You enter an
unfamiliar building for a job interview. The receptionist tells you to make a
left turn at the end of the corridor to get to your interviewer’s office. Easy
instructions, but your brain has to remember them nonetheless. For the past
decade, theoretical neuroscientists have proposed that, to do this job, neurons
in the parietal cortex act as a kind of memory container: once you have learned
that you need to make a left, dedicated ‘left-turn’ neurons are persistently
active until you have reached the end of the hall, have turned, and can forget
about it again. In addition to having lots of supporting evidence and enjoying
intuitive appeal, the memory-container model has the advantage that, once the
appropriate neurons are activated, they can potentially hold on to the ‘left-turn’
memory indefinitely (for instance, allowing you to get a drink of water before
heading to the office).
However, a
recent paper in the journal Nature has added to a growing list of evidence
contradicting this model. In the paper, Princeton researchers Christopher
Harvey, Philip Coen, and David Tank describe how ‘left-turn’ neurons in the
parietal cortex of mice fire in a stereotypical cascade as the animals navigate
along a virtual-reality corridor. The sequence begins with a small number of ‘left-turn’
neurons activating the next group and then falling silent again (see image),
while the new group in turn activates yet another subset, and so forth until
the end of the cascade is reached at the end of the corridor. In contrast to
the memory-container model, this kind of dynamic activation sequence could be
more similar to your car’s sat nav, constantly keeping you up to date on when
you will have to turn left. Like a sat nav, dynamic memories could become more
prominent when you are navigating through a complicated environment and have to
make a left turn at the right time or in the right place (say, for instance,
that there are lots of possible left turns, and you must remember to turn
behind the drink fountain). Perhaps previous researchers may have failed to
pick up on such dynamics because their memory tasks did not involve this aspect
(in a typical experiment, a participant will receive instructions to make an
eye movement to a certain location, remember the location for a few seconds,
and then execute the movement).
The notion of
dynamical memories is particularly interesting to our research because it
relates to the idea that memories are an anticipation to act in a certain way
(turn left) at a specified place (the end of the corridor) and a specified time
(in about 10 seconds) – something we have been exploring in recent papers as
well (i.e., research briefing from May 7th).
Reference:
Harvey CD, Coen P and Tank DW (2012) Choice-specific sequences in parietal cortex during a virtual-navigation decision task. Nature; 484(7392):62-8
Hey Nick - Thanks for the post! I love this result, it reminds of other really cool work by Fujisawa/Amarasingham/Harrison/Buzsaki, Meyers/Freedman/Kreiman/Miller/Poggio, Crowe/Averbeck/Chafee and others showing how dynamic population coding really is, when you consider the population response as a function of time. So what does it all mean for working memory? Do we have to reconsider the persistent firing model of maintenance? Are stationary mnemonic activation states old news? And how does this all square with oscillations? From these results and others, it seems like the trajectory for population coding is complex, rather than recurrent. Perhaps oscillations influence the overall context within which these dynamic states unfold? Perhaps each state in the sequence is nested in an overall oscillation, like a theta carrier rhythm? I guess this would suggest a revision of the Lisman/Jensen model, with nested gamma activity reflecting a unique code within each cycle!? It is a shame optical imaging used here doesn't give an LFP-like measure of oscillatory activity. But still, a great paper and nice result!
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