A vaguely related anecdote: working memory was one of the things that was damaged after my stroke; for a while afterwards I was incapable of remembering more than two or three items when asked to repeat a list. I wasn’t exactly stupider than I am now, but I was something pretty similar to stupid. I couldn’t understand complex arguments, I couldn’t solve logic puzzles that required a level of indirection, I would often lose track of the topic of a sentence halfway through.
Of course, there was other brain damage as well, so it’s hard to say what causes what, and the plural of anecdote is not data. But subjectively it certainly felt like the thing that was improving as I recovered was my ability to hold things in memory… not so much number of items, as reliability of the buffers at all. I often had the thought as I recovered that if I could somehow keep improving my working memory—again, not so much “add slots” but make the whole framework more reliable—I would end up cleverer than I started out.
It would appear that all of us have very similar amounts of working memory space. It gets very complicated very fast, and there are some aspects that vary a lot. But in general, its capacity appears to be the bottleneck of fluid intelligence (and a lot of crystallized intelligence might be, in fact, learned adaptations for getting around this bottleneck).
How superior would it be? There are some strong indication that adding more “chunks” to the working space would be somewhat akin to adding more qubits to a quantum computer: if having four “chunks” (one of the most popular estimates for an average young adult) gives you 2^4 units of fluid intelligence, adding one more would increase your intelligence to 2^5 units. The implications seem clear.
I’m curious as to why this comment has been downvoted. Kalla seems to be making an essentially uncontroversial and correct summary of what many researchers think is the relevance of working memory size
(Note: it is not downvoted as I write this comment.)
First let me say that I have enjoyed kalla’s recent contributions to this site, and hope that the following won’t come across as negative. But to answer your question, I at least question both the uncontrovertiality and correctness of the summary, as well as the inference that more working memory increases abilities exponentially quickly. Kalla and I discussed some of this above and he doesn’t think that his claims hinge on specific facts about working memory, so most of this is irrelevant at this point, but might answer your question.
EDIT: Also, by correctness I mainly mean that I think our (us being cognitive scientists) understanding of this issue is much less clear than kalla’s post implies. His summary reflects my understanding of the current working theory, but I don’t think the current working theory is generally expected to be correct.
Although the exact relationship isn’t known, there’s a strong connection between IQ and working memory—apparently both in humans and animals. E.g. Matzel & Kolata 2010:
Accumulating evidence indicates that the storage and processing capabilities of the human working memory system co-vary with individuals’ performance on a wide range of cognitive tasks. The ubiquitous nature of this relationship suggests that variations in these processes may underlie individual differences in intelligence. Here we briefly review relevant data which supports this view. Furthermore, we emphasize an emerging literature describing a trait in genetically heterogeneous mice that is quantitatively and qualitatively analogous to general intelligence (g) in humans. As in humans, this animal analog of g co-varies with individual differences in both storage and processing components of the working memory system. Absent some of the complications associated with work with human subjects (e.g., phonological processing), this work with laboratory animals has provided an opportunity to assess otherwise intractable hypotheses. For instance, it has been possible in animals to manipulate individual aspects of the working memory system (e.g., selective attention), and to observe causal relationships between these variables and the expression of general cognitive abilities. This work with laboratory animals has coincided with human imaging studies (briefly reviewed here) which suggest that common brain structures (e.g., prefrontal cortex) mediate the efficacy of selective attention and the performance of individuals on intelligence test batteries. In total, this evidence suggests an evolutionary conservation of the processes that co-vary with and/or regulate “intelligence” and provides a framework for promoting these abilities in both young and old animals.
Hence, we might conclude—setting
aside the above mentioned caveats for such analyses—that [Working Memory Capacity]
and g share the largest part of their variance (72%) but are not
identical. [...] Our methodological critique notwithstanding, we believe that
Ackerman et al. (2005) are right in claiming that WMC is not the
same as g or as gf or as reasoning ability. Our argument for a
distinction between these constructs does not hinge on the size of
the correlation but on a qualitative difference: On the side of
intelligence, there is a clear factorial distinction between verbal
and numerical abilities (e.g., Su¨ß et al., 2002); on the side of
WMC, tasks with verbal contents and tasks with numerical contents
invariably load on the same factor (Kyllonen & Christal,
1990; Oberauer et al., 2000). This mismatch between WMC and
intelligence constructs not only reveals that they must not be
identified but also provides a hint as to what makes them different.
We think that verbal reasoning differs from numerical reasoning in
terms of the knowledge structures on which they are based: Verbal
reasoning involves syntax and semantic relations between natural
concepts, whereas numerical reasoning involves knowledge of
mathematical concepts. WMC, in contrast, does not rely on conceptual
structures; it is a part of the architecture that provides
cognitive functions independent of the knowledge to which they
are applied. Tasks used to measure WMC reflect this assumption
in that researchers minimize their demand on knowledge, although
they are bound to never fully succeed in that regard. Still, the
minimization works well enough to allow verbal and numerical
WM tasks to load substantially on a common factor. This suggests
that WMC tests come closer to measuring a feature of the cognitive
architecture than do intelligence tests.
Now this has me wondering if its possible to increase your own working memory via practice or some other means. I shall go do some reading on the matter.
I like this series of thoughts, but I wonder about just how superior a human with 2 or 3 times the working memory would be.
Currently, do all humans have the same amount of working memory? If not, how “superior” are those with more working memory ?
A vaguely related anecdote: working memory was one of the things that was damaged after my stroke; for a while afterwards I was incapable of remembering more than two or three items when asked to repeat a list. I wasn’t exactly stupider than I am now, but I was something pretty similar to stupid. I couldn’t understand complex arguments, I couldn’t solve logic puzzles that required a level of indirection, I would often lose track of the topic of a sentence halfway through.
Of course, there was other brain damage as well, so it’s hard to say what causes what, and the plural of anecdote is not data. But subjectively it certainly felt like the thing that was improving as I recovered was my ability to hold things in memory… not so much number of items, as reliability of the buffers at all. I often had the thought as I recovered that if I could somehow keep improving my working memory—again, not so much “add slots” but make the whole framework more reliable—I would end up cleverer than I started out.
Take it for what it’s worth.
It would appear that all of us have very similar amounts of working memory space. It gets very complicated very fast, and there are some aspects that vary a lot. But in general, its capacity appears to be the bottleneck of fluid intelligence (and a lot of crystallized intelligence might be, in fact, learned adaptations for getting around this bottleneck).
How superior would it be? There are some strong indication that adding more “chunks” to the working space would be somewhat akin to adding more qubits to a quantum computer: if having four “chunks” (one of the most popular estimates for an average young adult) gives you 2^4 units of fluid intelligence, adding one more would increase your intelligence to 2^5 units. The implications seem clear.
I’m curious as to why this comment has been downvoted. Kalla seems to be making an essentially uncontroversial and correct summary of what many researchers think is the relevance of working memory size
(Note: it is not downvoted as I write this comment.)
First let me say that I have enjoyed kalla’s recent contributions to this site, and hope that the following won’t come across as negative. But to answer your question, I at least question both the uncontrovertiality and correctness of the summary, as well as the inference that more working memory increases abilities exponentially quickly. Kalla and I discussed some of this above and he doesn’t think that his claims hinge on specific facts about working memory, so most of this is irrelevant at this point, but might answer your question.
EDIT: Also, by correctness I mainly mean that I think our (us being cognitive scientists) understanding of this issue is much less clear than kalla’s post implies. His summary reflects my understanding of the current working theory, but I don’t think the current working theory is generally expected to be correct.
Although the exact relationship isn’t known, there’s a strong connection between IQ and working memory—apparently both in humans and animals. E.g. Matzel & Kolata 2010:
or Oberauer et al. 2005:
Now this has me wondering if its possible to increase your own working memory via practice or some other means. I shall go do some reading on the matter.
Thanks for the links!