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Tracking receptive field dynamics in CA1 and the
entorhinal cortex
with an adaptive point process filtering algorithm
Loren M. Frank1,
U.T. Eden1,
R. Barbieri1,
V. Solo2
Matt A. Wilson3 and
Emery N. Brown1
1Harvard/MIT
2University of New South Wales, Sydney, Australia
3Riken - MIT Neuroscience Institute
Neural receptive fields are dynamic: the nature of a neuron's response
to a stimulus can change over time as a result of experience. In the
CA1 region of the hippocampus, place cells' spatial receptive fields
increase in total firing rate, and move and become skewed in the
direction opposite the animal's direction of motion as a result of
repeated passes through the place field (Mehta et al. 1997, 2000).
Here we extend those findings by developing an adaptive point process
filtering algorithm that allows us to estimate receptive field shape
on a millisecond time scale without binning over time or space (Brown
et al. 2000). Our algorithm allowed us to estimate a firing rate
function for each cell that depends on both the animal's position and
the history of spiking. We applied this algorithm to simultaneously
recorded neurons from the CA1 subregion of the hippocampus and from
the superficial and deep layers of the entorhinal cortex (EC) of rats
running along a U shaped track. The EC was chosen as a recording site
because superficial EC cells provide the main source of neocortical
input to the hippocampus and deep EC cells are the primary targets of
neocortically bound hippocampal outputs. We found that including
history dependence in our model improved the goodness-of-fit to the
data, suggesting that examining firing rate as a function of
behavioral correlates alone may not accurately describe neural
activity patterns. Overall, our results for CA1 were consistent with
those of Mehta et al. (1997, 2000). At the same time, the place
fields of superficial and deep EC cells did not show a tendency to
move backwards along the animal's direction of motion. The most
striking finding was that, on average, the spatial firing rate
functions of superficial and deep EC cells, like those of CA1 cells,
increased in total area while the variance of these functions either
decreased or remained constant. In addition, the increase in total
firing was significantly faster in CA1 than in the deep EC. These
results suggest that place specific activity in both CA1 and the EC
sharpens over the course of the animal's experience and that receptive
field plasticity may occur on a faster time scale in CA1 as compared
to the EC. Thus, our findings support the hypothesis that the
hippocampus is a site of rapid learning as compared to the EC. More
generally, we believe that our algorithm may provide a new and
powerful tool for analyzing the dynamics of receptive field
plasticity.