Goetz, Lea;
(2018)
Single neuron computation in vivo.
Doctoral thesis (Ph.D), UCL (University College London).
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Abstract
Single neurons form the fundamental information processing units of the brain. Yet despite our growing knowledge of the electrophysiological and molecular properties of single neurons and their dendrites, little is known about their contribution to information processing in vivo, which depends strongly on the patterns of synaptic input and the way in which they engage active dendritic mechanisms. Here, I address the input-output function of single neurons in vivo and the role played by active dendrites in pyramidal neurons of mouse primary visual cortex using a dual modelling and experimental approach. First, I developed and tested new experimental techniques to map functional synaptic input in vivo: I have established an ultrastructural method to label active synapses received by the dendrites of an identified neuron during sensory processing in vivo, while measuring its output with somatic whole-cell recording. I show how to use the styryl dye FM1-43FX as an activity-dependent in vivo label which can be read out using focused ion-beam electron microscopy (FIBSEM) and I developed a pipeline for the semi-automated segmentation of the resulting FIBSEM volumes. Second, to study dendritic computation and the role of dendritic spikes in vivo, I have constructed a detailed biophysical model of a layer 2/3 pyramidal neuron, and a model of the synaptic input it receives during visual stimulation in vivo. Both models are tightly constrained by experimental data from the literature, including direct patch-clamp recordings from layer 2/3 dendrites in vivo. My work answers longstanding questions about the synaptic input patterns received by single neurons in vivo and the computations implemented by their integration in active dendrites: I provide a detailed biophysical mechanism for the transformation of synaptic inputs, via dendritic nonlinearities, to somatic output and elucidate the role of active dendrites for the function of the neuron.
| Type: | Thesis (Doctoral) |
|---|---|
| Qualification: | Ph.D |
| Title: | Single neuron computation in vivo |
| Event: | UCL (University College London) |
| Open access status: | An open access version is available from UCL Discovery |
| Language: | English |
| Additional information: | Copyright © The Author 2018. Original content in this thesis is licensed under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) Licence (https://creativecommons.org/licenses/by/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request. |
| UCL classification: | UCL > Provost and Vice Provost Offices UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10062620 |
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