Imagine that you cannot wear your lucky socks for an upcoming test. In the event of failure, will you blame your absent clothing or your lack of preparation? The ability to identify which actions cause a particular event to occur is called "credit assignment". This ability allows individuals to properly make decisions and learn from their mistakes. Problems with credit assignment are linked to various mental health conditions, like addiction and obsessive-compulsive-disorders where individuals continue to believe that their drug-taking or rituals will lead to positive outcomes [1]. However, clinicians tend to define and diagnose mental illnesses in terms of their clinical symptoms, not by their underlying psychological traits or biological abnormalities [2]. No-one has yet studied how changes in the brain lead to the problems of credit assignment that are seen in psychiatric disorders. Solving this riddle will help us understand how humans can work out cause and effect, as well as what happens when they lose this ability. My plan with this fellowship is to i) extract clinically-relevant traits that describe a person's ability - or lack thereof - for credit assignment from a large database, ii) map them onto brain mechanisms, and iii) restore the identified circuit dysfunction and therefore reduce the related maladaptive behaviours in patients suffering from addiction. To do so, I will, in a first stage, collect a large-scale dataset ("big-data") from an online study where participants will assign credit to distinct stimuli that predict a variety of events. Computational learning models will be used to explain this large dataset by teasing apart the hidden attentional and learning features of credit assignment [3-5] and relate them to various psychiatric dimensions. These will then be contrasted against neural data (acquired with fMRI while participants carry out the same credit assignment task). This will help map out the full neural circuitry involved in credit assignment and relate it to the phenotype of mental health issues. In the second stage of the fellowship, I plan to use a cutting-edge technique called ultrasound neurostimulation to target the different parts of the brain that cause pathological credit assignment and over-reliance on habits. Ultrasound neurostimulation is an early-stage, non-invasive therapeutic technology that has the potential to improve the lives of millions of patients with mental health conditions by stimulating brain tissues with millimetre accuracy [6]. My previous research has recently shown that ultrasound can safely modulate activity in deep brain areas in macaques to elicit precise behavioural changes [7]. Importantly, its safe use in humans has also been established [8-9]. In sum, ultrasound neurostimulation will be used to restore the brain regions involved in credit assignment and alleviate the corresponding negative symptoms in patients. This approach has the potential to help the nearly two million patients suffering from maladaptive addictive behavioural patterns by designing new stimulation paradigms that effectively restore brain function. Moreover, besides addictive disorders, ultrasound brain therapy could also be used to restore normal functioning of brain circuits involved in anxiety, mood disorders, and obsessive-compulsive disorders for which effective therapies are desperately needed. [1] Everitt &al. NatNeuro. 8,1481-1489(2005). [2] Hyman &al. NatRevNeuro. 8,725-732(2007). [3] Fouragnan &al. NatComm. 6,8107(2015). [4] Fouragnan &al. SciRep. 7,4762(2017). [5] Queirazza, Fouragnan &al. forthcoming at Science Advances (2019). [6] Aubry JoAcoustSocAm. 143,1731-1731 (2018). [7] Fouragnan &al. NatNeuro. 22,797-808(2019). [8] Fomenko &al. BrainStim. 11,1209-1217(2018). [9] Tsai &al. MedHypo. 84,381-383 (2015).

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

Ultrasound is best known for imaging unborn babies. In this instance, sound waves travel through the body and their echoes are used to form images, with a very limited amount of energy remaining in the body. By focusing the sound waves to a small region in space, a bit like a magnifying glass focusing sunlight increases the heat energy to one place, the focused ultrasound energy increases, and this can be used to change the way cells behave in the body. Through the skull, this can be used to change how our brain functions in a safe, transient, and reversible way. This has therapeutic potential for treating disorders of the brain, like neurological disorders (Parkinson's disease) but also psychiatric disorders (addiction, depression). The technique is called Transcranial Ultrasound Stimulation (TUS). In a series of studies, our team have shown that TUS can safely and reversibly change brain activity up to two hours after intervention (Yaakub et al. 2023). Because these changes exceed the intervention period, the effects promote neuroplasticity - the ability of the brain to re-wire itself, a key function when considering new treatment for disorders of the brain. Although TUS has the potential to revolutionize how we treat the brain throughout life, both in general health and disease, TUS outcomes are variable. In our prior work, we have observed that the TUS effects depend on the "state" that the person is in, for example awake or sleeping (physiological state), or resting or focusing on a task (cognitive state). Changes in physiological or cognitive states cause changes in brain regional activity which consequently change how TUS impacts these brain regions. In this novel project, we will investigate for the first time the relationships between brain states and TUS (Aim 1) and whether recruitment of targeted brain regions improves TUS-induced plasticity. This is crucial for optimizing future treatment designs, particularly those leveraging cognitive-behavioral tasks during TUS therapies. For Aim 1, we will use three work packages (WP1-3), all focusing on the effects of the same TUS intervention on different states: 1) different states of consciousness (manipulated with different depth of anaesthesia), 2) different states of pain sensitivity (manipulated through experimental manipulation of pain development) and 3) different cognitive load (manipulated through complex versus simple learning tasks). Better refining the relationship between TUS and states will be vital to pave the way for effective clinical interventions, particularly those combining cognitive-behavioral therapy and brain stimulation. Another important aspect of TUS is that it can reach any region in the brain - in the order of millimetres - even deep in the brain, unlike more traditional methods that remain superficial and not spatially accurate. This is important when trying to assess the role of specific nuclei in the brain or specific regions. Some regions of the brain have specific functions, for example, a region A can be linked to a function A, while another brain region B can be linked to a function B. By modulating regions A and B on different days, one can assess the role of these regions. However, sometimes a function is linked to the way regions communicate with one other and not solely on the region themselves. In theory, this could be assessed through concurrent brain stimulation of the two regions. In this new line of research, we will also pursue the idea that TUS can be used at different locations of the brain at the same time, in order to change communication between brain regions (Aim 2 - Work Package 4 [WP4]). We want to show that concurrent multisite TUS is safe and can increase outcome measures by providing additional ways of intervening in the brain. This will increase the potential of TUS applications and open a new avenue for thinking about non-invasive brain stimulation which considers the dynamism of brain networks.

Even a moderate decrease in how well our kidneys work (by 20-30%) at levels that would not refer a patient to the kidney clinic, can double the risk of future heart disease. For example, in the UK, more than 5million people are predicted to have diabetes by 2030. Of those, approximately 40% (2 million) will develop kidney complications and many will require dialysis as their disease progresses. Patients with diabetes whose kidneys do not work well are up to 10 times more likely to die from strokes and heart attacks in the next 10 years than those who do not. It is therefore important to find new ways to protect the kidney. The millions of bugs that live in our digestive system, especially gut; known as the gut microbiota, affect how we use our food. One way that these bugs in our guts can communicate with their host is by producing chemicals (called metabolites) that I and other researchers have shown that can also affect how our kidneys work. In this research, I want to find new ways to protect the kidney by reducing harmful metabolites produced by the bacteria that live in our gut. In pilot studies, using machine learning and data from 2200 patients from Germany, France and Denmark, I discovered that a chemical made by bugs from the amino acid phenylalanine called phenylacetylglutamine can be harmful for the kidney, while another chemical that can also be made from phenylalanine called 3-phenylpropionate is protective. Now, working together with leading scientists and medical doctors from Germany, France, Denmark and Canada I will use machine learning and big data analyses to see if the balance of these chemicals in the blood can be used as an early warning sign of future serious kidney and heart complications in humans. In addition to the original study (MetaCardis, N=2200) I generated my pilot data in, I will also use information from two human studies that followed and collected data from healthy people (Longitudinal Canadian Study of Aging with 9,500 participants) or people at early stages of chronic kidney disease (German CKD with 5,000 participants) for up to 6 years. For this part of my work, I will use a wealth of information from 16,700 individuals from three independent human studies that has costed tens of millions of pounds to be collected. Then, in the second part of my study, in London and Oxford, together with a Research Assistant I will hire as part of this project and in collaborations with scientist from the Imperial College National Heart and Lung Institute and MRC Harwell, I will treat cells and mice that have diabetes and high blood pressure with these chemicals to study how they change the way the heart and kidney works. In this way, I hope to better understand their mode of action and how to better protect the heart and the kidney by harnessing the microbiome. Finally, in London and Oxford at the Imperial College NHLI and MRC-Harwell and in collaboration with the leading expert of bacterial phenylalanine metabolism from the University of Stamford in the USA, I together with the Research Assistant will test modified bacteria, existing drugs and probiotics in mice to see if I can restore the balance between these chemicals and protect these mice from heart and kidney disease. By re-purposing interventions already safe for use in patients I hope to be able to "hack" the microbiome to produce a beneficial chemical instead of a harmful one. In summary, if successful, my research will introduce a new risk factor (microbiota phenylalanine metabolism) that can help medical doctors better predict which patient is more at risk of heart attack or kidney failure and prioritise treatment. Additionally, my work will generate new information to improve our understanding of how the bacteria in our gut change the way our kidneys and heart works. Finally, by finding ways to re-program microbiome phenylalanine metabolism, my work can directly lead to human clinical trials.

Understanding how people's social and economics lives relate to their health is essential to improving the nation's health, society in general and the economy. Researchers in biomedical, social and economic sciences use robust, high quality data from world-leading studies to help develop this understanding. This research helps reveal hidden facts about the complex social and biological processes at work behind our everyday lives. This proposal seeks to support this ambition to better understand people's lives and their health. It is based on Understanding Society - a rich social and economic study, which interviews the same families every year and has recently included a health interview where nurses took a number of 'biomarkers' or objective health measurements. These objective measures such as blood pressure, lung function and blood samples, have subsequently been analysed for indicators of heart disease, diabetes and anaemia, liver and kidney function and frailty. The project is led by a multi-disciplinary research team with international partners and has two broad aims: * to contribute new scientific knowledge about the two-way relationship between people's social, economic, environmental circumstances and health; * to build understandings of the value of and capacity for using biomarkers, genetic social and economic data together in collaborative projects. The proposal will include a suite of exemplar research projects, which will not only address important research questions but demonstrate the value of inter-disciplinary [data and] research in these fields. It will investigate and use the best statistical techniques, and share learning with colleagues about these approaches. In addition, we will also: *undertake a set of 'outreach' initiatives in specific social science disciplines - such as geography, economics and sociology - to investigate and disseminate the value of employing biomarkers to address social research questions relevant to them. *establish a fellowship scheme for new researchers to propose projects at the interface of social and health sciences, which will be carried out with joint mentorship by social and biomedical scientists. * hold a range of workshops and training events, and produce supporting resources, such as special datasets, to build understanding and capacity of the use of biomarkers in social science research. * develop international collaborations to draw expertise from across the world into the project, and hold an annual master class and conference with contributions from them; * involve policy makers in the oversight of the project, as well as set aside some funds for them to undertake analyses of the data relevant to their policy responsibilities. Policy relevant findings will be shared widely through briefings and a policy event. This research will help to identify when and how health problems emerge in ways that enable policy makers to target policies more effectively. It will also help us understand how poor health affects people's ability to live their lives, which again may enable policy makers to identify appropriate times and situations when these negative consequences can be prevented or reduced. Such research directly contributes to the ESRC's strategic priority to influence behaviours and inform interventions. It will also improve the capacity of the research community to engage in this kind of research leading to future developments in this field.