TY - JOUR
T1 - When neuromodulation met control theory
AU - Guidotti, Roberto
AU - Basti, Alessio
AU - Pieramico, Giulia
AU - D’Andrea, Antea
AU - Makkinayeri, Saeed
AU - Pettorruso, Mauro
AU - Roine, Timo
AU - Ziemann, Ulf
AU - Ilmoniemi, Risto J.
AU - Luca Romani, Gian
AU - Pizzella, Vittorio
AU - Marzetti, Laura
N1 - Publisher Copyright: © 2025 The Author(s). Published by IOP Publishing Ltd.
| openaire: EC/H2020/810377/EU//ConnectToBrain
PY - 2025/2
Y1 - 2025/2
N2 - The brain is a highly complex physical system made of assemblies of neurons that work together to accomplish elaborate tasks such as motor control, memory and perception. How these parts work together has been studied for decades by neuroscientists using neuroimaging, psychological manipulations, and neurostimulation. Neurostimulation has gained particular interest, given the possibility to perturb the brain and elicit a specific response. This response depends on different parameters such as the intensity, the location and the timing of the stimulation. However, most of the studies performed so far used previously established protocols without considering the ongoing brain activity and, thus, without adaptively targeting the stimulation. In control theory, this approach is called open-loop control, and it is always paired with a different form of control called closed-loop, in which the current activity of the brain is used to establish the next stimulation. Recently, neuroscientists are beginning to shift from classical fixed neuromodulation studies to closed-loop experiments. This new approach allows the control of brain activity based on responses to stimulation and thus to personalize individual treatment in clinical conditions. Here, we review this new approach by introducing control theory and focusing on how these aspects are applied in brain studies. We also present the different stimulation techniques and the control approaches used to steer the brain. Finally, we explore how the closed-loop framework will revolutionize the way the human brain can be studied, including a discussion on open questions and an outlook on future advances.
AB - The brain is a highly complex physical system made of assemblies of neurons that work together to accomplish elaborate tasks such as motor control, memory and perception. How these parts work together has been studied for decades by neuroscientists using neuroimaging, psychological manipulations, and neurostimulation. Neurostimulation has gained particular interest, given the possibility to perturb the brain and elicit a specific response. This response depends on different parameters such as the intensity, the location and the timing of the stimulation. However, most of the studies performed so far used previously established protocols without considering the ongoing brain activity and, thus, without adaptively targeting the stimulation. In control theory, this approach is called open-loop control, and it is always paired with a different form of control called closed-loop, in which the current activity of the brain is used to establish the next stimulation. Recently, neuroscientists are beginning to shift from classical fixed neuromodulation studies to closed-loop experiments. This new approach allows the control of brain activity based on responses to stimulation and thus to personalize individual treatment in clinical conditions. Here, we review this new approach by introducing control theory and focusing on how these aspects are applied in brain studies. We also present the different stimulation techniques and the control approaches used to steer the brain. Finally, we explore how the closed-loop framework will revolutionize the way the human brain can be studied, including a discussion on open questions and an outlook on future advances.
KW - closed loop neuromodulation
KW - control theory
KW - DBS
KW - neurofeedback
KW - neurostimulation
KW - TMS
UR - http://www.scopus.com/inward/record.url?scp=85218501962&partnerID=8YFLogxK
U2 - 10.1088/1741-2552/ad9958
DO - 10.1088/1741-2552/ad9958
M3 - Review Article
C2 - 39622179
AN - SCOPUS:85218501962
SN - 1741-2560
VL - 22
SP - 1
EP - 24
JO - Journal of Neural Engineering
JF - Journal of Neural Engineering
IS - 1
M1 - 011001
ER -