Brain-computer interfaces and human factors: the role of language and cultural differences—Still a missing gap?

The paper addresses the research question of how language and cultural differences, as human factors, influence BCI performance and should be incorporated into BCI research and design. BCIs have expanded from clinical use to broader applications, and prior work shows user traits (motivation, mood, cognition) and states affect BCI efficiency and literacy. However, the user’s language abilities and cultural background remain understudied despite their relevance for understanding instructions, using language-based paradigms (e.g., P300 spellers), and shaping perception, cognition, and emotion. The article proposes that systematic consideration of language (including embodied grounding) and cultural differences can improve assessment, training, and usability, ultimately advancing BCIs from lab to real-world contexts.

The perspective synthesizes evidence that human factors modulate BCI outcomes, highlighting gaps regarding language and culture. Prior BCI work has examined satisfaction, technology experience, cognitive load, personality, motivation, mood, attention, memory, and imagery, particularly in P300 and SMR BCIs. Language-related studies show EEG/ERP signatures (e.g., N400) can index implicit language processing in patients with disorders of consciousness (DOC) and support command-following paradigms. Semantic classical conditioning and imagery paradigms have been used to enable communication while minimizing higher-order language demands. Reviews indicate residual implicit language abilities in a substantial portion of DOC patients and variable success in command-following. Emerging work demonstrates that BCI-based training can improve language functions (e.g., aphasia). Embodied language research shows action and emotion words engage motor and affective systems and modulate EEG rhythms (mu/beta), suggesting potential for augmenting SMR and RSVP paradigms. In multilingual contexts, traditional P300 spellers have largely focused on single languages; recent approaches incorporate multilingual language models. Cultural neuroscience and HCI literature demonstrate that culture shapes perception, spatial reference frames, self-referential processing, emotion communication, personality, and technology beliefs, all relevant to BCI design and performance.

This is a perspective/hypothesis paper. It conducts a narrative synthesis of prior empirical findings from BCI, cognitive neuroscience, neurolinguistics, cultural psychology/neuroscience, and HCI, and proposes hypotheses and a framework for language- and culture-sensitive BCIs. No new experimental data were collected; instead, the author draws on published studies, reviews, and example paradigms to identify research gaps and actionable directions (e.g., language assessment batteries, embodied language tasks, multilingual models, and culture-aware interface design).

- Language abilities are critical yet understudied human factors in BCIs. EEG/ERP markers (especially N400) can detect implicit language processing and support assessments in DOC and other vulnerable users. - Reported ranges: residual implicit language abilities are present in approximately 33–78% of DOC patients; command-following via BCIs is possible in about 20–50% of DOC patients; semantic classical conditioning paradigms achieved about 65–68.8% accuracy in healthy users and have shown feasibility in patient groups. - BCI-based language training can improve linguistic processing and ERP profiles in clinical populations (e.g., aphasia), with gains beyond spontaneous recovery and transfer beyond trained tasks. - Embodied language (action and emotion words) robustly engages sensorimotor and affective systems, modulating mu/beta rhythms and ERPs, offering unobtrusive alternatives to enhance SMR BCIs and RSVP spellers and to communicate motivational/emotional preferences. - Multilingualism and bilingual brain organization can influence cognitive functions and neural patterns relevant to BCI (attention, imagery, semantic conditioning, fluency). Incorporating multilingual language models extends P300 speller access and accuracy across language backgrounds. - Culture shapes perception, spatial reference frames, self-referential processing, emotion expression, personality, and attitudes toward technology, all of which can modulate BCI usability and performance. Cross-cultural HCI design guidelines can inform culture-sensitive BCI engineering. - Advances in NLP and AI, along with EEG-based decoding, support movement from single-word decoding to continuous, cross-language speech/language decoding for real-world BCI communication.

Addressing the research question, the synthesis shows that both language and culture systematically modulate the cognitive, affective, and neural processes that BCIs rely on. Evidence from ERP/N400 paradigms supports the feasibility of assessing implicit language abilities and enabling command-following in patients with limited overt responsiveness. Training studies suggest BCIs can remediate language deficits and potentially transfer benefits to other cognitive functions. Embodied language offers a practical route to improve classification and user engagement without complex motor control. Multilingual and cross-cultural considerations are vital for equitable access and performance, as language background and cultural context influence perception, self-relevance, motivation, and technology acceptance. Integrating standardized language assessments, multilingual models, and cross-cultural design principles into BCI pipelines can reduce BCI illiteracy/inefficiency, enhance usability, and better align with diverse users’ needs.

The paper advances a framework for language- and culture-sensitive BCIs, arguing these factors should be fundamental in user-centered BCI research and engineering. It proposes implementing EEG-based tools to assess implicit/explicit language abilities, leveraging embodied language for improved control and preference communication, integrating multilingual language models and AI-driven decoding, and adopting cross-cultural HCI guidelines for interface design. Future research should: (1) develop standardized, multimodal BCI language assessment and training batteries spanning phonology, semantics, syntax, imagery, and command-following; (2) validate embodied language tasks across BCI types; (3) test multilingual models across diverse linguistic profiles; (4) systematically examine cultural influences on perception, self-relevance, agency, motivation, and personality in BCI contexts; and (5) translate these insights to real-world applications across clinical, educational, and everyday settings.

As a perspective/hypothesis article, no new empirical data are presented. Reported effects and ranges derive from heterogeneous prior studies with varying methodologies, populations, and outcome measures, which may limit generalizability. Proposed frameworks (e.g., standardized language assessments, embodied language paradigms, culture-sensitive design) require prospective validation across diverse user groups, languages, and cultural contexts. Potential confounds (e.g., severity of impairment, sensory limitations, fatigue, technology familiarity) need careful control in future studies.