Itch and pain are distinct aversive sensations. We previously identified segregated neuronal populations in the anterior cingulate cortex (ACC) that selectively respond to pain and itch stimuli and reported full-trace classification with a mean-frequency difference, leaving the broader calcium-transient properties associated with this separation unresolved. Here, we reanalyzed denoised in vivo calcium traces from stimulus-responsive ACC neurons and quantified interpretable response features, including peak rate, peak interval, rise and decay area under the curve (AUC), and rise and decay slope. Pain- and itch-associated neurons differed across multiple single-neuron calcium features. Trace-based stochastic gradient descent (SGD) classification separated the two groups, indicating that their response profiles contain label-discriminative information. Notably, classification performance was only weakly affected by neuron-wise z -scoring, suggesting that separation is not explained solely by simple amplitude scaling. A mouse-constrained shuffled-label control reduced classification performance, supporting the contribution of within-mouse label-associated structure while also highlighting mouse-level sampling constraints. Paired mouse summaries and mouse-exclusive validation showed limited cross-animal consistency, whereas within-mouse neighborhood analysis retained local label-associated organization. UMAP of full traces provided descriptive visualization of neuron-level response organization. Together, these results show that interpretable calcium response features carry meaningful itch−/pain-associated structure among the analyzed responsive ACC neurons.
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Lee et al. (2026) studied this question.
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