Comments on ‘Orthographic Processing in Baboons (Papio papio)’

We were recently asked by Nature News to comment on the Science paper by Grainger and colleagues showing that baboons can acquire orthographic processing skills, and to clarify its relation to human orthographic processing skills. I wrote up some comments, of which  Nature published just one in their article “Baboons can learn to recognize words“, but they were kind enough to link to our website, so I’m posting the remainder here.

What Grainger and colleagues have shown, is that baboons can learn the ‘written fingerprint’ of a language without knowing the language.

For English speakers, it may be more intuitive to imagine the task the baboons were given if they consider that they are themselves doing an experiment in a language they don’t know. For instance, imagine that you are seated in front of a computer screen. You are then presented with a letter sequence which either is an existing word in the Basque language, or a distractor letter sequence (a nonword), and you have to decide which is which. Since Basque is different from all other languages you know, you have to guess, and you are told whether your guess is correct or not. However, after some trials you start seeing that there are similarities between the letter sequences you are presented with and letter sequences you have previously seen. Based on the feedback you get, you start making informed guesses about which stimuli are Basque words and which are nonword distractors.

The difficulty of this task depends on the kind of distractor stimuli. Below you’ll see a sequence of Basque five-letter words, mixed with five-letter distractors which are just random sequences of alphabetic letters. It’s easy to find out which words are Basque, because the distractors have no relation to the Basque orthographic patterns.

ezfec erosi tafqp ontsa wlftk
eurak edkzt tjtsj pjfwl puska
pscwf cobbf busti gosez medio

(bold: words, regular: nonwords)

Now imagine that you have to do the same, but with the following sequence. This is much harder, because the nonwords are derived from the same orthographic patterns as the words.

ordez oinez salmo koroa oirat
gorga adere eupez surda halbo
zerga berme agiri gekal edeti

(bold: words, regular: nonwords)

What the baboons did, had a degree of difficulty in between the first task and the second task. The nonwords were composed primarily of bigrams (letter pairs) which occur very rarely in English words, while the words were composed primarily of bigrams which occur very often in English words. So, the baboons learned to discriminate between orthographically very typical English letter strings and  orthographically very atypical English letter strings. What’s more, Grainger and colleagues also showed that the less similar nonwords were to previously presented words, the higher the probability was that the baboons would make a nonword response.

Grainger and colleagues also analyzed data from the British Lexicon project, a very large experiment that we published recently (Keuleers, Lacey, Rastle & Brysbaert, 2012, [open access]) and found traces of the same behavior for humans. In our experiment, each of 78 participants responded to nearly 30.000 trials, deciding whether a presented sequence was an English word or not. Of course, the main difference was that our participants knew most of the English words. Therefore, they didn’t have to rely on the statistical regularities in orthographic patterns to make a decision. In contrast to Grainger and colleagues, we also made it exceptionally difficult for our participants to distinguish between the words and the nonwords based on these orthographic patterns. Still, as we  also reported earlier (Keuleers & Brysbaert, 2011 [preprint]), Grainger and colleagues found that, in addition to their knowledge of English, and despite extreme efforts, our participants partly relied on the orthographic similarities between the current stimulus and the previously presented stimuli to decide whether a stimulus was a word or not.

The new study adds to the evidence that orthographic processing can occur without linguistic processing. More importantly, showing this in baboons demonstrates that orthographic processing can be independent of the capacity to acquire high-level linguistics skills.

The new findings don’t have immediate practical use. However, they do have implications for research in language acquisition, bilingualism, visual word recognition, emotional processing, executive control, and many other fields, where word/nonword decision experiments are used very often with human participants . Usually, the reaction time to words is the variable of interest. The basic assumption in all of these experiments is that the meaning of the presented words is activated when making a decision. Now, if such an experiment can accurately be performed by baboons, it is clear that that experiment does not require accessing the meaning of those words, and results are tainted. Therefore, in ordinary experiments, the nonwords must be meticulously chosen so that the differences between words and nonwords is minimized. We have written a free application called Wuggy to do that (http://crr.ugent.be/Wuggy). It is used by researchers to generate nonwords that match the orthographic patterns in words as closely as possible, for languages from English to Vietnamese (Keuleers & Brysbaert, 2010 [preprint]).

Since not everyone has access to baboons to check whether their experiment is valid,  we have also written an algorithm (Keuleers & Brysbaert, 2011 [preprint][code]) that tries to perform this type of experiment as accurately as possible without knowing the language. The mechanism used by the algorithm (exemplar-based learning) is very similar to the one that I hypothesize is used by the baboons. We intend to look at Grainger and colleagues’ data to see how similar they are .

References

Keuleers, E., & Brysbaert, M. (2010). Wuggy: A multilingual pseudoword generator. Behavior Research Methods, 42(3), 627-633. [preprint]

Keuleers, E., & Brysbaert, M. (2011). Detecting inherent bias in lexical decision experiments with the LD1NN algorithm. The Mental Lexicon, 6 (1). [preprint]

Keuleers, E., Lacey, P., Rastle, K., & Brysbaert, M. (2012). The British Lexicon Project: Lexical decision data for 28,730 monosyllabic and disyllabic English words. Behavior Research Methods, 44, 287-304, doi: 10.3758/s13428-011-0118-4 [open access]

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