CENTRAL PROBLEMS IN SINGLE CELL COMPUTATION
16-18 September 2002
By invitation only
B10 Seminar Room, Alexandra House, 17 Queen Square, London, WC1N 3AR
|Input-output relationships of cortical
synaptic connections during complex patterns of activation
|Hugh Robinson, Department of
Physiology, University of Cambridge, UK
|The postsynaptic response at a cortical
synaptic connection appears to depend on its activation history over a wide range of
timescales, and also has significant randomness. Because the trajectory of responses is
shaped by stochastic release behaviour at individual terminals, which influences
subsequent transmitter release, the dynamics of responses to individual synaptic
connections is richer and more difficult to describe than the ensemble average response.
The number of functional contacts between pairs of cortical cells is typically very low,
so that the time-correlated behaviour of individual connections may be functionally more
relevant than their average behaviour. We have used a new approach to characterising the
input-output map of individual synaptic connections during arbitrary, complex stimulation.
The history of activation and response is captured by a delay vector (or embedding) of
both response amplitudes and of intervals between presynaptic APs. Synaptic transmission
is represented by the mapping of delay vectors to their subsequent response amplitude.
Defining a measure of distance between different vectors, the reliability and variability
of the synaptic input-output map can be quantified by the extent to which near-neighbour
delay vectors lead to similar responses. We applied this to paired recordings between
pyramidal neurons in young rat cortical slices, with long (> 30 minutes),
non-repeating, natural-like presynaptic spike trains. Near-neighbour prediction of
synaptic responses was much more accurate than a best-fit model of short-term plasticity.
The timescale of activation which measurably contributed to predictability was usually
several minutes, but depended on the structure of the stimulus train. With Poisson
stimulation, delay vectors were much more highly clustered than expected by chance,
reflecting a wide spread in the transmission reliability of patterns within the stimulus.
Reliability also distinguished classes of response with different amplitude distributions:
reliably-stimulated responses had tightly-clustered amplitude distributions, while
unreliably-stimulated responses did not. We are using this method to classify the dynamics
of synaptic connections, and to examine the effects of long-term plasticity on the
synaptic input-output relationship during natural, complex stimulation patterns.
|Joint work with Ingo Kleppe
|Supported by the BBSRC and the Boehringer