Cerebral Cortex

In task-oriented teams, long-term coordination among specialized roles may contribute to shared patterns of cognition and behavior, yet little is known about how such experience is reflected in brain functional organization. Here, we examined whether cross-individual differences in whole-brain functional connectivity were associated with court position and team membership in professional volleyball players. In the resting-state and naturalistic volleyball game-viewing conditions, we analyzed dyadic functional connectivity differences to test whether effects of shared position and team were evident across intrinsic and contextually engaged brain states, controlling for differences in playing time and performance-related statistics. We found that same-position players showed smaller functional connectivity differences. These effects were most prominent and widespread across brain networks during game viewing, whereas at rest they were specific to the somatomotor network. Team membership was also associated with smaller functional connectivity differences during game viewing, although position x team interactions varied across networks after covariate adjustment. A complementary machine learning classifier further showed that shared position could be predicted from intersubject differences in functional connectivity with accuracy exceeding a frequency-based baseline. Together, these findings suggest that shared role-specific and team-based experience may contribute to structured similarity in functional brain organization within a real-world team setting.

The relationship between cortical morphology and intelligence during adolescence has been widely studied, with existing literature reporting varying degrees of association across different modeling approaches. This study provides a comprehensive comparison of model performance in investigating the association between crystallized intelligence and cortical surface area using data from 11,351 subjects in the Adolescent Brain Cognitive Development (ABCD) study. We evaluate ten widely used models ranging from linear regression to graph convolutional networks across three covariate adjustment formulations: full (no adjustment), partial (age and sex adjusted), and total surface area (TSA) partial (age, sex, and TSA adjusted). Using bootstrap resampling with 50 iterations, we estimate the fraction of variance explained (FVE) for each model. Our results suggest that more complex models do not lead to higher FVE, with LASSO having the highest FVE of 15.9% (full formulation), Ridge at 10.5% (partial formulation), and Principal Component Regression (PCR) with 102 PCs at 2.5% (TSA partial formulation). Our results also reveal that the relationship between cortical surface area and crystallized intelligence is predominantly driven by global factors age, sex, and TSA, rather than by localized cortical surface area.

The persistence of a left-handed minority of slightly over 10% of the population is enigmatic because it is associated with stigma, increased psychopathology, and cognitive deficits. In a community sample of 9,352 individuals (age range 8-21 years) with neurobehavioral assessments, left-handers (N=1,281, 673 male) indeed showed greater psychopathology and performed more poorly than right-handers (N=8,076, 3,839 male) on tests of executive function, memory, complex cognition, and social cognition, while excelling in motor speed. Furthermore, the variance was higher and within-individual variability (WIV) - the extent to which scores in the different domains varied within individuals - was higher in left-handers. Since low WIV indicates even distribution of abilities while high WIV reflects specialization in circumscribed areas, the finding indicates that left-handers are "neurocognitive specialists". This combination of behavioral traits could confer resilience against natural selection pressures and help explain preponderance of left-handers in highly specialized professions requiring specific talents. Our findings encourage more research on left-handers, who are currently excluded from multiple brain behavior studies.

Functional connectivity (FC) is a statistical measure that reflects the degree of phase consistency between two signals and provides insights about potential interactions between two brain regions. Previous studies have reported conflicting results on the effect of meditation on FC, with some showing enhancement while others reporting suppression of FC. However, even though meditation increases power over a broad frequency range between 15-200 Hz and beyond, most FC studies have reported changes over fixed and narrow frequency bands below 50 Hz. Further, meditation-induced changes in power spectral density (PSD) and FC have never been compared with changes with other factors such as age, gender and stimulus. We recorded electroencephalogram (EEG) from open-eyed meditators (N=35) and their gender-and age-matched controls (N=36) and found that meditation was associated with a state decrease in FC across a broad frequency range (15-200 Hz), while PSD showed both trait and state enhancement. Furthermore, visual gratings, which are known to enhance narrow-band gamma power, led to reduced gamma FC in both meditators and controls. We also compared the effect of aging and gender on a different dataset of healthy middle-aged (N=78) and elderly (N=89) participants and found differences in distinct frequency bands that were limited to a narrow range. We also found that often-used average referencing heavily distorted the FC and gave uninterpretable results. Overall, our results suggest distinct neural mechanisms underlying healthy aging, vision, and meditation and further recommend caution while using average referencing to study phase-based metrics. Significance statementMeditation research has reported inconsistent effects on functional connectivity (FC), partly because most studies examined only narrow low-frequency bands despite meditation altering brain activity across a much broader frequency band. This study demonstrates that meditation produces a broadband state reduction in FC across 15-200 Hz, while simultaneously enhancing power. In contrast, healthy aging, gender, and visual stimulation showed frequency-specific effects confined to alpha (8-12 Hz) and high-beta (20-36 Hz) bands, highlighting meditations unique large-scale neural signature. The study also shows that average referencing can severely distort phase-based FC estimates, leading to misleading interpretations. These findings clarify conflicting literature, distinguish meditation from other neural modulators, and provide important methodological guidance for EEG connectivity research.

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.

Infant environments are rich in rhythms, many of which are social in nature. These rhythms are proposed to play an important role in early communication and interpersonal synchrony. In this cross-sectional electroencephalography (EEG) study with 3- and 6-month-olds (n=31 and n=30, respectively), we examined whether the infant brain tracks the rhythmicity of locomotion-related biological motion in the visual domain and which experiential factors relate to this ability. We found robust neural tracking of biological motion rhythms at both ages, with no effects of age or orientation (upright or inverted). Additionally, we found that caregiver-reported practice of infant carrying/babywearing and caregiver attitudes toward social touch were linked to infant neural tracking of biological motion rhythms, particularly in the inverted condition. Finally, exploratory analyses revealed a lateralisation effect, whereby the left hemisphere processed rightward (vs. leftward) biological motion rhythms more strongly. Our findings suggest that from early on, the infant brain tracks the rhythmicity of whole-body biological motion. Furthermore, caregiver touch-related practices, particularly infant carrying/babywearing, may play a role in infant neural tracking of socially-relevant rhythms.

Attention is a function that enables selection and integration of multiple sources of information. However, how these demands influence neural coding of information is not well understood. In this study we used EEG to examine how the selection vs. integration of stimuli shapes the content and geometry reflected on neural patterns, during both preparation and target processing. Participants performed a size judgement task in a cue-target paradigm that, depending on the block, required judging either the size of a selected item and ignoring the additional stimulus or integrating both items to respond. Decoding analyses showed that under selection demands, categorical templates of the cued stimulus were activated during preparation and target coding, contrasting with integration, where the cued category was active only during preparation. Notably, RSA suggested a specific exemplar encoding during its processing, that was sustained also across the post-stimulus window during selection, yet not under integration contexts. Our results also suggest that attentional demands shape the similarity between stimulus categories, by increasing the distance between selected stimuli and distractors or by increasing the similarity between to-be-integrated stimuli. Overall, this study uncovers the dynamics of stimulus encoding under selection and integration demands, offering crucial advances to understand how top-down processes shape information representation in the human brain.

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.

The heartbeat-evoked potential (HEP) reflects the cortical processing of cardiac afferent signals. However, it remains unclear whether trial-level interoceptive prediction errors can be quantified directly from spontaneous resting cardiac fluctuations and whether these model-derived errors are associated with HEP amplitude. Here, we applied a Kalman filter, implemented as a sequential Bayesian estimation procedure, to resting-state EEG and ECG recordings from 21 healthy adults to estimate trial-by-trial signed prediction errors in RR-intervals. Positive prediction errors reflected unexpected cardiac deceleration, whereas negative prediction errors reflected unexpected cardiac acceleration. Cluster-based permutation tests showed that unexpected cardiac acceleration was associated with greater fronto-centro-parietal HEP amplitude than unexpected deceleration in an early post-R-peak window, spanning FC1, CP1, Pz, CP2, Cz, C4 and FC2 from 215 to 250 ms. A Bayesian linear mixed-effects model further indicated a credible negative association between signed prediction error and HEP amplitude after controlling for respiratory phase and preceding RR interval. In a secondary connectivity analysis, unexpected acceleration was associated with stronger Cz-to-frontal beta-band phase synchrony during a later post-R-peak window from 250 to 500 ms. Exploratory individual-difference analyses suggested that neuroticism was negatively correlated with late frontal HEP amplitude during unexpected acceleration, but not during unexpected deceleration or when trials were pooled across conditions. These findings demonstrate that spontaneous cardiac fluctuations can be used to derive trial-level computational estimates of interoceptive prediction error and that these estimates are reflected in early HEP amplitude. They further suggest that the cortical processing of unexpected cardiac acceleration may be related to individual differences in affective personality traits.

The types of faces that infants see impact their developing ability to engage with and individuate people from familiar and unfamiliar social groups, a phenomenon known as perceptual narrowing. However, the neural mechanisms that underlie infants processing of different faces as a function of experience remain poorly understood. To address this gap, the present study analyzes electroencephalography data collected while 3-month-olds (N=24), 6-month-olds (N=26), and 9-month-olds (N=18) viewed female and male faces of a familiar or unfamiliar social group. Infants neural responses to faces differed by group familiarity from 3 months of age, with increased responses to the more familiar face types in early components (P1, N290), and to the more unfamiliar face types in later components (P400, Nc). Face sex and group familiarity interacted to shape N290 and P400 amplitudes at 3- and 9-months. Specifically, N290 amplitudes were greater in response to female faces of a familiar group at 3 months, and to male faces of a familiar group at 9 months. In contrast, P400 amplitudes were greater in response to male faces of an unfamiliar group at 3 months old, and greatest in response to both female faces of a familiar group and to male faces of an unfamiliar group at 9 months. Source reconstruction of the Nc revealed greater reconstructed current density in response to faces of an unfamiliar social group across all ages. These findings contribute to a growing body of knowledge examining how perceptual experiences shape infants understanding of their social world.

Task-evoked decreases in blood-oxygenation-level-dependent (BOLD) signals are a well-recognized phenomenon in functional magnetic resonance imaging (fMRI) studies. These deactivations are most prominent in the default mode network (DMN), a set of regions most active at rest. The metabolic basis of task-induced BOLD fMRI deactivations remains unclear. To address this question, we used PET/MRI to simultaneously measure BOLD fMRI and cerebral glucose consumption (CMRglc) during visuomotor and language tasks in 22 cognitively unimpaired older adults (15 female, 7 male). Task performance increased BOLD signals in task-relevant regions and decreased BOLD signals in the DMN. Positive BOLD responses generally coincided with increases in CMRglc. In contrast, CMRglc did not decrease in regions showing negative BOLD responses; instead, it typically increased. In particular, the posterior cingulate cortex showed significant CMRglc elevations in conjunction with negative BOLD responses. Whole-brain intensity normalization partially restored task-induced decreases in CMRglc, indicating that relative reductions appear in regions in which CMRglc increases are smaller than the global average. Overall, our results imply that BOLD fMRI deactivations can occur in conjunction with stable or even increased glucose consumption.

Regions within ventral occipito-temporal cortex exhibit category-selective BOLD responses during episodic encoding and retrieval of visual information. How these regions interact with other brain areas during successful encoding and retrieval, and whether these interactions relate to memory performance, remains unclear. The present study examined category-selective functional connectivity using psychophysiological interaction (PPI) analyses in younger and older adults during the encoding and retrieval of word-image associations. Seed regions comprised three scene-selective regions - the parahippocampal place area, medial place area, and occipital place area - and one object-selective region, the lateral occipital complex (LOC). During encoding, scene-selective regions exhibited greater connectivity with posterior occipital and occipitotemporal regions during scene relative to object encoding, whereas the LOC exhibited less extensive connectivity with similar posterior regions during object encoding. During retrieval, both scene- and object-selective regions demonstrated increased connectivity with left lateral prefrontal and parietal cortices during the retrieval of their preferred category. Age differences in scene-selective connectivity were evident at both phases. Moreover, associations between source memory performance and scene-selective connectivity were significant only in younger adults. These findings suggest that scene- and object-selective regions exhibit convergent patterns of functional connectivity during encoding and retrieval which, for scenes, vary with age.

The proliferation of gambling advertising has intensified concerns regarding its influence on vulnerable populations, yet the neural mechanisms underlying cue-reactivity to these stimuli remain underexplored in ecologically valid settings. This study protocol proposes a novel methodological framework to investigate prefrontal cortical responses to gambling advertisements in individuals with varying degrees of gambling experience. Materials and methods: This cross-sectional study will recruit 44 participants, divided into a clinical group (individuals with high-frequency gambling or gambling disorder) and a matched control group. Neural activity will be recorded using fNIRS while participants view gambling-related, neutral, violent, and sexual stimuli. Secondary measures include validated scales for gambling severity (SOGS), impulsivity, sensation seeking, and alexithymia. Data analysis will primarily utilize inter-subject correlation (ISC) to quantify neural synchronization and multiband frequency decomposition to capture dynamic affective processing. Advanced preprocessing, including short-channel regression, will be applied to ensure signal robustness. Discussion: By combining portable neuroimaging with a data-driven ISC approach, this study aims to identify objective neural markers of gambling vulnerability. The findings will provide novel insights into the idiosyncratic processing of commercial stimuli, potentially informing public health policies and the development of more effective evidence-based regulations for gambling marketing.

Efficient multimodal designs that capture differences across cognitive domains and variations in cognitive demand remain limited. In this study, we tested a compact framework with 58 healthy participants who completed multimodal electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) sessions. The framework comprised two complementary batteries: the HCP-aligned multitask paradigm (HCP-mini), which integrates eight HCP-aligned cognitive tasks and rest within a single run, and an extended N-back task ranging from 0-back to 7-back. Designed to support broad cross-domain coverage and matched multimodal assessment, the two batteries captured the expected group-level behavioural structure across modalities. Behavioural performance exceeded chance levels or aligned with findings from previous studies in both EEG and fMRI. Descriptive intraclass correlation coefficient (ICC) analyses showed numerically higher within-modality run-to-run values than between-modality values. At the neural level, HCP-mini fMRI activation patterns closely recapitulated the canonical large-scale task organisation of the original HCP dataset, with corresponding task pairs showing the strongest spatial similarity. Together, these findings demonstrate a compact and efficient framework for multimodal characterisation of cognition across domains and graded cognitive demands.

Abstract: BACKGROUND: Perivascular spaces (PVS), visible on brain MRI, contribute to the brain clearance system and are associated with age and neurodegenerative disorders. While lower volumes of PVS in the forebrains white matter and basal ganglia have been also demonstrated in preterm-born neonates, the long-term trajectory of PVS after premature birth remains unclear. This study tests for altered PVS volumes in very preterm/very low birthweight-born (VP/VLBW) adults compared to full-term controls and explores potential associations with cognitive performance. METHODS: PVS were assessed on T2-weighted MRI from 97 VP/VLBW and 89 full-term (FT) subjects at 26 years from the prospective, population-based Bavarian Longitudinal Study. PVS volume and count was based on automated nnU-Net-based segmentation. Regional PVS volumes were normalized by corresponding regional parenchyma volumes. Cognitive performance was assessed by the Wechsler Adult Intelligence Scale. MANCOVA was used for PVS group comparisons, Spearman rank correlations for testing PVS relationships with birth variables and cognitive scores. RESULTS: VP/VLBW-born adults showed significantly higher normalized PVS volumes in bilateral basal ganglia (p < 0.001, partial eta-squared = 0.096) and insula-related white matter (p = 0.001, partial eta-squared = 0.057). In the basal ganglia, higher PVS volumes were negatively correlated with gestational age (rho = -0.223, p = 0.030) and positively correlated with the Intensity of Neonatal Treatment Index (rho = 0.222, p = 0.030) in the VP/VLBW group. PVS volume was not associated with IQ scores. CONCLUSION: We demonstrate region-specific alterations of perivascular spaces in VP/VLBW-born adults. Data suggest that prematurity has lasting impact on the PVS.

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.

In contemporary Cognitive Neuroscience, increasing attention is devoted to brain-body interactions, as an expanding body of literature suggests that processing the external world may not emerge from the brain in isolation but rather from the coordinated contribution of multiple bodily systems. These interactions have been extensively studied in the context of interoception. However, evidence linking them to visual perception remains scarce. To address this gap, the present study examines heart-brain interactions during a visual feature integration task. The task of the participants required shape and color integration of features to identify a target while inhibiting distractor-related information. Cardiac and neural activity were simultaneously recorded, enabling the assessment of the heart rate (HR), heart-evoked potentials (HEP), and, albeit seldom reported previously, heart-evoked oscillations (HEO). Pre-stimulus cardiac-related neural activity differed between correctly and incorrectly integrated features. HEO analysis revealed alpha and low beta band modulations before target onset, which vanished when cardiac time-locking was removed, indicating that they were specifically driven by brain-heart coupling rather than by ongoing brain activity alone. These findings provide the first evidence that HEO dynamics contribute to successful perceptual integration and extend previous work on HEPs from stimulus detection to higher-level perceptual processes. More broadly, they suggest that cardiac signals shape early brain states that bias perception, supporting theoretical frameworks proposing an active role for bodily signals in perceptual processing. HighlightsO_LIPre-stimulus heart-evoked potentials differ between correct and incorrect feature integration. C_LIO_LIHeartbeat-locked alpha and low beta activity increase before correct feature integration C_LIO_LIPre-stimulus oscillatory effects vanish without cardiac activity, revealing HEO contribution. C_LIO_LIBrain-heart coupling biases perceptual outcomes. C_LI

Zero-shot learning from functional magnetic resonance imaging (fMRI) data offers a principled approach to decoding conceptual knowledge without requiring training examples for every target concept. The Semantic Output Code (SOC) framework, introduced by Palatucci et al. [2009], operationalises this idea through a two-stage pipeline: a regression-based mapping from voxel activations to a semantic feature space (the S map), followed by nearest-neighbour retrieval over a semantic knowledge base (the L map). Despite its foundational role in the field, no fully documented, open-source replication of this framework has been published on the original Mitchell et al. [2008] fMRI dataset. We present such a replication and extend it through a systematic evaluation of every major design choice in the pipeline. Using the official 25-verb co-occurrence feature space from Mitchell et al. [2008] and the correlation-stability voxel selection criterion, our pipeline achieves a mean pairwise 2-way forced-choice accuracy of 76.5% (SD = 4.9%, range: 70.0%-84.1%) across all nine subjects of the Mitchell dataset, within 0.5 percentage points of the published benchmark of 77%. We document and resolve a previously unreported evaluation artefact caused by a degenerate zero-vector knowledge base entry for one stimulus word (skyscraper), which suppressed accuracy by approximately 8 percentage points under the broken configuration. Sensitivity analyses across regularisation strength, voxel count, and knowledge base normalisation demonstrate that the pipeline is robust to hyperparameter choice within a broad operating range, with voxel count being the single most impactful factor. Substantial inter-subject variability is documented, with pairwise accuracy ranging from 70.0% (P9) to 84.1% (P1), a spread of 14.1 percentage points that exceeds the difference between our mean and the Mitchell benchmark. All code, the expanded 60-word knowledge base, and the complete evaluation pipeline are released as open-source software at https://github.com/Rashed525/fmri-zsl-pipeline.

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

Vocal communication involves a series of cognitive processes, which can be broadly categorized into three components: perceiving communicative signals; deciding whether and how to respond; and generating vocal motor output. These processes must work harmoniously, with integration and bridging between components being crucial for effective communication. Previous research on vocal communication has typically focused on specific brain regions or isolated cognitive functions, often lacking a holistic perspective of macro-scale, whole-cortical dynamics and their role in the complete communication process. Therefore, although the cortical areas associated with each cognitive component have been localized in humans, the macro-scale cortical dynamics underlying the integration of these cognitive processes remain unknown. Building on recent findings linking macro-scale cortical dynamics to behavioral performance, we hypothesized that traveling wave like cross-areal interactions play a role in integrating the three communicative components. To test this hypothesis, we recorded whole-cortical activity using epidural electrocorticography (ECoG) while subject marmosets vocally interacted with partners. We found theta-band activation in several cortical areas, including the parietal and auditory cortices, while listening to partners calls. This activity was further modulated depending on whether the subjects engaged in vocal interactions, potentially representing the transformation of sensory processing into decision-making and vocal motor preparation. Given the widespread nature of this modulation, we next characterized whole-brain activity patterns by employing a novel analytical method, Weakly Orthogonal Conjugate Contrast Analysis (WOCCA). This analysis revealed that cortical activity could be decomposed into two distinct traveling wave like propagation patterns, a rotational and a translational wave, and both waves discriminated communicative conditions consistent with localized activity. The rotational wave further represented vocal motor preparation through trigger-like temporal pattern. In addition, the magnitude of the translational wave immediately before subjects vocal production correlated with the vocal production-induced suppression of high-gamma-band activity, particularly in the prefrontal and auditory cortices. As vocalization-induced suppression is believed to reflect sensory prediction, the translational wave may propagate specific decision-related or acoustic information necessary for subsequent vocal production to local cortical areas. These findings suggest that the brain orchestrates the sequential cognitive processes underlying vocal communication through macro-scale traveling waves.