It looks like it isn’t working properly. I wondered why I couldn’t get a perfect score on even a short 1-back test. I figured out by experimentation that I could get a perfect score if I pushed the buttons whenever the sound/graphic matched the very first one displayed (instead of the one n turns ago).

I’m not a Haskell programmer, but after staring at the code (version 0.0.2) I think the problem is at line 196 of hback.hs. I think it should be:

else (randomElem lst (Just (hist !! ((length hist) - n))))

With this change, a 1-back and 2-back test seems to score my responses as I would expect.

Another small improvement is that on line 371 (hback.hs), if you add “2> /dev/null” to the mplayer system command string, it prevents mplayer (on my system) from dumping a lot of crap to the output.

By all means. While I am as much a skeptic as the next guy, I just wanted to respond to Mork’s comment from a logical reasoning view. I’ve simply made explicit all the premises. This way, if my reasoning is wrong (as it may very well be), it will be very easy for someone to point out where my fallacies lie.

a = “Improved performance at task T”
b = “Increased Gf score”
c = “X tangible advantage”

> Suppose you show that improved performance at task T increases Gf scores, and suppose you show that increased Gf scores correlate with other advantages.

a -> b
b -> c
Therefore, a -> c

> If you wanted to show that the stronger statement holds, you would have to show that
> the only effect of task T is to increase your Gf score, whatever that is,

d = “Unknown/not considered side-effect”

Two scenarios:

a -> (b and d)
b -> c
d -> not c OR c
Therefore, a -> c and we can correctly test both (a -> b) and (b -> c) separately.

a -> (b and d)
b -> not c
d -> not c OR c
Therefore, a may or may not imply c, but we don’t know because we only tested (b -> c).
Overall: Best case scenario, we show the first case to be true. Worst case scenario, we
have simply shown that one of our premises is false.

I think we sometimes forget in logic a false premise does not invalidate a conclusion.

> and that any increase of your Gf score has exactly one ‘kind’ of effect.

We can never be sure it’s the only effect. Just as in the above scenarios, I’m only interested in whether it will be one of the effects (even if our premise is false).

> As a more intuitive example, suppose we apply this reasoning to IQ instead of Gf scores
> Suppose you can show that a certain type of training increases IQ scores without
> any observable benefit in different tasks

t = “Some task T1″
r = “Some other task T2″
p = “Improve IQ score”

t -> p
r -> p
t -> c
r -> not c
Therefore, t -> p -> c && r -> p -> not c, cannot both be true. If one of these tasks implies c, it’s specifically because there is some other additional premise we did not consider (see above discussion with d).

If anything, testing the original two premises separately will make the chance of showing the correlation to be false higher, specifically because most likely the hypothesis is wrong. But a true correlation, would in fact show the premise to be more general and stronger than just testing a -> c.

> Clearly, this does not mean that /any/ task that increases your IQ will not be beneficial outside the IQ test.

See above. My reasoning suggests that this statement is invalid and misleading. There must be some additional effects created by one task and not the other that correlates to the “additional tangible effects”. If both tasks increase IQ but only one task has “additional tangible effects”, our goal should be to pinpoint those other differences and stop focusing on IQ.

> I’m no neuroscientist, and I admit I do not know very much about how well-established Gf is as a proxy for ‘general’
> cognitive capacity, but it seems exceedingly unlikely to me that every useful (high-level, not overly specialized)
> cognitive capacity correlates with Gf, and that (conversely) every change in Gf correlates with a change in cognitive capacity.

Yes, this may be most likely true. But unless we test strong correlations, we only get back weak premises. People would still be trying to square the circle if pi was not proved to be a transcendental number.

> I agree, but there needs to be some division of labor. Let’s try to produce more conclusive proof that some protocol does indeed “increase Gf test scores”. Separately we can try to show some correlation of “increased Gf test scores” to some more tangible advantage.

I contend that the two statement separately are weaker than the original statement (that the protocol/training produces “more tangible advantages”).
Suppose you show that improved performance at task T increases Gf scores, and suppose you show that increased Gf scores correlate with other advantages.
Why would this imply that improved performance at task T correlates with other advantages? (I realize that it /sounds/ obvious at some level, but I don’t see any logical reason for it to be true.)
If you wanted to show that the stronger statement holds, you would have to show that the only effect of task T is to increase your Gf score, whatever that is, and that any increase of your Gf score has exactly one ‘kind’ of effect. And that it is exactly this effect that leads to the “more tangible advantages”.
As a more intuitive example, suppose we apply this reasoning to IQ instead of Gf scores (yes, I know that they aren’t the same — I’m only concerned with the logical inference).
Suppose you can show that a certain type of training increases IQ scores without any observable benefit in different tasks (i.e., the training benefits are very specialized). Clearly, this does not mean that /any/ task that increases your IQ will not be beneficial outside the IQ test. Similarly, it shouldn’t be hard to imagine that some tasks may increase both your IQ and more generally useful skills, while other tasks may only increase your IQ by training very specialized (IQ testing-related) skills.
I’m no neuroscientist, and I admit I do not know very much about how well-established Gf is as a proxy for ‘general’ cognitive capacity, but it seems exceedingly unlikely to me that every useful (high-level, not overly specialized) cognitive capacity correlates with Gf, and that (conversely) every change in Gf correlates with a change in cognitive capacity.
All I’m saying is that if the task increases both Gf and, say, working memory, neither of the following two statements follows automatically (i.e., as a tautology):
1) any increase in Gf increases working memory
2) any increase in working memory increases Gf
So if you show that some task X increases Gf, and, independently, that an increased Gf correlates with a general skill/capacity, that still does not show that task X increases that general skill/capacity.
It is possible that the link applies in some cases, but I would be surprised if cognitive training had so localized and predictable effects that we can generalize it to any task increasing Gf :-)

Speaking of path finding though, haha, there are lots of games out there that basically do just that. Those “collect all the crystals” kinds of games :)

@Cogfun:
Apropos alternative memory training — let me rephrase. I am interested in any suggested ways to give the control participants something to do that at least vaguely seems related to “training” but won’t actually help them with their final score (assuming the current theories on why this works are in fact true). Jaeggi et al. used a control group that simply did not have to show up to the training sessions. I think a more appropriate test would be to give the control group something to work on that’s not known to increase concentration / working memory; although I’m still looking for suggestions. Ideas would be greatly appreciated

Regarding spatial vs visual, I don’t claim expertise in this, but I think one can make some good educated guesses. Whether you like it or not, with or without the grid structure, there is a spatial element to the block presentation (I suspect Jaeggi et al. intended it to be this way). The question would be how “spatial” it looks. So, relatively and subjectively speaking, the test on cogfun has less of a “spatial” look (but that’s probably also due to the grey background appearing and disappearing with each presentation).

Using your plot method, reproductions of the Jaeggi et al. test I have seen so far would be close to (1,0) (static focus point plus rotation). I have thought about making a spatial-only version and visual-only version, but questioned whether users would find having an extra test useful. In this case, an s-only and v-only would mean two extra tests that focus on similar working memory mechanisms. Addressing your points (a) and (b), I would think (a) already achieves a “spatial-only” effect if the appearance of the visual stimuli is sufficiently randomized. In (b) it seems like you are asking the user to remember a camera angle; I would suspect this to be a different kind of abstraction. (c) is easy: all you have to do is generate random images sufficiently different from one another.

Regarding a difference in spatial vs visual performance, again I don’t claim expertise but I would guess that “spatial stimuli” is easier to remember than than visual. This is because the spatial stimulus is still presented visually, which accesses more pathways (visual+others) during the encoding/retrieval step. You could present the spatial stimuli by sounds coming from different directions, and at that point there will be spatial-auditory coactivation. It will be interesting to find out exactly how different this is, but I am guessing it is less relevant to the question of how effective the dual n-back task is as a WM training paradigm.

As for memory training that doesn’t stress working memory, what are you thinking about specifically? To my understanding you are always dealing with LTM or non-LTM (STM/buffer, visual scratchpad, WM, whichever you choose) or the process in between. One training task I am very interested in myself is how to get more pathways involved in encoding stimuli; this would essentially speed up LTM transfer. The obvious thing to do is mnemonics training, but the determining factor here is more of self-motivated hard work than clever strategy :)