Event Details

Wednesday, 24 August 2016
12:00 pm - 1:00 pm
QBI Level 7 Auditorium
UQ Location:
Queensland Brain Institute (St Lucia)
Event category(s):

Event Contact

Ms Deirdre Wilson
334 66300
Org. Unit:
Queensland Brain Institute

Event Description

Full Description:
Dr Simon R Schultz
Head, Neural Coding Laboratory,
Department of Bioengineering, Imperial College, London, UK

Title: Analysis of information encoding and dynamics in optically recorded cortical circuits

Abstract: In recent years, technology for large-scale recording of neural circuit dynamics, at single cell resolution, has progressed extremely rapidly. Several international initiatives, including the US NIH BRAIN Initiative, mean that we are likely to see further developments, including the ability to manipulate as well as read out neural ensemble activity. As well as enhancing our understanding of numerous basic questions in systems neuroscience, we can hope that these techniques are likely to be of translational benefit, by allowing the characterisation of changes to circuit behaviour in mouse models of neurodegenerative disorders to be studied in great detail and across scales. Scalable data analysis tools capable of taking into consideration patterns of neural ensemble activity, however, become a limiting factor once neural population sizes exceed a few tens of neurons.

In the past, I have developed information theoretic methods for analysing how information is represented in spike trains fired by small ensembles of neurons. In this talk, I will describe several approaches we are taking to scale these approaches up to tens and hundreds of neurons recorded simultaneously through two photon calcium imaging. We take two quite different approaches. In the first approach, we consider the calcium time series from the neural ensemble as a multivariate continuous time series, and employ approaches from nonlinear dynamics, together with dimensionality reduction. In the second, we use a calcium transient detection algorithm to instead represent the data as a digitized multineuron spike train, and make strong but testable assumptions about the underlying variability. In the talk, I will describe the application of these methods to data from a number of cortical circuits: neocortical, archicortical (hippocampus) and the cerebellar cortical circuit.

Directions to UQ

Google Map:
To St Lucia Campus, UQ Ipswich, and UQ Gatton.

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