Fig. 4: Changes in key neuronal properties of selective number sensitive neurons with numerosity training. | Nature Communications

Fig. 4: Changes in key neuronal properties of selective number sensitive neurons with numerosity training.

From: Learning-induced reorganization of number neurons and emergence of numerical representations in a biologically inspired neural network

Fig. 4: Changes in key neuronal properties of selective number sensitive neurons with numerosity training.The alternative text for this image may have been generated using AI.

A Normalized tuning curves for the pre-trained network: The plots show the mean normalized activation values (by input stimuli (1 to 9, on the x-axis), grouped by neurons of each preferred numerosity (PN), for layers (a) V1, (b) V2, (c) V3, and (d) IPS. B Normalized tuning curves for the post-training network for layers (a) V1, (b) V2, (c) V3, and (d) IPS. C Tuning precision: Acuity of the tuning curves as measured by the weighted average precision of the best fitting Gaussian tuning curves for each numerosity. Training leads to improving precision across layers, but primarily in IPS. Each dot represents the tuning precision for a preferred numerosity from 1 to 9. D Stability: the rank correlation (Kendall’s tau) or preservation of relative rank order of numerosities across conditions. Values >0 indicate better than chance level agreement, and values close to 1 indicate almost perfect rank order preservation across conditions. Improvements in stability increase as we move from V1 to IPS. E Selectivity: the proportion of comparisons where neuronal responses are higher for the PN. Higher selectivity indicates higher consistency of preference for the PN. Selectivity improves post training only in the IPS layer. F Numerical distance effect (NDE) is calculated as the average slope of selectivity versus input distance for each neuron, and averaged over number sensitive neurons. Improvements in NDE are highest in the IPS layer. The circles represent median values, the thick bars show the IQR (50% CI) and the thin bars show the 95% CI. D–F The circles represent median values, the thick bars show the IQR (50% CI) and the thin bars show the 95% CI. G NDE in the IPS layer: (a) Average selectivity and (b) Activation difference are both shown as a function of the numerical distance between pairwise input stimuli. The distance effects increase sharply from pre-trained (blue) to post-training (red). Source data are provided as a Source Data file.

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