organisation - the Instituto Gulbenkian de Ciência

PLASTICITY CONSEQUENCES OF NATURALISTIC SPIKE TRAINS
AT SINGLE SYNAPSES
Naturally occurring patterns of activity are complex in structure and have an
irregular distribution of action potentials. Thus far, synaptic plasticity at individual
inputs has been assessed through delivery of regular patterns of activity.
We aim to mimic the varied input patterns observed in vivo with glutamate
uncaging at individual spines, in order to determine what are the structural
and plasticity correlates of these forms of activity. We will determine how such
complex trains of activity interact across multiple synapses within a dendritic
branch. We will use this information to model neuronal information processing
in order to develop an understanding of the learning rules which govern
synaptic weight changes.
We have established a collaboration in order to obtain in vivo electrophysiological
recordings from hippocampal CA3 neurons. Experiments in which electrophysiological
recordings are coupled with 2-photon imaging in hippocampal
organotypic slice cultures are underway in order to monitor the structural and
plasticity correlates of spike timing dependent plasticity. This form of plasticity
depends on the integration of events at single inputs, similarly to what is
observed endogenously.
AUTOMATIC DENDRITIC SPINE DETECTION AND ANALYSIS
The combination of live 2-photon imaging and glutamate uncaging allows us
to investigate how neuronal structure and function are correlated at the level
of individual spines following synaptic activity. In addition to changes in the
volume of the spine head, many other changes in spine structure have been
observed, for example, changes in the length of the spine neck. Such changes
are difficult to quantify with existing methodologies, and therefore we aim to
develop automated data analysis tools for handling both the large data sets
and the many variables to be analysed. We aim to achieve greater precision and
flexibility in the quantification of structural changes, as well as to significantly
enhance the efficacy of data analysis.
Thus far, we have developed an automated, multi-level, region based segmentation
method to detect dendritic spines from two-photon laser scanning microscopy
images. Identified structures in two-photon images of dendritic spines
are used to train the segmentation algorithm. This is the first step towards a
broader automated dendritic spine detection and analysis framework.
IGC ANNUAL REPORT ‘11
RESEARCH FELLOWS
76