Neuroanatomical markers of social cognition in neglected adolescents.

Growing up in neglectful households can impact multiple aspects of social cognition. However, research on neglect's effects on social cognition processes and their neuroanatomical correlates during adolescence is scarce. Here, we aimed to comprehensively assess social cognition processes (recognition of basic and contextual emotions, theory of mind, the experience of envy and Schadenfreude and empathy for pain) and their structural brain correlates in adolescents with legal neglect records within family-based care. First, we compared neglected adolescents (n = 27) with control participants (n = 25) on context-sensitive social cognition tasks while controlling for physical and emotional abuse and executive and intellectual functioning. Additionally, we explored the grey matter correlates of these domains through voxel-based morphometry. Compared to controls, neglected adolescents exhibited lower performance in contextual emotional recognition and theory of mind, higher levels of envy and Schadenfreude and diminished empathy. Physical and emotional abuse and executive or intellectual functioning did not explain these effects. Moreover, social cognition scores correlated with brain volumes in regions subserving social cognition and emotional processing. Our results underscore the potential impact of neglect on different aspects of social cognition during adolescence, emphasizing the necessity for preventive and intervention strategies to address these deficits in this population.

Brain health in diverse settings: How age, demographics and cognition shape brain function.

Diversity in brain health is influenced by individual differences in demographics and cognition. However, most studies on brain health and diseases have typically controlled for these factors rather than explored their potential to predict brain signals. Here, we assessed the role of individual differences in demographics (age, sex, and education; n = 1298) and cognition (n = 725) as predictors of different metrics usually used in case-control studies. These included power spectrum and aperiodic (1/f slope, knee, offset) metrics, as well as complexity (fractal dimension estimation, permutation entropy, Wiener entropy, spectral structure variability) and connectivity (graph-theoretic mutual information, conditional mutual information, organizational information) from the source space resting-state EEG activity in a diverse sample from the global south and north populations. Brain-phenotype models were computed using EEG metrics reflecting local activity (power spectrum and aperiodic components) and brain dynamics and interactions (complexity and graph-theoretic measures). Electrophysiological brain dynamics were modulated by individual differences despite the varied methods of data acquisition and assessments across multiple centers, indicating that results were unlikely to be accounted for by methodological discrepancies. Variations in brain signals were mainly influenced by age and cognition, while education and sex exhibited less importance. Power spectrum activity and graph-theoretic measures were the most sensitive in capturing individual differences. Older age, poorer cognition, and being male were associated with reduced alpha power, whereas older age and less education were associated with reduced network integration and segregation. Findings suggest that basic individual differences impact core metrics of brain function that are used in standard case-control studies. Considering individual variability and diversity in global settings would contribute to a more tailored understanding of brain function.

Moral Disengagement in Adolescent Offenders: Its Relationship with Antisocial Behavior and Its Presence in Offenders of the Law and School Norms.

This study focuses on understanding the relationship between moral disengagement mechanisms in adolescents who engage in law-breaking activities and those who violate school norms. To do so, we administered the Mechanisms of Moral Disengagement Scale (MMDS), which evaluates moral justification, euphemistic labeling, advantageous comparison, deflection of responsibility, diffusion of responsibility, distortion of consequences, dehumanization, and attribution of blame, to 366 adolescents (60.1% males (n = 220) and 39.9% females (n = 146)). Our results confirmed the hypothesis that law-breaking adolescents presented a higher degree of moral disengagement than those adolescents who violate school norms. Additionally, we found that adolescents who violated school norms displayed significantly higher levels of dehumanization than the controls, and law-breaking adolescents obtained the highest score in this domain. Our findings allow us to suggest that the presence of the dehumanization mechanism in adolescents who violate school norms could be used as an early indicator of the emergence of antisocial behaviors, since this was the only component of moral disengagement that significantly differentiated this group from the controls in the study.

A pre-registered, multi-lab non-replication of the action-sentence compatibility effect (ACE).

The Action-sentence Compatibility Effect (ACE) is a well-known demonstration of the role of motor activity in the comprehension of language. Participants are asked to make sensibility judgments on sentences by producing movements toward the body or away from the body. The ACE is the finding that movements are faster when the direction of the movement (e.g., toward) matches the direction of the action in the to-be-judged sentence (e.g., Art gave you the pen describes action toward you). We report on a pre-registered, multi-lab replication of one version of the ACE. The results show that none of the 18 labs involved in the study observed a reliable ACE, and that the meta-analytic estimate of the size of the ACE was essentially zero.

Classifying Parkinson's Disease Patients With Syntactic and Socio-emotional Verbal Measures.

Frontostriatal disorders, such as Parkinson's disease (PD), are characterized by progressive disruption of cortico-subcortical dopaminergic loops involved in diverse higher-order domains, including language. Indeed, syntactic and emotional language tasks have emerged as potential biomarkers of frontostriatal disturbances. However, relevant studies and models have typically considered these linguistic dimensions in isolation, overlooking the potential advantages of targeting multidimensional markers. Here, we examined whether patient classification can be improved through the joint assessment of both dimensions using sentential stimuli. We evaluated 31 early PD patients and 24 healthy controls via two syntactic measures (functional-role assignment, parsing of long-distance dependencies) and a verbal task tapping social emotions (envy, Schadenfreude) and compared their classification accuracy when analyzed in isolation and in combination. Complementarily, we replicated our approach to discriminate between patients on and off medication. Results showed that specific measures of each dimension were selectively impaired in PD. In particular, joint analysis of outcomes in functional-role assignment and Schadenfreude improved the classification accuracy of patients and controls, irrespective of their overall cognitive and affective state. These results suggest that multidimensional linguistic assessments may better capture the complexity and multi-functional impact of frontostriatal disruptions, highlighting their potential contributions in the ongoing quest for sensitive markers of PD.

From discourse to pathology: Automatic identification of Parkinson's disease patients via morphological measures across three languages.

Embodied cognition research on Parkinson's disease (PD) points to disruptions of frontostriatal language functions as sensitive targets for clinical assessment. However, no existing approach has been tested for crosslinguistic validity, let alone by combining naturalistic tasks with machine-learning tools. To address these issues, we conducted the first classifier-based examination of morphological processing (a core frontostriatal function) in spontaneous monologues from PD patients across three typologically different languages. The study comprised 330 participants, encompassing speakers of Spanish (61 patients, 57 matched controls), German (88 patients, 88 matched controls), and Czech (20 patients, 16 matched controls). All subjects described the activities they perform during a regular day, and their monologues were automatically coded via morphological tagging, a computerized method that labels each word with a part-of-speech tag (e.g., noun, verb) and specific morphological tags (e.g., person, gender, number, tense). The ensuing data were subjected to machine-learning analyses to assess whether differential morphological patterns could classify between patients and controls and reflect the former's degree of motor impairment. Results showed robust classification rates, with over 80% of patients being discriminated from controls in each language separately. Moreover, the most discriminative morphological features were associated with the patients' motor compromise (as indicated by Pearson r correlations between predicted and collected motor impairment scores that ranged from moderate to moderate-to-strong across languages). Taken together, our results suggest that morphological patterning, an embodied frontostriatal domain, may be distinctively affected in PD across languages and even under ecological testing conditions.

Evaluating the reliability of neurocognitive biomarkers of neurodegenerative diseases across countries: A machine learning approach.

Accurate early diagnosis of neurodegenerative diseases represents a growing challenge for current clinical practice. Promisingly, current tools can be complemented by computational decision-support methods to objectively analyze multidimensional measures and increase diagnostic confidence. Yet, widespread application of these tools cannot be recommended unless they are proven to perform consistently and reproducibly across samples from different countries. We implemented machine-learning algorithms to evaluate the prediction power of neurocognitive biomarkers (behavioral and imaging measures) for classifying two neurodegenerative conditions -Alzheimer Disease (AD) and behavioral variant frontotemporal dementia (bvFTD)- across three different countries (>200 participants). We use machine-learning tools integrating multimodal measures such as cognitive scores (executive functions and cognitive screening) and brain atrophy volume (voxel based morphometry from fronto-temporo-insular regions in bvFTD, and temporo-parietal regions in AD) to identify the most relevant features in predicting the incidence of the diseases. In the Country-1 cohort, predictions of AD and bvFTD became maximally improved upon inclusion of cognitive screenings outcomes combined with atrophy levels. Multimodal training data from this cohort allowed predicting both AD and bvFTD in the other two novel datasets from other countries with high accuracy (>90%), demonstrating the robustness of the approach as well as the differential specificity and reliability of behavioral and neural markers for each condition. In sum, this is the first study, across centers and countries, to validate the predictive power of cognitive signatures combined with atrophy levels for contrastive neurodegenerative conditions, validating a benchmark for future assessments of reliability and reproducibility.

Fatigue in multiple sclerosis is associated with multimodal interoceptive abnormalities.

BACKGROUND: Fatigue ranks among the most common and disabling symptoms in multiple sclerosis (MS). Recent theoretical works have surmised that this trait might be related to alterations across interoceptive mechanisms. However, this hypothesis has not been empirically evaluated. OBJECTIVES: To determine whether fatigue in MS patients is associated with specific behavioral, structural, and functional disruptions of the interoceptive domain. METHODS: Fatigue levels were established via the Modified Fatigue Impact Scale. Interoception was evaluated through a robust measure indexed by the heartbeat detection task. Structural and functional connectivity properties of key interoceptive hubs were tested by magnetic resonance imaging (MRI) and resting-state functional MRI. Machine learning analyses were employed to perform pairwise classifications. RESULTS: Only patients with fatigue presented with decreased interoceptive accuracy alongside decreased gray matter volume and increased functional connectivity in core interoceptive regions, the insula, and the anterior cingulate cortex. Each of these alterations was positively associated with fatigue. Finally, machine-learning analysis with a combination of the above interoceptive indices (behavioral, structural, and functional) successfully discriminated (area under the curve > 90%) fatigued patients from both non-fatigued and healthy controls. CONCLUSION: This study offers unprecedented evidence suggesting that disruptions of neurocognitive markers subserving interoception may constitute a signature of fatigue in MS.

Explicit and implicit monitoring in neurodegeneration and stroke.

Monitoring is a complex multidimensional neurocognitive phenomenon. Patients with fronto-insular stroke (FIS), behavioural variant frontotemporal dementia (bvFTD) and Alzheimer's disease (AD) show a lack of self-awareness, insight, and self-monitoring, which translate into anosognosia and daily behavioural impairments. Notably, they also present damage in key monitoring areas. While neuroscientific research on this domain has accrued in recent years, no previous study has compared monitoring performance across these brain diseases and none has applied a multiple lesion model approach combined with neuroimaging analysis. Here, we evaluated explicit and implicit monitoring in patients with focal stoke (FIS) and two types of dementia (bvFTD and AD) presenting damage in key monitoring areas. Participants performed a visual perception task and provided two types of report: confidence (explicit judgment of trust about their performance) and wagering (implicit reports which consisted in betting on their accuracy in the perceptual task). Then, damaged areas were analyzed via structural MRI to identify associations with potential behavioral deficits. In AD, inadequate confidence judgments were accompanied by poor wagering performance, demonstrating explicit and implicit monitoring impairments. By contrast, disorders of implicit monitoring in FIS and bvFTD patients occurred in the context of accurate confidence reports, suggesting a reduced ability to turn self-knowledge into appropriate wagering conducts. MRI analysis showed that ventromedial compromise was related to overconfidence, whereas fronto-temporo-insular damage was associated with excessive wagering. Therefore, joint assessment of explicit and implicit monitoring could favor a better differentiation of neurological profiles (frontal damage vs AD) and eventually contribute to delineating clinical interventions.

Robust automated computational approach for classifying frontotemporal neurodegeneration: Multimodal/multicenter neuroimaging.

INTRODUCTION: Timely diagnosis of behavioral variant frontotemporal dementia (bvFTD) remains challenging because it depends on clinical expertise and potentially ambiguous diagnostic guidelines. Recent recommendations highlight the role of multimodal neuroimaging and machine learning methods as complementary tools to address this problem. METHODS: We developed an automatic, cross-center, multimodal computational approach for robust classification of patients with bvFTD and healthy controls. We analyzed structural magnetic resonance imaging and resting-state functional connectivity from 44 patients with bvFTD and 60 healthy controls (across three imaging centers with different acquisition protocols) using a fully automated processing pipeline, including site normalization, native space feature extraction, and a random forest classifier. RESULTS: Our method successfully combined multimodal imaging information with high accuracy (91%), sensitivity (83.7%), and specificity (96.6%). DISCUSSION: This multimodal approach enhanced the system's performance and provided a clinically informative method for neuroimaging analysis. This underscores the relevance of combining multimodal imaging and machine learning as a gold standard for dementia diagnosis.

Inducción de estados afectivos a través de imágenes. Segunda validación colombiana del Sistema Internacional de Imágenes Afectivas (IAPS) / Induction of Affective States with Pictures: Second Colombian Validation of the International Affective Pictures System (IAPS)

Resumen El objetivo del presente estudio es validar un segundo grupo de imágenes del Sistema Internacional de Imágenes Afectiva (IAPS) en población colombiana, con el fin de aumentar el banco de imágenes que puedan ser utilizadas en investigaciones en los campos de la emoción, la atención y la memoria, entre otros. Se validaron 240 imágenes pertenecientes a los conjuntos 15, 16, 17 y 18 del IAPS en una muestra de 1.222 personas provenientes de cinco ciudades del país (Bogotá, Medellín, Cali, Barranquilla y Bucaramanga). Para evaluar la respuesta emocional ante las imágenes en las dimensiones de valencia, arousal y dominancia se utilizó el Self-Assessment Manikin (SAM). Los resultados mostraron que las imágenes se distribuyeron de la forma esperada en el espacio afectivo bidimensional compuesto por las dimensiones de valencia y arousal. Se identificó un sesgo emocional positivo en los hombres y un sesgo emocional negativo en las mujeres. Las diferencias entre regiones y estrato socioeconómico se presentaron únicamente en arousal y dominancia, no en valencia. En conjunto, los resultados sugieren que estas imágenes pueden ser utilizadas para inducir estados afectivos en la población colombiana de forma controlada, lo que permite su uso para el estudio científico y experimental de diferentes procesos psicológicos, como la emoción, la motivación y la atención.

Abstract The aim of this study was to validate a second group of images of the International Affective Pictures System (IAPS) in Colombian population, in order to increase the bank of images that can be used in research in the fields of emotion, attention and memory, among others. 240 pictures belonging to sets 15, 16, 17 and 18 of the IAPS were validated in a sample of 1222 participants from five cities in the country (Bogotá, Medellín, Cali, Barranquilla and Bucaramanga). To assess the emotional response to images in the valence, arousal and dominance dimensions, the Self-Assessment Manikin (SAM) was used. The results showed that the pictures were distributed as expected in the two-dimensional affective space composed of the valence and arousal dimensions. A positive emotional bias was identified in men and a negative emotional bias in women. The differences between regions and socioeconomic strata were presented only in arousal and dominance, not in valence. Together, the results suggest that these images can be used to induce affective states in the Colombian population in a controlled manner, which allows their use for the scientific and experimental study of different psychological processes, such as emotion, motivation and attention.

How meaning unfolds in neural time: Embodied reactivations can precede multimodal semantic effects during language processing.

Research on how the brain construes meaning during language use has prompted two conflicting accounts. According to the 'grounded view', word understanding involves quick reactivations of sensorimotor (embodied) experiences evoked by the stimuli, with simultaneous or later engagement of multimodal (conceptual) systems integrating information from various sensory streams. Contrariwise, for the 'symbolic view', this capacity depends crucially on multimodal operations, with embodied systems playing epiphenomenal roles after comprehension. To test these contradictory hypotheses, the present magnetoencephalography study assessed implicit semantic access to grammatically constrained action and non-action verbs (n = 100 per category) while measuring spatiotemporally precise signals from the primary motor cortex (M1, a core region subserving bodily movements) and the anterior temporal lobe (ATL, a putative multimodal semantic hub). Convergent evidence from sensor- and source-level analyses revealed that increased modulations for action verbs occurred earlier in M1 (∼130-190 ms) than in specific ATL hubs (∼250-410 ms). Moreover, machine-learning decoding showed that trial-by-trial classification peaks emerged faster in M1 (∼100-175 ms) than in the ATL (∼345-500 ms), with over 71% accuracy in both cases. Considering their latencies, these results challenge the 'symbolic view' and its implication that sensorimotor mechanisms play only secondary roles in semantic processing. Instead, our findings support the 'grounded view', showing that early semantic effects are critically driven by embodied reactivations and that these cannot be reduced to post-comprehension epiphenomena, even when words are individually classified. Briefly, our study offers non-trivial insights to constrain fine-grained models of language and understand how meaning unfolds in neural time.

Consistent Gradient of Performance and Decoding of Stimulus Type and Valence From Local and Network Activity.

The individual differences approach focuses on the variation of behavioral and neural signatures across subjects. In this context, we searched for intracranial neural markers of performance in three individuals with distinct behavioral patterns (efficient, borderline, and inefficient) in a dual-valence task assessing facial and lexical emotion recognition. First, we performed a preliminary study to replicate well-established evoked responses in relevant brain regions. Then, we examined time series data and network connectivity, combined with multivariate pattern analyses and machine learning, to explore electrophysiological differences in resting-state versus task-related activity across subjects. Next, using the same methodological approach, we assessed the neural decoding of performance for different dimensions of the task. The classification of time series data mirrored the behavioral gradient across subjects for stimulus type but not for valence. However, network-based measures reflected the subjects' hierarchical profiles for both stimulus types and valence. Therefore, this measure serves as a sensitive marker for capturing distributed processes such as emotional valence discrimination, which relies on an extended set of regions. Network measures combined with classification methods may offer useful insights to study single subjects and understand inter-individual performance variability. Promisingly, this approach could eventually be extrapolated to other neuroscientific techniques.

Reading Shakespearean tropes in a foreign tongue: Age of L2 acquisition modulates neural responses to functional shifts.

Functional shifts (FSs) - morphosyntactically marked words evoking coherent but novel meanings - are ubiquitous in English and, specially, in Shakespearean literature. While their neural signatures have been explored in native speakers, no study has targeted foreign-language users, let alone comparing early and late bilinguals. Here, we administered a validated FS paradigm to subjects from both populations and evaluated time-frequency modulations evoked by FS and control sentences. Early bilinguals exhibited greater sensitivity towards FSs, indexed by reduced fronto-posterior theta-band oscillations across semantic- and structural-integration windows. Such oscillatory modulations may represent a key marker of age-of-acquisition effects during foreign-language wordplay processing.

Negation markers inhibit motor routines during typing of manual action verbs.

We explored whether negation markers recruit inhibitory mechanisms during keyboard-based action-verb typing. In each trial, participants read two sentences: the first featured a context (There is a contract) and the second ended with a relevant verb which had to be immediately typed. Crucially, the verb could describe manual actions, non-manual actions or non-motor processes, with either affirmative (You do sign it) or negative (You don't sign it) polarity. We assessed the impact of verb type and polarity on two typing dimensions: motor programming (lapse between target onset and first keystroke) and motor execution (lapse between first and last keystroke). Negation yielded no effect on motor planning, but it selectively delayed typing execution for manual-action verbs, irrespective of the subjects' typing skills. This suggests that processing negations during comprehension of manual-action sentences recruits inhibitory mechanisms acting on same-effector movements. Our novel finding extends embodied models of language and effector-specific motor-language integration.

Altered neural signatures of interoception in multiple sclerosis.

Multiple sclerosis (MS) patients present several alterations related to sensing of bodily signals. However, no specific neurocognitive impairment has yet been proposed as a core deficit underlying such symptoms. We aimed to determine whether MS patients present changes in interoception-that is, the monitoring of autonomic bodily information-a process that might be related to various bodily dysfunctions. We performed two studies in 34 relapsing-remitting, early-stage MS patients and 46 controls matched for gender, age, and education. In Study 1, we evaluated the heartbeat-evoked potential (HEP), a cortical signature of interoception, via a 128-channel EEG system during a heartbeat detection task including an exteroceptive and an interoceptive condition. Then, we obtained whole-brain MRI recordings. In Study 2, participants underwent fMRI recordings during two resting-state conditions: mind wandering and interoception. In Study 1, controls exhibited greater HEP modulation during the interoceptive condition than the exteroceptive one, but no systematic differences between conditions emerged in MS patients. Patients presented atrophy in the left insula, the posterior part of the right insula, and the right anterior cingulate cortex, with abnormal associations between neurophysiological and neuroanatomical patterns. In Study 2, controls showed higher functional connectivity and degree for the interoceptive state compared with mind wandering; however, this pattern was absent in patients, who nonetheless presented greater connectivity and degree than controls during mind wandering. MS patients were characterized by atypical multimodal brain signatures of interoception. This finding opens a new agenda to examine the role of inner-signal monitoring in the body symptomatology of MS.

Increased moral condemnation of accidental harm in institutionalized adolescents.

Social deprivation, as faced by children in institutional rearing, involves socio-cognitive deficits that may persist into adolescence. In particular, two relevant domains which prove sensitive to pre-adult neurodevelopment are theory of mind (ToM) and moral judgment (a complex skill which partially depend upon ToM). However, no study has assessed moral evaluation in adolescents with a history of institutional care, let alone its relationship with ToM skills. The present study aims to bridge this gap, focusing on moral evaluation of harmful actions in institutionalized adolescents (IAs). Relative to adolescents raised with their biological families, IAs exhibited less willingness to exculpate protagonists for accidental harms, suggesting an under-reliance on information about a person's (innocent) intentions. Moreover, such abnormalities in IAs were associated with ToM impairments. Taken together, our findings extend previous findings of delayed ToM under social deprivation, further showing that the development of moral cognition is also vulnerable to the impact of institutionalization. These results could pave the way for novel research on the role of institutional rearing in ToM and moral development during adolescence.

Weighted Symbolic Dependence Metric (wSDM) for fMRI resting-state connectivity: A multicentric validation for frontotemporal dementia.

The search for biomarkers of neurodegenerative diseases via fMRI functional connectivity (FC) research has yielded inconsistent results. Yet, most FC studies are blind to non-linear brain dynamics. To circumvent this limitation, we developed a "weighted Symbolic Dependence Metric" (wSDM) measure. Using symbolic transforms, we factor in local and global temporal features of the BOLD signal to weigh a robust copula-based dependence measure by symbolic similarity, capturing both linear and non-linear associations. We compared this measure with a linear connectivity metric (Pearson's R) in its capacity to identify patients with behavioral variant frontotemporal dementia (bvFTD) and controls based on resting-state data. We recruited participants from two international centers with different MRI recordings to assess the consistency of our measure across heterogeneous conditions. First, a seed-analysis comparison of the salience network (a specific target of bvFTD) and the default-mode network (as a complementary control) between patients and controls showed that wSDM yields better identification of resting-state networks. Moreover, machine learning analysis revealed that wSDM yielded higher classification accuracy. These results were consistent across centers, highlighting their robustness despite heterogeneous conditions. Our findings underscore the potential of wSDM to assess fMRI-derived FC data, and to identify sensitive biomarkers in bvFTD.

Early bilateral and massive compromise of the frontal lobes.

The frontal lobes are one of the most complex brain structures involved in both domain-general and specific functions. The goal of this work was to assess the anatomical and cognitive affectations from a unique case with massive bilateral frontal affectation. We report the case of GC, an eight-year old child with nearly complete affectation of bilateral frontal structures and spared temporal, parietal, occipital, and cerebellar regions. We performed behavioral, neuropsychological, and imaging (MRI, DTI, fMRI) evaluations. Neurological and neuropsychological examinations revealed a mixed pattern of affected (executive control/abstraction capacity) and considerably preserved (consciousness, language, memory, spatial orientation, and socio-emotional) functions. Both structural (DTI) and functional (fMRI) connectivity evidenced abnormal anterior connections of the amygdala and parietal networks. In addition, brain structural connectivity analysis revealed almost complete loss of frontal connections, with atypical temporo-posterior pathways. Similarly, functional connectivity showed an aberrant frontoparietal network and relative preservation of the posterior part of the default mode network and the visual network. We discuss this multilevel pattern of behavioral, structural, and functional connectivity results. With its unique pattern of compromised and preserved structures and functions, this exceptional case offers new constraints and challenges for neurocognitive theories.

Action-semantic and syntactic deficits in subjects at risk for Huntington's disease.

Frontostriatal networks play critical roles in grounding action semantics and syntactic skills. Indeed, their atrophy distinctively disrupts both domains, as observed in patients with Huntington's disease (HD) and Parkinson's disease, even during early disease stages. However, frontostriatal degeneration in these conditions may begin up to 15 years before the onset of clinical symptoms, opening avenues for pre-clinical detection via sensitive tasks. Such a mission is particularly critical in HD, given that patients' children have 50% chances of inheriting the disease. Against this background, we assessed whether deficits in the above-mentioned domains emerge in subjects at risk to develop HD. We administered tasks tapping action semantics, object semantics, and two forms of syntactic processing to 18 patients with HD, 19 asymptomatic first-degree relatives, and sociodemographically matched controls for each group. The patients evinced significant deficits in all tasks, but only those in the two target domains were independent of overall cognitive state. More crucially, relative to controls, the asymptomatic relatives were selectively impaired in action semantics and in the more complex syntactic task, with both patterns emerging irrespective of the subjects' overall cognitive state. Our findings highlight the relevance of these dysfunctions as potential prodromal biomarkers of HD. Moreover, they offer theoretical insights into the differential contributions of frontostriatal hubs to both domains while paving the way for innovations in diagnostic procedures.