Journal of Cognitive Neuroscience

Past work has indicated that expectation can modulate neural responses to visual stimuli, but it is unclear whether these effects remain consistent across different types of unexpected stimuli. Here, we measured and compared neural prediction effects associated with semantic category and presentation frequency-based expectations in real-world object stimuli. Participants (n = 35) viewed real-world object images in rapid serial visual presentation (RSVP) streams. Semantically unexpected stimuli occurred when a stimulus was presented in a semantically incongruent stream. Low-frequency violations occurred when a rarely presented stimulus was displayed in a semantically congruent stream. Multivariate pattern analysis of electroencephalography (EEG) was used to quantify and compare the degree of information represented in neural activity for stimuli in different prediction conditions. Semantically expected stimuli yielded lower decoding accuracy relative to random (unpredictable) stimuli (125-313 ms post-onset) while semantically unexpected stimuli exhibited increased decoding accuracy (199-238 ms & 523-559 ms). Low-frequency violations yielded decoding accuracy which was not significantly different from semantically expected stimuli. Exploratory analyses indicated that dissimilarity between expected and presented stimuli quantified in terms of higher-level stimulus features, but not low-level visual features, modulated the observed neural prediction effects. These results demonstrate that different types of prediction violations have distinct modulatory effects on neural responses, providing novel insight into the neural implementation of predictive processing.

Saccades made during memory maintenance prioritize memory for the saccade target, but it is unclear if this benefit is specific to a location or extends across memorized objects. In three experiments, we examined whether saccadic selection spreads to other locations within the same object. In Experiment 1, we asked observers to remember three oriented Gabors presented either within contour-defined objects or without object structure. A subsequent movement cue prompted observers to move their eyes to the indicated location. We then probed memory for stimuli at locations equidistant from the saccade target, in either the same or a different object. Memory was best for stimuli at locations congruent with the saccade target, and consistently weaker for other stimuli presented in the same or a different object than the saccade target. In Experiment 2, we created more complex objects by adding more object features to the stimulus. Again, memory performance was best for stimuli congruent with the saccade target location, whereas memory in incongruent trials was worse and similar for stimuli in the same and different object as the saccade target. In Experiment 3, we tested if saccadic selection is present and propagates within the object in a change detection task. Again, memory performance (i.e., change detection) was best at the saccade target location. However, this memory benefit also spread to other locations within the same object. Our results imply that saccadic selection in visual working memory is primarily space-based but can also spread towards locations within the object where a saccade was directed.

When humans learn under conditions of uncertainty, they dynamically adjust how they prepare for and respond to feedback. In navigating uncertain environments, the brain minimizes error by continuously refining internal models via memory updating (MU). Feedback is critical for MU, and anticipatory neural mechanisms shape how feedback is processed, likely reflecting learned environmental certainty. However, the literature has largely focused on post-feedback activity, leaving pre-feedback certainty-related mechanisms less understood. The present study aims to address this gap by examining how certainty modulates anticipatory states, preceding feedback and subsequent MU. We examined oscillatory activity prior to performance feedback in a reanalysis of EEG data previously published by Hassall and colleagues (2023). Twenty-one participants (16 female, Mage = 25.81 years) predicted the strength of cartoon characters with varying predictability levels which were learned through exposure. Feedback on prediction accuracy was presented via an animated rising bar. Results revealed that theta power is modulated by accumulative feedback. Linear mixed-effects models revealed an interaction between predictability-related certainty and learning stage: in late learning, higher performance was associated with increased pre-feedback alpha and beta power for low-certainty trials, whereas in early learning, higher performance was associated with decreased beta power. These learning-related modulations in alpha and beta power suggest that initial learning is marked by adaptable exploratory processing. Subsequent learning exhibited increased alpha-mediated inhibition and beta-related anticipatory activity for lower certainty trials, indicative of dynamic strategy refinement and selective engagement of task-relevant information. These results demonstrate that certainty shapes preparatory oscillatory activity associated with MU.

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.

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.

Flow state, characterized by optimal engagement and performance, represents a key concept in understanding human performance and cognitive resource allocation. Grounded in Csikszentmihalyis and Sherrys flow theory and the Limited Capacity Model of Motivated Mediated Message Processing (LC4MP), this study investigated physiological and neural correlates of flow state during a simulated driving task under different music conditions and difficulty levels. Using a 2 x 3 factorial design with 20 participants, this study examined self-selected versus non-self-selected music across three difficulty levels, testing the relationship between task switching, cognitive resource allocation, and flow state. Physiological measures included heart rate and EEG (alpha/theta power) using a 4-channel Muse 2 headband, alongside a self-report measure of flow experience. Hierarchical linear modeling revealed significant physiological changes during self-selected music: heart rate decreased ({beta} = -5.15, p < .001), while alpha ({beta} = 5829.77, p < .001) and theta power ({beta} = 7637.24, p < .001) increased. Task difficulty also showed significant effects, with heart rate decreasing during hard ({beta} = -6.70, p < .001) and moderate ({beta} = -3.40, p = .001) conditions. In particular, while physiological measures showed robust changes, the self-reported flow state did not reach significance. Task switching rates showed significant decreases during self-selected music ({beta} = -0.86, p < .001) and hard difficulty ({beta} = -0.61, p < .001), supporting the LC4MP frameworks predictions regarding cognitive resource allocation. These findings demonstrate how task switching and cognitive resource allocation relate to flow state induction. The results highlight the importance of multimodal measurement approaches and demonstrate that personal relevance through music selection and task difficulty significantly influence physiological and neural responses during performance. Future research should employ more comprehensive measurement approaches to better capture the complexity of flow-related neural activity and its relationship to task switching and cognitive resource allocation.

Goal-directed behavior often requires sustained effort across a sequence of interdependent decisions, yet the determinants of persistence in such contexts remain poorly understood. Here, we investigated how individuals regulate persistence in a novel sequential effort-based task in which they controlled an avatar through successive checkpoints to reach a final goal and could make repeated attempts following failure. At each attempt, participants could choose either to persist in the same task or to disengage toward an easier but less rewarding alternative. We found that decisions to persist or disengage were jointly shaped by multiple interacting factors. Disengagement increased with task difficulty and lower skill level. It also increased with repeated attempts and time-on-task, indexing fatigue, and with accumulated errors, indexing lack of progress. Conversely, proximity to the goal promoted persistence and shaped decision dynamics by reducing choice conflict during persistence decisions and increasing hesitation during disengagement near the goal. Notably, clearing the first checkpoint produced a sharp increase in persistence, suggesting that early success plays a pivotal role. Furthermore, persistence reflected both retrospective and prospective evaluations of effort, with prior investment promoting commitment and anticipated effort reducing it. Finally, disengagement was preceded by short-term performance decline but not by gradual increases in decision conflict, suggesting relatively abrupt strategy shifts following repeated failures. Together, these findings provide a comprehensive account of persistence in sequential effortful tasks, showing that decisions to persist or disengage are jointly shaped by multiple factors related to fatigue, (lack of) progress, goal proximity, and early success.

Given the limited capacity of working memory (WM), prioritization is essential for efficient information processing. Whether prioritization acts primarily at encoding, or dynamically shapes representations during maintenance, is currently unclear. Here, we employed a two-item delayed-match-to-sample task and compared prioritization conditions in which the testing order of items was either known in advance or not. Behaviorally, prioritization selectively reduced guess rates, without affecting precision. Using multivariate pattern analysis, we decoded stimulus information from EEG voltage and indexed internal attention using alpha-band patterns. Prioritization did not alter decodable representations during encoding. During maintenance, however, prioritization enhanced both voltage-based decodability and alpha power-based decodability for the currently prioritized item. Mediation analyses further indicated that alpha-based attentional signals influenced behavior indirectly, via voltage-based representational strength, which is consistent with the idea that internal attention supports performance by strengthening prioritized representations during memory maintenance. Significance StatementWM is capacity-limited, requiring the prioritization of information most relevant to current task demands. Whether prioritization is established at encoding or emerges during maintenance, and how it improves working memory performance, remains unclear. Comparing conditions with and without advance priority knowledge, we found that prioritization occurred primarily during maintenance rather than encoding. We also found that prioritization improved performance by directing internal attention to prioritized items, strengthening their neural representations and increasing their accessibility. This finding provides insight into the flexibility of working memory in the updating of already-encoded information.

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.

As avatars become more commonplace, understanding how the brain processes emotional expressions in virtual faces is critical. We compared behavioral and neural responses to real and virtual faces expressing seven emotions (anger, disgust, fear, joy, sadness, surprise, neutral). In Experiment 1 (n=61), participants rated the similarity between paired faces. Expressions conveying the same emotion were rated as highly similar across face types, whereas mismatched emotions yielded substantially lower similarity ratings, indicating perceived emotional meaning was preserved despite differences in face realism. In Experiment 2 (n=91), functional near-infrared spectroscopy was used to measure brain activity while participants viewed the same stimuli. General-linear-model analyses revealed greater activation limited to visual areas for 1) virtual faces and 2) surprise and neutral expressions. Functional connectivity analyses, however, revealed network level differences between face type and emotion across the brain. Real faces elicited stronger connectivity patterns across frontal, central-temporal, and parietal regions, whereas high-arousal emotions (fear, anger, and joy) were associated with broader network engagement than other expressions. Our results suggest face-type processing occur in early visual areas, and despite perceptual similarity, different emotions on real and virtual faces are associated with distinct patterns of network level connectivity across the brain.

Musical rhythm is often experienced with a periodic beat, serving as a temporal reference for coordination with the rhythm. Thus far, models of beat processing have mainly relied on representing sensory inputs as patterns of onset timing, with limited consideration of other sensory features. Here, we challenge this view by showing that the internal representation of beat is affected by other temporal features of the stimulus beyond onset timing alone. We recorded electroencephalography (EEG) while participants listened to rhythmic sequences designed to elicit a beat. Across conditions, we manipulated the duration of the tones conveying the rhythms, while keeping all other parameters identical, including overall intensity, speed, and rhythmic pattern structure. Crucially, the beat periodicity was enhanced in neural activity with increased sound duration, even though the beat periodicity was not prominent in the acoustic features, thus ruling out basic sensory confounds. These results demonstrate the preferential role of longer sound durations in fostering temporal scaffolding processes that integrate fast rhythmic inputs into behavior-relevant internal structures such as the beat. More generally, our findings are compatible with a holistic processing account whereby a range of features beyond onset timing may be integrated into a neural representation of rhythm. Graphical Abstract: Fig. 2EEG was recorded while listeners heard rhythmic sequences eliciting a beat. Sound duration (sonic duty cycle) was varied across four conditions while speed, pattern, and intensity stayed constant. Beat-related EEG responses increased with longer sounds, and were enhanced in all conditions compared to auditory nerve model envelopes, which did not show prominent energy at the beat periodicity, ruling out sensory confounds. Results support holistic rhythm processing beyond onset timing alone. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=101 SRC="FIGDIR/small/721298v1_fig2.gif" ALT="Figure 2"> View larger version (27K): org.highwire.dtl.DTLVardef@10a0599org.highwire.dtl.DTLVardef@f5a95forg.highwire.dtl.DTLVardef@42d1ceorg.highwire.dtl.DTLVardef@dc58a7_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 2.C_FLOATNO EEG and auditory nerve model output analysis based on magnitude spectrum and autocorrelation. Each row represents a duty cycle condition. The two columns on the left represent the magnitude spectrum-based analysis. The first column represents the group-level averaged magnitude spectra at a pool of fronto-central electrodes, across conditions. Beat-related frequencies are shown in red, and beat-unrelated frequencies are shown in blue. Scalp topographies of the neural activity measured at the average magnitudes of beat-related (in red circle) and unrelated (in blue circle) frequencies are represented as insets. The second column represents the normalized magnitude spectra obtained from the auditory nerve model output for each duty cycle sequence. The two columns on the right represent the autocorrelation-based analysis (for visualization purposes, only a subset of lags from 0 to 2.4 s corresponding to the pattern duration is shown). The first column represents the group-level averaged autocorrelation function measured from the same pool of fronto-central electrodes, across conditions. Beat-related lags are shown in red, and beat-unrelated lags are shown in blue. The second column represents the autocorrelation function of the auditory nerve model output for each duty cycle sequence. C_FIG

Conversations can feel effortlessly engaging or, conversely, difficult and unrewarding. Multiple factors contribute to the experienced quality and outcomes of a conversation, among them how interlocutors align with each other. The present study investigated speech-to-speech, brain-to-speech, and brain-to-brain coordination as markers of interpersonal alignment, examining their relationship with jointly perceived interaction quality and mutual affinity between conversational partners. Pairs of previously unacquainted participants (dyads) engaged in multiple short, free-form conversations on topics of varying interest while their vocal and neural activity were simultaneously recorded in a dual-EEG ("hyperscanning") setup. We analyzed interlocutors prosodic adaptation, neural speech tracking, and neural coordination during each conversation. At the speech-to-speech level, our findings reveal that partners with more positive mutual impressions became more similar in their volume and voice quality over the course of the experiment session, reflecting greater prosodic convergence. At the brain-to-speech level, we found no reliable effect of interaction quality on neural tracking of unfolding speech within any individual region, although topographical differences suggested relative modulation across scalp sites. Finally, at the brain-to-brain level, our findings show that higher perceived interaction quality enhanced inter-brain relationships across frequency bands (alpha and theta) and temporal dependencies (concurrent/near-instantaneous and recurrent/listener-lagging), with the strongest effects observed for concurrent alpha-band coupling. These findings suggest that distinct coordination processes are involved in how interlocutors experience an interaction and how they establish relational affinity, casting new light into the mechanisms that make a conversation worthwhile.

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.

Evidence suggests that information represented more reliably in neural activity patterns across repeated exposures is more likely to be remembered. However, this relationship varies across category-selective regions of the ventral visual cortex. Specifically, for house stimuli neural reliability has been robustly linked to memory outcomes in the parahippocampal place area (PPA), but less consistently for faces in the fusiform face area (FFA). The reason for this mismatch is unknown. To address this discrepancy, we implemented a novel within-category manipulation by presenting highly face-like and non-face-like house stimuli during fMRI, followed by a memory test. Non-face-like houses were more likely to be remembered than face-like houses. Although face-likeness did not elicit face-selective responses in the FFA, representational reliability in ventral visual cortices, particularly in the FFA, showed an association with individual differences in memory performance. Finally, symmetry emerged as a potential perceptual factor underlying differences in mnemonic outcomes.

Visual working memory (vWM) is often linked to conscious experience and visual imagery, but it is typically described as a system that stores separate, independent items. These assumptions are difficult to reconcile, given the unified nature of conscious experience. Here, we test the hypothesis that vWM relies on at least two distinct representations: an underlying, unconscious memory trace and a consciously accessible, integrated representation. A total of 216 participants performed a change-detection task, in which they rated their perceptual awareness of the memory display during the maintenance interval. Critically, we manipulated the statistical properties of the displays (average item size and size variability) to probe sensitivity to unified ensemble-level structure. Results revealed a dissociation between subjective and objective measures. Perceptual awareness increased for displays with larger, more variable items, whereas objective performance improved for displays with smaller, less variable items. Despite this difference, subjective awareness still predicted performance, and even incorrect responses showed consistent biases rather than random guesses. Importantly, individual differences in imagery vividness (VVIQ) were selectively associated with subjective awareness and estimation bias, but not with objective correctness. These precision biases were further shaped by display statistics, suggesting that multiple representations can guide behavior. Together, our findings support a reinterpretation of vWM performance in which task responses can draw on both unconscious and consciously accessible representations. One possible explanation for these behavioral patterns is that subjective experience reflects integrated, ensemble-like representations, while objective performance depends more strongly on item-specific information. Public significance statementsWorking memory allows us to temporarily hold and use information, and differences in this ability are closely linked to broader cognitive skills such as intelligence. This study shows that these differences may not depend only on how much information people can store, but also on how they experience it: some individuals appear to rely more on consciously accessible, image-like representations, especially when memory is uncertain or prone to error. By demonstrating that subjective experience and the vividness of imagery can shape behavior independently of objective accuracy, these findings suggest that how we use memory may be as important as how much we can store, with implications for understanding individual differences in cognition.

Effective sensory processing relies on both attention and the motor system, yet whether motor activity could provide attention-like functions to regulate perception remains unknown. We hypothesized that rhythmic motor signals could provide phasic regulation of prioritizing and sampling perceptual targets. Using an auditory attentional blink paradigm that created a temporal deficit in selective attention, we found that temporally aligned finger tapping improved the probe detection during the attentional blink window but impaired performance when attentional resources were abundant. Furthermore, transcranial alternating current stimulation (tACS) over the right sensorimotor cortex alleviated attentional blink when the probe was close to the peak of the stimulation, whereas stimulation over the left aggravated attentional blink when the probe was close to the trough. These results suggest that the motor system is a resource-dependent rhythmic regulator of attentional sampling. Motor signals can override attentional bottlenecks, suggesting the motor system as an active shaper of cognitive processes.

Response inhibition, the ability to suppress contextually inappropriate actions, is a cornerstone of cognitive control and is commonly assessed using paradigms such as the go/no-go task. However, traditional go/no-go paradigms rely on binary outcomes such as commission errors, which offer limited insight into the dynamic, graded behavioral adjustments underlying successful stopping. The present study developed a novel mouse-tracking go/no-go paradigm with a dynamic start to capture inhibitory processes during ongoing execution. Twenty-three healthy young adults completed the task in two sessions separated by approximately one week to evaluate the test-retest reliability of standard behavioral measures (error rates and reaction times), and three kinematic features: path length, mean velocity, and mean acceleration. Results revealed robust differences between go and no-go trials across all measures. Successful inhibition was characterized by significantly shorter path lengths and reduced mean velocity and acceleration compared to go trials. Critically, all measures demonstrated moderate-to-good test-retest reliability across sessions, with intraclass correlation coefficients ranging from .75 to .85 for go trials and from .59 to .83 for no-go trials. These findings establish construct validity and psychometric reliability of the current mouse-tracking go/no-go paradigm. The demonstrated stability of these measures provides the methodological foundation for their use in cross-sectional, longitudinal, and intervention research targeting inhibitory control.

Flow, as defined by Mihalyi Csikszentmihalyi (1975), is a holistic sensation experienced when individuals are fully immersed in an activity, resulting in a mental state characterized by a diminished sense of self and altered perception of time. To investigate the global neural dynamics underlying flow, we employed EEG microstate analysis to capture the spatial and temporal properties of dominant transient global brain states (Lehmann et al., 1998). In a study involving 43 participants playing the video game Thumper for 25 minutes, we extracted three four-minute EEG segments from each session corresponding to reported experiences of flow, boredom, and frustration, as determined by self-reports and performance metrics. Across conditions, six distinct microstate topographies (A-F) accounted for most of the global variance. Given that reduced self-referential processing is a key feature of flow, we hypothesized that flow would modulate the properties of microstates C and E, which have been associated with brain regions resembling the default mode network (DMN). Compared to boredom and frustration, the flow condition showed significantly decreased global explained variance, mean duration, time coverage, and occurrence frequency of microstate E, as well as reduced mean duration and time coverage of microstate C. These findings suggest that microstates associated with self-referential processing are shorter and less frequent during flow than during boredom and frustration. This supports the notion that the flow experience modulates global brain dynamics, particularly within the DMN. Furthermore, our results align with previous research reporting reduced DMN activity during meditative and psychedelic states, reinforcing the idea of diminished self-awareness in such conditions.

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

Humans possess an astounding ability to acquire complex movement sequences with limited practice. Motor sequence learning engages a distributed network of brain regions that show distinct learning-related changes: the prefrontal cortex (PFC) is predominantly involved early in learning, whereas the primary motor cortex (M1) becomes increasingly engaged later in learning. Because motor regions mature relatively earlier than the PFC during development, we examined how children and adults differ in the time course of neural changes underlying motor sequence learning. Using functional magnetic resonance imaging (fMRI), we compared brain activation in children (7-10 years, N = 39, 17 female) and adults (20-32 years, N = 39, 19 female) during an associative visuomotor learning task. In both age groups, response times decreased with sequence repetition, with greater reductions in adults than in children. Across age groups, early learning was associated with heightened PFC activation, whereas later learning was characterized by increased activation in left M1 and bilateral supplementary motor area. Children and adults showed comparable decreases in PFC activation and PFC-M1 connectivity with sequence repetition. In contrast, adults exhibited larger learning-related increases in activation and stability of multivariate patterns in left M1. Together, these findings indicate that although both age groups engage the PFC similarly to support increased control demands in early learning, children show less pronounced modulation of M1 activation and representational similarity, suggesting that M1s capacity to form stable, sequence-related representations may still be developing in middle childhood. Significance StatementAlthough motor sequence learning has been widely studied in adults, less is known about how brain activation changes as learning progresses during childhood. This question is particularly relevant because prefrontal cortex (PFC) and primary motor cortex (M1) both support motor learning, but mature at different rates, with PFC developing relatively later than M1. Here, we used functional MRI to compare children (7-10 years) and adults performing a motor sequence learning task. We found no age-related differences in PFC engagement early in learning; instead children showed less refinement of M1 activation and neural representations over the course of learning than adults. These findings provide new insight into how the brain supports motor learning throughout development.