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440 A. J. Aguilar-Herrera et al.
Fig. 30.4 Multimodal data processing pipeline for MoBI studies in naturalistic settings. The
framework supports synchronized preprocessing and artifact removal across video, EEG, EOG,
and IMU signals. It consists of four stages: Stage 0 (Data Understanding and Annotation), Stage
1 (Eye Artifact Removal), Stage 2 (Motion Artifact Removal), and Stage 3 (Source-Space Artifact
Removal). This full pipeline is used for offline data cleaning and analysis. A simplified real-time
implementation using H-infinity ANC is currently employed during live performances for visualization, but is not yet configured for closed-loop neurofeedback or BCI control
Figure 30.4 illustrates our multimodal processing pipeline designed to manage
this complexity. The framework accommodates real-world noise, supports adaptive
artifact removal, and preserves ecologically meaningful signal featu res. It is structured into four major stages: Stage 0: Data Understanding, Stage 1: Eye Artifact
Removal, Stage 2: Motion Artifact Removal, and Stage 3: Source-Space Artifact
Removal.
At Stage 0, raw data streams—including EEG (
nels), IMU
and timestamped video ( 24 fps)—are synchronized and aligned to
data,
28 channels), EOG ( 4 chan-
a common sampling rate. An initial impedance check flags noisy or disconnected
EEG channels, which may be reconstructed if necessary. Simultaneously, art domain
experts (e.g., choreographers, composers) annotate artistic or behaviorally significant events, such as shifts in rhythm, posture, eye contact, or audience response.
These annotations help to define task-relevant segments and establish ground truth
for interpretation. A multimodal data visualization layer allows for real-time inspection and cross-modal verification of artifacts and cognitive events.
Stage 1 focuses on ocular artifact removal. Traditional EEG filtering pipelines are
insufficient in naturalistic settings where eye movements, blinks, and gaze shifts
30 Understanding the Creative Brain in Action 441
occur continuously and unpredictably. To address this, we apply a robust adaptive
noise cancellation method that treats each EEG channel as an independent subsystem
(Kilicarslan et al.,
such
as blinks, lateral saccades, and amplitude drifts—without distorting spatial or
2016). This technique selectively filters eye-related artifacts—
temporal dynamics of nearby channel s.
Stage 2 addresses motion artifacts, which are especially prevalent in MoBI
studies involving full-body movement, expressive gestures, or walking. Unlike
traditional artifact rejection techniques (e.g., Independent Component Analysis or
Artifact Subspace Reconstruction), which often underperform in movement-rich
contexts, we employ a Volterra-based nonlinear adaptive filtering method
(Kilicarslan & Contreras Vidal,
s—such as those generated by gait harmonics or upper-limb gestures—and
artifact
2019). This approach models complex motion
suppresses them without remo ving task-relevant brain activity. It is robust, real-time
compatible, and generalizable to various ecological contexts, including unstructured,
improvisational performances.
After filtering, data undergo segment rejection, artifact subspace reconstruction,
and
independent component analysis (ICA) to isolate and remove residual noise. The
pipeline is designed to minimize unnecessary data loss while retaining neural signals
relevant to embodied cognition and creative behavior.
Stage 3 focuses on source-space artifact removal. Cleaned EEG data are subjected
back-projection, followed by dipole fitting and independent component inspec-
to
tion. Components are classified and spatially localized using a combination of
automated heuristics and manual validation. Artifactual dipoles—those associated
with muscle noise or residual motion—are removed prior to analysis. The resulting
dataset represents a high-fidelity, source-level reconstruction suitable for eventrelated or network-based analyses.
Parallel to these technical procedures is the equally essential task of event
labeling
and segmentation. In contrast to lab-based paradigms, MoBI studies rarely
rely on time-locked stimuli. Instead, they require post-hoc annotation of complex,
unscripted behaviors that may be culturall y or artistically significant. In these cases,
expert annotation—sometimes down to the frame— is necessary to identify meaningful segments for comparison (e.g., shifts in tone, role transitions, audience
interaction). This work often involves dramaturgs, composers, and other domain
experts, and requires the development of ontology-aware coding schemas that bridge
scientific and artistic frameworks.
The time cost of this process should not be underestimated. Creating a single
analys
is-ready dataset may involve weeks of iterative work—filtering, synchronizing, aligning metadata, and segmenting events across modalities. The pipeline must
support both algorithmic scalability and human interpretability, ensuring that
datasets are robust enough for analysis yet transparent enough to support crossdisciplinary review.
Together, these strategies form a flexible, real-world-ready data processing
framewo
rk. By balancing automation with expert annotation, and artifact removal
with ecological validity, the system supports the scientific goals of MoBI while
honoring the creative and embodied realities in which it operates.
442 A. J. Aguilar-Herrera et al.
30.6 Challenges and Limitations
In controlled laboratory environments, experimental rigor is prioritized through
standardization and isolation. In contrast, MoBI studies conducted in naturalistic
settings must contend with the complexities of real-world contexts. Whil e these
contexts introduce invaluable ecological validity, enabling the study of human
behavior as embedded in social, emotional, and physical environments. They also
present multifactorial challenges that impact data acquisition, system design, and
long-term project sustainability.
Technological Barriers
While consumer-grade EEG devices have improved, many MoBI applications—
particula
that is not easily scalable. Synchronizing neural recordings across multiple mobile
units is prone to latency jitter, sampling drift, and connection loss, especially in
WiFi-congested environments such as galleries or performance venues. Achieving
temporal alignment across multiple EEG systems, audio-video feeds, and movement
data remains an open technical front ier.
electrodes
enough to blend into costumes or avoid occlusion in video capture. In live performance, even small issues—like a forehead electrode detaching due to sweat or facial
makeup—can compromise entire sessions. Solutions such as customized caps,
adhesives, or electrode holders must be tailored per study, often requiring engineering intervention.
must juggle streaming protocols (e.g., LSL, OSC), signal buffering, and computational loads across platforms, often with minimal documentation or community
support. Signal dropout or latency spikes can interrupt feedback loops, making
closed-loop BCI applications especially fragile in public-facing demonstrations.
rly those involving hype rscanning—still require research-grade equipment
Hardware also presents limitations in form factor and wearability. For instance,
must maintain consistent contact during movement, yet be discreet
Moreover, interoperability between devices is rarely seamless. Real-time systems
Logistical and Environmental Constraints
The logistical footprint of a MoBI study is often larger than anticipated. Participants
—whether dancers, actors, musicians, or visitors—must arrive early for headset
fitting, signal quality testing, and calibration. These procedures can be timeconsuming and may interfere with rehearsal schedules, particularly in artistic settings where time is limited and performance preparation is paramount.
In fieldwork settings, venue limitations often dictate what is technically feasible.
Power
outlets, lighting conditions, background noise, and WiFi bandwidth can all
influence data quality. Performing in open-air settings, for example, introduces
humidity and wind artifacts that affect both sensors and behavior. Coordinating
with venue staff, obtaining permissions, and ensuring safety protocols (e.g., wireless
interference testing) add further overhead.
30 Understanding the Creative Brain in Action 443
Aesthetic integration is another important, though less technical, concern. The
visual presence of EEG headsets, cables, or amplifiers may clash with the artistic
intent or disrupt the experience of the audience. In interactive installations, participants may feel self-conscious wearing equipment that appears medical or foreign.
Designing aesthetically mindful and culturally sensitive setups requires input from
artists and often bespoke fabrication.
Ethical and Intellectual Property Considerations
The intersection of neuroscience, the arts, and public engagement raises pressing
ethical
and legal questions that remain insufficiently addressed in current MoBI
research practices. One such concern involves music and multimedia stimuli, which
are frequently integral to MoBI-art collaborations. While these elements may be
used under educational or scientific pretexts, their incorporation in publicly shared
datasets implicates copyright law. At present, no clear, standardized mechanism
exists for the sharing of copyrighted media in neuroimaging studies, even when the
stimuli are critical to the interpretation of results. This lack of clarity hampers data
sharing and undermines reproducibility.
There is a similar need to protect the rights of artists and public figures who
participa
te in MoBI experiments, particularly in performance settings. These individuals may be identifiable in video recordings, event annotations, or biometric
traces, raising concerns about consent, publicity rights, and long-term data governance. As MoBI research increasingly engages with high-visibility participants and
public platforms, guidelines must be developed to ensure ethical representation,
protect creative ownership, and respect participant privacy in both research outputs
and dissemination activities.
Sustainability and Institutional Support
The operationalization of MoBI research often relies on unstable, short-term funding
structure
s. Many collaborative projects between neuroscience and the arts are funded
through time-limited grants that do not support long-term maintenance of equipment, personnel, or data infrastructure. The creation of open-source pipelines and
shared resources is a promising step, but such efforts require sustained institutional
commitment and cross-sector coordination.
Finally, researchers are frequently expected to balance the dual demands of
experi
mental rigor and public impact. Designing participatory, context-rich experiences while maintaining scientific reproducibility remains an unsolved challenge.
Furthermore, existing evaluation metrics fail to capture the full impact of MoBI
projects, particularly those situated at the interface of research, performance, and
public educat ion. Novel frameworks are needed to assess community engagement,
cross-cultural resonance, and non-quantifiable outcomes in a manner that respects
the hybrid nature of this emerging domain.
444 A. J. Aguilar-Herrera et al.
30.7 Conclusion
Across theaters, classrooms, and galleries, mobile EEG has shown us that brain
activity in real-world settings is not only measurable—it is meaningfully shaped by
the surround ing environment, movement, and social interaction. From actors sharing
a scene to dancers navigating improvised choreography, our studies reaffirm a
fundamental insight: cognition is embodied, relational, and responsive to context.
MoBI enables us to study these phenomena as they unfold, not in isolation, but
within the complex rhythms of everyday and artistic life.
What have we learned? That rigorous neuroscience can coexist with artistic
expres
sion. With thoughtful planning, EEG equipment can be embedded into costumes and performances. That movement and emotion are not confounds to be
minimized, but essential components of the experiences we aim to study. And
most importantly, that public-facing research can deepen both scientific insight
and community engagement—when it is conducted with care, cultural awareness,
and collaboration.
We encourage researchers to build upon and adapt the MoBI framework
presented in this chapter. It is not a one-size-fits-all protocol, but a flexible guide
designed for real-world complexity. It supports diverse teams in crafting research
that is technically sound, ethically grounded, and relevant to the communities it
involves.
Looking forward, the potential of interdisciplinary EEG research lies in its ability
scale—across sites, cultures, and time. This will require more robust tools for
to
multimodal data integration, more accessible workflows, and continued collaboration between artists, engineers, neuroscientists, and educators. As new technologies
emerge—such as generative AI, real-time feedback systems, and portable BCI
applications—they must be integrated with attention to both scientific validity and
human experience.
This work is already being advanced by initiatives such as the NSF BRAIN
AccelNet: Movement, Music, and BrainHealth, and the NIH U24 Music and
Dementia Research Network. These networks create new pathways for transdisciplinary research, workforce training, and STEAM outreach—ensuring that discoveries are not only made, but shared and translated across domains.
Ultimately, MoBI research challenges us to rethink where and how neuroscience
happens. By stepping outside the lab, we open new doors—not just for data
collection, but for inclusion, creativity, and meaningful collaboration. It is in these
spaces—shared, dynamic, and alive—that we may come to better understand the
brain as it truly functions: in motion, in connection, and in context.
Acknowledgments We extend our deepest gratitude to the many contributors who made this work
possible. This chapter is the result of sustained collaboration among artists, scientists, students, and
institutions who shared a commitment to exploring the brain in action. We thank our interdisciplinary collaborators and research participants for their creativity, time, and trust. Support from
funding agencies—including the National Science Foundation (NSF BRAIN #2137255, AccelNet
#2412731, and NCS programs), the National Institutes of Health (NIH), and the University of
30 Understanding the Creative Brain in Action 445
Houston—was instrumental in developing and refining the MoBI framework. We also acknowledge
the vital contributions of our partner institutions, including Rice University, the Menil Collection,
Sam Houston State University, the Children’s Museum of Houston, the Midtown Arts and Theater
Center Houston (MATCH), and the Museo de Arte Contemporáneo de Monterrey (MARCO), for
providing platforms to integrate neuroscience into public, artistic, and educational space
s.
Appendix
List: Traveling with MoBI Equipment
(a) Typical items needed for a mobile EEG setup.
A standard MoBI travel kit includes the core EEG recording system (often a
wireless
mentary sensing equipment such as EOG electrodes, inertial measurement units
(IMUs), and manual trigger devices. We also pack laptops with the acquisition
and synchronization software pre-installed, spare electrodes, conductive gels,
batteries, chargers, and appropriate power adapters for the destination country.
Rugged transport cases with custom foam inserts protect sensitive gear from
shocks and humidity. Backup cables, connectors, and video cameras are also
part of the kit. Finally, we carry printed and digital copies of technical documentation, electrode placement diagrams, and setup schematics.
(b) Packing tips for international travel.
We carry the duplicates from the most irreplaceable components such as ampli-
ers, transmitters, and dongles to reduce the risk of loss or damage. Items are
fi
packed in lockab le, impact-resistant cases, with each component labeled with its
name, model, and serial number. A photographic inventory accompanies every
component, servin g as both an internal checklist and a reference for customs
inspections. Power compatibility is addressed in advance, with voltage converters and plug adapters included for all destinations. Scheduling extra time
before and after flights is essential to accommodate inspection procedures,
especially when traveling with multiple cases of sensitive electronics.
(c) Customs and logistical considerations.
International transportation of MoBI equipment often involves complex customs
procedu
re-imported for research purposes. One highly effective solution is the ATA
Carnet, an internationally recognized customs document that functions as a
“passport for goods.” The Carnet permits the temporary, duty-free importation
of professional equipment, thereby streamlining border crossings and minimizing the risk of delays or unexpected fees.
equipment transportation. The process for obtaining one is relatively
straightforward:
28-channel cap with amplifiers and transmitters) along with comple-
res, particularly when equipment is temporarily exported and
Our team adopted the ATA Carnet as a standard practice for all international
446 A. J. Aguilar-Herrera et al.
1. Prepare a detailed inventory listing each item’s description, serial number,
approximate value, and country of origin.
2. Submit this information via the official ATA Carnet portal (https://www.
atacarnet.com/).
3. Pay an issuance fee, which is determined by the value of the equipment and
the
number of countries to be visited.
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Part VI
Multimodal EEG Applications
Chapter 31
Combining EEG and Transcranial Electric
Brain Stimulation
Heiko I. Stecher, Sreekari Vogeti, Daniel Strüber,
and Christoph S. Herrmann
Abstract Neuromodulation techniques, such as transcranial electric stimulation,
offer
the possibility of modulating brain activity and, in turn, behavior. Electroencephalography (EEG) is the ideal tool to demonstrate such alterations of brain
activity and prove that neuromodulation actually achieves a modulation of brain
activity. However, care must be taken to use the right approaches and technical
equipment. This book chapter reviews recent developments and provides recommendations for recording EEG before, during, and after brain stimulation sessions.
Keywords Aperiodic brain activity
· Artifact removal · Closed-loop stimulation ·
EEG · Neuromodulation · Periodic brain activity · Transcranial alternating current
stimulation · Transcranial direct current stimulation · Transcranial random noise
stimulation
H. I. Stecher · D. Strüber
Experimental Psychology Lab, Department of Psychology, Carl-von-Ossietzky Universität,
Oldenburg, Germany
S. Vogeti
Experimental Psychology Lab, Department of Psychology, Carl-von-Ossietzky Universität,
Oldenburg, Germany
Cluster for Excellence “Hearing for All”, Carl-von-Ossietzky Universität, Oldenburg, Germany
C. S. Herrmann (*)
Experimental Psychology Lab, Department of Psychology, Carl-von-Ossietzky Universität,
Oldenburg, Germany
Cluster for Excellence “Hearing for All”, Carl-von-Ossietzky Universität, Oldenburg, Germany
Research Center Neurosensory Science, Carl von Ossietzky Universitßt, Oldenburg, Germany
e-mail:
christoph.herrmann@uol.de; christoph.herrmann@uni-oldenburg.de
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2026
T.
Warbrick (ed.), The EEG Handbook,
https://doi.org/10.1007/978-3-032-20450-9_31
451