was conducted. Statistical significance was calculated using the Wilcoxon signed-rank test. The explained variance between well-trained models and linear models was compared, highlighting that task-driven models provide higher neural explainability compared to data-driven models, especially in active movements. Figure 3 Center-out reaching experiments and linear encoding models of neural activity
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