Michael T. Ullman’s research while affiliated with Georgetown University and other places

Second language (L2) grammar learning is difficult. Two frameworks—the psycholinguistic lexical bottleneck hypothesis and the neurocognitive declarative/procedural model—predict that faster L2 lexical processing should facilitate L2 incidental grammar learning. We tested these predictions in a pretest–posttest syntactic adaptation study of English relative‐clause attachment preferences. First‐language German speakers listened to relative clauses disambiguated to the English low‐attachment preference ( secretaries of the professor who is/naps at home )—via either a copula (e.g., is ), which should be processed rapidly (copula group; n = 48), or a lexical verb (e.g., naps ), which should be processed more slowly (lexical group; n = 48). Only the copula group showed significant pretest‐to‐posttest learning. Moreover, the amount of learning was predicted by procedural learning abilities in the copula group, but by vocabulary size in the lexical group. The results, which are consistent with both frameworks, show that the L2 lexicon impacts L2 grammar learning, and reveal moderating psycholinguistic and neurocognitive variables.

Substantial progress has been made in understanding the neurocognitive underpinnings of learning math. Building on this work, it has been hypothesized that declarative and procedural memory, two domain-general learning and memory systems, play important roles in acquiring math skills. In a longitudinal study, we tested whether in fact declarative and procedural memory predict children’s math skills during elementary school years. A sample of 109 children was tested across grades 2, 3 and 4. Linear mixed-effects regression and structural equation modeling revealed the following. First, learning in declarative but not procedural memory was associated with math skills within each grade. Second, declarative but not procedural memory in each grade was related to math skills in all later grades (e.g., declarative memory in grade 2 was related to math skills in grade 4). Sensitivity analyses showed that the pattern of results was robust, except for the longitudinal prediction of later math skills when accounting for stable inter-individual differences via the inclusion of random intercepts. Our findings highlight the foundational role of early domain-general learning and memory in children’s acquisition of math.

Processing action words (e.g., fork, throw) engages neurocognitive motor representations, consistent with embodied cognition principles. Despite age-related neurocognitive changes that could affect action words, and a rapidly aging population, the impact of healthy aging on action-word processing is poorly understood. Previous research suggests that in lexical tasks demanding semantic access, such as picture naming, higher motor-relatedness can enhance performance (e.g., fork vs. pier)—particularly in older adults, perhaps due to the age-related relative sparing of motor-semantic circuitry, which can support action words. However, motor-relatedness was recently found to affect performance in younger but not older adults in lexical decision. We hypothesized this was due to decreased semantic access in this task, especially in older adults. Here we tested effects of motor-relatedness on 2,174 words in younger and older adults not only in lexical decision but also in reading aloud, in which semantic access is minimal. Mixed-effects regression, controlling for phonological, lexical, and semantic variables, yielded results consistent with our predictions. In lexical decision, younger adults were faster and more accurate at words with higher-motor relatedness, whereas older adults showed no motor-relatedness effects. In reading aloud, neither age group showed such effects. Multiple sensitivity analyses demonstrated that the patterns were robust. Altogether, whereas previous research indicates that in lexical tasks demanding semantic access, higher motor-relatedness can enhance performance, especially in older adults, evidence now suggests that such effects are attenuated with decreased semantic access, which in turn depends on the task as well as aging itself.

Developmental language disorder (DLD) is a common neurodevelopmental disorder with adverse impacts that continue into adulthood. However, its neural bases remain unclear. Here we address this gap by systematically identifying and quantitatively synthesizing neuroanatomical studies of DLD using co-localization likelihood estimation, a recently developed neuroanatomical meta-analytic technique. Analyses of structural brain data (22 peer-reviewed papers, 577 participants) revealed highly consistent anomalies only in the basal ganglia (100% of participant groups in which this structure was examined, weighted by group sample sizes; 99.8% permutation-based likelihood the anomaly clustering was not due to chance). These anomalies were localized specifically to the anterior neostriatum (again 100% weighted proportion and 99.8% likelihood). As expected given the task dependence of activation, functional neuroimaging data (11 peer-reviewed papers, 414 participants) yielded less consistency, though anomalies again occurred primarily in the basal ganglia (79.0% and 95.1%). Multiple sensitivity analyses indicated that the patterns were robust. The meta-analyses elucidate the neuroanatomical signature of DLD, and implicate the basal ganglia in particular. The findings support the procedural circuit deficit hypothesis of DLD, have basic research and translational implications for the disorder, and advance our understanding of the neuroanatomy of language.

Cognitive neuroscience has highlighted the cerebral cortex while often overlooking subcortical structures. This cortical proclivity is found in basic and translational research on many aspects of cognition, especially higher cognitive domains such as language, reading, music, and math. We suggest that, for both anatomical and evolutionary reasons, multiple subcortical structures play substantial roles across higher and lower cognition. We present a comprehensive review of existing evidence, which indeed reveals extensive subcortical contributions in multiple cognitive domains. We argue that the findings are overall both real and important. Next, we advance a theoretical framework to capture the nature of (sub)cortical contributions to cognition. Finally, we propose how new subcortical cognitive roles can be identified by leveraging anatomical and evolutionary principles, and we describe specific methods that can be used to reveal subcortical cognition. Altogether, this review aims to advance cognitive neuroscience by highlighting subcortical cognition and facilitating its future investigation. Expected final online publication date for the Annual Review of Neuroscience, Volume 45 is July 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

A large body of evidence suggests that people spontaneously and implicitly learn about regularities present in the visual input. Although theorized as critical for reading, this ability has been demonstrated mostly with pseudo-fonts or highly atypical artificial words. We tested whether local statistical regularities are extracted from materials that more closely resemble one’s native language. In two experiments, Italian speakers saw a set of letter strings modelled on the Italian lexicon and guessed which of these strings were words in a fictitious language and which were foils. Unknown to participants, words could be distinguished from foils based on their average bigram frequency. Surprisingly, in both experiments, we found no evidence that participants relied on this regularity. Instead, lexical decisions were guided by minimal bigram frequency, a cue rooted in participants’ native language. We discuss the implications of these findings for accounts of statistical learning and visual word processing. (please find the full article here: http://doi.org/10.5334/joc.209 )