Memory improvement via stimulation of temporal cortex

Stimulation of temporal cortex with electrodes at memory encoding time boosted recall by 15%, in humans.

In the first phase, researchers listened to brain activity while subjects were memorizing nouns. They trained a model to try to predict, based on the brain activity at encoding time, if that word would be remembered or not. In the second phase, researchers ran the model while subjects were memorizing words, and if the model predicted that the word was more than 50% likely to be forgotten, they zapped the brain for 0.5 seconds (through a single pair of adjacent electrodes in the lateral temporal cortex, at amplitudes ranging from 0.5 mA to 1.5 mA (for electrodes deep in the cortex) or 3.5 mA (for the cortical surface) (amplitude was the maximum within this range such that stimulation didn’t appear to cause afterdischarges). Stimulation in this fashion improved recall by 15%. After stimulation, the classifier was more likely to say that the subject would remember the word, which might suggest that the stimulation improved recall by sometimes nudging the brain into a state that the classifier recognized as good for memory encoding.

As an aside, imo one should keep in mind that this doesn’t necessarily mean that this would be a good thing to do every time you are learning something. The way i like to think about this experiment is to imagine that you have some big machine that you don’t know how it works. The machine sometimes makes humming noises and other times it makes sputtering noises. You notice that when it makes the sputtering noise, this correlates somewhat with it not doing its job so well. So, whenever you hear a sputtering noise, you kick it really hard. Sometimes when you kick it, it makes it hum again. You record data and find out that if you kick it when it sputters, that improves output by 15%. That’s very interesting, but does it mean that it’s a good idea to kick the machine whenever it sputters? No — maybe kicking the machine damages it a little (or has some small probability of damaging it sometimes), or maybe the sputtering was something (such as a self-cleaning cycle) that the machine needs to do for its long-term health even at the cost of short-term performance. In other words, there is a clear gain to kicking the machine when it sputters, but it is unknown if there is also a subtle cost.

 

Youssef Ezzyat, Paul A. Wanda, Deborah F. Levy, Allison Kadel, Ada Aka, Isaac Pedisich, Michael R. Sperling, Ashwini D. Sharan, Bradley C. Lega, Alexis Burks, Robert E. Gross, Cory S. Inman, Barbara C. Jobst, Mark A. Gorenstein, Kathryn A. Davis, Gregory A. Worrell, Michal T. Kucewicz, Joel M. Stein, Richard Gorniak, Sandhitsu R. Das, Daniel S. Rizzuto & Michael J. Kahana. Closed-loop stimulation of temporal cortex rescues functional networks and improves memory.

 

https://www.wired.com/story/ml-brain-boost

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Hippocampus may still have a role in recalling old memories

Paraphrasing/adding to the article abstract: prevailing theory suggests that long-term memories are encoded via a two-phase process requiring temporary involvement of the hippocampus followed by permanent storage in the neocortex. However this group found that, even weeks later, after the memories are supposed to be independent of the hippocampus, they could disrupt recall by briefly suppressing hippocampal CA1. The suppression must be brief; if they suppress CA1 for a long time recall works again. This suggests that, long after memory formation, the memory is not primarily stored in the hippocampus, but the hippocampus is still somehow involved in recall. The research also implicates anterior cingulate cortex in recall. Abstract after the break.

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Dopamine error

(pun intended). I am embarrassed to say that earlier today I remarked to a colleague that dopamine only encodes unexpected reward, not unexpected lack of reward. This is (afaik) incorrect. It has a baseline level of firing that goes down when there is an unexpected lack of reward (see fig 1 in Wolfram Schultz, Peter Dayan, P. Read Montague. A Neural Substrate of Prediction and Reward)

However, because it can only go down so far, the negative signal is clipped, which might have consequences (see Yael Niv, Michael O Duff, Peter Dayan. Dopamine, uncertainty and TD learning).

The previous article mentions that some other people think that maybe dopamine is tracking uncertainty as well as reward. This one talks about a theory that acetylcholine is related to expected uncertainty, and norepinephrine is related to unexpected uncertainty:
Angela Yu, Peter Dayan. Expected and Unexpected Uncertainty: ACh and NE in the Neocortex (huh, all those papers had Peter Dayan as one of the authors) (btw I haven’t read all of the papers I’m posting here)

Since we’re on the subject of temporal difference learning, I’ll mention that in my opinion temporal difference learning may be a model of how futures/speculators in financial markets are supposed to propagate future price changes back in time to the present (if you think of the market as a cognitive system). I haven’t formalized this idea yet, though.

Increasing adult hippocampal neurogenesis is sufficient to improve pattern separation.

Sahay A, Scobie KN, Hill AS, O’Carroll CM, Kheirbek MA, Burghardt NS,
Fenton AA, Dranovsky A, Hen R. Increasing adult hippocampal neurogenesis is sufficient to improve
pattern separation. Nature. 2011 Apr 3

http://www.nature.com/nature/journal/vaop/ncurrent/full/nature09817.html

Abstract after the break.

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Genetic tagging of the particular neurons in the basolateral amygdala that store a particular engram

When we learn new information we use only a tiny fraction of the neurons in our brain for that particular memory trace. In order to allow the molecular study of those specific neurons we combined elements of the tet system with a promoter that is activated by high level neural activity (the cfos promoter) to generate mice in which a genetic tag can be introduced into neurons that are active at a given point in time. The tag can be maintained for a prolonged period, creating a precise record of the neural activity pattern at a specific point in time. Using fear conditioning we found that the same neurons activated during learning were reactivated when the animal recalled the fearful event. We also found that these neurons were no longer activated following memory extinction, consistent with the idea that extinction modifies a component of the original memory trace.

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Frequency of gamma oscillations routes flow of information in the hippocampus

Supplementary Figure 1:  A schematic illustrating the main finding. Slow gamma is maximal on the descending portion of the theta wave, and fast gamma peaks near the trough. Slow gamma serves to synchronize CA1 with inputs arriving from CA3, and fast gamma synchronizes CA1 with MEC input.

Supplementary Figure 1: A schematic illustrating the main finding. Slow gamma is maximal on the descending portion of the theta wave, and fast gamma peaks near the trough. Slow gamma serves to synchronize CA1 with inputs arriving from CA3, and fast gamma synchronizes CA1 with MEC input.

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