Frontiers in Human Neuroscience

Reading skills modulate the audiovisual congruency effect in orthographic processing in children: an ERP study

2026-04-02

Christina G. Lutz, Seline Coraj, Aline Kressebuch, Sarah V. Di Pietro, Iliana I. Karipidis, Silvia Brem

IntroductionIntegration of written and spoken information is crucial for reading acquisition. Correspondingly, individuals with reading difficulties exhibit deficiencies in audiovisual (AV) congruency processing. The timeline of AV congruency processing in children and the influence of reading skills on this process, however, remain largely unclear. Therefore, we examined when and how reading skills modulate AV congruency processing for orthographic (words, pseudowords) and non-orthographic conditions (objects).MethodsEighty-two native German-speaking 2nd and 3rd graders completed an explicit task involving the matching of AV congruent and incongruent orthographic and non-orthographic stimuli, while EEG was recorded.ResultsBehaviorally, poorer reading skills were associated with lower performance and slower responses for orthographic conditions. Neurally, topographic EEG analyses revealed congruency effects emerging after 300 ms for orthographic conditions and around 200 ms for objects. ERP analyses showed that reading skills modulated the N400 incongruency effect more strongly for orthographic than non-orthographic stimuli.DiscussionIn summary, poorer reading skills were associated with slower AV matching and a weaker N400 incongruency effect for orthographic conditions. These findings suggest that while reading skills might not broadly affect AV congruency processing, they critically impact the AV congruency processing of orthographic information, potentially hindering struggling readers’ ability to effectively use preceding auditory information to process print.

Editorial: Genetics and mechanisms of neurodevelopmental disorders

2026-04-02

Anjana Munshi, Ajay Kumar, Santasree Banerjee

Executive dysfunction as a transdiagnostic mechanism of psychopathology: a neurocognitive framework for diagnosis and intervention

2026-04-02

Sandra Carvalho

Psychiatric disorders are typically classified using categorical diagnostic systems based on symptom clusters. However, these frameworks often fail to capture the cognitive and neurobiological mechanisms that transcend diagnostic boundaries and influence everyday functioning. Executive dysfunction, encompassing impairments in inhibitory control, working memory, cognitive flexibility, planning, and emotion regulation, was historically linked to focal damage in prefrontal brain regions. Converging evidence from neuropsychology, cognitive neuroscience, genetics, and clinical research indicates that executive dysfunction is prevalent across multiple psychiatric conditions and closely linked to functional impairment. This theory-driven article proposes that executive dysfunction represents a transdiagnostic dimension of psychopathology reflecting a shared neurocognitive vulnerability. Disruptions in both “cool” executive processes (e.g., cognitive control and working memory) and “hot” executive processes (e.g., emotion regulation and motivational control) may constitute a common pathway through which diverse psychiatric disorders impair adaptive functioning. Executive dysfunction is further conceptualized as an intermediate phenotype linking genetic liability, distributed neural circuit disruption, and everyday behavioral regulation. This perspective supports a shift toward transdiagnostic, mechanism-based mental health interventions that prioritize executive functioning as a central target for improving real-world functioning and long-term recovery.

Editorial: Cognitive enhancement by brain stimulation techniques

2026-04-01

Elias Ebrahimzadeh, Hamid Soltanian-Zadeh

Evidence for temporal-coherence-based segregation of complex auditory scenes in the newborn human brain

2026-04-01

Silvia Polver, Petra Kovács, Gábor P. Háden, István Sziller, István Winkler, Brigitta Tóth

Detecting a target sound within a mixture of sounds (referred to as auditory stream segregation) is crucial for perception in natural environments, a skill humans and animals excel at. This study investigates the role of temporal coherence in auditory stream segregation in human newborns using high-density EEG recordings. Sleeping newborns were exposed to temporally coherent auditory tone sequences embedded in random background tones, and their event-related responses were analyzed. The results indicate that newborns can segregate auditory streams based on temporal coherence, suggesting that this stream segregation is driven by automatic mechanisms from birth, as evidenced by brain responses resembling the object-related negativity (ORN) event-related potential (ERP) component. However, discriminating among different signal-to-noise ratios requires further fine-tuning, as evidenced by delayed latencies in neonates compared to adults. These findings indicate that temporal coherence aids in detecting and orienting toward salient stimuli, thereby laying the foundation for the development of abilities such as selective attention and speech perception.

Commentary: A cross-continental comparative analysis of the neurological manifestations of Long COVID

2026-03-31

Luis Mesquita da Fonseca

Electroencephalogram-based multimodal attention level classification using deep learning techniques

2026-03-27

Yi Zhong, Zhenyu Wang, Xi Zhao, Tianheng Xu, Ting Zhou, Honglin Hu

This study aims to develop a novel attention level prediction method using a multimodal brain-computer interface system that integrates electroencephalogram (EEG), electrocardiogram (ECG), and electrooculogram (EOG) signals to enhance prediction accuracy and robustness. We propose the Multi-Feature Enhanced Attention Network (MEAN), which leverages the complementary strengths of these signals: EEG provides insights into brain electrical activity, ECG captures heart rate variability to reflect emotional and cognitive states, and EOG records eye movements for contextual attention level information. The model is designed to address the limitations of single-modality signals, such as noise susceptibility and limited information range. Experimental results demonstrate that MEAN achieves an average accuracy of 0.9524, outperforming traditional models. The model exhibits superior adaptability, particularly in handling EEG and multimodal data, and shows enhanced predictive performance compared to existing approaches. In conclusion, the proposed MEAN model effectively integrates multimodal physiological signals to improve attention level prediction, offering a robust and accurate solution for applications requiring attention level monitoring. This research provides a foundation for advancing applications in education, work efficiency assessment, and cognitive enhancement technologies, highlighting the potential of multimodal approaches for understanding and predicting attention states.

Individualized electrode subset improves the calibration accuracy of an EEG P300-design brain-computer interface for people with severe cerebral palsy

2026-03-26

Si Long Jenny Tou, Seth A. Warschausky, Petra Karlsson, Jane E. Huggins

IntroductionThis study examined the effect of individualized electroencephalogram (EEG) electrode location selection for non-invasive P300-design brain-computer interfaces (BCIs) in people with varying severity of cerebral palsy (CP) in a post-hoc offline analysis.MethodsA forward selection algorithm was used to select the best performing eight electrodes (of an available 32) to construct an individualized electrode subset for each participant. Custom electrode subset size was chosen to be 8 because BCI accuracy of the individualized subset was compared to accuracy of a widely used default subset.ResultsAcross 51 participants, individualized subsets improved calibration accuracy only for the severe CP cohort (mean +28.6% absolute; 95% CI [13.4%, 46.1%]; p < 0.0001). No group-level benefit was detected for mild CP or typically developing controls, although several individuals in these groups improved (2/17 mild CP; 1/10 controls). In the subset with held-out testing data (mild CP and controls), calibration gains did not translate to higher testing accuracy; among controls, the subset effect was reduced on testing (−9.6%, 95% CI [−13.3%, −5.8%], p < 0.0001), with no evidence of change for mild CP. Participants with severe CP typically required larger subsets to approach asymptotic accuracy, whereas ≤ 8 electrodes were sufficient for most others.DiscussionThe findings suggested that electrode selection can accommodate atypical neuroanatomy in people with severe CP, while the default electrode locations are sufficient for people with milder impairments from CP and typically developing individuals.

Processing ergativity in compound light verb constructions: electrophysiological evidence from Hindi

2026-03-25

Anna Merin Mathew, R. Muralikrishnan, Mahima Gulati, Shikha Bhattamishra, Kamal Kumar Choudhary

IntroductionErgativity marks subject arguments as agents of a transitive event and thereby signals verbal transitivity and influences language comprehension.MethodWe report here on an event-related brain potentials (ERP) study in Hindi, in which we investigated this interconnection to ascertain whether the ergative case as a processing cue and its ERP correlates can be generalized across and within ergative languages. The case marking on the subject argument (ergative or nominative case) in our study either matched or mismatched with the transitivity of the light verb (transitive or intransitive) in compound light verb constructions.ResultsErgative case violations due to an intransitive light verb evoked an N400 effect, whereas nominative case violations due to a transitive light verb elicited a P600 effect.DiscussionThe results reveal neurophysiological differences in the processing of ergative and nominative case alignment modulated by the transitivity of the light verbs. The findings highlight the need for cross-linguistic research to aim beyond universality and elucidate the mechanism underlying the processing of language-specific structural variations.

The clock drawing test as a screening tool for detecting cognitive decline: an analysis in adults and elderly people from Natal (RN)

2026-03-25

Letícia Ellen Cunha Pereira, Felipe Nalon Castro, Katie Moraes de Almondes

IntroductionThe Clock Drawing Test (CDT) is widely used as a screening instrument for cognitive decline due to its simplicity and rapid administration. Despite its widespread clinical use, evidence regarding its diagnostic performance in the Brazilian Northeast region remains scarce.MethodsThis study examined CDT performance in a clinical sample of 113 adults and older adults assessed at a neuropsychology service in Northeastern Brazil, focusing on CDT ability to identify cognitive decline and the effects of age, educational level, and clinical diagnoses. The study tested the following hypotheses: (1) there is a significant association between age and CDT scores; (2) there are significant differences in CDT scores across different educational levels; (3) there are significant differences in CDT scores across different clinical conditions, indicating potential for differential diagnosis; and (4) the test would demonstrate high sensitivity, specificity, and accuracy in the overall sample, as well as high sensitivity in detecting each diagnostic condition. Using Shulman’s scoring method, descriptive analyses, Spearman’s correlation, Kruskal–Wallis tests and metrics of sensitivity, specificity, and accuracy were conducted.ResultsThe sample had a mean age of 65.19 years and was predominantly characterized by low educational attainment. A negative, albeit weak, correlation was observed between age and CDT scores, as well as significant differences across educational levels. Diagnostic group comparisons also revealed significant differences, most notably between cognitively unimpaired individuals and patients diagnosed with Major Neurocognitive Disorder due to Alzheimer’s disease. Although the CDT demonstrated adequate specificity, its overall sensitivity and accuracy were low. Sensitivity was high for Major Neurocognitive Disorder Due to Alzheimer’s Disease, moderate for Major Neurocognitive Disorder due to Non-Alzheimer’s Disease (Major Vascular Neurocognitive Disorder, Parkinson’s Disease, Mixed Dementia, Wernicke–Korsakoff syndrome and Major Frontotemporal Neurocognitive Disorder) and low for Mild Neurocognitive Disorder.DiscussionThese findings demonstrate that Shulman’s method of CDT is not suitable for assessing cognitive decline in the illiterate and low-education population and raise important concerns regarding its standalone clinical utility, especially in specific neurological conditions. The present study underscores the need for future research employing alternative scoring methods and more representative samples to refine the applicability and diagnostic value of the CDT in clinical practice.