BCI Applications to Creativity: Review and Future Directions, from little-c to C2
Abstract
:1. Introduction
1.1. Brain–Computer Interface
1.2. Creativity: Some Definitions
1.3. The Role of BCI in the Study of Creativity
2. Materials and Methods
2.1. Stage 1: Identifying the Research Question
2.2. Stage 2: Identifying Relevant Studies
2.3. Stage 3: Study Selection
2.4. Stage 4: Charting the Data
2.5. Stage 5: Collating, Summarizing, and Reporting the Results
3. Results
3.1. Characteristics of the Studies
3.2. Clinical Applications
3.3. Art Experience in Real-World Settings
3.4. Content Creation
3.4.1. Proto-Creativity
3.4.2. Creative Artifacts Production
3.5. Participants’ Engagement
4. Discussion, Conclusions, and Future Directions
4.1. Highlights from the Scoping Review
4.2. Future Directions and Perspectives
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Authors | Year | Country | Sample | Creativity | Assessment | BCI | Main Results |
---|---|---|---|---|---|---|---|
Clinical applications | |||||||
Levican et al. [19] | 2018 | Chile | N = 1 | Music | Music composition | Enobio-8 EEG | - |
Münßinger et al. [20] | 2010 | Germany | N = 3 ALS patients N = 10 healthy participants | Painting | Brain Painting | 16-channel USBamp | Of patients, 2/3 reached above 89% accuracy. |
Miranda [21] | 2006 | UK | - | Music | Music composition | EEG (geodesic net, 19 ch) | - |
Art experience in real-world settings | |||||||
Pedersen et al. [22] | 2015 | Canada | - | Painting | Selection of Klee’s art | Muse | - |
Herrera-Arcos et al. [23] | 2017 | Mexico and USA | N = 25 | Painting appreciation | Favorite piece | Muse | Suppression of beta while viewing favorite piece over frontal sites. |
BCI for creative content creation | |||||||
Proto-creativity | |||||||
Todd et al. [24] | 2012 | UK | N = 8 | Proto-painting | Painting (free and copy) | EEG with BCI2000 software suite | Task 3 (free drawing) was perceived as the one which allowed for a greater sense of control and was the most enjoyable. Task 2 (copy) was the preferred task. |
Tang et al. [25] | 2022 | China | N = 20 | Proto-painting | Painting (free and copy) | EEG BioSemi (12 ch) | Hybrid stimulus interface (P300 + SSVEP) was more accurate than P300 alone (88.92%). |
Hamadicharef et al. [26] | 2010 | Singapore | - | Proto-music | Music composition | EEG (15 ch) | - |
Pinegger et al. [27] | 2015 | Austria | N = 5 | Proto-music | Music composition | Mobita EEG system (8 ch) | Three participants reached accuracies above 77% and could produce a given melody. |
Vamvakousis and Ramirez [28] | 2014 | Spain | N = 4 | Proto-music | Arpeggio shift | Emotiv Epoc (14 ch) | Selection accuracy from 83 to 100%. |
Creative outcomes | |||||||
Riccio et al. [29] | 2022 | Spain, Norway, and Italy | - | Painting | Emotion categorization | EEG database | Happiness, fear, and sadness had the highest sensitivity (>58%) while anger just reached 22% (with a higher sensitivity). |
Kim H.-J. and Kim S.-Y. [30] | 2015 | Korea | - | Painting | Self portrait | Neurosky Mindwave | - |
Folgieri and Zichella [31] | 2012 | Italy | Task 1: N = 7 Task 2: N = 4 | Music | Music composition | Neurosky Mindwave | After a few minutes of training, participants were able to reproduce the notes by thinking of them, with 40–50% immediate success. |
Folgieri et al. [32] | 2017 | Italy | - | Sound and visual display | DRACLE | Neurosky Mindwave | - |
Cádiz and de la Cuadra [33] | 2014 | Chile | - | Sound and visual display | Multisensorial performance | KARA1: Neurosky Mindwave KARA2: Emotiv Epoc | - |
Tokunaga and Lyons [34] | 2020 | Japan | - | Sound and visual display | Mandala | Neurosky Mindwave | - |
Participants’ engagement | |||||||
Yan et al. [35] | 2016 | China | N = 48 | Sound and visual display | Adaptive theatre performance | Emotiv Epoc (14 ch) | It is possible to detect significant decreasing thresholds during adaptive theatre performance. There was a better recall of the performance content when using performing cues. The audience was more attracted by multiple performing cues than single performing cues during opera. |
Ramchurn et al. [36] | 2018 | UK | - | Movie composition | Brain-controlled movie | Neurosky Mindwave | - |
Ramchurn et al. [37] | 2018 | UK | N = 33 questionnaires | Music composition | Musical Soundtracks for BCI Systems | Neurosky Mindwave | The users understood the presence of a relation between the visual elements of the film and the soundtrack. |
Marchesi et al. [38] | 2011 | Italy | - | Movie composition | Brain-interactive movie | Neurosky Mindwave | - |
Marchesi [39] | 2012 | Italy | - | Correlates of mood during cinema | Video editing | Neurosky Mindwave | - |
Zioga et al. [40] | 2018 | UK | N = 7 | Live performance | Live performance and video projection | MyndPlay Brain-BandXL | Correlation between the participants’ answers, special elements of the performance, and the audience’s attention, and emotional engagement. The performer’s results were consistent with the recall of representations and the increase in cognitive load. |
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Vanutelli, M.E.; Salvadore, M.; Lucchiari, C. BCI Applications to Creativity: Review and Future Directions, from little-c to C2. Brain Sci. 2023, 13, 665. https://doi.org/10.3390/brainsci13040665
Vanutelli ME, Salvadore M, Lucchiari C. BCI Applications to Creativity: Review and Future Directions, from little-c to C2. Brain Sciences. 2023; 13(4):665. https://doi.org/10.3390/brainsci13040665
Chicago/Turabian StyleVanutelli, Maria Elide, Marco Salvadore, and Claudio Lucchiari. 2023. "BCI Applications to Creativity: Review and Future Directions, from little-c to C2" Brain Sciences 13, no. 4: 665. https://doi.org/10.3390/brainsci13040665
APA StyleVanutelli, M. E., Salvadore, M., & Lucchiari, C. (2023). BCI Applications to Creativity: Review and Future Directions, from little-c to C2. Brain Sciences, 13(4), 665. https://doi.org/10.3390/brainsci13040665