Doctor Mónica Sousa

i3S is looking to recruit a senior researcher with an established international reputation in Neural Cell Biology and strong expertise in securing, managing and leading collaborative research projects and teams/institutional units.

“A Focus on 3D Printed Lenses: Rapid prototyping, low-cost microscopy and enhanced imaging for the life sciences”

High-quality glass lenses are commonplace in the design of optical instrumentation used across the biosciences. However, research-grade glass lenses are often costly, delicate and, depending on the prescription, can involve intricate and lengthy manufacturing - even more so in bioimaging applications. This seminar will outline 3D printing as a viable low-cost alternative for the manufacture of high-performance optical elements, where I will also discuss the creation of the world’s first fully 3D printed microscope and other implementations of 3D printed lenses. Our 3D printed lenses were generated using consumer-grade 3D printers and pose a 225x materials cost-saving compared to glass optics. Moreover, they can be produced in any lab or home environment and offer great potential for education and outreach. Following performance validation, our 3D printed optics were implemented in the production of a fully 3D printed microscope and demonstrated in histological imaging applications. We also applied low-cost fabrication methods to exotic lens geometries to enhance resolution and contrast across spatial scales and reveal new biological structures. Across these applications, our findings showed that 3D printed lenses are a viable substitute for commercial glass lenses, with the advantage of being relatively low-cost, accessible, and suitable for use in optical instruments. Combining 3D printed lenses with open-source 3D printed microscope chassis designs opens the doors for low-cost applications for rapid prototyping, low-resource field diagnostics, and the creation of cheap educational tools.

How do we sleep?

There is no consensus on if sleep is for the brain, body or both. But the difference in how we feel following disrupted sleep or having a good night of continuous sleep is striking. Understanding how and why we sleep will likely give insights into many aspects of health. In this talk I will outline our recent work on how the prefrontal cortex can signal to the hypothalamus to regulate sleep preparatory behaviours and sleep itself, and how other brain regions, including the ventral tegmental area, respond to psychosocial stress to induce beneficial sleep. I will also outline our work on examining the function of the glymphatic system, and whether clearance of molecules from the brain is enhanced during sleep or wakefulness.

Neurogenic versus Oligodendrogenic progenitors in the postnatal brain. Different adaptations, different porperties

Retinal circuits for colour vision in a tetrachromate

Towards multipurpose biophysics-based mathematical models of cortical circuits

Starting with the work of Hodgkin and Huxley in the 1950s, we now have a fairly good understanding of how the spiking activity of neurons can be modelled mathematically. For cortical circuits the understanding is much more limited. Most network studies have considered stylized models with a single or a handful of neuronal populations consisting of identical neurons with statistically identical connection properties. However, real cortical networks have heterogeneous neural populations and much more structured synaptic connections. Unlike typical simplified cortical network models, real networks are also “multipurpose” in that they perform multiple functions. Historically the lack of computational resources has hampered the mathematical exploration of cortical networks. With the advent of modern supercomputers, however, simulations of networks comprising hundreds of thousands biologically detailed neurons are becoming feasible (Einevoll et al, Neuron, 2019). Further, a large-scale biologically network model of the mouse primary visual cortex comprising 230.000 neurons has recently been developed at the Allen Institute for Brain Science (Billeh et al, Neuron, 2020). Using this model as a starting point, I will discuss how we can move towards multipurpose models that incorporate the true biological complexity of cortical circuits and faithfully reproduce multiple experimental observables such as spiking activity, local field potentials or two-photon calcium imaging signals. Further, I will discuss how such validated comprehensive network models can be used to gain insights into the functioning of cortical circuits.