Conference Agenda

Many forms of sensory signals are experienced along an intensity continuum – loudness, brightness, vibration strength. Frequently, sensory inputs must be categorized to make choices: “Turn off the machine if the vibration gets too strong.” We trained rats to classify vibrissal vibrations as “strong” or “weak.” The basic elements of such an operation are (i) representing the incoming sensory signal, (ii) representing the boundary, or criterion, that separates “strong” from “weak,” and (iii) generating a judgment based upon a comparison between the first two elements. Data revealed that rats were less likely to report a vibration as “strong” if the preceding trial’s vibration was high-intensity, and vice versa. By a combination of psychophysics and computational modelling, the "repulsive" serial effects could be explained as the comparison of ongoing sensory input against a criterion constructed as the time-weighted average of the history of recent stimuli. Thus, the decision boundary is not the fixed category border set by the investigator but a brain criterion that is updated, trial by trial. Next, we ask how such operations might be distributed across neuronal populations in the primary vibrissal somatosensory cortex (vS1) together with primary vibrissal motor cortex (vM1), a downstream frontal cortical target of vS1. Can boundary updating be mediated by long-lasting adaptation in vS1 or,alternatively, does it involve higher stages of perceptual processing? Decoding of neuronal population firing in vS1 revealed no systematic influence of earlier trials on the processing of new stimuli. By contrast, in vM1 the representation of the ongoing stimulus was biased according to past stimuli: mirroring the rats’ choices, a vM1population decoder classified the current stimulus as less “strong” when the rat received a high-intensity vibration in the previous trial, and vice versa. In sum, tactile perception could be decoded within distributed cortical networks.

Animals evolved a wide range of approaches to attract opposite-sex partners, and most of these strategies rely on the integration of courtship cues across multiple sensory modalities.

In rodents, male mice attract females using a combination of olfactory (i.e. pheromones and molecules contained in their urine and scents) and acoustic (i.e. ultrasound vocalizations, USVs) cues. During early life, females establish memories of both odors and sounds of their father, a process called sexual imprinting. Females can later recall these imprinted memories to find the most suitable partner, avoiding mating with their close relatives and reducing inbreeding. How does the brain differentially represent imprinted and novel courtship cues? To address this question we implemented an interdisciplinary approach to characterize neuronal responses to courtship cues across the whole-brain: we combined acute sensory stimulations with whole-brain immunolabelling of immediate early genes (cFOS), iDISCO tissue clearing, and light sheet microscopy. We focused on olfaction, exposing female mice to either the urine of their own father (imprinted) or the urine of a sexually experienced male of a different strain (novel). Brains were then processed and activated brain areas were mapped by looking at cFOS expression across all regions. We found that both stimuli significantly increased neuronal activity in several brain areas compared to a control group, with novel cues recruiting a larger number of areas, including a subset of thalamic and hypothalamic regions. Moreover, by looking at brain areas cross-correlation within each experimental group, we found stronger correlations across brain regions with novel stimuli compared to imprinted ones. Future experiments will aim to explore the overlap between recruited networks under multimodal conditions, when odours are paired with USVs. Finally, we are in the process of extending our findings to wild mice to understand the degree of generalization of our results.

Open Science aims to make scientific knowledge openly available, accessible, and reusable to everyone for the benefits of science and society. It includes various movements and practices and it has rapidly become the new normal in research. Practicing Open Science also requires to manage research data responsibly and to share them with complete documentation and in line with the FAIR guiding principles for scientific data management[1] to enable reuse by humans and machines. This is even more important when collecting large amounts of valuable data that are relevant to multiple scientific questions. During this presentation, I will highlight how the Open Science paradigm can be successfully applied in Neuroscience, in particular when big data is involved, with practical examples and with reference to existing tools, platforms, and standards in this field.

[1] Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016). https://doi.org/10.1038/sdata.2016.18

The tuning properties and functional roles of individual neurons and brain networks in primates are typically characterized during wakefulness, but little is known about their functioning during sleep. The challenges of recording freely moving primates and the lack of a validated method for distinguishing wakefulness and sleep states from intracortical recordings leave this issue unresolved. The aim of this study is to identify potential biomarkers of wakefulness and sleep states from chronic multi-electrode intracortical recordings in freely behaving monkeys. Nocturnal telemetric neural recordings have been carried out from the ventral premotor cortex of two monkeys in their home-cage. A 32-channel neural data logger was used to record broadband neural signals synchronized with an infrared-sensitive video camera. By analyzing the temporal dynamics of different local field potential (LFP) frequency bands, multi- and single-unit activity, we revealed repeatable patterns of variation of these biological signals. Using a data-driven approach that makes no a priori assumptions about the number, identity, and temporal dynamics of wake-sleep phases, we identified distinctive features of neural signals that alternate during the night in a reliable and repeatable manner, allowing us to accurately predict animal behavior and its nocturnal brain states. These innovative analytical and technical approaches pave the way for studying the functional architecture of wake-sleep transitions from the cellular and network level in freely moving primates.