Vogels Group

Computational Neuroscience and Neurotheory

The Vogels Group is looking to build models of neurons and neuronal networks that distill and re-articulate the current knowledge of how nervous systems compute at a mechanistic level. In particular, the group is interested in the neuronal interplay of excitatory and inhibitory activity in cortex and how these dynamics can form reliable sensory perceptions, stable memories, and motor outputs.

More specifically, the work in our lab is divided into three main areas:

1) Plasticity

The group aims to find the rules governing how the brain updates its synaptic connections in order to learn and adapt to a changing world. In collaboration with experimentalists working on various systems from humans to the fruit fly, we build mechanistic models of synaptic plasticity to help elucidate (i) how plasticity differs across different cell types in cortical networks, (ii) how learning is guided by neuromodulatory signals, (iii) how learning changes across development, and (iv) how changes in synaptic connections affect the resulting neuronal network dynamics used for computation.

2) Network dynamics and computation

The Vogels group seeks to understand how neuronal networks process and transform sensory inputs, store and manipulate memories, and send motor outputs. By building and analysing models of spiking and firing-rate neuronal networks, the group studies the role of inhibition and excitatory-inhibitory balance in processing and gating the flow of information, and how contextual and reinforcement signals modify network properties to produce the flexible and complex dynamics seen in current large-scale neuronal recordings.

3) Ion channels and single-neuron biophysics

The Vogels Group builds detailed biophysical models of single neurons in order to understand the complex input-output relationships at the level of single neurons and their dendritic branches. In collaboration with researchers at EPFL (Lausanne) and the CNCB (Oxford), they have created an extensive database of ion channel models and their relationships, to facilitate better experimentally-constrained modelling (ICGenealogy). The Group is now working to expand this resource into other areas of neuroinformatics in order to help make sense of the large amounts of data that experimental and computational neuroscience currently produces.