Pixel-wise statistical mapping with voltage-sensitive dye imaging reveals differential hippocampal circuit effects of bisphenol A and related phenolic analogs

Exposure to environmental chemicals such as bisphenol A (BPA) may affect neural circuit function in subtle and spatially distributed ways that are difficult to attribute to a single circuit element. Here, we developed a voltage-sensitive dye (VSD) imaging analysis pipeline for acute male mouse hippocampal slices. This approach measures stimulus-evoked fractional changes in VSD fluorescence ( ΔF / F 0 ) to generate pixel-wise normalized maps, averages response magnitude within anatomically defined regions of interest (ROIs), and visualizes control-versus-compound differences using pixel-wise statistical maps before and after false discovery rate (FDR) adjustment. We applied this pipeline to compare the acute effects of BPA with those of two structurally related phenolic analogs. Evoked responses were quantified by their peak amplitude and time integral across hippocampal trisynaptic pathways at two stimulation levels determined from input–output relationships, with or without the GABA A receptor antagonist gabazine (SR-95531; 10 μM). The phenolic analogs reduced circuit responses across multiple ROI-defined conditions, whereas BPA produced comparatively limited effects. These alterations varied with pathway, subfield, age, response metric, and inhibitory state. These findings demonstrate the utility of integrating ROI averages with pixel-wise statistical maps for detecting condition-dependent circuit-level differences between structurally related compounds and indicate that BPA-related phenolic analogs can differ from BPA itself in their acute effects on hippocampal circuitry. Significance Statement Exposure to environmental chemicals may alter brain circuit activity in subtle, spatially distributed ways. We developed a voltage-sensitive dye imaging pipeline for acute mouse hippocampal slices that combines regional summaries with pixel-wise statistical maps, quantifying regional response magnitude while localizing where statistically supported differences are expressed within evoked response fields. Using this framework, we compared the acute hippocampal circuit effects of bisphenol A (BPA) with those of two structurally related phenolic analogs. Under acute slice conditions, statistically supported response reductions were detected more consistently for the phenolic analogs than for BPA, depending on age, inhibitory state, hippocampal subfield, and response metric. These results show how integrated regional and pixel-wise analysis improves circuit-level phenotyping of structurally related compounds.