Social dysfunction is a defining feature of many psychiatric and neurodevelopmental disorders, yet effective treatments are lacking. Intranasal oxytocin (OT) is suggested as a promising treatment. The ability of OT to cross the blood-brain-barrier (BBB), however, is very limited. In addition, little is known about social cognition circuits in primates affected by OT, due to the lack of site-specific OT administration tools. We will develop a new, non-invasive approach to administer OT directly to specific parts of the brain using focused ultrasound-induced BBB opening. We will test behaviorally and functionally how the social cognition circuitry can be modulated by OT delivered to specific brain sites. Our project aims to decipher the precise role of oxytocin pathways in primate social behavior which will pave the way for improved treatments of social dysfunction.

Imagine trying to navigate through a busy city, you can be a bit overwhelmed by all the traffic around you, the smell from a bakery or the sounds of a construction site. Still, from this stream of sensory input you're able to select an item that is relevant for you, for example a street sign. This powerful capacity is called selective attention, and although it is crucial in daily life, the cortical mechanisms of it are still largely unclear. We here propose to apply unique imaging technologies that will allow us to image thousands of neurons, while the animals are involved in well-controlled tasks. Moreover, by using novel histological methods we will be able to establish the cell-types of these neuronal populations as well. This will allow us to investigate the microcircuit of selective attention at unprecedented detail, helping us to understand how this cognitive functions could be impaired in mental diseases like schizophrenia and autism.

In the context of the global plastic pollution crisis, IsotoplastX aims to provide a more comprehensive view of micro- and nano-plastics (MNPs) impact on human health. It focuses on their fate and behavior from the cell to the whole animal, comparing their respective size-dependent and chemical contaminants “vectorization" effects using radiolabeling to reach realistic environmental exposure doses.

Psychiatric disorders such as schizophrenia or mood disorders are frequent and cause heavy burden. Advances in their diagnosis, assessment or treatment are limited by our poor understanding of their mechanisms, especially comparing psychiatry with other medical domains. Neuroimaging (mostly MRI) has allowed a better understanding of these conditions and the identification of involved neural networks. However, the detailed anatomical, cellular, metabolic or energetic brain correlated of these disorders are very poorly known. Almost all MRI studies in psychiatry used MRI with a 1.5 or 3 Teslas magnetic field. For around 20 years, vendors have developed scanners with a higher magnetic field (7T and beyond, as the 11.7T MRI at NeuroSpin). This stronger magnetic field allows an improved signal to noise ratio, leading to a higher spatial and temporal resolution, with applications in "conventional" anatomical or functional MRI (allowing laminar MRI or an improvement in clinical diagnostic performances in neurology). These high fields also allow the development of new MRI modalities such as X nuclei imaging (sodium, phosphorus, lithium), which are tricky to perform with a lower field. 7T MRI use in psychiatry has yet been limited because 7T MRI were closer to prototypes than clinically-usable machines, were difficult to tune and generated a lot of artifacts. A better mastership of their use has led to the very recent marketing of a "CE"-labelled machine for clinical use (Siemens Terra, 2019). While there are currently less than 100 7T MRI in function in the world, numerous research centers and hospitals are planning to buy one of them. Till today, ultra high field MRI has brought many promises without delivering much in psychiatry nor having developed a "killer app". One cause for this situation is the important gap between experts of this technology (physicists, methodologists) and researchers in psychiatry. One counterexample of this is the ANR-funded project BipLi7, using the 7T MRI at NeuroSpin to study brain lithium concentration and distribution in bipolar patients treated with lithium. The common work of physicists (F. Boumezbeur) and clinical researchers (J. Houenou, F. Bellivier) at NeuroSpin has allowed the generation fo important results, showing a high in vivo concentration of lithium in the hippocampus of patients, something that was previously unknown (Stout et al., Biol Psychiatry, 2020). Our goal is thus to generalize this approach coupling methodologists and clinicians on a European scale, to achieve all the potential of ultra high field MRI to solve crucial questions in psychiatry, in clinical studies on mechanisms, transition to and effects of therapeutic interventions in these disorders. We will conduct multicentric clinical studies using 7T MRI across Europe, within a network gathering physicists and researchers in psychiatry. Each workpackage will perform at least one multicentric clinical study testing a scientific question brought by "clinical" researchers and using methods at 7T developed by the methodologists. These studies will use e.g. X nuclei imaging, very high resolution MRI, spectroscopy.... to solve questions about schizophrenia, bipolar disorder.... This project should lead to important advances in the understanding of psychiatric disorders but also induce a leverage effect to develop the applications of 7T MRI on a global scale in research in psychiatry.

In a continuous stream of auditory signals, accurately predicting the occurrence of particular events (a noise indicating a danger, or a phoneme that is important for understanding a sentence) is essential for adaptive behavior. These temporal predictions help us to precisely orient attention in time, which is crucial to prevent a capacity-limited cognitive system from overload. Predicting future events relies on a mental representation of the temporal structure of sound, but this representation, and the underlying neural dynamics, are not well studied. WHEN investigates the representation and functional consequences of temporal predictions for audition by combining concepts and tools from statistical learning with established timing paradigms and neuroimaging methods with high spatial and temporal resolution. Aim 1 is to provide a computational account of the unfolding of temporal predictions in human behaviour, using Bayesian observer models. The resulting model will be brought to bear on the neural dynamics implementing temporal predictions using electro-encephalography. Aim 2 will investigate the functional consequences of temporal predictions for audition in an extensive psychophysical approach, to clarify whether temporal predictions benefit both detection and discrimination of auditory attributes. Aim 3 will then test the interaction of temporal and sensory predictions in audition, by assessing the neural signatures of temporal predictions in specialized auditory regions. To reach this aim, we will take advantage of the excellent spatial and temporal resolution of magnetoencephalography. Given the particular relevance of timing for audition, a better understanding of the mechanisms supporting the temporal efficiency of auditory processing is critical. This project is designed to address fundamental research questions of human cognition at the junction of timing and hearing.