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TRENDS in Neurosciences Vol.26 No.3 March 2003
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When neurons form memories
Pascal Fries, Guillén Fernández and Ole Jensen
F.C. Donders Centre for Cognitive Neuroimaging, Adelbertusplein 1, 6525 EK Nijmegen, The Netherlands
Although long-term memory is central among our
cognitive functions, the search for a direct neurophysiological correlate to it has proven difficult. The formation of new memories depends on the hippocampus
and adjacent cortex, but the final storage is thought to
be in a widely distributed neocortical network. Recent
experiments, using simultaneous recordings from hundreds of sites in monkey neocortex, have revealed the
activation of such a distributed network – probably
reflecting the consolidation of long-term memory
storage.
Long-term memory is a hallmark trait of the functioning
of our CNS. The second experience is never exactly the
same as the first. Each event leaves a trace in our brain
that shapes the way future encounters are handled.
However, it appears that the neocortical brain areas
that produce our conscious experience of an event
cannot at the same time directly store this event for
later recall. Rather, an intermediate trace is initially
stored in the medial temporal lobe (MTL), an area that
includes the archicortical hippocampus and the adjacent
cortical areas (the entorhinal, perirhinal and parahippocampal cortices) [1]. Subsequently, memories gradually
become independent of the MTL and established in
neocortex [2] by an operation called consolidation [3].
Memory consolidation is presumably based on a medial
temporal – neocortical interaction and might take place
predominantly during periods of rest or sleep, when no
new events are processed [4,5].
Distributed memories
A central finding in lesion studies of memory is that
consolidated, MTL-independent long-term memories
are not destroyed entirely by circumscribed lesions in
the neocortex [6,7]. This has led to the idea that neocortical memory traces are widely distributed [8,9] and
probably encoded in the strength of synaptic connections among neurons across large areas of neocortex
[10]. This notion received substantial experimental
support, and numerous theoretical modelling studies
have demonstrated the remarkable capacity of distributed storage in networks with modifiable synaptic
connections [11]. However, although distributed memory storage became the dominant concept in the field,
it evaded direct neurophysiological demonstration until
very recently.
The distributed nature that renders neocortical
memory storage so powerful has made it very hard
to study. The number of neurons in our brain is
Corresponding author: Pascal Fries ([email protected]).
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daunting and the number of their connections even
more so. Demonstrating that an event has changed
neuronal interactions requires simultaneous recordings
from hundreds of neurons distributed over the cortex of
behaving animals, and a sophisticated correlation
analysis of the recorded neuronal activity. Kari Hoffman and Bruce McNaughton recently succeeded in this
technical tour de force [12]. They implanted four
different neocortical areas of macaque monkeys each
with 144 electrodes. Each electrode could be positioned
independently to isolate the spiking activity of a single
neuron. The implanted areas were the posterior
parietal cortex, the motor cortex, the somatosensory
cortex and the dorsal prefrontal cortex. The monkeys
were trained to perform tasks that co-activated
neurons in those areas. During the recordings, monkeys first performed the trained tasks and then they
rested quietly.
Long-range neuronal interactions
During task performance, a network of neurons
distributed over all four recorded areas was activated,
as expected. The remarkable finding was that neurons
that had been active together during task performance
‘re-enacted’ their play during the following rest period,
despite the fact that no task was performed (Fig. 1).
The neuronal activity patterns were indeed generated
by the preceding task performance and were not simply
a default state of the system. This was demonstrated
by recording from neurons during a control rest period
just before task performance. The activation patterns
shared by the task and the post-task rest could not be
found during the pre-task rest.
Activation patterns during task performance contain
temporal structure because different neurons are
involved at different times during the task. Additional
analyses revealed that the reactivation of patterns
during the post-task rest period preserved some of the
temporal order of neuronal activation from the task.
This finding is particularly interesting in the light of
theoretical work demonstrating that sequence information can be synaptically encoded and recalled by
physiologically realistic learning rules [13]. Thus, the
sequential reactivation during the rest period suggests
that not only a given event, but also the particular
sequence of events, is being consolidated.
Although the study by Hoffman and McNaughton
provided important new insights, it also raises new questions. The most important unresolved issue is probably
whether the observed neocortical reactivations are truly a
correlate of consolidation of declarative memory or whether
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TRENDS in Neurosciences Vol.26 No.3 March 2003
they are correlates of other forms of learning and memory,
such as skill learning. Because the formation of new
declarative memories depends crucially on the MTL, cortical
reactivations should do so as well if they have a functional
role in declarative memory. There seem to be at least two
complementary ways of confirming an interaction between
the MTL and the neocortex. One approach would be to record
simultaneously from both structures and test for correlations between MTL and neocortex related to reactivation
during sleep. A second crucial experiment would require a
permanent lesion or transient inactivation of the MTL. If
neocortical reactivations are indeed a signature of memory
traces being activated by MTL, as suggested by Hoffman and
McNaughton, these reactivations should disappear and
memory performance should decrease in a post-rest test
whenever the MTL is effectively inactivated.
Pre-task rest
Task
References
Post-task rest
TRENDS in Neurosciences
Fig. 1. The left half of the figure illustrates the three behavioral conditions studied
by Hoffman and McNaughton: the pre-task rest period, the task period and the
post-task rest period [12]. The right half illustrates the main results of the neurophysiological recordings. Two neurons are depicted that respond selectively to
two different aspects of the task. One of the neurons responds to the red dot on
the computer screen that has to be touched by the monkey to obtain juice; the
other responds to the actual juice reward. During the pre-task rest period, the
monkey is not particularly concerned with red dots or juice, but could be ‘dreaming’ of a banana. Consequently, the ‘red-dot neuron’ and the ‘juice-reward neuron’
do not show a particular coordinated firing pattern. This changes during the task,
when the red dot neuron and the juice-reward neuron are repeatedly activated in
temporal succession. This sequence of activation is spontaneously reactivated
during the post-task rest, when no task is performed but the recent experience from
the task period is consolidated into long-term memory. Modified, with permission,
from Ref. [14]. q (2001) Nature Publishing Group (http://www.nature.com/).
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0166-2236/03/$ - see front matter q 2003 Elsevier Science Ltd. All rights reserved.
doi:10.1016/S0166-2236(03)00023-7
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