Neurobiology of Language

Two decades of research have provided evidence for gray matter volume (GMV) differences in developmental dyslexia (or reading disability, RD) in the left perisylvian cortex. However, there are concerns about result inconsistencies, likely attributable to small sample sizes, lenient statistical thresholds, and insufficient accounting for demographic variables and global GMV (Ramus et al., 2018). To address these concerns, we conducted a Discovery and Replication Study (N=262) using data from the Adolescent Brain Cognitive Development Study. We found GMV differences between the RD and Control Groups did not replicate across the Discovery and Replication Studies using voxel-based morphometry (VBM) in Statistical Parametric Mapping (SPM), and that a more conservative threshold yielded far fewer results. We then conducted Reproducibility Studies and first found that when using surface-based morphometry in FreeSurfer instead of VBM, the Discovery and the Replication Study results again failed to converge. Second, we combined all groups in a factorial VBM/SPM analysis and the interaction analysis provided quantitative confirmation for diverging between-group difference results across the two studies. Third, we tested for the role of covariates of no interest and found that when total GMV is not controlled for, this divergence dissipates and group differences in RD (main effect of Reading Ability) are amplified. In conclusion, replication of GMV differences in RD is low, even when using large, well-matched groups, and analyses approaches play a modulating role. As such, results from prior studies using lenient statistical thresholds and not accounting for total GMV should therefore be viewed with caution.

The present study examined whether thematic reversal anomalies are processed similarly across subject and object experiencer constructions in Malayalam. Event-related brain potentials (ERPs) were recorded as 30 first-language speakers of Malayalam read transitive sentences with the two types of experiencer verbs, in which the thematic role assignment for the preceding arguments was either correct or reverse. The reversal anomaly became apparent only at the position of the experiencer verb. A linear mixed-models analysis confirmed a biphasic N400-P600 effect at the verb for both verb types when the argument roles were reverse. Thus, our results suggest a uniform processing strategy for TRAs irrespective of the type of experiencer verb involved. However, the N400 amplitude was larger for the object experiencer verb compared to subject experiencer verbs. We suggest that the quantitative difference observed for object experiencer verbs is due to the inverse linking of grammatical function and thematic roles associated with these verbs. In other words, verb-specific linking properties modulate the processing of TRAs involving object experiencer verbs. We argue that this modulation occurs because the parser recalibrates cue weighting when the expected form-to-meaning mappings are overridden by the inverse linking properties of object experiencer verbs.

Humans comprehend language incrementally, updating the representation of sentence meaning with each incoming word. These updates are guided by the distance between each perceived word and prior expectations--the prediction error. The alignment between large language models (LLMs) and cortical activity inspires the hypothesis that the cortical computation of prediction error is Surface-based, driven by statistical patterns of word form co-occurrence. In contrast, psycholinguistic models propose that prediction error computation is Meaning-based, driven by word semantics. We used polysemic words with ambiguous semantics to distinguish these models: ambiguity would introduce uncertainty into meaning representations and hence the prediction error, if Meaning-based, but would not affect the prediction error, if Surface-based. We examined how ambiguity influenced prediction error signatures in self-paced reading times and magnetoencephalographic (MEG) neural responses during sentence processing. While an LLM-based proxy of prediction error robustly predicted reading times and neural responses to unambiguous words, it failed to predict either under ambiguity. That is, prediction error computation was altered by uncertainty in word meaning, which supports the Meaning-based model and corroborates the essential role of word meaning in predictive language processing. Our findings highlight an important limitation of LLMs as in silico models of the human language faculty.

PurposeTo examine speech iconicity for shape in aphasia, we compared iconicity ratings from people with aphasia to those from neurologically intact individuals and evaluated how iconicity relates to phonological and semantic processing profiles in aphasia. MethodEleven people with aphasia and 11 age- and gender-matched neurologically intact participants rated how rounded or pointed 50 auditory pseudowords sounded using a 5-point scale. Ratings from participants with aphasia were compared to predicted iconicity ratings derived from reference ratings from prior work and to ratings from neurologically intact participants. For each participant with aphasia, correlations between individual ratings and predicted ratings were related to measures of phonological and semantic processing. ResultsRatings from people with aphasia were significantly correlated with both the predicted ratings and the ratings from neurologically intact participants. The strength of the correlation between individual ratings and predicted ratings did not differ significantly between groups, although there was a trend toward weaker correlations in the aphasia group. There were indications that greater language impairment was associated with greater disruption of iconicity ratings; in particular, deficits in phonological segmentation and semantic processing were associated with reduced sensitivity to shape iconicity. ConclusionThese findings suggest that sensitivity to shape iconicity is preserved in individuals with aphasia to varying degrees. The specific nature of language impairment appears to play an important role in determining iconicity processing in aphasia.

People frequently gesture while speaking, even when listeners cannot see them--for instance, during phone calls or behind barriers. Congenitally blind individuals also gesture, indicating that gestures serve functions beyond visual communication. Previous models of gesture production (e.g., Kita & Ozyurek, 2003; Rauscher et al., 1996) suggest that gestures facilitate speech, but they rely heavily on behavioural data and provide limited insight into temporal dynamics. This study used magnetoencephalography (MEG), a neuroimaging technique with high temporal resolution, to investigate when gestures influence speech. Twenty-three native Japanese speakers took part in a storytelling task under two conditions: Gesture-Required (gesture use instructed) and Gesture-Prohibited (hands kept still). Participants described cartoon clips across multiple sessions (30 trials x 3 sessions per condition). Using speech onset as the reference point, we compared root mean square (RMS) values within a -0.25 to 0 second window. RMS values were higher in the Gesture-Prohibited condition, with increased activity in the bilateral anterior temporal lobes (Left ATL: p = .049; Right ATL: p = .027), but not in motor regions (p = .29). These findings suggest that gestures reduce neural load in language-related regions before articulation. Co-speech gestures may support speech planning by facilitating lexical retrieval or semantic structuring. The lack of motor region effects indicates that this influence is linguistic rather than motoric. This study provides direct direct neurophysiological evidence of the timing of gesture-speech interaction, supporting models that view gestures as an integral part of speech production.

Impaired reading, i.e., alexia, is common after left hemisphere stroke. The most common deficit in alexia is a difficulty reading aloud pronounceable novel words, also called pseudowords. While semantic and phonological processes both subserve reading real words, pseudoword reading deficits in alexia are typically ascribed to phonological deficits alone. Some theories, however, suggest that pseudoword reading relies in part on lexical-semantic knowledge, such that semantic deficits could also contribute to poor pseudoword reading in alexia. Leveraging a large sample of left-hemisphere stroke survivors, we examine the cognitive and neural substrates of pseudoword reading accuracy and two error types: lexicalization errors, where a pseudoword is incorrectly read as a real word, and nonword errors, where a pseudoword is read as an incorrect nonword. 76 left-hemisphere stroke survivors read 60 pseudowords aloud, and performed two pseudoword repetition tasks to assess phonological processing and two picture naming tasks to assess mappings between lexical semantics and phonology. Regression models assessed how pseudoword repetition and naming related to overall accuracy and rates of lexicalization and nonword errors in pseudoword reading. Voxel-based and connectome lesion-symptom mapping localized the neural territory responsible for these errors. Both pseudoword repetition and naming independently related to pseudoword reading accuracy. Pseudoword repetition but not naming deficits predicted higher rates of lexicalization errors, while naming but not pseudoword repetition deficits predicted higher rates of nonword errors. Greater nonword error rate also predicted smaller imageability effects in real word reading (t(71)=-3.2, p=0.002). Lexicalization errors were associated with lesions to and disconnections of the left putamen and basal ganglia. Nonword errors were associated with lesions to the superior and middle temporal gyri, as well as broad temporo-parietal disconnections, overlapping with previous lesion-mapping results implicating these regions in semantic contributions to word reading. These results suggest that lexicalization errors result from impaired planning and execution of novel motor plans, causing a reliance on the well-learned motor plans associated with lexical items. In contrast, greater rates of nonword errors, relative to lexicalization errors, occur when semantic contributions to reading are impaired. Overall, these findings demonstrate that semantic processes are involved in reading pseudowords, at least in stroke alexia. These findings support connectionist accounts of reading in which damage in the direct orthography to phonology route for reading leads to reliance on semantic representations, even for pseudowords, suggesting a reinterpretation of pseudoword reading as a pure measure of phonological reading deficits.

Prior studies have reported inconsistent results for neuroanatomical differences between early bilinguals and monolinguals. These studies primarily measured gray matter volume (GMV), involved small samples, and prioritized adults. Few studies of early bilinguals have measured cortical thickness (CT), which offers more anatomical specificity. It remains unclear whether results derived from differing metrics and approaches (e.g., vertex-versus parcel-wise analyses) converge. Using data from the Adolescent Brain Cognitive DevelopmentSM (ABCD) Study, we compared neuroanatomy between large groups of early cultural Spanish-English bilingual and English monolingual children (N = 1,209) matched on age, pubertal status, sex, handedness, socioeconomic status (SES), and nonverbal reasoning. Whole-brain voxel-based morphometry revealed areas of greater and of lesser GMV in bilinguals than monolinguals across all lobes. Vertex-wise CT analyses similarly identified widespread differences, with bilinguals showing areas of both thicker and thinner cortex. We contextualized these findings with parcel-wise CT analyses (average CT values), utilizing two atlases of differing spatial granularity. Parcel-wise results showed good correspondence with vertex-wise findings when implementing the more fine-grained atlas (Destrieux), but use of the coarser atlas (Desikan-Killiany) provided results that led to different conclusions. Finally, we tested for interaction effects between bilingualism and SES on CT and found several regions where differences between bilinguals and monolinguals in CT were modulated by SES. Together, these findings indicate that early bilingualism is associated with extensive neuroanatomical differences relative to monolinguals during childhood, and that these results can vary as a function of neuroanatomical metric, analysis approach, atlas granularity, and SES. Research HighlightsEarly Spanish-English bilingual and monolingual children differ in gray matter volume and cortical thickness across multiple brain regions. Cortical thickness differences between bilinguals and monolinguals cannot be firmly attributed to adaptations associated with language or executive control. Socioeconomic status modulates cortical differences between early bilinguals and monolinguals, revealing unique thickness patterns for those with lower versus higher SES backgrounds. Parcel-wise between-group cortical thickness results are affected by atlas choice and can influence the interpretation of the findings.

Verbal fluency is a behavioral task that requires the generation of words from a semantic category (category fluency) or words beginning with a specific letter (letter fluency). Although word production engages a frontal-temporal-parietal network, no studies have tested how lesions to temporal and parietal lobe areas that represent semantic and phonological knowledge dampen neural responses in the left pars triangularis and the left pars opercularis, two adjacent regions in the left inferior frontal gyrus implicated in word search and retrieval. Here, 52 patients with temporal lobe lesions underwent clinical functional MRI while performing the category and letter fluency tasks. We investigated where lesion presence was inversely related to the magnitude of task-specific neural responses in pars triangularis and pars opercularis using a technique referred to as voxel-based lesion activity mapping (VLAM). We found that lesions to the left anterior superior temporal gyrus, left temporal pole, left hippocampus, left insula, and underlying inferior fronto-occipital fasciculus were associated with reduced neural responses in the left pars triangularis during the category fluency task. Lesion damage to the right hippocampus was associated with reduced neural responses in the left pars opercularis during category fluency. By contrast, lesions to the left posterior superior temporal gyrus, left supramarginal gyrus, left parietal operculum, and the inferior fronto-occipital fasciculus and left arcuate fasciculus were associated with reduced neural responses in the left pars triangularis and the left pars opercularis during the letter fluency task. These results suggest that anatomically dissociable brain networks interact with the left inferior frontal gyrus when different search strategies constrain the retrieval of word representations.

Iconicity refers to systematic links between word form and meaning. Although evidence for iconicity in natural language continues to grow, its neural basis remains unclear. Using functional magnetic resonance imaging (fMRI) and multivariate pattern analysis (MVPA), we examined iconic shape associations of auditory real words and pseudowords. The pseudowords were matched to the real words in phonemic and phonotactic properties, while differing primarily in the absence of learned semantic representations. Participants listened to each item and judged whether it sounded rounded or pointed. Searchlight MVPA revealed significant decoding for both stimulus types. For real words, iconic shape associations were decoded above chance in regions associated with visual and haptic shape processing (left lateral occipital complex and left anterior intraparietal sulcus), visual imagery (bilateral precuneus), phonological processing (bilateral supramarginal gyri), and semantic processing (left middle frontal and right superior frontal gyri). For pseudowords, significant decoding was found in regions associated with multisensory feature organization (right posterior intraparietal sulcus) and language processing (left angular and inferior frontal gyri). Together, these findings provide evidence for neural mechanisms mediating iconic associations, with language-related areas involved for both real words and pseudowords, and visual processing for real words.

The internal representations of large language models (LLMs) correlate, or "align", with human neural activity during language comprehension. One view holds that this alignment reflects shared sensitivity to statistical patterns in LLMs and humans, while others hold that it reflects, at least in part, the emergence of shared linguistic representations in these systems. Here, we investigate whether hierarchical linguistic composition, a property believed to be fundamental to human language, modulates LLM-brain alignment. To this end, we manipulated syntax, compositional semantics, and associative semantics in English sentences that were presented to both an LLM and human participants during an electroencephalography (EEG) experiment. We matched linguistically manipulated stimuli in predictability, which allows us to tease apart alignment induced by linguistic structure from statistical factors. By comparing LLM-EEG alignment scores that were derived using a linear encoding model across predictability-matched conditions, we evaluate how linguistic manipulations modulate the alignment between human EEG reading data and contextual embeddings extracted word-by-word from the hidden layers of GPT2-XL. Three key patterns emerge: (1) increased alignment for word sequences with syntactic structure, (2) decreased alignment for sentences with compositional semantics, and (3) associative semantics does not modulate alignment. These observed linguistic modulations of LLM-EEG alignment take place above and beyond predictability. Our results indicate that associative semantics is encoded similarly by LLMs and the brain, as are at least some aspects of syntactic structure, while compositional semantics is more uniquely encoded in the human brain.

Computational models are a linchpin in our understanding of the neurocognitive basis of reading. These models can simulate idealized profiles of alexia syndromes, but in reality, individuals with alexia present with a wide range of mixed deficits rather than idealized syndromes. To provide a complete cognitive theory of reading, computational models must be able to account for this individual variation. However, this has never been demonstrated. We test oral reading and non-reading phonological and semantic processing in 83 left-hemisphere stroke survivors. We show that individual alexia profiles can be simulated by applying graded phonology and semantic lesions to an artificial neural network model of reading, creating "matched models" that represent individual stroke survivors. The severity of damage to the semantic and phonological layers of the matched models was highly correlated with directly-measured semantic and phonological processing deficits. However, we also identify systematic ways in which the models fail to simulate the reading performance of their matched stroke survivors. Our results support theories of alexia that rely on process-based deficits, demonstrate the feasibility of large-scale individualized modelling of alexia, and suggest ways to further improve the correspondence of models and human reading behavior.

Prior studies in bilinguals have reported relationships between brain structure and the dimensions of (i) language proficiency or (ii) language balance (the discrepancy between a bilinguals two proficiencies), but rarely both, even though they are highly related. These studies were often conducted in late bilinguals and the analyses limited to regions of interest. Here, we tested for relationships between brain structure and these two dimensions in 46 early cultural Spanish-English bilinguals (mean age = 16.7 years) at the level of the whole brain for gray matter volume (GMV) and cortical thickness (CT). Results revealed a positive association between GMV and proficiency in the weaker language in the right angular gyrus (AG; BA 39) extending into the superior temporal gyrus (BA 22). More balanced bilingualism was also associated with more GMV in the AG (BA 39), in addition to less GMV in left postcentral gyrus (BA 1), right cerebellum lobule IX and right superior occipital gyrus (BA 18). However, these relationships between GMV and balance disappeared after controlling for language proficiency. No significant associations were observed for CT and these two dimensions of language. Our findings suggest that relationships between GMV and balance are driven by language proficiency, and that the relationship between GMV and language proficiency likely does not involve language-specific mechanisms, given the location of the association is in the right inferior parietal cortex. Together, this study separates the neuroanatomical bases of these two language dimensions and places them in brain regions outside those usually targeted in prior studies. HighlightsO_LINeuroanatomy was correlated with proficiencies in early Spanish-English bilinguals C_LIO_LIRight angular gyrus gray matter volume (GMV) was positively related to proficiency C_LIO_LIGMV was positively related to balance, but not after controlling for proficiency C_LIO_LIRelations with these language dimensions are located outside of language cortex C_LIO_LINo significant associations were observed for cortical thickness C_LI

Predicting post-stroke aphasia severity remains challenging, in part because language outcomes reflect not only focal cortical damage but also widespread disruption of structural and functional networks. Computational models of large-scale cortical dynamics offer a principled way to infer these network-level consequences from patient-specific lesions. Here, we present and evaluate REWIRED, a lesion-informed cortical dynamics framework designed to simulate individualized alterations in large-scale brain network organization after stroke. We first evaluated whether simulation-derived functional connectivity captured patient-specific variation in empirical functional connectivity beyond lesion burden and structural disconnection alone. We then developed a multiscale feature set combining lesion volume, lesion distribution patterns, probabilistic disconnectome metrics, and simulation-derived measures of functional connectivity and effective information flow (EIF). Finally, using a nested support vector regression (SVR) framework in a separate dataset, we tested whether simulation-derived features improve prediction of chronic aphasia severity, measured by the Western Aphasia Battery - Revised Aphasia Quotient (WAB-AQ), beyond lesion-distribution and structural-connectivity predictors. Simulation-derived functional connectivity significantly predicted empirical functional connectivity beyond local lesion burden and structural disconnection alone. With respect to WAB-AQ prediction, lesion-based (Set 1) and disconnectome-based (Set 2a) features alone yielded modest accuracy. Adding simulation-derived features (Set 2b) produced substantial gains, and the full feature set (Set 3) achieved the best performance (RMSE = 14.5; r = 0.83), reaching accuracy that is competitive with recent multimodal neuroimaging approaches, despite relying solely on lesion-distribution inputs. EIF measures were consistently selected as top predictors, indicating that disruptions in interregional communication patterns carry behaviorally relevant information not captured by structural features alone. These results support REWIRED as a framework for linking structural injury to distributed network dysfunction and behavioral outcomes. By integrating lesion information with large-scale cortical dynamics modeling, REWIRED provides a foundation for future individualized modeling of recovery and rehabilitation.

It has been proposed that bilinguals have better executive function (EF) arising from the constant selection of one language while inhibiting the other, and gray matter has been found to differ in bilinguals in regions linked to EF (frontal-parietal and subcortical structures). Attention Deficit Hyperactivity Disorder (ADHD) is associated with poorer EF and neuroanatomical differences underlying EF. Given the EF advantage in bilinguals, we investigated whether a bilingual experience affects EF performance and brain structure differentially in those with ADHD. Using the Adolescent Brain and Cognitive Development Study, we compared early Spanish-English bilinguals and English-speaking monolinguals with and without ADHD. ANOVAs for the Flanker, Working Memory, and Card Sort Tasks revealed no main effects of Language Experience (Bilingual versus Monolingual), a main effect of Diagnostic Group for Card Sort (ADHD worse than Controls), and no interaction effects on performance for any task. ANOVAs for gray matter volume (GMV) revealed a main effect of Language Experience in many regions, a main effect of Diagnostic Group in some regions, but no interactions. GMV in left thalamus was affected by both ADHD and bilingualism, but the effect of ADHD was not significantly diminished or enhanced by the dual-language experience. For cortical thickness, there was a main effect of Language Experience in several regions, no main effect of Diagnostic Group, and no interactions. Taken together, bilingualism has some impact on EF performance, a strong impact on neuroanatomy, but there was no disproportionate impact by bilingualism on the differences caused by ADHD for any measure. Research HighlightsExecutive function and brain structure differ in ADHD and in bilinguals, prompting the need to investigate interactive effects. Bilingualism did not disproportionately affect performance differences in ADHD for executive function, nor for gray matter volume or for cortical thickness differences in ADHD. Gray matter volume was less in ADHD than non-ADHD, as well as greater in bilinguals than monolinguals in the left thalamus, but without interaction effect. These independent effects indicate that the brain basis of ADHD is not impacted by a dual-language experience.

Context is critical for both human and artificial speech comprehension systems. While the role of preceding context in speech processing has been well documented, the neural mechanisms supporting the integration of subsequent input -- phonemes and words that occur in the future -- remain poorly understood. Here, we leverage advances in artificial speech systems to model the contribution of different sources of context on the neural encoding of speech in the human brain. For neural encoding, context-informed but not context-uninformed speech model embeddings explain unique variance in human neural activity beyond acoustics, including in early speech processing regions. In particular, model embeddings informed by past, future, and surrounding context explain activity in distinct intracranial electrodes. These electrodes are left-lateralised, and spatially intermixed in the temporal lobe. We find that beyond-word context is crucial for the representational quality of speech model embeddings, and in particular for the encoding of abstract linguistic information. Our finding that spatially neighboring yet distinct neural populations in the temporal lobe encode representations shaped by different contextual sources (past, future, and surrounding input) provides key insight into the neural circuitry that integrates multiple forms of contextual information. Furthermore, our results may inform the downstream use of self-supervised speech representations in language technology tasks, and in models of speech comprehension in the human brain.

Learning to read requires linking auditory and visual information, yet how the developing brain maps information across sensory modalities remains poorly understood. To shed light on this topic we employed functional MRI to investigate hemodynamic brain responses during spoken and written word or pseudoword recognition in 61 primary school children with different levels of reading experience. Audiovisual representational similarity of activation patterns in the inferior frontal gyrus, inferior parietal lobule, superior temporal gyrus, and temporo-occipital cortex, increased linearly with school grade and this effect was largest in the left posterior superior temporal gyrus. Our results suggest that learning to read is related to a progressively increasing similarity of auditory and visual word representations within canonical language areas.

The success of large language models (LLMs) across diverse NLP tasks has elevated the importance of reasoning chain optimization as a critical step in aligning model behavior with task objectives. Existing reasoning chain tuning methods often rely on black-box heuristics or gradient-free search, which lack interpretability, generalization, and sample efficiency. In this work, we introduce Thoughts-as-Planning, a novel framework that formalizes reasoning chain optimization as a sequential decision-making process over a latent semantic space. We model the LLM as a partially observable environment and learn a latent world model that simulates the effect of reasoning chain edits on downstream outputs. A proximity-preserving embedding space is constructed to encode reasoning chain-response dynamics, enabling planning via gradient descent or reinforcement learning. Our method supports multi-scale abstraction, allowing reasoning chain edits at token, segment, and instruction levels to be integrated into a unified planner. Through extensive experiments on language understanding and generation tasks, we demonstrate that Thoughts-as-Planning outperforms state-of-the-art reasoning chain tuning baselines in efficiency, robustness, and generalization, while offering interpretability through its structured planning trajectory. Our code is available at https://github.com/FastLM/Thoughts-as-Planning.

This study investigates whether neural tracking of linguistic information extends from read speech to spontaneous conversation. Using the temporal response function (TRF) framework, we validate our approach on a read-speech EEG dataset and then apply it to EEG recordings from natural conversations. We observe reliable neural tracking of key linguistic predictors, including word onset, part-of-speech surprisal, and lexical surprisal, in spontaneous speech, with effects around 200, 400, and 600 ms. These results provide new evidence that linguistic neural tracking operates in natural conversational settings and confirm the feasibility of EEG studies in ecologically valid contexts.

A hallmark of human intelligence is the ability to use tools. Yet the cognitive processes supporting this ability remain debated. One contemporary view holds that mechanical reasoning is central for tool use, especially in the case of tools with which we have no prior experience. However, previous support for the role of mechanical reasoning often relies on circular logic, wherein poor performance on novel tool-use tasks is taken as evidence that impaired mechanical reasoning causes tool-use deficits in limb apraxia. To address this limitation, we independently assessed mechanical reasoning and novel tool use in separate tasks in individuals with limb apraxia, and compared their performance to individuals without apraxia. We also examined whether these two abilities are similarly associated with other cognitive abilities including motor imagery, mental rotation of non-body objects, general reasoning, and spatial working memory. Finally, we explored brain-behavior relationships using support vector regression lesion-symptom mapping. Our behavioral and imaging data together showed that mechanical reasoning does not underlie novel tool-use deficits in apraxia. Graphical analysis further revealed that novel tool use and mechanical reasoning loaded onto distinct latent clusters: novel tool use was strongly associated with other praxis abilities yet separable from cognitive abilities that require reasoning and mental simulation, whereas mechanical reasoning was primarily linked to other high-level reasoning abilities but not tool use. These findings challenge the notion that mechanical reasoning is central to tool-use ability, and instead suggest that tool use is more likely to be an intuitive or automatic process.

Reading is a critical skill in modern society. Most research on reading is conducted in school age children or young adults. However, acquired brain disorders often affect reading ability, and these disorders tend to occur in older adults. It is therefore critical to examine the normative distribution of reading behavior and the brain basis of reading in older adults. Here, we provide trial-wise single word and pseudoword oral reading and lexical decision data, as well as structural, functional, and diffusion-weighted MRI data from 116 neurotypical adults aged 22 to 84 years (mean = 59). Accuracy, response times, and errors are provided for corpora that are parametrically modulated in frequency, imageability, and regularity for real words and consistency of spelling-sound mapping for pseudowords. This dataset includes both minimally processed behavior (trial-wise data) and MRI data, and participant- and item-wise summary metrics and processed MRI data. These data serve both as a normative sample for reading behavior in older adults, but also as a valuable resource for identifying novel brain-behavioral relationships.