Prolonged Synaptic Integration in Perirhinal Cortical Neurons
1 Department of Psychology, 2 Interdepartmental Neuroscience Program, and 3 Department of Cellular and Molecular Physiology, Yale University, New Haven, Connecticut 06520 Beggs, John M., James R. Moyer Jr., John P. McGann, and Thomas H. Brown. Prolonged Synaptic Integration in Perirhinal Corti...
Saved in:
Published in | Journal of neurophysiology Vol. 83; no. 6; pp. 3294 - 3298 |
---|---|
Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
United States
Am Phys Soc
01.06.2000
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | 1 Department of Psychology,
2 Interdepartmental Neuroscience Program, and
3 Department of Cellular and Molecular
Physiology, Yale University, New Haven, Connecticut 06520
Beggs, John M.,
James R. Moyer Jr.,
John P. McGann, and
Thomas H. Brown.
Prolonged Synaptic Integration in Perirhinal Cortical Neurons. J. Neurophysiol. 83: 3294-3298, 2000. Layer II/III of rat perirhinal cortex (PR) contains numerous
late-spiking (LS) pyramidal neurons. When injected with a depolarizing current step, these LS cells typically delay spiking for one
or more seconds from the onset of the current step and then
sustain firing for the duration of the step. This pattern of
delayed and sustained firing suggested a specific computational role
for LS cells in temporal learning. This hypothesis predicts and
requires that some layer II/III neurons should also exhibit delayed and sustained spiking in response to a train of excitatory
synaptic inputs. Here we tested this prediction using
visually guided, whole cell recordings from rat PR brain slices. Most
LS cells (19 of 26) exhibited delayed spiking to synaptic
stimulation (>1 s latency from the train onset), and the majority of
these cells (13 of 19) also showed sustained firing that
persisted for the duration of the synaptic train (5-10 s duration).
Delayed and sustained firing in response to long synaptic trains has
not been previously reported in vertebrate neurons. The data are
consistent with our model that a circuit containing late spiking
neurons can be used for encoding long time intervals during associative learning. |
---|---|
Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 ObjectType-Article-1 ObjectType-Feature-2 |
ISSN: | 0022-3077 1522-1598 |
DOI: | 10.1152/jn.2000.83.6.3294 |