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Towards an optimization of functional localizers in non-human primate imaging with (fMRI) frequency-tagging
Marie-Alphรฉe Laurent, Pauline Audurier, Vanessa De Castro, Xiaoqing Gao, Jean-Baptiste Durand, Jacques Jonas, Bruno Rossion, Benoit R. Cottereau
Date / Location: Monday, 11 July 2022 / S03-498
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Aims Non-human primate (NHP) neuroimaging can provide essential insights into the neural basis of human cognitive functions. While functional fMRI localizers can play an essential role in reaching this objective (Russ et al., 2021), they often differ substantially across species in terms of paradigms, measured signals and data analysis, biasing the comparisons. Here we introduce a functional frequency-tagging face localizer for NHP imaging, successfully developed in humans and outperforming standard โface localizersโ (Gao et al., 2018). Methods FMRI recordings were performed in two awake macaques. Within a rapid 6Hz stream of natural images of non-face objects, 7 human or monkey face stimuli were presented in bursts every 9s during a 243s run. We also included control conditions with phase-scrambled versions of all images. As in humans, runs were analyzed in the frequency domain where face-selective responses were objectively identified and quantified at the peak of the face-stimulation frequency (0.111Hz) and its second harmonic (0.222Hz). Results Focal activations with high signal-to-noise ratio were observed in regions previously described as face-selective, mainly in the STS (clusters PL, ML, MF; also, AL, AF), both for human and monkey faces. Robust activations were also found in the prefrontal cortex of one monkey in the PVL and PO clusters. Conclusions Face-selective responses were highly reliable, excluding all contributions from low-level visual cues contained in the amplitude spectrum of the images. These observations indicate that fMRI frequency-tagging provides a valid approach to objectively compare human and monkey neural face recognition systems within the same framework.