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Determinants of pattern recognition by cerebellar Purkinje cells

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Giseli De Sousa at University of Hertfordshire
Giseli De Sousa
Rod Adams
Rod Adams
Rod Adams
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Neil Davey
Neil Davey
Neil Davey
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Volker Steuber at University of Hertfordshire
Volker Steuber
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BMC Neuroscience
Open Access
Poster presentation
Determinants of pattern recognition by cerebellar Purkinje cells
Giseli de Sousa*, Rod Adams, Neil Davey and Volker Steuber
Address: Science and Technology Research Institute, University of Hertfordshire, Hatfield Herts, AL10 9AB, UK
Email: Giseli de Sousa* - g.sousa@herts.ac.uk
* Corresponding author
Many theories of cerebellar function assume that long-
term depression (LTD) of parallel fiber (PF) synapses ena-
bles Purkinje cells (PCs) to learn to recognize PF activity
patterns. According to the classic view, a PC can store and
learn to distinguish PF activity patterns that have been
presented repeatedly together with climbing fibre (CF)
input to the cell. The resulting LTD of the PF synapses is
often assumed to lead to a decreased rate of PC simple
spike firing, a reduction in the inhibition of their target
neurons in the deep cerebellar nuclei and thus an
increased output from the cerebellum. We have recently
shown by combining computer simulations with electro-
physiological recordings in slices and in awake behaving
mice that the readout of learned patterns in PCs may oper-
ate in a fundamentally different way. Our simulations and
experiments predict that the best criterion to distinguish
between learned and novel patterns is the duration of a
pause in firing that occurs after presentation of a pattern,
with shorter pauses in response to learned patterns [1].
Although our previous simulations have used a biophysi-
cally detailed PC model that has been tuned to generate
realistic behaviours under in vitro and in vivo conditions,
we have applied a simplified learning rule where the
AMPA receptor conductance of an active PF synapse is
halved every time a PF pattern is learned. Moreover, our
previous simulations have not incorporated the LTD of
inhibitory synapses that can be induced when the PC
receives coincident CF input [2], and that could poten-
tially counteract the effect of the depression of the excita-
tory PF synapses. Here, we study the effect of inhibitory
synaptic plasticity on pattern recognition, and we explore
a variation of our original learning rule that has been
adapted to result in a better match to experimental data
on LTD induction in slices [2,3].
To study the effect of plasticity at the synapses between
inhibitory interneurons and PCs, we presented the model
with feed-forward inhibitory input, which followed the
excitatory input with a time delay of 1.4 ms [1,2]. Initially,
we chose an inhibition/excitation ratio of one, in the
range of experimental observations in vitro [2]. We then
introduced LTD at the inhibitory synapses and evaluated
the pattern recognition performance for varying numbers
of learned patterns. We found that the performance was
unaffected by the presence of inhibitory LTD, even in the
extreme case when the inhibitory plasticity was restricted
to the presentation of learned PF patterns. Our simula-
tions predict that LTD based pattern recognition is very
robust in the presence of LTD at inhibitory synapses.
By dividing the synaptic weights of active PFs by two for
every pattern that was learned, our original learning rule
could result in very small AMPA receptor conductances for
large numbers of learned patterns. However, LTD induc-
tion in cerebellar slices hardly ever results in the depres-
sion of responses to less than 50% of the pre-induction
baseline [2,3]. We studied the effect of saturating LTD in
our simulations and found that the pattern recognition
performance was very sensitive to the value at which the
synaptic weights saturated. In contrast to a corresponding
artificial neural network, which was unaffected by the
value at which LTD saturated, pause based pattern recog-
nition in the PC model deteriorated drastically in the pres-
ence of higher saturation values and therefore smaller
amounts of LTD. To result in satisfactory pattern recogni-
tion, LTD had to depress the AMPA receptor conductances
from Seventeenth Annual Computational Neuroscience Meeting: CNS*2008
Portland, OR, USA. 19–24 July 2008
Published: 11 July 2008
BMC Neuroscience 2008, 9(Suppl 1):P67 doi:10.1186/1471-2202-9-S1-P67
This abstract is available from: http://www.biomedcentral.com/1471-2202/9/S1/P67
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in the PC model down to at least 70% of their baseline
values, and optimal performance resulted from setting the
weights to zero and silencing the synapses completely.
Interestingly, large numbers of silent PF synapses have
been observed in another experimental study [4]. Our
simulation results suggest that it will be crucial to explore
these discrepancies to understand the connection between
PF LTD and pattern recognition.
References
1. Steuber V, Mittmann W, Hoebeek FE, Silver RA, De Zeeuw CI,
Hausser M, De Schutter E: Cerebellar LTD and pattern recog-
nition by Purkinje cells. Neuron 2007, 54:121-136.
2. Mittmann W, Hausser M: Linking synaptic plasticity and spike
output at excitatory and inhibitory synapses onto cerebellar
Purkinje cells. J Neurosci 2007, 27:5559-5570.
3. Wang S-H, Denk W, Hausser M: Coincidence detection in single
dendritic spines mediated by calcium release. Nat Neurosci
2000, 3:1266-1273.
4. Isope P, Barbour B: Properties of unitary granule cell – Purkinje
cell synapses in adult rat cerebellar slices. J Neurosci 2002,
22:9668-9678.
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