Neurophysiological data obtained in primates suggests that merely observing others' actions can modulate activity in the observer's motor cortices. In humans, it has been suggested that these multimodal vicarious responses extend well beyond the motor cortices, including somatosensory and insular brain regions, which seem to yield vicarious responses when witnessing others' actions, sensations, or emotions (Gazzola and Keysers, 2009). Despite the wealth of data with respect to shared action responses in the monkey motor system, whether the somatosensory and insular cortices also yield vicarious responses during observation of touch remains largely unknown. Using independent tactile and motor fMRI localizers, we first mapped the hand representations of two male monkeys' primary (SI) and secondary (SII) somatosensory cortices. In two subsequent visual experiments, we examined fMRI brain responses to (1) observing a conspecific's hand being touched or (2) observing a human hand grasping or mere touching an object or another human hand. Whereas functionally defined “tactile SI” and “tactile SII” showed little involvement in representing observed touch, vicarious responses for touch were found in parietal area PFG, consistent with recent observations in humans (Chan and Baker, 2015). Interestingly, a more anterior portion of SII, and posterior insular cortex, both of which responded when monkeys performed active grasping movements, also yielded visual responses during different instances of touch observation.SIGNIFICANCE STATEMENTCommon coding of one's own and others' actions, sensations, and emotions seems to be widespread in the brain. Although it is currently unclear to what extent human somatosensory cortices yield vicarious responses when observing touch, even less is known about the presence of similar vicarious responses in monkey somatosensory cortex. We therefore localized monkey somatosensory hand representations using fMRI and investigated whether these regions yield vicarious responses while observing various instances of touch. Whereas “tactile SI and SII” did not elicit responses during touch observation, a more anterior portion of SII, in addition to area PFG and posterior insular cortex, all of which responded during monkeys' own grasping movements, yielded vicarious responses during observed touch.

In natural vision, primates actively move their eyes several times per second via saccades. It remains unclear whether, during this active looking, visual neurons exhibit classical retinotopic properties, anticipate gaze shifts or mirror the stable quality of perception, especially in complex natural scenes. Here, we let 13 monkeys freely view thousands of natural images across 4.6 million fixations, recorded 883 h of neuronal responses in six areas spanning primary visual to anterior inferior temporal cortex and analyzed spatial, temporal and featural selectivity in these responses. Face neurons tracked their receptive field contents, indicated by category-selective responses. Self-consistency analysis showed that general feature-selective responses also followed eye movements and remained gaze-dependent over seconds of viewing the same image. Computational models of feature-selective responses located retinotopic receptive fields during free viewing. We found limited evidence for feature-selective predictive remapping and no viewing-history integration. Thus, ventral visual neurons represent the world in a predominantly eye-centered reference frame during natural vision.

Humans perceive illusory faces in everyday objects with a face-like configuration, an illusion known as face pareidolia. Face-selective regions in humans and monkeys, believed to underlie face perception, have been shown to respond to face pareidolia images. Here, we investigated whether pareidolia selectivity in macaque inferotemporal cortex is explained by the face-like configuration that drives the human perception of illusory faces. We found that face cells responded selectively to pareidolia images. This selectivity did not correlate with human faceness ratings and did not require the face-like configuration. Instead, it was driven primarily by the “eye” parts of the illusory face, which are simply object parts when viewed in isolation. In contrast, human perceptual pareidolia relied primarily on the global configuration and could not be explained by “eye” parts. Our results indicate that face-cells encode local, generic features of illusory faces, in misalignment with human visual perception, which requires holistic information.

A bstract: Recent progress in multimodal AI and ‘language-aligned’ visual representation learning has rekindled debates about the role of language in shaping the human visual system. In particular, the emergent ability of ‘language-aligned’ vision models (e.g. CLIP) – and even pure language models (e.g. BERT) – to predict image-evoked brain activity has led some to suggest that human visual cortex itself may be ‘language-aligned’ in comparable ways. But what would we make of this claim if the same procedures could model visual activity in a species without language? Here, we conducted controlled comparisons of pure-vision, pure-language, and multimodal vision-language models in their prediction of human (N=4) and rhesus macaque (N=6, 5:IT, 1:V1) ventral visual activity to the same set of 1000 captioned natural images (the ‘NSD1000’). The results revealed markedly similar patterns in model predictivity of early and late ventral visual cortex across both species. This suggests that language model predictivity of the human visual system is not necessarily due to the evolution or learning of language perse , but rather to the statistical structure of the visual world that is reflected in natural language.

Neuroscience has long relied on macaque studies to infer human brain function, yet identifying functionally corresponding brain regions across species and measurement modalities remains a fundamental challenge. This is especially true for the higher-order cortex, where functional interpretations are constrained by narrow hypotheses and anatomical landmarks are often nonhomologous. We present a data-driven approach for mapping functional correspondence across species using rich, naturalistic stimuli. By directly comparing macaque electrophysiology with human fMRI responses to 700 natural scenes, we identify fine-grained alignment based on response pattern similarity, without relying on predefined tuning concepts or hand-picked stimuli. As a test case, we examine the ventral face patch system, a well-studied but contested domain in cross-species alignment. Our approach resolves a long-standing ambiguity by supporting a correspondence between macaque ML and human FFA and between AL and more anterior temporal cortex in humans. This result is consistent with full-brain anatomical warping but inconsistent with prior studies limited by narrow functional hypotheses. These findings show that natural image-evoked response patterns provide a robust foundation for cross-species functional alignment, supporting scalable comparisons as large-scale primate recordings become more widespread.