Cross-modal representation of identity in primate hippocampus

Faces and voices are the dominant social signals used to recognize individuals amongst human and nonhuman primates. Yet, evidence that information across these signals can be integrated into a modality-independent representation of individual identity in the primate brain has been reported only in human patients. Here we show that, like humans, single neurons in the marmoset monkey hippocampus exhibit invariant neural responses when presented with the faces or voices of specific individuals. However, we also identified a population of single neurons in hippocampus that was responsive to the cross-modal identity of multiple conspecifics, not only a single individual. An identity network model revealed population-level, cross-modal representations of individuals in hippocampus, underscoring the broader contributions of many neurons to encode identity. This pattern was further evidenced by manifold projections of population activity which likewise showed separability of individuals, as wel..., Neurophysiological recordings were performed using 64-channel microwire brush arrays while subjects were head and body restrained in a chair. Visual stimuli were presented on a LED screen positioned 24 cm in front of the animal.  Acoustic stimuli were presented at 70–80 dB SPL. All behavior was collected in an anechoic chamber illuminated only by the screen. Stimulus presentation was controlled using custom software and eye position was monitored by infrared camera tracking of the pupil. Subjects initiated trials by holding fixation of gaze for 100ms at a center fixation dot on the screen, at which point stimulus presentation was initiated. The stimulus consisted of the face and/or voice of a familiar conspecific. 
Neurophysiological recordings were processed into spike times using the open-source package, Spyking Circus [1], which were then included in the dataset using custom MATLAB and python scripts. Handling of common recording errors is demonstrated in at the beginning of the exam..., No specialized programs and/or software are required to open the data.  The data is in a human-readable format that can be opened in most text editors.