journal article·2025-11-08Open access

ERP Signatures of Stimulus Choice in Gaze-Independent BCI Communication

Alice Mado Proverbio, Yldjana Dishi

Applied Sciences· Volume 15· Issue 22

Abstract

This study aimed to identify electrophysiological markers (event-related potentials, ERPs) of intentional, need-related mental activity under controlled gaze fixation, with potential applications in brain–computer interface (BCI) development for individuals with severe motor impairments. Methods: Using stimuli from the PAIN Pictionary—a pictogram database for non-verbal communication in locked-in syndrome (LIS) contexts—neural responses were recorded via high-density EEG in 30 neurologically healthy adults (25 included after artifact-based exclusion). Participants viewed randomized sequences of pictograms representing ten fundamental need categories (e.g., “I am cold”, “I’m in pain”), with one category designated as the target per sequence. Each pictogram was followed by a visual cue prompting a button press: during training, participants executed the press; during the main task, they performed right-hand motor imagery while maintaining central fixation. Results: ERP analyses revealed a robust P300 response (450–650 ms; p < 0.0002) over centro-parietal regions for target cues, reflecting enhanced attentional allocation and stimulus choice. An early Contingent Negative Variation (CNV, 450–750 ms; p = 0.008) over fronto-lateral sites indicated anticipatory attention and motor preparation, while a left-lateralized late CNV (2250–2750 ms; p = 0.035) appeared to embody the preparation of a finalized motor plan for the forthcoming right-hand imagined response. A centro-parietal P600 component (600–800 ms; p = 0.044) emerged during response monitoring, reflecting evaluative and decisional processes. SwLORETA source analyses localized activity within a distributed network spanning prefrontal, premotor, motor, parietal, and limbic areas. Conclusions: These findings demonstrate that motor imagery alone can modulate pattern-onset ERP components without overt movement or gaze shifts, supporting the translational potential of decoding need-related intentions for thought-driven communication systems in individuals with profound motor impairments.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: EEG and Brain-Computer Interfaces · Traumatic Brain Injury Research · Free Will and Agency

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Cognitive Electrophysiology Laboratory, Department of Psychology, University of Milano-Bicocca, Piazza dell’Ateneo Nuovo 1, 20162 Milan, Italy

Master’s Program in “Human-Centered Artificial Intelligence” HCAI, Department of Philosophy, University of Milan, 20122 Milan, Italy

Funding

Italian Ministry of University and Research

References (51)

Show source-provided references
1. Herbert, C. (2024). Analyzing and computing humans by means of the brain using Brain-Computer Interfaces. Front. Hum. Neurosci., 17.10.3389/fnhum.2023.1286895 ↗
2. Arns, M., Sokhadze, E., and Birbaumer, N. (2025). Neurofeedback and Brain-Machine Interfaces: Where are We Now?. Applied Psychophysiology and Biofeedback, Springer.10.1007/s10484-025-09735-9 ↗
3. Neuropsychological and neurophysiological aspects of brain-computer-interface (BCI) control in paralysis10.1113/JP278775 ↗
4. Brain-computer interfaces for communication and control10.1016/S1388-2457(02)00057-3 ↗
5. Talking off the top of your head: Toward a mental prosthesis utilizing event-related brain potentials10.1016/0013-4694(88)90149-6 ↗
6. A novel P300-based brain-computer interface stimulus presentation paradigm: Moving beyond rows and columns10.1016/j.clinph.2010.01.030 ↗
7. (C)overt attention and visual speller design in an ERP-based brain-computer interface10.1186/1744-9081-6-28 ↗
8. Gaze-independent BCI-spelling using rapid serial visual presentation (RSVP)10.1016/j.clinph.2012.12.050 ↗
9. Emotional faces boost up steady-state visual responses for brain-computer interface10.1097/WNR.0b013e32834308b0 ↗
10. Kuś, R., Duszyk, A., Milanowski, P., Łabęcki, M., Bierzyńska, M., Radzikowska, Z., Michalska, M., Zygierewicz, J., Suffczyński, P., and Durka, P.J. (2013). On the quantification of SSVEP frequency responses in human EEG in realistic BCI conditions. PLoS ONE., 8.10.1371/journal.pone.0077536 ↗
11. SSVEP-based BCI using ultra-low-frequency and high-frequency peripheral flickers10.1088/1741-2552/addf82 ↗
12. Siribunyaphat, N., Tohkhwan, N., and Punsawad, Y. (2025). Investigation of Personalized Visual Stimuli via Checkerboard Patterns Using Flickering Circles for SSVEP-Based BCI System. Sensors, 25.10.3390/s25154623 ↗
13. Spatial Attention Effects on P300 BCI Performance: ERP and Eye-Tracking Study10.3103/S009639252360028X ↗
14. Does the ‘P300′ speller depend on eye gaze?10.1088/1741-2560/7/5/056013 ↗
15. Single-Trial Stimuli Classification from Detected P300 for Augmented Brain-Computer Interface: A Deep Learning Approach
16. Machine learning classification of motivational states: Insights from EEG analysis of perception and imagery10.1016/j.eswa.2025.127076 ↗
17. Neural signatures of imaginary motivational states: Desire for music, movement and social play10.1007/s10548-024-01047-1 ↗
18. Proverbio, A.M., and Pischedda, F. (2023). Measuring brain potentials of imagination linked to physiological needs and motivational states. Front. Hum. Neurosci., 17.10.3389/fnhum.2023.1146789 ↗
19. MIRACLE: MInd ReAding CLassification Engine10.1109/TNSRE.2023.3301507 ↗
20. Classify four imagined objects with EEG signals10.1007/s12065-021-00577-y ↗
21. The Neural Dynamics of Facial Identity Processing: Insights from EEG-Based Pattern Analysis and Image Reconstruction10.1523/ENEURO.0358-17.2018 ↗
22. Reading into the mind’s eye: Boosting automatic visual recognition with EEG signals10.1016/j.neucom.2019.12.076 ↗
23. Toward enhanced P300 speller performance10.1016/j.jneumeth.2007.07.017 ↗
24. Workload. measurement in a communication application operated through a P300-based brain–computer interface10.1088/1741-2560/8/2/025028 ↗
25. Spüler, M. (2015, January 25–29). A Brain-Computer Interface (BCI) system to use arbitrary Windows applications by directly controlling mouse and keyboard. Proceedings of the 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Milan, Italy.10.1109/EMBC.2015.7318554 ↗
26. Evidence for distinct beta resonance frequencies in human EEG related to specific sensorimotor cortical areas10.1016/S1388-2457(01)00661-7 ↗
27. Brain activity during a lower limb functional task in a real and virtual environment: A comparative study10.3233/NRE-161426 ↗
28. Gaze independent brain-computer speller with covert visual search tasks10.1016/j.clinph.2010.10.049 ↗
29. Proverbio, A.M., and Pischedda, F. (2023). Validation of a Pictionary-based communication tool for assessing individual needs and motivational states in locked-in patients: P.A.I.N. set. Front. Cogn. Section Percept.10.3389/fcogn.2023.1112877 ↗
30. The five percent electrode system for high-resolution EEG and ERP measurements10.1016/S1388-2457(00)00527-7 ↗
31. Standardized low-resolution brain electromagnetic tomography (sLORETA): Technical details
32. swLORETA: A novel approach to robust source localization and synchronization tomography10.1088/0031-9155/52/7/002 ↗
33. ASA--Advanced Source Analysis of continuous and event-related EEG/MEG signals10.1023/B:BRAT.0000032867.41555.d0 ↗
34. Evidence for premotor cortex activity during dynamic visuospatial imagery from single-trial functional magnetic resonance imaging and event-related slow cortical potentials10.1006/nimg.2001.0850 ↗
35. Brain-computer communication and slow cortical potentials10.1109/TBME.2004.827067 ↗
36. The thought-translation device (TTD): Neurobehavioral mechanisms and clinical outcome10.1109/TNSRE.2003.814439 ↗
37. Temporal downscaling of movement reveals duration-dependent modulation of motor preparatory potentials in humans10.1016/j.neuroscience.2025.08.004 ↗
38. Cortical activation associated with motor preparation can be used to predict the freely chosen effector of an upcoming movement and reflects response time: An fMRI decoding study10.1016/j.neuroimage.2018.08.060 ↗
39. The effect of response type (motor output versus mental counting) on the intracerebral distribution of the slow cortical potentials in an externally cued (CNV) paradigm10.1016/j.brainresbull.2006.10.012 ↗
40. Current source density analysis of CNV during temporal gap paradigm10.1023/A:1007816201345 ↗
41. Preparatory visuo-motor cortical network of the contingent negative variation estimated by current density10.1016/S1053-8119(03)00295-7 ↗
42. The role of inhibition from the left dorsal premotor cortex in right-sided focal hand dystonia10.1016/j.brs.2009.03.004 ↗
43. The left parietal and premotor cortices: Motor attention and selection10.1016/j.neuroimage.2003.09.011 ↗
44. Forstmann, B.U., Wolfensteller, U., Derrfuss, J., Neumann, J., Brass, M., Ridderinkhof, K.R., and von Cramon, D.Y. (2008). When the choice is ours: Context and agency modulate the neural bases of decision-making. PLoS ONE, 3.10.1371/journal.pone.0001899 ↗
45. Nonlinear responses within the medial prefrontal cortex reveal when specific implicit information influences economic decision making10.1111/j.1552-6569.2005.tb00303.x ↗
46. Involvement of the primary motor cortex in controlling movements executed with the ipsilateral hand differs between left- and right-handers10.1162/jocn_a_00018 ↗
47. Cerebellar Modulation of Cortically Evoked Complex Movements in Rats
48. Brain regions with mirror properties: A meta-analysis of 125 human fMRI studies10.1016/j.neubiorev.2011.07.004 ↗
49. Multiple channel detection of steady-state visual evoked potentials for brain-computer interfaces10.1109/TBME.2006.889160 ↗
50. Volosyak, H., Cecotti, H., Valbuena, D., and Gräser, A. (2009, January 23–26). Evaluation of the Bremen SSVEP based BCI in real world conditions. Proceedings of the 2009 IEEE International Conference on Rehabilitation Robotics, Kyoto, Japan.10.1109/ICORR.2009.5209543 ↗
51. 30+ years of P300 brain-computer interfaces10.1111/psyp.13569 ↗