The Hebb repetition effect as a laboratory analogue of language acquisition: Learning three lists at no cost.

Saint‐Aubin, Jean; Guérard, Katherine

doi:10.1037/cep0000136

Cited by 8 publications

(6 citation statements)

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“…The Hebb repetition effect has been demonstrated with a broad range of materials, including lists of digits (Hebb, 1961; Oberauer & Meyer, 2009), letters (Mızrak & Oberauer, 2022; Oberauer et al, 2015; Page et al, 2006), syllables (Norris et al, 2018; Saint-Aubin & Guérard, 2018; Szmalec et al, 2009), words (Page et al, 2013), faces (Horton et al, 2008; Johnson & Miles, 2019), and sequences of spatial locations (Couture & Tremblay, 2006; Gagnon et al, 2005; Guérard et al, 2011; Sukegawa et al, 2019; Tremblay & Saint-Aubin, 2009). However, several studies failed to observe repetition learning effects for visual stimuli such as visuospatial arrays of colors or shapes, even after many repetitions (Fukuda & Vogel, 2019; Logie et al, 2009; Olson & Jiang, 2004; Shimi & Logie, 2019).…”

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Testing expectations and retrieval practice modulate repetition learning of visuospatial arrays.

Musfeld,

Souza,

Oberauer

2024

Journal of Experimental Psychology: Learning, Memory, and Cogni

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One of the best-known demonstrations of long-term learning through repetition is the Hebb effect: Immediate recall of a memory list repeated amidst nonrepeated lists improves steadily with repetitions. However, previous studies often failed to observe this effect for visuospatial arrays. Souza and Oberauer (2022) showed that the strongest determinant for producing learning was the difficulty of the test: Learning was consistently observed when participants recalled all items of a visuospatial array (difficult test) but not if only one item was recalled, or recognition procedures were used (less difficult tests). This suggests that long-term learning was promoted by increased testing demands over the short term. Alternatively, it is possible that lower testing demands still lead to learning but prevented the application of what was learned. In four preregistered experiments (N = 981), we ruled out this alternative explanation: Changing the type of memory test midway through the experiment from less demanding (i.e., single item recall or recognition) to a more demanding test (i.e., full item recall) did not reveal hidden learning, and changing it from the more demanding to a less demanding test did not conceal learning. Mixing high and low demanding tests for nonrepeated arrays, however, eventually produced Hebb learning even for the less demanding testing conditions. We propose that testing affects long-term learning in two ways: Expectations of the test difficulty influence how information is encoded into memory, and retrieval consolidates this information in memory.

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confidence: 99%

Testing expectations and retrieval practice modulate repetition learning of visuospatial arrays.

Musfeld,

Souza,

Oberauer

2024

Journal of Experimental Psychology: Learning, Memory, and Cogni

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“…This so-called Hebb repetition effect has been studied extensively and replicated with various kinds of materials, including letters ( 5 , 6 ), words ( 7 ), spatial locations ( 8 , 9 ), visuospatial configurations ( 10 , 11 ), and faces ( 12 , 13 ). Some researchers have proposed that the Hebb repetition effect can be used as a model for human language acquisition, in particular the learning of new word forms ( 2 , 14 – 17 ), stressing the universality of the effect as an example of very general human learning processes. This general process is the acquisition of chunks ( 18 ), that is, of unified representations of repeatedly encountered configurations of elements, such as the sequence of phonemes that form a word or the constellations of chess pieces that form a recognizable pattern for experienced players ( 2 , 19 – 21 ).…”

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Repetition learning is neither a continuous nor an implicit process

Musfeld

Souza

Oberauer

2023

Proc. Natl. Acad. Sci. U.S.A.

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Learning advances through repetition. A classic paradigm for studying this process is the Hebb repetition effect: Immediate serial recall performance improves for lists presented repeatedly as compared to nonrepeated lists. Learning in the Hebb paradigm has been described as a slow but continuous accumulation of long-term memory traces over repetitions [e.g., Page & Norris, Phil. Trans. R. Soc. B 364 , 3737–3753 (2009)]. Furthermore, it has been argued that Hebb repetition learning requires no awareness of the repetition, thereby being an instance of implicit learning [e.g., Guérard et al., Mem. Cogn. 39 , 1012–1022 (2011); McKelvie, J. Gen. Psychol. 114 , 75–88 (1987)]. While these assumptions match the data from a group-level perspective, another picture emerges when analyzing data on the individual level. We used a Bayesian hierarchical mixture modeling approach to describe individual learning curves. In two preregistered experiments, using a visual and a verbal Hebb repetition task, we demonstrate that 1) individual learning curves show an abrupt onset followed by rapid growth, with a variable time for the onset of learning across individuals, and that 2) learning onset was preceded by, or coincided with, participants becoming aware of the repetition. These results imply that repetition learning is not implicit and that the appearance of a slow and gradual accumulation of knowledge is an artifact of averaging over individual learning curves.

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“…The same repeating sequence (e.g., S1–S1) was never repeated back to back across the encoding phases of two successive trials. We used three repeating sequences, rather than one as was used in the original Hebb paradigm, with the intention to minimize awareness of the repetition manipulation as it has been demonstrated that multiple sequences can be learned in the classic Hebb repetition paradigm at no cost ( 28 , 29 ). In all, there were four trial types: (1) repeat match, (2) repeat mismatch, (3) novel match, (4) novel mismatch, across three different levels of delay for a total of 12 conditions.…”

Section: Methodsmentioning

confidence: 99%

Multivariate FMRI Signatures of Learning in a Hebb Repetition Paradigm With Tone Sequences

2021

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Important information from the environment often arrives to the brain in temporally extended sequences. Language, music, actions, and complex events generally unfold over time. When such informational sequences exceed the limited capacity of working memory, the human brain relies on its ability to accumulate information in long-term memory over several encounters with a complex stimulus. A longstanding question in psychology and neuroscience is whether the neural structures associated with working memory storage—often viewed as capacity limited and temporary—have any builtin ability to store information across longer temporal delays. According to the classic Hebbian dual memory theory, temporally local “activity traces” underlie immediate perception and working memory, whereas “structural traces” undergird long-term learning. Here we examine whether brain structures known to be involved in working maintenance of auditory sequences, such as area Spt, also show evidence of memory persistence across trials. We used representational similarity analysis (RSA) and the Hebb repetition paradigm with supracapacity tonal sequences to test whether repeated sequences have distinguishable multivoxel activity patterns in the auditory-motor networks of the brain. We found that, indeed, area Spt and other nodes of the auditory dorsal stream show multivoxel patterns for tone sequences that become gradually more distinct with repetition during working memory for supracapacity tone-sequences. The findings suggest that the structures are important for working memory are not “blank slates,” wiped clean from moment to moment, but rather encode information in a way can lead to cross-trial persistence.

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The Hebb repetition effect as a laboratory analogue of language acquisition: Learning three lists at no cost.

Cited by 8 publications

References 23 publications

Testing expectations and retrieval practice modulate repetition learning of visuospatial arrays.

Testing expectations and retrieval practice modulate repetition learning of visuospatial arrays.

Repetition learning is neither a continuous nor an implicit process

Multivariate FMRI Signatures of Learning in a Hebb Repetition Paradigm With Tone Sequences

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