Hebbian learning can explain rhythmic neural entrainment to statistical regularities

In many domains, learners extract recurring units from continuous sequences. For example, in unknown languages, fluent speech is perceived as a continuous signal. Learners need to extract the underlying words from this continuous signal and then memorize them. One prominent candidate mechanism is statistical learning, whereby learners track how predictive syllables (or other items) are of one another. Syllables within the same word predict each other better than syllables straddling word boundaries. But does statistical learning lead to memories of the underlying words-or just to pairwise associations among syllables? Electrophysiological results provide the strongest evidence for the memory view. Electrophysiological responses can be time-locked to statistical word boundaries (e.g., N400s) and show rhythmic activity with a periodicity of word durations. Here, I reproduce such results with a simple Hebbian network. When exposed to statistically structured syllable sequences (and when the underlying words are not excessively long), the network activation is rhythmic with the periodicity of a word duration and activation maxima on word-final syllables. This is because word-final syllables receive more excitation from earlier syllables with which they are associated than less predictable syllables that occur earlier in words. The network is also sensitive to information whose electrophysiological correlates were used to support the encoding of ordinal positions within words. Hebbian learning can thus explain rhythmic neural activity in statistical learning tasks without any memory representations of words. Learners might thus need to rely on cues beyond statistical associations to learn the words of their native language. RESEARCH HIGHLIGHTS: Statistical learning may be utilized to identify recurring units in continuous sequences (e.g., words in fluent speech) but may not generate explicit memory for words. Exposure to statistically structured sequences leads to rhythmic activity with a period of the duration of the underlying units (e.g., words). I show that a memory-less Hebbian network model can reproduce this rhythmic neural activity as well as putative encodings of ordinal positions observed in earlier research. Direct tests are needed to establish whether statistical learning leads to declarative memories for words.

Generic learning mechanisms can drive social inferences: The role of type frequency

How do we form opinions about typical and morally acceptable behavior in other social groups despite variability in behavior? Similar learning problems arise during language acquisition, where learners need to infer grammatical rules (e.g., the walk/walk-ed past-tense) despite frequent exceptions (e.g., the go/went alternation). Such rules need to occur with many different words to be learned (i.e., they need a high type frequency). In contrast, frequent individual words do not lead to learning. Here, we ask whether similar principles govern social learning. Participants read a travel journal where a traveler observed behaviors in different imaginary cities. The behaviors were performed once by many distinct actors (high type frequency) or frequently by a single actor (low type frequency), and could be good, neutral or bad. We then asked participants how morally acceptable the behavior was (in general or for the visited city), and how widespread it was in that city. We show that an ideal observer model estimating the prevalence of behaviors is only sensitive to the behaviors' type frequency, but not to how often they are performed. Empirically, participants rated high type frequency behaviors as more morally acceptable more prevalent than low type frequency behaviors. They also rated good behaviors as more acceptable and prevalent than neutral or bad behaviors. These results suggest that generic learning mechanisms and epistemic biases constrain social learning, and that type frequency can drive inferences about groups. To combat stereotypes, high type frequency behaviors might thus be more effective than frequently appearing individual role models.

Musical instrument familiarity affects statistical learning of tone sequences

Most listeners have an implicit understanding of the rules that govern how music unfolds over time. This knowledge is acquired in part through statistical learning, a robust learning mechanism that allows individuals to extract regularities from the environment. However, it is presently unclear how this prior musical knowledge might facilitate or interfere with the learning of novel tone sequences that do not conform to familiar musical rules. In the present experiment, participants listened to novel, statistically structured tone sequences composed of pitch intervals not typically found in Western music. Between participants, the tone sequences either had the timbre of artificial, computerized instruments or familiar instruments (piano or violin). Knowledge of the statistical regularities was measured as by a two-alternative forced choice recognition task, requiring discrimination between novel sequences that followed versus violated the statistical structure, assessed at three time points (immediately post-training, as well as one day and one week post-training). Compared to artificial instruments, training on familiar instruments resulted in reduced accuracy. Moreover, sequences from familiar instruments - but not artificial instruments - were more likely to be judged as grammatical when they contained intervals that approximated those commonly used in Western music, even though this cue was non-informative. Overall, these results demonstrate that instrument familiarity can interfere with the learning of novel statistical regularities, presumably through biasing memory representations to be aligned with Western musical structures. These results demonstrate that real-world experience influences statistical learning in a non-linguistic domain, supporting the view that statistical learning involves the continuous updating of existing representations, rather than the establishment of entirely novel ones.

Space modulates cross-domain transfer of abstract rules in infants

Developmental studies have shown that infants exploit ordinal information to extract and generalize repetition-based rules from a sequence of items. Within the visual modality, this ability is constrained by the spatial layout within which items are delivered given that a left-to-right orientation boosts infants' rule learning, whereas a right-to-left orientation hinders this ability. Infants' rule learning operates across different domains and can also be transferred across modalities when learning is triggered by speech. However, no studies have investigated whether the transfer of rule learning occurs across different domains when language is not involved. Using a visual habituation procedure, we tested 7-month-old infants' ability to extract rule-like patterns from numerical sequences and generalize them to non-numerical sequences of visual shapes and whether this ability is affected by the spatial orientation. Infants were first habituated to left-to-right or right-to-left oriented numerical sequences instantiating an ABB rule and were then tested with the familiar rule instantiated across sequences of single geometrical shapes and a novel (ABA) rule. Results showed a transfer of learning from number to visual shapes for left-to-right oriented sequences but not for right-to-left oriented ones (Experiment 1) even when the direction of the numerical change (increasing vs. decreasing) within the habituation sequences violated a small-left/large-right number-space association (Experiment 2). These results provide the first demonstration that visual rule learning mechanisms in infancy operate at a high level of abstraction and confirm earlier findings that left-to-right oriented directional cues facilitate infants' representation of order.

A case-study of language-specific executive disorder

Executive control is recruited for language processing, particularly in complex linguistic tasks. Although the issue of the existence of an executive control specific to language is still an open issue, there is much evidence that executively-demanding language tasks rely on domain-general rather than language-specific executive resources. Here, we addressed this issue by assessing verbal and non-verbal executive capacities in LG, an aphasic patient after a stroke. First, we showed that LG's performance was spared in all non-verbal tasks regardless of the executive demands. Second, by contrasting conditions of high and low executive demand in verbal tasks, we showed that LG was only impaired in verbal task with high executive demand. The performance dissociation between low and high executive demand conditions in the verbal domain, not observed in the non-verbal domain, shows that verbal executive control partly dissociates from non-verbal executive control. This language-specific executive disorder suggests that some executive processes might be language-specific.

Short-Term Memory for Serial Order Moderates Aspects of Language Acquisition in Children With Developmental Language Disorder: Findings From the HelSLI Study

Previous studies of verbal short-term memory (STM) indicate that STM for serial order may be linked to language development and developmental language disorder (DLD). To clarify whether a domain-general mechanism is impaired in DLD, we studied the relations between age, non-verbal serial STM, and language competence (expressive language, receptive language, and language reasoning). We hypothesized that non-verbal serial STM differences between groups of children with DLD and typically developing (TD) children are linked to their language acquisition differences. Fifty-one children with DLD and sixty-six TD children participated as part of the HelSLI project in this cross-sectional study. The children were 4-6-year-old monolingual native Finnish speakers. They completed several tests of language and cognitive functioning, as well as new game-like tests of visual and auditory non-verbal serial STM. We used regression analyses to examine how serial STM moderates the effect of age on language. A non-verbal composite measure of serial visual and auditory STM moderated cross-sectional development of receptive language in the children with DLD. This moderation was not observed in the TD children. However, we found more rapid cross-sectional development of non-verbal serial STM in the TD children than in the children with DLD. The results suggest that children with DLD may be more likely to have compromised general serial STM processing and that superior non-verbal serial STM may be associated with better language acquisition in children with DLD.