Saturday, 12 May 2012

Journal Club:Twists and turns through memory space

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).

After instructions to make a left- or right-hand turn at the end of a virtual reality corridor, left- or right-turn neurons activate in a specific sequence. Single neurons fall completely silent following a brief activation burst, so that the average activity during the memory delay is low. Nevertheless, the sparse but specific activation sequence is sufficient to predict whether the animal will make a left or right turn at the end of the corridor.
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).

The new empirical evidence for dynamic memories now raises the theoretical challenge of showing how the brain is capable of quickly creating new sequences. After all, we are able to remember which way to go within seconds of entering a completely new environment. Another open question, which was not addressed in the article, is whether or not we can use dynamic memories to remember continuous quantities: the receptionist may tell you that the office is 40 feet away. Do you now have an activation sequence remembering ’40 feet’ in the parietal cortex? Is this sequence more similar to the ’30 feet’ sequence than to the ’20 feet’ sequence? Further, when we see a sign in the corridor indicating that the location of the interview has been moved, can we integrate this new information into the ongoing memory sequence? Does it then branch off into a new sequence? The many open questions will direct memory research toward exciting new directions.

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

1 comment:

  1. 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!