ERC FUNDED PROJECTS

Crustal magmatism is periodic on a very wide range of timescales from pulses of continental crustal growth, through formation of granite batholiths, to eruptions from individual volcanic centres. The cause of this periodicity is not understood. I aim to address this long-standing geological problem through a combination of experiments, petrological methods and numerical models via a novel proposal that periodicity arises because of the highly non-linear ( critical ) behaviour of magma crystallinity with temperature in a series of linked crustal magma reservoirs. The ultimate objective is to answer five fundamental questions: " Why is crustal magmatism episodic? " How are large batholiths formed of rather similar magmas over long periods of time? " How do large bodies of eruptible magma develop that can lead to huge, caldera-forming eruptions? " What controls the chemistry of crustal magmas? Why are some compositions over-represented relative to others? " What is the thermal structure beneath volcanic arcs and how does it evolve with time? The project will address these questions through case studies of three contrasted active volcanoes: Nevado de Toluca, Mexico; Soufriere St Vincent, Lesser Antilles; and Mount Pinatubo, Philippines. For each volcano I will use experimental petrology to constrain the phase relations of the most recently erupted magma as a function of pressure, temperature, volatile content and oxygen fugacity in the shallow, sub-volcanic storage region. I will also carry out high-pressure phase equilibria on coeval Mg-rich basaltic rocks from each area with the aim of constraining the lower crustal conditions under which the shallow magmas were generated and use diffusion chronometry to constrain the frequency of magmatic pulses in the sub-volcanic reservoirs. The project will result in a quantum leap forwards in how experimental and observational petrology can be used to understand magmatic behaviour beneath hazardous volcanoes

2 959 518 €

Start date: 2010-04-01, End date: 2015-03-31

What is the fundamental unit of computation in the brain? Answering this question is crucial not only for understanding how the brain works, but also for building accurate models of brain function, which require abstraction based on identification of the essential elements for carrying out computations relevant to behaviour. We will directly test the possibility that single dendritic branches may act as individual computational units during behaviour, challenging the classical view that the neuron is the fundamental unit of computation. We will address this question using a combination of electrophysiological, anatomical, imaging, molecular, and modeling approaches to probe dendritic integration in pyramidal cells and Purkinje cells in mouse cortex and cerebellum. We will define the computational rules for integration of synaptic input in dendrites by examining the responses to different spatiotemporal patterns of excitatory and inhibitory inputs. We will use computational modeling to extract simple rules describing dendritic integration that captures the essence of the computation. Next, we will determine how these rules are engaged by patterns of sensory stimulation in vivo, by using various strategies to map the spatiotemporal patterns of synaptic inputs to dendrites. To understand how physiological patterns of activity in the circuit engage these dendritic computations, we will use anatomical approaches to map the wiring diagram of synaptic inputs to individual dendrites. Finally, we will manipulate dendritic function using molecular tools, in order to provide causal links between specific dendritic computations and sensory processing. These experiments will provide us with deeper insights into how single neurons act as computing devices, and how fundamental computations that drive behaviour are implemented on the level of single cells and neural circuits.

2 416 078 €

Start date: 2010-06-01, End date: 2016-05-31

The development of scientific models suffers from two related problems: ever-growing number of experimental results and scientists’ cognitive limitations (including cognitive biases). This multidisciplinary project (psychology, computer modelling, computer science and cognitive neuroscience) addresses these problems by developing a novel methodology for generating scientific models automatically. The methodology is general and can be applied to any science where experimental data are available. The method treats models as computer programs and evolves a population of models using genetic programming. The extent to which the models fit the empirical data is used as a fitness function. The best models–potentially modified by cross-over and mutation–are selected for the next generation. Pilot simulations have established the validity of the methodology with simple experiments. To demonstrate that the methodology is sound, can be used with complex datasets and can be generalised across sciences, four related strands of research are planned. First, ‘Building New Tools’ develops the methodology and creates techniques to understand and compare the evolved models. Second, ‘Explaining Human Data’ uses the methodology to explain a wide range of data on human cognition. This will be done in two steps: (a) data without learning (working memory and attention); and (b) data with learning (categorisation, implicit learning and explicit learning). Third, ‘Explaining Animal Data’ develops models to account for various aspects of animal behaviour, focusing on conditioning and categorisation. Finally, ‘Explaining Neuroscience Data’ extends the methodology to account for data combining information about cognitive and brain processes. This project explores virgin territory and thus opens up a new field of research. It combines insights from experimental psychology, cognitive modelling, cognitive neuroscience and computer science, disciplines in which the PI has strong track record.

2 182 339 €

Start date: 2019-11-01, End date: 2024-10-31

The development of an embryo requires the spatially structured emergence of tissues and organs. This process relies on the early establishment of a coordinate system in the form of three orthogonal axes that act as a reference for laying down the body plan, a template for the organism. Genetic analysis of this process has revealed an underlying transcriptional blueprint that links the coordinate system and the body plan. However, the way in which the gene products contribute to the emergence of the body plan remains an open question. A reason for this is that this process involves feedbacks and integration between the activity of Gene Regulatory Networks (GRNs) and the mechanics of multicellular ensembles, and that probing this relationship is experimentally challenging. In the case of mammalian embryos, which are particularly important as models for human development, our gaps in knowledge of these events are larger than in other organisms. This is partly due to the challenges associated with uterine development but also, and increasingly, because of the cost of mice and the difficulty of obtaining large numbers of embryos, as required for mechanistic experiments. In this project we shall use gastruloids, a novel and versatile Pluripotent Stem Cells based experimental system that we have developed for the study of mammalian development, to gain insights into the molecular and cellular basis underlying the emergence of the mammalian body plan. Gastruloids lack anterior neural structures and over a period of five days become organized in the fashion of a midgestation mouse embryo. We shall use the experimental versatility of the Gastruloid system to probe into the functional relationships between the mechanical activities of multicellular ensembles and the dynamics of GRNs that underlie the emergence of the mammalian body plan.

2 480 300 €

Start date: 2019-10-01, End date: 2024-09-30