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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.

Abstract Cognitive studies on Parkinson’s disease (PD) reveal abnormal semantic processing. Most research, however, fails to indicate which conceptual properties are most affected and capture patients’ neurocognitive profiles. Here, we asked persons with PD, healthy controls, and individuals with behavioral variant frontotemporal dementia (bvFTD, as a disease control group) to read concepts (e.g., ‘sun’) and list their features (e.g., hot). Responses were analyzed in terms of ten word properties (including concreteness, imageability, and semantic variability), used for group-level comparisons, subject-level classification, and brain-behavior correlations. PD (but not bvFTD) patients produced more concrete and imageable words than controls, both patterns being associated with overall cognitive status. PD and bvFTD patients showed reduced semantic variability, an anomaly which predicted semantic inhibition outcomes. Word-property patterns robustly classified PD (but not bvFTD) patients and correlated with disease-specific hypoconnectivity along the sensorimotor and salience networks. Fine-grained semantic assessments, then, can reveal distinct neurocognitive signatures of PD.

Abstract Situated models suggest that social concepts are grounded in interpersonal experience. However, few studies have tested this notion experimentally, and none has targeted individuals with reduced social interaction. Here, we assessed comprehension of text-level social and non-social concepts in persons with and without autistic-like traits. Participants read a social and a non-social text and answered questionnaires targeting social and non-social concepts, respectively. We compared behavioral outcomes, gauged their contribution to subject-level classification, and examined their association with validated measures of autism. Persons with autistic-like traits showed selective deficits in grasping text-level social concepts, even adjusting for intelligence, memory, and vocabulary. Also, social concept comprehension was the only variable that significantly classified between groups. Finally, social concept outcomes correlated negatively with measures of autism, including social interaction. Our results suggest that reduced interpersonal experience selectively compromises text-level social concept processing, offering empirical constraints for situated models of social semantics.

Abstract Individuals with autism spectrum disorder (ASD) present difficulties in integrating mental state information in complex moral tasks. Yet, ASD research has not examined whether this process is influenced by emotions, let alone while capturing its neural bases. We investigated how language-induced emotions modulate intent-based moral judgment in ASD. In a fMRI task, 30 adults with ASD and 27 neurotypical controls read vignettes whose protagonists commit harm either accidentally or intentionally, and then decided how much punishment the protagonist deserved. Emotional content was manipulated across scenarios through the use of graphic language (designed to trigger arousing negative responses) vs. plain (just-the-facts, emotionless) language. Off-line functional connectivity correlates of task performance were also analyzed. In ASD, emotional (graphic) descriptions amplified punishment ratings of accidental harms, associated with increased activity in fronto-temporo-limbic, precentral, and postcentral/supramarginal regions (critical for emotional and empathic processes), and reduced connectivity among the orbitofrontal cortex and the angular gyrus (involved in mentalizing). Language manipulation did not influence intentional harm processing in ASD. In conclusion, in arousing and ambiguous social situations that lack intentionality clues (i.e. graphic accidental harm scenarios), individuals with ASD would misuse their emotional responses as the main source of information to guide their moral decisions. Conversely, in face of explicit harmful intentions, they would be able to compensate their socioemotional alterations and assign punishment through non-emotional pathways. Despite limitations, such as the small sample size and low ecological validity of the task, results of the present study proved reliable and have relevant theoretical and translational implications.

Abstract Action-concept outcomes are useful targets to identify Parkinson’s disease (PD) patients and differentiate between those with and without mild cognitive impairment (PD-MCI, PD-nMCI). Yet, most approaches employ burdensome examiner-dependent tasks, limiting their utility. We introduce a framework capturing action-concept markers automatically in natural speech. Patients from both subgroups and controls retold an action-laden and a non-action-laden text (AT, nAT). In each retelling, we weighed action and non-action concepts through our automated Proximity-to-Reference-Semantic-Field (P-RSF) metric, for analysis via ANCOVAs (controlling for cognitive dysfunction) and support vector machines. Patients were differentiated from controls based on AT (but not nAT) P-RSF scores. The same occurred in PD-nMCI patients. Conversely, PD-MCI patients exhibited reduced P-RSF scores for both texts. Direct discrimination between patient subgroups was not systematic, but it yielded best outcomes via AT scores. Our approach outperformed classifiers based on corpus-derived embeddings. This framework opens scalable avenues to support PD diagnosis and phenotyping.

Anticipating social stress evokes strong reactions in the organism, including interoceptive modulations. However, evidence for this claim comes from behavioral studies, often with inconsistent results, and relates almost solely to the reactive and recovery phase of social stress exposure. Here, we adopted an allostatic-interoceptive predictive coding framework to study interoceptive and exteroceptive anticipatory brain responses using a social rejection task. We analyzed the heart-evoked potential (HEP) and task-related oscillatory activity of 58 adolescents via scalp EEG, and 385 human intracranial recordings of three patients with intractable epilepsy. We found that anticipatory interoceptive signals increased in the face of unexpected social outcomes, reflected in larger negative HEP modulations. Such signals emerged from key brain allostatic-interoceptive network hubs, as shown by intracranial recordings. Exteroceptive signals were characterized by early activity between 1-15 Hz across conditions, and modulated by the probabilistic anticipation of reward-related outcomes, observed over distributed brain regions. Our findings suggest that the anticipation of a social outcome is characterized by allostatic-interoceptive modulations that prepare the organism for possible rejection. These results inform our understanding of interoceptive processing and constrain neurobiological models of social stress.

Although social functioning relies on working memory, whether a social-specific mechanism exists remains unclear. This undermines the characterization of neurodegenerative conditions with both working memory and social deficits. We assessed working memory domain-specificity across behavioral, electrophysiological, and neuroimaging dimensions in 245 participants. A novel working memory task involving social and non-social stimuli with three load levels was assessed across controls and different neurodegenerative conditions with recognized impairments in: working memory and social cognition (behavioral-variant frontotemporal dementia); general cognition (Alzheimer’s disease); and unspecific patterns (Parkinson’s disease). We also examined resting-state theta oscillations and functional connectivity correlates of working memory domain-specificity. Results in controls and all groups together evidenced increased working memory demands for social stimuli associated with frontocinguloparietal theta oscillations and salience network connectivity. Canonical frontal theta oscillations and executive-default mode network anticorrelation indexed non-social stimuli. Behavioral-variant frontotemporal dementia presented generalized working memory deficits related to posterior theta oscillations, with social stimuli linked to salience network connectivity. In Alzheimer’s disease, generalized working memory impairments were related to temporoparietal theta oscillations, with non-social stimuli linked to the executive network. Parkinson’s disease showed spared working memory performance and canonical brain correlates. Findings support a social-specific working memory and related disease-selective pathophysiological mechanisms.

Summary: Background: Global brain health initiatives call for improving methods for the diagnosis of Alzheimer's disease (AD) and frontotemporal dementia (FTD) in underrepresented populations. However, diagnostic procedures in upper-middle-income countries (UMICs) and lower-middle income countries (LMICs), such as Latin American countries (LAC), face multiple challenges. These include the heterogeneity in diagnostic methods, lack of clinical harmonisation, and limited access to biomarkers. Methods: This cross-sectional observational study aimed to identify the best combination of predictors to discriminate between AD and FTD using demographic, clinical and cognitive data among 1794 participants [904 diagnosed with AD, 282 diagnosed with FTD, and 606 healthy controls (HCs)] collected in 11 clinical centres across five LAC (ReDLat cohort). Findings: A fully automated computational approach included classical statistical methods, support vector machine procedures, and machine learning techniques (random forest and sequential feature selection procedures). Results demonstrated an accurate classification of patients with AD and FTD and HCs. A machine learning model produced the best values to differentiate AD from FTD patients with an accuracy = 0.91. The top features included social cognition, neuropsychiatric symptoms, executive functioning performance, and cognitive screening; with secondary contributions from age, educational attainment, and sex. Interpretation: Results demonstrate that data-driven techniques applied in archival clinical datasets could enhance diagnostic procedures in regions with limited resources. These results also suggest specific fine-grained cognitive and behavioural measures may aid in the diagnosis of AD and FTD in LAC. Moreover, our results highlight an opportunity for harmonisation of clinical tools for dementia diagnosis in the region. Funding: This work was supported by the Multi-Partner Consortium to Expand Dementia Research in Latin America (ReDLat), funded by NIA/NIH (R01AG057234), Alzheimer's Association (SG-20-725707-ReDLat), Rainwater Foundation, Takeda (CW2680521), Global Brain Health Institute; as well as CONICET; FONCYT-PICT (2017-1818, 2017-1820); PIIECC, Facultad de Humanidades, Usach; Sistema General de Regalías de Colombia (BPIN2018000100059), Universidad del Valle (CI 5316); ANID/FONDECYT Regular (1210195, 1210176, 1210176); ANID/FONDAP (15150012); ANID/PIA/ANILLOS ACT210096; and Alzheimer's Association GBHI ALZ UK-22-865742.

Abstract Traditional and mainstream legal frameworks conceive law primarily as a purely rational practice, free from affect or intuition. However, substantial evidence indicates that human decision-making depends upon diverse biases. We explored the manifestation of these biases through comparisons among 45 criminal judges, 60 criminal attorneys, and 64 controls. We examined whether these groups’ decision-making patterns were influenced by (a) the information on the transgressor’s mental state, (b) the use of gruesome language in harm descriptions, and (c) ongoing physiological states. Judges and attorneys were similar to controls in that they overestimated the damage caused by intentional harm relative to accidental harm. However, judges and attorneys were less biased towards punishments and harm severity ratings to accidental harms. Similarly, they were less influenced in their decisions by either language manipulations or physiological arousal. Our findings suggest that specific expertise developed in legal settings can attenuate some pervasive biases in moral decision processes.

Abstract 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.

Bilingualism research indicates that verbal memory skills are sensitive to age of second language (L2) acquisition (AoA). However, most tasks employ disconnected, decontextualized stimuli, undermining ecological validity. Here, we assessed whether AoA impacts the ability to recall information from naturalistic discourse in single-language and cross-linguistic tasks. Twenty-four early and 25 late Chinese-English bilinguals listened to real-life L2 newscasts and orally reproduced their information in English (Task 1) and Chinese (Task 2). Both groups were compared in terms of recalled information (presence and correctness of idea units) and key control measures (e.g., attentional skills, speech rate). Across both tasks, information completeness was higher for early than late bilinguals. This occurred irrespective of attentional speed, speech rate, and additional relevant factors. Such results bridge the gap between classical memory paradigms and ecological designs in bilingualism research, illuminating how particular language profiles shape information processing in daily communicative scenarios.

Beyond canonical deficits in social cognition and interpersonal conduct, behavioral variant frontotemporal dementia (bvFTD) involves language difficulties in a substantial proportion of cases. However, since most evidence comes from high-income countries, the scope and relevance of language deficits in Latin American bvFTD samples remain poorly understood. As a first step toward reversing this scenario, we review studies reporting language measures in Latin American bvFTD cohorts relative to other groups. We identified 24 papers meeting systematic criteria, mainly targeting phonemic and semantic fluency, naming, semantic processing, and comprehension skills. The evidence shows widespread impairments in these domains, often related to overall cognitive disturbances. Some of these deficits may be as severe as in other diseases where they are more widely acknowledged, such as Alzheimer's disease. Considering the prevalence and informativeness of language deficits in bvFTD patients from other world regions, the need arises for more systematic research in Latin America, ideally spanning multiple domains, in diverse languages and dialects, with validated batteries. We outline key challenges and pathways of progress in this direction, laying the ground for a new regional research agenda on the disorder.

The pressing call to detect sensitive cognitive markers of frontal lobe epilepsy (FLE) remains poorly addressed. Standard frameworks prove nosologically unspecific (as they reveal deficits that also emerge across other epilepsy subtypes), possess low ecological validity, and are rarely supported by multimodal neuroimaging assessments. To bridge these gaps, we examined naturalistic action and non-action text comprehension, combined with structural and functional connectivity measures, in 19 FLE patients, 19 healthy controls, and 20 posterior cortex epilepsy (PCE) patients. Our analyses integrated inferential statistics and data-driven machine-learning classifiers. FLE patients were selectively and specifically impaired in action comprehension, irrespective of their neuropsychological profile. These deficits selectively and specifically correlated with (a) reduced integrity of the anterior thalamic radiation, a subcortical structure underlying motoric and action-language processing as well as epileptic seizure spread in this subtype; and (b) hypoconnectivity between the primary motor cortex and the left-parietal/supramarginal regions, two putative substrates of action-language comprehension. Moreover, machine-learning classifiers based on the above neurocognitive measures yielded 75% accuracy rates in discriminating individual FLE patients from both controls and PCE patients. Briefly, action-text assessments, combined with structural and functional connectivity measures, seem to capture ecological cognitive deficits that are specific to FLE, opening new avenues for discriminatory characterizations among epilepsy types.

El desarrollo de biomarcadores de demencias efectivos y asequibles resulta esencial dada la dificultad de realizar un diagnóstico temprano de estas patologías. En este sentido, los métodos de electroencefalografía (EEG) brindan alternativas promisorias por su bajo costo, portabilidad y creciente robustez. En este trabajo, nos basamos en señales de EEG y en un novedoso método de intercambio de información para estudiar la conectividad en estado de reposo en pacientes afectados por la variante conductual de la demencia frontotemporal (vcDFT) y en un grupo control. Para evaluar la especificidad de los resultados obtenidos, también examinamos pacientes que padecen la enfermedad de Alzheimer (EA). El poder de clasificación de los patrones de conectividad resultantes se evaluó mediante un algoritmo de clasificación supervisada (máquina de soporte vectorial). Además, comparamos el poder de clasificación obtenido mediante (i) la conectividad funcional, (ii) una batería de pruebas neuropsicológicas pertinentes y (iii) la combinación de ambos. Los pacientes con vcDFT mostraron un patrón de hipoconectividad específico en conexiones frontotemporales de proximidad media, que no mostraron alteraciones en los pacientes con EA. Estas alteraciones en la conectividad funcional en la vcDFT se replicaron mediante EEG de baja densidad (20 electrodos). Por otra parte, mientras que las pruebas neuropsicológicas llevaron a una discriminación aceptable entre los pacientes con vcDFT y los del grupo control, la adición de los resultados de conectividad aumentó el poder de clasificación. Finalmente, la clasificación entre los pacientes con vcDFT y los con EA fue mejor cuando se usó como base la conectividad que cuando se usaron las pruebas neuropsicológicas. En conjunto, estos hallazgos enfatizan la relevancia de las mediciones EEG como biomarcadores de potencial aplicación clínica.

From molecular mechanisms to global brain networks, atypical fluctuations are the hallmark of neurodegeneration. Yet, traditional fMRI research on resting-state networks (RSNs) has favored static and average connectivity methods, which by overlooking the fluctuation dynamics triggered by neurodegeneration, have yielded inconsistent results. The present multicenter study introduces a data-driven machine learning pipeline based on dynamic connectivity fluctuation analysis (DCFA) on RS-fMRI data from 300 participants belonging to three groups: behavioral variant frontotemporal dementia (bvFTD) patients, Alzheimer's disease (AD) patients, and healthy controls. We considered non-linear oscillatory patterns across combined and individual resting-state networks (RSNs), namely: the salience network (SN), mostly affected in bvFTD; the default mode network (DMN), mostly affected in AD; the executive network (EN), partially compromised in both conditions; the motor network (MN); and the visual network (VN). These RSNs were entered as features for dementia classification using a recent robust machine learning approach (a Bayesian hyperparameter tuned Gradient Boosting Machines (GBM) algorithm), across four independent datasets with different MR scanners and recording parameters. The machine learning classification accuracy analysis revealed a systematic and unique tailored architecture of RSN disruption. The classification accuracy ranking showed that the most affected networks for bvFTD were the SN + EN network pair (mean accuracy = 86.43%, AUC = 0.91, sensitivity = 86.45%, specificity = 87.54%); for AD, the DMN + EN network pair (mean accuracy = 86.63%, AUC = 0.89, sensitivity = 88.37%, specificity = 84.62%); and for the bvFTD vs. AD classification, the DMN + SN network pair (mean accuracy = 82.67%, AUC = 0.86, sensitivity = 81.27%, specificity = 83.01%). Moreover, the DFCA classification systematically outperformed canonical connectivity approaches (including both static and linear dynamic connectivity). Our findings suggest that non-linear dynamical fluctuations surpass two traditional seed-based functional connectivity approaches and provide a pathophysiological characterization of global brain networks in neurodegenerative conditions (AD and bvFTD) across multicenter data.

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.

Do embodied semantic systems play different roles depending on when and how well a given language was learned? Emergent evidence suggests that this is the case for isolated, decontextualized stimuli, but no study has addressed the issue considering naturalistic narratives. Seeking to bridge this gap, we assessed motor-system dynamics in 26 Spanish-English bilinguals as they engaged in free, unconstrained reading of naturalistic action texts (ATs, highlighting the characters’ movements) and neutral texts (NTs, featuring low motility) in their first and second language (L1, L2). To explore functional connectivity spread over each reading session, we recorded ongoing high-density electroencephalographic signals and subjected them to functional connectivity analysis via a spatial clustering approach. Results showed that, in L1, AT (relative to NT) reading involved increased connectivity between left and right central electrodes consistently implicated in action-related processes, as well as distinct source-level modulations in motor regions. In L2, despite null group-level effects, enhanced motor-related connectivity during AT reading correlated positively with L2 proficiency and negatively with age of L2 learning. Taken together, these findings suggest that action simulations during unconstrained narrative reading involve neural couplings between motor-sensitive mechanisms, in proportion to how consolidated a language is. More generally, such evidence addresses recent calls to test the ecological validity of motor-resonance effects while offering new insights on their relation with experiential variables.

Interoception (the sensing of inner-body signals) is a multi-faceted construct with major relevance for basic and clinical neuroscience research. However, the neurocognitive signatures of this domain (cutting across behavioral, electrophysiological, and fMRI connectivity levels) are rarely reported in convergent or systematic fashion. Additionally, various controversies in the field might reflect the caveats of standard interoceptive accuracy (IA) indexes, mainly based on heartbeat detection (HBD) tasks. Here we profit from a novel IA index (md) to provide a convergent multidimensional and multi-feature approach to cardiac interoception. We found that outcomes from our IA-md index are associated with –and predicted by– canonical markers of interoception, including the hd-EEG-derived heart-evoked potential (HEP), fMRI functional connectivity within interoceptive hubs (insular, somatosensory, and frontal networks), and socio-emotional skills. Importantly, these associations proved more robust than those involving current IA indexes. Furthermore, this pattern of results persisted when taking into consideration confounding variables (gender, age, years of education, and executive functioning). This work has relevant theoretical and clinical implications concerning the characterization of cardiac interoception and its assessment in heterogeneous samples, such as those composed of neuropsychiatric patients.

Insights on the neurocognitive particularities of expert individuals have benefited from language studies on professional simultaneous interpreters (PSIs). Accruing research indicates that behavioral advantages in this population are restricted to those skills that are directly taxed during professional practice (e.g., translation as opposed to reading), but little is known about the neural signatures of such selective effects. To illuminate the issue, we recruited 17 PSIs and 15 non-interpreter bilinguals and compared behavioral and electrophysiological markers of word reading and translation from and into their native and non-native languages (L1 and L2, respectively). PSIs exhibited greater delta-theta (1–8 ​Hz) power across all tasks over varying topographies, but these were accompanied by faster performance only in the case of translation conditions. Moreover, neural differences in PSIs were most marked for L2-L1 translation (the dominant interpreting direction in their market), which exhibited maximally widespread modulations that selectively correlated with behavioral outcomes. Taken together, our results suggest that interpreting experience involves distinct neural signatures across reading and translation mechanisms, but that these are systematically related with processing efficiency only in domains that face elevated demands during everyday practice (i.e., L2-L1 translation). These findings can inform models of simultaneous interpreting, in particular, and expert cognitive processing, in general.

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.

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. Keywords: Frontal lobe, Neurodevelopmental disorders, Attention, Executive function, Language, Social cognition, Consciousness, DTI, MRI, fMRI

Impairments of action semantics (a cognitive domain that critically engages motor brain networks) are pervasive in early Parkinson’s disease (PD). However, no study has examined whether action semantic skills in persons with this disease can be influenced by non-invasive neuromodulation. Here, we recruited 22 PD patients and performed a five-day randomized, blinded, sham-controlled study to assess whether anodal transcranial direct current stimulation (atDCS) over the primary motor cortex, combined with cognitive training, can boost action–concept processing. On day 1, participants completed a picture–word association (PWA) task involving action-verb and object-noun conditions. They were then randomly assigned to either an atDCS (n = 11, 2 mA for 20 m) or a sham tDCS (n = 11, 2 mA for 30 s) group and performed an online PWA practice over three days. On day 5, they repeated the initial protocol. Relative to sham tDCS, the atDCS group exhibited faster reaction times for action (as opposed to object) concepts in the post-stimulation test. This result was exclusive to the atDCS group and held irrespective of the subjects’ cognitive, executive, and motor skills, further attesting to its specificity. Our findings suggest that action-concept deficits in PD are distinctively grounded in motor networks and might be countered by direct neuromodulation of such circuits. Moreover, they provide new evidence for neurosemantic models and inform a thriving agenda in the embodied cognition framework.

Abstract Empathy is a complex cognitive and affective process that allows humans to experience concern for others, comprehend their emotions, and eventually help them. In addition to studies with healthy subjects and various neuropsychiatric populations, a few reports have examined this domain focusing on mental health workers, whose daily work requires the development of a saliently empathic character. Building on this research line, the present population-based study aimed to (a) assess different dimensions of empathy for pain in mental health workers relative to general-physicians and non-medical workers; and (b) evaluate their relationship with relevant factors, such as moral profile, age, gender, years of experience, and workplace type. Relative to both control groups, mental health workers exhibited higher empathic concern and discomfort for others’ suffering, and they favored harsher punishment to harmful actions. Furthermore, this was the only group in which empathy variability was explained by moral judgments, years of experience, and workplace type. Taken together, these results indicate that empathy is continuously at stake in mental health care scenarios, as it can be affected by contextual factors and social contingencies. More generally, they highlight the importance of studying this domain in populations characterized by extreme empathic demands.

Abstract Developing effective and affordable biomarkers for dementias is critical given the difficulty to achieve early diagnosis. In this sense, electroencephalographic (EEG) methods offer promising alternatives due to their low cost, portability, and growing robustness. Here, we relied on EEG signals and a novel information-sharing method to study resting-state connectivity in patients with behavioral variant frontotemporal dementia (bvFTD) and controls. To evaluate the specificity of our results, we also tested Alzheimer’s disease (AD) patients. The classification power of the ensuing connectivity patterns was evaluated through a supervised classification algorithm (support vector machine). In addition, we compared the classification power yielded by (i) functional connectivity, (ii) relevant neuropsychological tests, and (iii) a combination of both. BvFTD patients exhibited a specific pattern of hypoconnectivity in mid-range frontotemporal links, which showed no alterations in AD patients. These functional connectivity alterations in bvFTD were replicated with a low-density EEG setting (20 electrodes). Moreover, while neuropsychological tests yielded acceptable discrimination between bvFTD and controls, the addition of connectivity results improved classification power. Finally, classification between bvFTD and AD patients was better when based on connectivity than on neuropsychological measures. Taken together, such findings underscore the relevance of EEG measures as potential biomarker signatures for clinical settings.

Abstract The current model of the Episodic Temporal Generalization task, where subjects have to judge whether pairs of auditory stimuli are equal in duration, predicts that results are scale-free and unaffected by the presentation order of the stimuli. To test these predictions, we conducted three experiments assessing sub- and supra-second standards and taking presentation order into account. Proportions were spaced linearly in Experiments 1 and 2 and logarithmically in Experiment 3. Critically, we found effects of duration range and presentation order with both spacing schemes. Our results constitute the first report of presentation order effects in the Episodic Temporal Generalization task and demonstrate that future studies should always consider duration range, number of trials and presentation order as crucial factors modulating performance.

Above and beyond the critical contributions of left perisylvian regions to language, the neural networks supporting pragmatic aspects of verbal communication in native and non-native languages (L1s and L2, respectively) have often been ascribed to the right hemisphere (RH). However, several reports have shown that left-hemisphere activity associated with pragmatic domains (e.g., prosody, indirect speech, figurative language) is comparable to or even greater than that observed in the RH, challenging the proposed putative role of the latter for relevant domains. Against this background, we report on an adult bilingual patient showing preservation of pragmatic verbal skills in both languages (L1: Spanish, L2: English) despite bilateral damage mainly focused on the RH. After two strokes, the patient sustained lesions in several regions previously implicated in pragmatic functions (vast portions of the right fronto-insulo-temporal cortices, the bilateral amygdalae and insular cortices, and the left putamen). Yet, comparison of linguistic and pragmatic skills with matched controls revealed spared performance on multiple relevant tasks in both her L1 and L2. Despite mild difficulties in some aspects of L2 prosody, she showed no deficits in comprehending metaphors and idioms, or understanding indirect speech acts in either language. Basic verbal skills were also preserved in both languages, including verbal auditory discrimination, repetition of words and pseudo-words, cognate processing, grammaticality judgments, equivalent recognition, and word and sentence translation. Taken together, the evidence shows that multiple functions of verbal communication can be widely spared despite extensive damage to the RH, and that claims for a putative relation between pragmatics and the RH may have been overemphasized in the monolingual and bilingual literature. We further discuss the case in light of previous reports of pragmatic and linguistic deficits following brain lesions and address its relation to cognitive compensation in bilingual patients.

Background: Adolescent offenders (AOs) are characterized by social-norm transgression and aggressive behaviors. Those traits have been associated with alterations in socio-cognitive processes, including facial emotion recognition. While this would suggest that AOs tend to interpret negative emotional cues as threatening information, most research has relied on context-free stimuli, thus failing to directly track integrative processes typical of everyday cognition.Methods: In this study, we assessed the impact of body language and surrounding context on facial emotion recognition in AOs and non-offenders (NOs). We recruited 35 AOs from a reform school for young male offenders and 30 NOs matched for age and sex with the former group. All participants completed a well-validated task aimed to determine how contextual cues (i.e., emotional body language and surrounding context) influence facial emotion recognition through the use of congruent and incongruent combinations of facial and bodily emotional information.Results: This study showed that AOs tend to overvalue bodily and contextual signals in emotion recognition, with poorer facial-emotion categorization and increased sensitivity to context information in incongruent face-body scenarios. This pattern was associated with executive dysfunctions and disruptive behaviors, as well as with gray matter (GM) of brain regions supporting body-face recognition [fusiform gyrus (FG)], emotion processing [cingulate cortex (CC), superior temporal gyrus (STG)], contextual integration (precuneus, STG), and motor resonance [cerebellum, supplementary motor area (SMA)].Discussion: Together, our results pave the way for a better understanding of the neurocognitive association between contextual emotion recognition, behavioral regulation, cognitive control, and externalized behaviors in AOs.

Processing of nouns and action verbs can be differentially compromised following lesions to posterior and anterior/motor brain regions, respectively. However, little is known about how these deficits progress in the course of neurodegeneration. To address this issue, we assessed productive lexical skills in a patient with posterior cortical atrophy (PCA) at two different stages of his pathology. On both occasions, he underwent a structural brain imaging protocol and completed semantic fluency tasks requiring retrieval of animals (nouns) and actions (verbs). Imaging results were compared with those of controls via voxel-based morphometry (VBM), whereas fluency performance was compared to age-matched norms through Crawford’s t-tests. In the first assessment, the patient exhibited atrophy of more posterior regions supporting multimodal semantics (medial temporal and lingual gyri), together with a selective deficit in noun fluency. Then, by the second assessment, the patient’s atrophy had progressed mainly toward fronto-motor regions (rolandic operculum, inferior and superior frontal gyri) and subcortical motor hubs (cerebellum, thalamus), and his fluency impairments had extended to action verbs. These results offer unprecedented evidence of the specificity of the pathways related to noun and action-verb impairments in the course of neurodegeneration, highlighting the latter’s critical dependence on damage to regions supporting motor functions, as opposed to multimodal semantic processes.

Recent embodied cognition research shows that access to action verbs in shallow-processing tasks becomes selectively compromised upon atrophy of the cerebellum, a critical motor region. Here we assessed whether cerebellar damage also disturbs explicit semantic processing of action pictures and its integration with ongoing motor responses. We evaluated a cognitively preserved 33-year-old man with severe dysplastic cerebellar gangliocytoma (Lhermitte-Duclos disease), encompassing most of the right cerebellum and the posterior part of the left cerebellum. The patient and eight healthy controls completed two semantic association tasks (involving pictures of objects and actions, respectively) that required motor responses. Accuracy results via Crawford’s modified t-tests revealed that the patient was selectively impaired in action association. Moreover, reaction-time analysis through Crawford’s Revised Standardized Difference Test showed that, while processing of action concepts involved slower manual responses in controls, no such effect was observed in the patient, suggesting that motor-semantic integration dynamics may be compromised following cerebellar damage. Notably, a Bayesian Test for a Deficit allowing for Covariates revealed that these patterns remained after covarying for executive performance, indicating that they were not secondary to extra-linguistic impairments. Taken together, our results extend incipient findings on the embodied functions of the cerebellum, offering unprecedented evidence of its crucial role in processing non-verbal action meanings and integrating them with concomitant movements. These findings illuminate the relatively unexplored semantic functions of this region while calling for extensions of motor cognition models.

La interocepción es un proceso complejo que abarca múltiples dimensiones, como la precisión, el aprendizaje y la conciencia. En este artículo, examinaremos si cada una de estas dimensiones se apoya en centros neurales especializados y distribuidos a lo largo de la extensa red interoceptiva. Para este fin, obtuvimos medidas de interocepción cardíaca en sujetos sanos y en pacientes que presentaban modelos de lesiones contrastivos de neurodegeneración y daño cerebral focal: la variante conductual de la demencia frontotemporal (vcDFT), la enfermedad de Alzheimer (EA) y lesiones fronto-insulares por accidente cerebrovascular. Se examinaron los correlatos neurales de las tres dimensiones a través de neuroimágenes estructurales y funcionales en estado de reposo y mediciones online del potencial evocado cardíaco (HEP, del inglés: heart evoked potential). Los tres grupos de pacientes presentaron déficits en la precisión interoceptiva, asociados con el daño insular, alteraciones de la conectividad y modulaciones anormales del HEP. El aprendizaje interoceptivo se vio afectado de manera diferencial en los pacientes con EA, lo que sugiere un rol clave de las redes de memoria en esta dimensión. Los resultados de la conciencia interoceptiva mostraron que los pacientes con vcDFT y EA sobreestimaron su desempeño. Este patrón se relacionó con anormalidades en las regiones anteriores cerebrales y en las redes involucradas en los procesos metacognitivos y ligadas a la pérdida de automonitoreo, bien descripta en la demencia. Nuestros hallazgos muestran cómo el daño en centros específicos de la amplia red fronto-temporo-insular compromete de manera diferenciada las dimensiones interoceptivas; y cómo las alteraciones estructurales afectan las conexiones funcionales más allá de esos centros críticos. Este es el primer estudio que presenta un modelo de lesión múltiple que revela las alteraciones del automonitoreo corporal y que ofrece nuevas perspectivas teóricas para profundizar en los fundamentos neuroanatómicos de las dimensiones interoceptivas.

Interoception, the monitoring of visceral signals, is often presumed to engage attentional mechanisms specifically devoted to inner bodily sensing. In fact, most standardized interoceptive tasks require directing attention to internal signals. However, most studies in the field have failed to compare attentional modulations between internally- and externally-driven processes, thus probing blind to the specificity of the former. Here we address this issue through a multidimensional approach combining behavioral measures, analyses of event-related potentials and functional connectivity via high-density electroencephalography, and intracranial recordings. In Study 1, 50 healthy volunteers performed a heartbeat detection task as we recorded modulations of the heartbeat-evoked potential (HEP) in three conditions: exteroception, basal interoception (also termed interoceptive accuracy), and post-feedback interoception (sometimes called interoceptive learning). In Study 2, to evaluate whether key interoceptive areas (posterior insula, inferior frontal gyrus, amygdala, and somatosensory cortex) were differentially modulated by externally- and internally-driven processes, we analyzed human intracranial recordings with depth electrodes in these regions. This unique technique provides a very fine grained spatio-temporal resolution compared to other techniques, such as EEG or fMRI. We found that both interoceptive conditions in Study 1 yielded greater HEP amplitudes than the exteroceptive one. In addition, connectivity analysis showed that post-feedback interoception, relative to basal interoception, involved enhanced long-distance connections linking frontal and posterior regions. Moreover, results from Study 2 showed a differentiation between oscillations during basal interoception (broadband: 35–110 Hz) and exteroception (1–35 Hz) in the insula, the amygdala, the somatosensory cortex, and the inferior frontal gyrus. In sum, this work provides convergent evidence for the specificity and dynamics of attentional mechanisms involved in interoception.

Recent works evince the critical role of visual short-term memory (STM) binding deficits as a clinical and preclinical marker of Alzheimer’s disease (AD). These studies suggest a potential role of posterior brain regions in both the neurocognitive deficits of Alzheimer’s patients and STM binding in general. Thereupon, we surmised that stimulation of the posterior parietal cortex (PPC) might be a successful approach to tackle working memory deficits in this condition, especially at early stages. To date, no causal evidence exists of the role of the parietal cortex in STM binding. A unique approach to assess this issue is afforded by single-subject direct intracranial electrical stimulation of specific brain regions during a relevant cognitive task. Electrical stimulation has been used both for clinical purposes and to causally probe brain mechanisms. Previous evidence of electrical currents spreading through white matter along well defined functional circuits indicates that visual working memory mechanisms are subserved by a specific widely distributed network. Here, we stimulated the parietal cortex of a subject with intracranial electrodes as he performed the visual STM task. We compared the ensuing results to those from a non-stimulated condition and to the performance of a matched control group. In brief, direct stimulation of the parietal cortex induced a selective improvement in STM. These results, together with previous studies, provide very preliminary but promising ground to examine behavioral changes upon parietal stimulation in AD. We discuss our results regarding: (a) the usefulness of the task to target prodromal stages of AD; (b) the role of a posterior network in STM binding and in AD; and (c) the potential opportunity to improve STM binding through brain stimulation.

A más de cincuenta años de su incepción, la Gramática Generativa (GG) se ha erigido como la teoría hegemónica en la neurolingüística. Incontables artículos científicos, libros completos e incluso departamentos universitarios dan por sentada la plausibilidad de la GG como modelo biológico del lenguaje humano y consagran sus esfuerzos investigativos a precisar los sustratos neurales de los constructos generativistas. Sin embargo, hay buenos motivos para dudar de la plausibilidad neurológica de esta teoría. La GG constituye una teoría analítica que caracteriza las propiedades estructurales de diversos constructos gramaticales sin preocuparse por indagar en cuestiones biológicas. Al mismo tiempo, y de manera apriorística, asume que tales descripciones abstractas representan la realidad neurológica del sistema lingüístico. Con todo, al contraponerse las tesis principales del generativismo con evidencia psicolingüística, neurocientífica y evolutiva, surgen varias incompatibilidades teóricas. En este sentido, el objetivo del presente trabajo es sintetizar parte de la evidencia multidisciplinar que pone en tela de juicio la plausibilidad neurológica de la GG en lo referente a (i) la concepción de las entidades lingüísticas, (ii) el sintactocentrismo y la tesis de la no redundancia, y (iii) la supuesta evolución de la Gramática Universal. A modo de cierre, se sugerirá que el generativismo no constituye la teoría lingüística más provechosa para el progreso de la neurolingüística.

El deterioro cognitivo durante el envejecimiento normal o patológico puede retrasarse mediante experiencias que fomentan la reserva cognitiva. En este sentido, algunos estudios indican que el bilingüismo retrasaría los síntomas de la enfermedad de Alzheimer. Sin embargo, la evidencia se basa en diseños retrospectivos que arrojan resultados contradictorios. Este trabajo analiza dichos resultados, identifica las principales variables detrás de sus discrepancias y propone alternativas metodológicas. Primero, caracterizamos los posibles factores de confusión, a saber: criterios para definir el bilingüismo, diferencias en los diseños muestrales, instrumentos empleados para estudiar las habilidades cognitivas y variables que modulan el desempeño cognitivo. Luego proponemos que estas limitaciones se podrían evitar mediante diseños experimentales y el uso de instrumentos adecuados para controlar eficazmente dichas variables. Además, sugerimos incorporar tareas que ya han demostrado patrones predecibles de desempeño contrastivo entre individuos bilingües y monolingües (desventajas bilingües en el vocabulario, efectos nulos en ciertos componentes de la memoria de trabajo y ventajas en el control inhibitorio), y otras que podrían sumar datos muy valiosos (como las tareas de interferencia proactiva). Estas consideraciones pueden arrojar luz no sólo sobre la relación entre bilingüismo y reserva cognitiva, sino también sobre mecanismos más generales de compensación cognitiva.

The decline of cognitive skills throughout healthy or pathological aging can be slowed down by experiences which foster cognitive reserve (CR). Recently, some studies on Alzheimer’s disease have suggested that CR may be enhanced by life-long bilingualism. However, the evidence is inconsistent and based on retrospective approaches featuring several methodological weaknesses. Some studies demonstrated at least four years of delay in dementia symptoms, while others did not find such an effect. Moreover, various methodological aspects vary from study to study. The present paper addresses contradictory findings, identifies possible lurking variables, and outlines methodological alternatives thereof. First, we characterize possible confounding factors that may have influenced extant results. Our focus is on the criteria to establish bilingualism, differences in sample design, the instruments used to examine cognitive skills, and the role of variables known to modulate life-long cognition. Second, we propose that these limitations could be largely circumvented through experimental approaches. Proficiency in the non-native language can be successfully assessed by combining subjective and objective measures; confounding variables which have been distinctively associated with certain bilingual groups (e.g., alcoholism, sleep disorders) can be targeted through relevant instruments; and cognitive status might be better tapped via robust cognitive screenings and executive batteries. Moreover, future research should incorporate tasks yielding predictable patterns of contrastive performance between bilinguals and monolinguals. Crucially, these include instruments which reveal bilingual disadvantages in vocabulary, null effects in working memory, and advantages in inhibitory control and other executive functions. Finally, paradigms tapping proactive interference (which assess the disruptive effect of long-term memory on newly learned information) could also offer useful data, since this phenomenon seems to be better managed by bilinguals and it becomes conspicuous in early stages of dementia. Such considerations may shed light not just on the relationship between bilingualism and CR, but also on more general mechanisms of cognitive compensation.

Studies on bilingual word reading and translation have examined the effects of lexical variables (e.g., concreteness, cognate status) by comparing groups of non-translators with varying levels of L2 proficiency. However, little attention has been paid to another relevant factor: translation expertise (TI). To explore this issue, we administered word reading and translation tasks to two groups of non-translators possessing different levels of informal TI (Experiment 1), and to three groups of bilinguals possessing different levels of translation training (Experiment 2). Reaction-time recordings showed that in all groups reading was faster than translation and unaffected by concreteness and cognate effects. Conversely, in both experiments, all groups translated concrete and cognate words faster than abstract and non-cognate words, respectively. Notably, an advantage of backward over forward translation was observed only for low-proficiency non-translators (in Experiment 1). Also, in Experiment 2, the modifications induced by translation expertise were more marked in the early than in the late stages of training and practice. The results suggest that TI contributes to modulating inter-equivalent connections in bilingual memory.

Social cognitive neuroscience (SCN) seeks to understand the brain mechanisms through which we comprehend others’ emotions and intentions in order to react accordingly. For decades, SCN has explored relevant domains by exposing individual participants to predesigned stimuli and asking them to judge their social (e.g., emotional) content. Subjects are thus reduced to detached observers of situations they play no active role in. However, the core of our social experience is construed through real-time interactions requiring the active negotiation of information with other people. To gain more relevant insights into the workings of the social brain, the incipient field of two-person neuroscience (2PN) advocates the study of brain-to-brain coupling through multi-participant experiments. In this paper, we argue that the study of online language-based communication constitutes a cornerstone of 2PN. First, we review preliminary evidence illustrating how verbal interaction may shed light on the social brain. Second, we advance methodological recommendations to design experiments within language-based 2PN. Finally, we formulate outstanding questions for future research.