8th May: Roland Jones, University of Bath
Room: F40 (Medical Sciences)
Extracting background synaptic conductances from spontaneous membrane potential fluctuations in cortical neurones in vitro.
Cortical neurones are embedded in a dense network and are the target of thousands of individual synapses continuously releasing excitatory (glutamate) and inhibitory (GABA) transmitters. This is thought to aid signal detection through stochastic resonance, where sub-threshold synaptic events are pushed above threshold due to the presence of background activity. Thus, the relative level of inhibitory and excitatory back- ground activity is a reflection of network activity and is instrumental in determining the excitability of any given neurone We have studied release of both glutamate and GABA in the entorhinal cortex (EC) using whole cell patch clamp recording of spontaneous synaptic currents in vitro, but this approach does not lend itself well to relating the level of background activity to cellular excitability. Rudolph et al. (2004) proposed a method of estimating global background synaptic conductances from measurement of fluctuations in membrane potential derived from intracellular recordings applied to high conductance states characteristic of cortical networks in vivo. We asked whether we can meaningfully estimate global background excitatory and inhibitory conductances under the quiescent conditions in EC slices in vitro, and used a variety of pharmacological manipulations to validate this approach and relate changes in background to cellular excitability.
15th May: Casimir Ludwig
Room: SM3 (Mathematics)
Information sampling for perceptual decision-making
The choice of an appropriate course of action depends on the state of the environment: different states call for different actions. Frequently, the state of the environment has to be inferred from noisy sensory information. I am interested in the way humans sample information, how their sampling strategy depends on the quality of information, and how the sampling strategy influences their decision-making. I will talk about experimental and theoretical work that tests an “information foraging” account of sampling behaviour.
22th May: Jon Witton
Room: SM3 (Mathematics)
Studying hippocampal network function in mouse models of cognitive disease
29th May: Cian O’Donnell, Salk Institute
Room: SM3 (Mathematics)
Rogue states: altered dimensionality of neural circuit activity in Fragile-X mice
Brain disorders such as autism and schizophrenia have been hypothesized to arise from an imbalance in excitation/inhibition in neural circuits. Why or how such an imbalance would be detrimental for neural coding remains unclear. We approached the problem by analysing two-photon in vivo neural population recordings from the cortex of both wild-type and Fragile-X Syndrome model mice at different stages of development. We developed a new statistical model for the probability distribution of all 2^N possible neural population activity patterns that required only N^2 parameters, where N is the number of neurons. Using this model we found that the dimensionality of population activity was lower in young Fragile-X than wild-type mice, but surprisingly switched in adulthood so that Fragile-X dimensionality was higher than wild-type. Finally we used a computational model of layer 2/3 somatosensory cortex to show which neural circuit components can give rise to these alterations in dimensionality. Our findings show how small changes in neural circuit parameters can have dramatic consequences for information processing.
5th June: Claire Mitchell, University of Leicester
Room: SM3 (Mathematics)
A high-speed, super-resolution multiphoton microscope for imaging neuronal processes
The newest generation of fluorescent calcium indicators make it easier than ever to optically interrogate neurons for non-invasive, spatially-resolved electrophysiology. Current fluorescent imaging techniques however, can be limited in depth penetration, speed and/or resolution. By taking a laser scanning microscope and exchanging the point detector for a camera, it is possible to increase the resolution by a factor of two, a technique known as image scanning microscopy. This talk will discuss the physical principle behind this resolution increase and describe how our multiphoton implementation of image scanning microscopy can achieve high speed, super-resolution imaging at depth by using acousto-optic devices. I will then present some recent results; imaging neuronal structures in zebrafish in vivo and super-resolved calcium imaging in mouse hippocampal slices.
12th June: Alain Nogaret, University of Bath
Room: AIMS 2A/B (location)
Construction of accurate neuron models from the assimilation of electrophysiological data.
I will report on recent results that use nonlinear optimization to construct accurate single compartment models of biological neurons. Our variational approach based on interior point optimization has been successfully applied to extract model parameters from electrophysiological recordings of real neurons from the zebra finch forebrain nucleus HVC. Our results automatically estimate the 72 model parameters and allows accurate predictions of the actual neuron response to be made to arbitrarily complex current stimulation protocols. These results provide an important foundational basis for building biologically realistic network models both computational and analogue hardware models for biomedical implants.