Triple-N dataset: large-scale fMRI-guided dense recordings of nonhuman primate neural responses to natural scenes

Understanding high-level visual processing requires data that capture both fine-grained neuronal activity and large-scale cortical organization. We present the Triple-N dataset, which extends the Natural Scenes Dataset (NSD) framework to macaques by combining functional magnetic resonance imaging with dense Neuropixels recordings in the inferotemporal cortex and early visual areas during the viewing of 1,000 NSD images. Neuropixels probes provide high-resolution population sampling, capturing hundreds of simultaneously isolated units with millisecond temporal precision. Using these data, we show that inferotemporal category-selective regions exhibit robust tuning for their preferred categories, and dense sampling further reveals diverse temporal response patterns and image-dependent latency variations that reflect both intrinsic neuronal properties and stimulus features. Aligning macaque electrophysiology with human NSD functional magnetic resonance imaging demonstrates cross-species correspondences and divergences in representational geometry. Overall, the Triple-N dataset lays a foundation for unifying single-neuron dynamics, cortical representations and cross-species comparisons, helping to shape a more comprehensive understanding of primate visual processing.