Controlled presentation of stimuli to anesthetized [1] or awake [2] animals suggested that neurons in sensory cortices respond to elementary features [3, 4], but we know little about neuronal responses evoked by social interactions. Here we investigate processing in the barrel cortex of rats engaging in social facial touch [5, 6]. Sensory stimulation by conspecifics differs from classic whisker stimuli such as deflections, contact poles [7, 8], or textures [9, 10]. A large fraction of barrel cortex neurons responded to facial touch. Social touch responses peaked when animals aligned their faces and contacted each other by multiple whiskers with small, irregular whisker movements. Object touch was associated with larger, more regular whisker movements, and object responses were weaker than social responses. Whisker trimming abolished responses. During social touch, neurons in males increased their firing on average by 44%, while neurons in females increased their firing by only 19%. In females, socially evoked and ongoing firing rates were more than 1.5-fold higher in nonestrus than in estrus. Barrel cortex represented socially different contacts by distinct firing rates, and the variation of activity with sex and sexual status could contribute to the generation of gender-specific neural constructs of conspecifics.

Social interactions involve multi-modal signaling. Here, we study interacting rats to investigate audio-haptic coordination and multisensory integration in the auditory cortex. We find that facial touch is associated with an increased rate of ultrasonic vocalizations, which are emitted at the whisking rate (∼8 Hz) and preferentially initiated in the retraction phase of whisking. In a small subset of auditory cortex regular-spiking neurons, we observed excitatory and heterogeneous responses to ultrasonic vocalizations. Most fast-spiking neurons showed a stronger response to calls. Interestingly, facial touch-induced inhibition in the primary auditory cortex and off-responses after termination of touch were twofold stronger than responses to vocalizations. Further, touch modulated the responsiveness of auditory cortex neurons to ultrasonic vocalizations. In summary, facial touch during social interactions involves precisely orchestrated calling-whisking patterns. While ultrasonic vocalizations elicited a rather weak population response from the regular spikers, the modulation of neuronal responses by facial touch was remarkably strong.DOI: http://dx.doi.org/10.7554/eLife.03185.001

Open research data are increasingly recognized as a quality indicator and an important resource to increase transparency, robustness and collaboration in science. However, no standardized way of reporting Open Data in publications exists, making it difficult to find shared datasets and assess the prevalence of Open Data in an automated fashion.We developed ODDPub (Open Data Detection in Publications), a text-mining algorithm that screens biomedical publications and detects cases of Open Data. Using English-language original research publications from a single biomedical research institution (n = 8689) and randomly selected from PubMed (n = 1500) we iteratively developed a set of derived keyword categories. ODDPub can detect data sharing through field-specific repositories, general-purpose repositories or the supplement. Additionally, it can detect shared analysis code (Open Code).To validate ODDPub, we manually screened 792 publications randomly selected from PubMed. On this validation dataset, our algorithm detected Open Data publications with a sensitivity of 0.73 and specificity of 0.97. Open Data was detected for 11.5% (n = 91) of publications. Open Code was detected for 1.4% (n = 11) of publications with a sensitivity of 0.73 and specificity of 1.00. We compared our results to the linked datasets found in the databases PubMed and Web of Science.Our algorithm can automatically screen large numbers of publications for Open Data. It can thus be used to assess Open Data sharing rates on the level of subject areas, journals, or institutions. It can also identify individual Open Data publications in a larger publication corpus. ODDPub is published as an R package on GitHub.

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