Neuroscience seminars

We recently analyzed a large cohort of multiple sclerosis (MS) autopsy cases of the Netherlands Brain Bank (NBB) and showed that 57% of the lesion in advanced MS is active (containing activated microglia/macrophages). These active lesions correlated with disease severity and differed between males and female MS patients.1 Already in normal appearing white matter microglia show early signs of demyelination.5 T cells are also frequently present in advanced stages of MS and have a tissue resident memory (Trm) phenotype, are more frequently CD8+ then CD4+, are located perivascular, enriched in active and mixed active/inactive MS lesions and correlated with lesion activity, lesion load and disease severity.2-4 Like Trm cells, B cells are located perivascular and were also enriched in active MS lesions but in lower numbers and a proportion of the MS patients had almost no detectable B cells in the regions analyzed. MS patients with limited presence of B cells had less severe MS, and less active and mixed active /inactive lesions. We conclude that advanced MS is characterize by a high innate and adaptive immune activity which is heterogeneous and relates to the clinical disease course.

The corpus callosum is the largest fibre tract in the brain of placental mammals and connects the two cerebral hemispheres. Corpus callosum dysgenesis is a developmental brain disorder that is commonly genetic and occurs in approximately 1:4000 live births. It is easily diagnosed by MRI or prenatal ultrasound and is found in isolation or together with other brain anomalies, or with other organ system defects in a large number of different congenital syndromes. Callosal dysgenesis is a structural brain wiring disorder that can impact brain function and cognition in heterogeneous ways. We aim to understand how early developmental mechanisms lead to circuit alterations that ultimately impact behaviour and cognition. Translated to Spanish by MD and Medical interpreter Trinidad Ott. El cuerpo calloso es el tracto de fibras más grande del cerebro de los mamíferos placentarios y conecta los dos hemisferios cerebrales. La disgenesia del cuerpo calloso es un trastorno del desarrollo del cerebro que comunmente es genético y ocurre en aproximadamente 1: 4000 nacidos vivos. Se diagnostica fácilmente mediante resonancia magnética o ecografía prenatal y se encuentra aislado o junto con otras anomalías cerebrales, o con otros defectos del sistema de órganos en un gran número de síndromes congénitos diferentes. La disgenesia callosa es un trastorno estructural del cableado cerebral que puede afectar la función cerebral y la cognición de formas heterogéneas. Nuestro objetivo es comprender cómo los primeros mecanismos del desarrollo conducen a alteraciones en los circuitos que, en última instancia, afectan el comportamiento y la cognición. Traducción al español por la Doctora e Intérprete Médica Trinidad Ott.

Remarkable advances in experimental neuroscience now enable us to simultaneously observe the activity of many neurons, thereby providing an opportunity to understand how the moment by moment collective dynamics of the brain instantiates learning and cognition. However, efficiently extracting such a conceptual understanding from large, high dimensional neural datasets requires concomitant advances in theoretically driven experimental design, data analysis, and neural circuit modeling. We will discuss how the modern frameworks of high dimensional statistics and deep learning can aid us in this process. In particular we will discuss: how unsupervised tensor component analysis and time warping can extract unbiased and interpretable descriptions of how rapid single trial circuit dynamics change slowly over many trials to mediate learning; how to tradeoff very different experimental resources, like numbers of recorded neurons and trials to accurately discover the structure of collective dynamics and information in the brain, even without spike sorting; deep learning models that accurately capture the retina’s response to natural scenes as well as its internal structure and function; algorithmic approaches for simplifying deep network models of perception; optimality approaches to explain cell-type diversity in the first steps of vision in the retina.

The curse of dimensionality plagues models of reinforcement learning and decision-making. The process of abstraction solves this by constructing abstract variables describing features shared by different specific instances, reducing dimensionality and enabling generalization in novel situations. Here we characterized neural representations in monkeys performing a task where a hidden variable described the temporal statistics of stimulus-response-outcome mappings. Abstraction was defined operationally using the generalization performance of neural decoders across task conditions not used for training. This type of generalization requires a particular geometric format of neural representations. Neural ensembles in dorsolateral pre-frontal cortex, anterior cingulate cortex and hippocampus, and in simulated neural networks, simultaneously represented multiple hidden and explicit variables in a format reflecting abstraction. Task events engaging cognitive operations modulated this format. These findings elucidate how the brain and artificial systems represent abstract variables, variables critical for generalization that in turn confers cognitive flexibility.

The neurotransmitter dopamine is essential for normal reward learning and motivational arousal processes. Indeed these core functions are implicated in the major neurological and psychiatric dopamine disorders such as schizophrenia, substance abuse disorders/addiction and Parkinson's disease. Over the years, we have made significant strides in understanding the dopamine system across multiple levels of description, and I will focus on our recent advances in the computational description, and brain circuit mechanisms that facilitate the dual role of dopamine in learning and performance. I will specifically describe our recent work with imaging the activity of dopamine axons and measurements of dopamine release in mice performing various behavioural tasks. We discovered wave-like spatiotemporal activity of dopamine in the striatal region, and I will argue that this pattern of activation supports a critical computational operation; spatiotemporal credit assignment to regional striatal subexperts. Our findings provide a mechanistic description for vectorizing reward prediction error signals relayed by dopamine.

Humans spend a lifetime learning, storing and refining a repertoire of motor memories. However, it is unknown what principle underlies the way our continuous stream of sensori-motor experience is segmented into separate memories and how we adapt and use this growing repertoire. Here we develop a principled theory of motor learning based on the key insight that memory creation, updating, and expression are all controlled by a single computation – contextual inference. Unlike dominant theories of single-context learning, our repertoire-learning model accounts for key features of motor learning that had no unified explanation and predicts novel phenomena, which we confirm experimentally. These results suggest that contextual inference is the key principle underlying how a diverse set of experiences is reflected in motor behavior.

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.

Both computational and experimental results in single neurons and small networks demonstrate that very similar network function can result from quite disparate sets of neuronal and network parameters. Using the crustacean stomatogastric nervous system, we study the influence of these differences in underlying structure on differential resilience of individuals to a variety of environmental perturbations, including changes in temperature, pH, potassium concentration and neuromodulation. We show that neurons with many different kinds of ion channels can smoothly move through different mechanisms in generating their activity patterns, thus extending their dynamic range.

My research at the interface of neurobiology, biomechanics, and behavior seeks to understand how the timing precision of sensory input structures locomotor output. My lab studies the flight behavior of the fruit fly, Drosophila melanogaster, combining powerful genetic tools available for labeling and manipulating neural circuits with cutting-edge imaging in awake, behaving animals. This work has the potential to fundamentally reshape understanding of the evolution of insect flight, as well as highlight the tremendous importance of timing in the context of locomotion. Timing is crucial to the nervous system. The ability to rapidly detect and process subtle disturbances in the environment determines whether an animal can attain its next meal or successfully navigate complex, unpredictable terrain. While previous work on various animals has made tremendous strides uncovering the specialized neural circuits used to resolve timing differences with sub-microsecond resolution, it has focused on the detection of timing differences in sensory systems. Understanding of how the timing of motor output is structured by precise sensory input remains poor. My research focuses on an organ unique to fruit flies, called the haltere, that serves as a bridge for detecting and acting on subtle timing differences, helping flies execute rapid maneuvers. Understanding how this relatively simple insect canperform such impressive aerial feats demands an integrative approach that combines physics, muscle mechanics, neuroscience, and behavior. This unique, powerful approach will reveal the general principles that govern sensorimotor processing.

By continuously producing electrical signals, neurones are amongst the most energy-demanding cells in the organism. Resting ionic levels are restored via metabolic pumps that receive the necessary energy from oxygen supplied by blood vessels. Intense spontaneous neural activity is omnipresent in the developing CNS. It occurs during short, well-defined periods that coincide precisely with the timing of angiogenesis. Such coincidence cannot be random; there must be a universal mechanism triggering spontaneous activity concurrently with blood vessels invading neural territories for the first time. However, surprisingly little is known about the role of neural activity per se in guiding angiogenesis. Part of the reason is that it is challenging to study developing neurovascular networks in tri-dimensional space in the brain. We investigate these questions in the neonatal mouse retina, where blood vessels are much easier to visualise because they initially grow in a plane, while waves of spontaneous neural activity (spreading via cholinergic starburst amacrine cells) sweep across the retinal ganglion cell layer, in close juxtaposition with the growing vasculature. Blood vessels reach the periphery by postnatal day (P) 7-8, shortly before the cholinergic waves disappear (at P10). We discovered transient clusters of auto-fluorescent cells that form an annulus around the optic disc, gradually expanding to the periphery, which they reach at the same time as the growing blood vessels. Remarkably, these cells appear locked to the frontline of the growing vasculature. Moreover, by recording waves with a large-scale multielectrode array that enables us to visualise them at pan-retinal level, we found that their initiation points are not random; they follow a developmental centre-to-periphery pattern similar to the clusters and blood vessels. The density of growing blood vessels is higher in cluster areas than in-between clusters at matching eccentricity. The cluster cells appear to be phagocytosed by microglia. Blocking Pannexin1 (PANX1) hemichannels activity with probenecid completely blocks the spontaneous waves and results in the disappearance of the fluorescent cell clusters. We suggest that these transient cells are specialised, hyperactive neurones that form spontaneous activity hotspots, thereby triggering retinal waves through the release of ATP via PANX1 hemichannels. These activity hotspots attract new blood vessels to enhance local oxygen supply. Signalling through PANX1 attracts microglia that establish contact with these cells, eventually eliminating them once blood vessels have reached their vicinity. The auto-fluorescence that characterises the cell clusters may develop only once the process of microglial phagocytosis is initiated.

To enable the understanding and repair of complex biological systems, such as the brain, we are creating novel optical tools that enable molecular-resolution maps of such systems, as well as technologies for observing and controlling high-speed physiological dynamics in such systems. First, we have developed a method for imaging specimens with nanoscale precision, by embedding them in a swellable polymer, homogenizing their mechanical properties, and exposing them to water – which causes them to expand manyfold isotropically. This method, which we call expansion microscopy (ExM), enables ordinary microscopes to do nanoscale imaging, in a multiplexed fashion – important, for example, for brain mapping. Second, we have developed a set of genetically-encoded reagents, known as optogenetic tools, that when expressed in specific neurons, enable their electrical activities to be precisely driven or silenced in response to millisecond timescale pulses of light. Finally, we are designing, and evolving, novel reagents, such as fluorescent voltage indicators and somatically targeted calcium indicators, to enable the imaging of fast physiological processes in 3-D with millisecond precision. In this way we aim to enable the systematic mapping, control, and dynamical observation of complex biological systems like the brain. The talk will be simultaneously interpreted English-Spanish) by the Interpreter, Mg. Lourdes Martino. Para permitir la comprensión y reparación de sistemas biológicos complejos, como el cerebro, estamos creando herramientas ópticas novedosas que permiten crear mapas de resolución molecular de dichos sistemas, así como tecnologías para observar y controlar la dinámica fisiológica de alta velocidad en dichos sistemas. Primero, hemos desarrollado un método para obtener imágenes de muestras con precisión a nanoescala, incrustándolas en un polímero hinchable, homogeneizando sus propiedades mecánicas y exponiéndolas al agua, lo que hace que se expandan muchas veces isotrópicamente. Este método, que llamamos microscopía de expansión (ExM), permite que los microscopios ordinarios obtengan imágenes a nanoescala, de forma multiplexada, lo que es importante, por ejemplo, para el mapeo cerebral. En segundo lugar, hemos desarrollado un conjunto de reactivos codificados genéticamente, conocidos como herramientas optogenéticas, que cuando se expresan en neuronas específicas, permiten que sus actividades eléctricas sean activadas o silenciadas con precisión en respuesta a pulsos de luz en una escala de tiempo de milisegundos. Finalmente, estamos diseñando y desarrollando reactivos novedosos, como indicadores de voltaje fluorescentes e indicadores de calcio dirigidos somáticamente, para permitir la obtención de imágenes de procesos fisiológicos rápidos en 3-D con precisión de milisegundos. De esta manera, nuestro objetivo es permitir el mapeo sistemático, el control y la observación dinámica de sistemas biológicos complejos como el cerebro. La conferencia será traducida simultáneamente al español por la intérprete Mg. Lourdes Martino.

I will review advances in understanding the cortical encoding of speech-related oral movements. These discoveries are being translated to develop algorithms to decode speech from population neural activity.