Angus Silver

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Angus Silver

FRS
Angus Silver Royal Society.jpg
Angus Silver at the Royal Society admissions day in London, July 2017
Born
Robin Angus Silver
Alma mater Coventry Polytechnic (BSc)
University College London (PhD)
Scientific career
Fields Neuroscience
Neuroinformatics
Microscopy
Thesis Calcium as a second messenger in neuronal growth cones  (1990)
Website silverlab.org

Robin Angus Silver FRS [1] is Professor of Neuroscience and a Wellcome Trust Principal Research Fellow at University College London. [2] [3] [4] His laboratory studies neurotransmission and artificial neural networks by combining in vitro and in vivo experimental approaches with quantitative analysis and computational models developed in silico . [5] [6] [7]

Contents

Education

Silver was educated at Coventry Polytechnic where he graduated in 1986 with a Bachelor of Science degree in Physical Sciences. [3] He completed postgraduate study at University College London where he was awarded a PhD in Neuroscience in 1990 for research investigating calcium signalling and second messenger systems in neural growth cones. [8]

Research and career

Silver's work has contributed to our understanding of synaptic and neuronal function and to information processing in the brain. [9] By developing and applying methods for quantifying synaptic properties his work has shown how central synapses transmit and transform signals and can sustain high frequency signalling. He has quantified the functional properties of electrical synapses and established how neurons can perform certain arithmetic operations. [1] [10]

Using theoretical approaches, he has provided insights into the structure and function of neural circuits, showing that synaptic connectivity within the cerebellar input layer is optimal for encoding information and separating overlapping activity patterns. [1]

Silver's group have developed new tools for studying circuit function. These include a high-speed random access 3D scanning fluorescence microscope that uses an acousto-optic lens to scan and focus the laser beam, enabling measurement of spatially distributed neuronal activity at high speed. He has also coordinated the development of software for building models of neural circuits, (neuroConstruct), [6] a language for standardising model descriptions (NeuroML), [7] and a repository of standardized models and infrastructure for collaborative model development, OpenSourceBrain. [11] [5]

Silver's research has been funded by the Biotechnology and Biological Sciences Research Council (BBSRC), European Research Council (ERC) and the Wellcome Trust. [12]

Awards and honours

Silver was elected a Fellow of the Royal Society (FRS) in 2017. [1]

Related Research Articles

<span class="mw-page-title-main">Neuron</span> Electrically excitable cell found in the nervous system of animals

Within a nervous system, a neuron, neurone, or nerve cell is an electrically excitable cell that fires electric signals called action potentials across a neural network. Neurons communicate with other cells via synapses, which are specialized connections that commonly use minute amounts of chemical neurotransmitters to pass the electric signal from the presynaptic neuron to the target cell through the synaptic gap.

The development of the nervous system, or neural development (neurodevelopment), refers to the processes that generate, shape, and reshape the nervous system of animals, from the earliest stages of embryonic development to adulthood. The field of neural development draws on both neuroscience and developmental biology to describe and provide insight into the cellular and molecular mechanisms by which complex nervous systems develop, from nematodes and fruit flies to mammals.

Computational neuroscience is a branch of neuroscience which employs mathematics, computer science, theoretical analysis and abstractions of the brain to understand the principles that govern the development, structure, physiology and cognitive abilities of the nervous system.

<span class="mw-page-title-main">Neural circuit</span> Network or circuit of neurons

A neural circuit is a population of neurons interconnected by synapses to carry out a specific function when activated. Multiple neural circuits interconnect with one another to form large scale brain networks.

<span class="mw-page-title-main">Neuronal noise</span> Random electric fluctuations in neurons

Neuronal noise or neural noise refers to the random intrinsic electrical fluctuations within neuronal networks. These fluctuations are not associated with encoding a response to internal or external stimuli and can be from one to two orders of magnitude. Most noise commonly occurs below a voltage-threshold that is needed for an action potential to occur, but sometimes it can be present in the form of an action potential; for example, stochastic oscillations in pacemaker neurons in suprachiasmatic nucleus are partially responsible for the organization of circadian rhythms.

<span class="mw-page-title-main">Synaptic pruning</span> Process of synapse elimination that occurs between early childhood and the onset of puberty

Synaptic pruning, a phase in the development of the nervous system, is the process of synapse elimination that occurs between early childhood and the onset of puberty in many mammals, including humans. Pruning starts near the time of birth and continues into the late-20s. During pruning, both the axon and dendrite decay and die off. It was traditionally considered to be complete by the time of sexual maturation, but this was discounted by MRI studies.

The development of the nervous system in humans, or neural development or neurodevelopment involves the studies of embryology, developmental biology, and neuroscience to describe the cellular and molecular mechanisms by which the complex nervous system forms in humans, develops during prenatal development, and continues to develop postnatally.

Synaptic noise refers to the constant bombardment of synaptic activity in neurons. This occurs in the background of a cell when potentials are produced without the nerve stimulation of an action potential, and are due to the inherently random nature of synapses. These random potentials have similar time courses as excitatory postsynaptic potentials (EPSPs) and inhibitory postsynaptic potentials (IPSPs), yet they lead to variable neuronal responses. The variability is due to differences in the discharge times of action potentials.

Connectomics is the production and study of connectomes: comprehensive maps of connections within an organism's nervous system. More generally, it can be thought of as the study of neuronal wiring diagrams with a focus on how structural connectivity, individual synapses, cellular morphology, and cellular ultrastructure contribute to the make up of a network. The nervous system is a network made of billions of connections and these connections are responsible for our thoughts, emotions, actions, memories, function and dysfunction. Therefore, the study of connectomics aims to advance our understanding of mental health and cognition by understanding how cells in the nervous system are connected and communicate. Because these structures are extremely complex, methods within this field use a high-throughput application of functional and structural neural imaging, most commonly magnetic resonance imaging (MRI), electron microscopy, and histological techniques in order to increase the speed, efficiency, and resolution of these nervous system maps. To date, tens of large scale datasets have been collected spanning the nervous system including the various areas of cortex, cerebellum, the retina, the peripheral nervous system and neuromuscular junctions.

<span class="mw-page-title-main">Nonsynaptic plasticity</span> Form of neuroplasticity

Nonsynaptic plasticity is a form of neuroplasticity that involves modification of ion channel function in the axon, dendrites, and cell body that results in specific changes in the integration of excitatory postsynaptic potentials and inhibitory postsynaptic potentials. Nonsynaptic plasticity is a modification of the intrinsic excitability of the neuron. It interacts with synaptic plasticity, but it is considered a separate entity from synaptic plasticity. Intrinsic modification of the electrical properties of neurons plays a role in many aspects of plasticity from homeostatic plasticity to learning and memory itself. Nonsynaptic plasticity affects synaptic integration, subthreshold propagation, spike generation, and other fundamental mechanisms of neurons at the cellular level. These individual neuronal alterations can result in changes in higher brain function, especially learning and memory. However, as an emerging field in neuroscience, much of the knowledge about nonsynaptic plasticity is uncertain and still requires further investigation to better define its role in brain function and behavior.

Developmental plasticity is a general term referring to changes in neural connections during development as a result of environmental interactions as well as neural changes induced by learning. Much like neuroplasticity, or brain plasticity, developmental plasticity is specific to the change in neurons and synaptic connections as a consequence of developmental processes. A child creates most of these connections from birth to early childhood. There are three primary methods by which this may occur as the brain develops, but critical periods determine when lasting changes may form. Developmental plasticity may also be used in place of the term phenotypic plasticity when an organism in an embryonic or larval stage can alter its phenotype based on environmental factors. However, a main difference between the two is that phenotypic plasticity experienced during adulthood can be reversible, whereas traits that are considered developmentally plastic set foundations during early development that remain throughout the life of the organism.

<span class="mw-page-title-main">Retrograde tracing</span> Technique for mapping neural circuits in the "upstream" direction, from target to source

Retrograde tracing is a research method used in neuroscience to trace neural connections from their point of termination to their source. Retrograde tracing techniques allow for detailed assessment of neuronal connections between a target population of neurons and their inputs throughout the nervous system. These techniques allow the "mapping" of connections between neurons in a particular structure and the target neurons in the brain. The opposite technique is anterograde tracing, which is used to trace neural connections from their source to their point of termination. Both the anterograde and retrograde tracing techniques are based on the visualization of axonal transport.

NeuroML is an XML based model description language that aims to provide a common data format for defining and exchanging models in computational neuroscience. The focus of NeuroML is on models which are based on the biophysical and anatomical properties of real neurons.

An autapse is a chemical or electrical synapse from a neuron onto itself. It can also be described as a synapse formed by the axon of a neuron on its own dendrites, in vivo or in vitro.

<span class="mw-page-title-main">Michael Hausser</span>

Michael A. Häusser FRS FMedSci is professor of Neuroscience, based in the Wolfson Institute for Biomedical Research at University College London (UCL).

<span class="mw-page-title-main">Dimitri Kullmann</span> British neurologist

Dimitri Michael Kullmann is a professor of neurology at the UCL Institute of Neurology, University College London (UCL), and leads the synaptopathies initiative funded by the Wellcome Trust. Kullmann is a member of the Queen Square Institute of Neurology Department of Clinical and Experimental Epilepsy and a consultant neurologist at the National Hospital for Neurology and Neurosurgery.

<span class="mw-page-title-main">Yves-Alain Barde</span> Swiss neurobiologist working in Britain

Yves-Alain Barde is a professor of Neurobiology at Cardiff University. He was elected a Fellow of the Royal Society (FRS) in 2017.

<span class="mw-page-title-main">Neil Burgess (neuroscientist)</span> British neuroscientist (born 1966)

Neil Burgess is a British neuroscientist. He has been a professor of cognitive neuroscience at University College London since 2004 and a Wellcome Trust Principal Research Fellow since 2011. He has made important contributions to understanding memory and spatial cognition by developing computational models relating behaviour to activity in biological neural networks.

Tara Keck is an American-British neuroscientist and Professor of Neuroscience and Wellcome Trust Senior Research Fellow, at University College London working in the Department of Neuroscience, Physiology, and Pharmacology. She is the Vice-Dean International for the Faculty of Life Sciences. She studies experience-dependent synaptic plasticity, its effect on behaviour and how it changes during ageing and age-related diseases. She has worked in collaboration with the United Nations Population Fund on approaches for healthy ageing. Her recent work has focused on loneliness in older people, with a focus on gender. She was named a UNFPA Generations and Gender Fellow in 2022.

<span class="mw-page-title-main">Brain cell</span> Functional tissue of the brain

Brain cells make up the functional tissue of the brain. The rest of the brain tissue is structural or connective called the stroma which includes blood vessels. The two main types of cells in the brain are neurons, also known as nerve cells, and glial cells, also known as neuroglia.

References

  1. 1 2 3 4 Anon (2017). "Professor Angus Silver FRS". royalsociety.org. London: Royal Society. One or more of the preceding sentences incorporates text from the royalsociety.org website where:
    “All text published under the heading 'Biography' on Fellow profile pages is available under Creative Commons Attribution 4.0 International License.” -- "Terms, conditions and policies | Royal Society". Archived from the original on 11 November 2016. Retrieved 9 March 2016.{{cite web}}: CS1 maint: bot: original URL status unknown (link)
  2. Angus Silver publications indexed by the Scopus bibliographic database. (subscription required)
  3. 1 2 Anon (2017). "Professor Angus Silver at UCL". iris.ucl.ac.uk. Archived from the original on 6 October 2017. Retrieved 16 August 2017.
  4. Angus Silver publications from Europe PubMed Central
  5. 1 2 Eglen, Stephen J; Marwick, Ben; Halchenko, Yaroslav O; Hanke, Michael; Sufi, Shoaib; Gleeson, Padraig; Silver, R Angus; Davison, Andrew P; Lanyon, Linda; Abrams, Mathew; Wachtler, Thomas; Willshaw, David J; Pouzat, Christophe; Poline, Jean-Baptiste (2017). "Toward standard practices for sharing computer code and programs in neuroscience". Nature Neuroscience . 20 (6): 770–773. doi:10.1038/nn.4550. ISSN   1097-6256. PMC   6386137 . PMID   28542156.
  6. 1 2 Gleeson, Padraig; Steuber, Volker; Silver, R. Angus (2007). "neuroConstruct: A Tool for Modeling Networks of Neurons in 3D Space". Neuron . 54 (2): 219–235. doi:10.1016/j.neuron.2007.03.025. ISSN   0896-6273. PMC   1885959 . PMID   17442244.
  7. 1 2 Friston, Karl J.; Gleeson, Padraig; Crook, Sharon; Cannon, Robert C.; Hines, Michael L.; Billings, Guy O.; Farinella, Matteo; Morse, Thomas M.; Davison, Andrew P.; Ray, Subhasis; Bhalla, Upinder S.; Barnes, Simon R.; Dimitrova, Yoana D.; Silver, R. Angus (2010). "NeuroML: A Language for Describing Data Driven Models of Neurons and Networks with a High Degree of Biological Detail". PLOS Computational Biology . 6 (6): e1000815. Bibcode:2010PLSCB...6E0815G. doi: 10.1371/journal.pcbi.1000815 . ISSN   1553-7358. PMC   2887454 . PMID   20585541. Open Access logo PLoS transparent.svg
  8. Silver, Robin Angus (1990). Calcium as a second messenger in neuronal growth cones. london.ac.uk (PhD thesis). University of London. OCLC   941024084.
  9. Rothman, Jason Seth; Kocsis, Laszlo; Herzog, Etienne; Nusser, Zoltan; Silver, Robin Angus (2016). "Physical determinants of vesicle mobility and supply at a central synapse". eLife . 5 (e15133). doi: 10.7554/eLife.15133 . ISSN   2050-084X. PMC   5025287 . PMID   27542193. Open Access logo PLoS transparent.svg
  10. Silver, R. Angus (2010). "Neuronal arithmetic". Nature Reviews Neuroscience . 11 (7): 474–489. doi:10.1038/nrn2864. ISSN   1471-003X. PMC   4750293 . PMID   20531421.
  11. Anon (2017). "Open Source Brain: Modelling the brain, together". OpenSourceBrain.org.
  12. Anon (2017). "Members of the Silver Lab". silverlab.org/members.