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Jose del R. Millan

The University of Texas at Austin

CNBI Lab

Clinical Neuroprosthetics and Brain Interaction LabCNBI Lab

 

 
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    • Closed-Loop Brain Stimulation as a Potential Intervention for Cognitive Decline
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Sinergia

New Treatments for Induction of Motor Plasticity after Stroke

Recent progress has enabled an improved understanding of how the brain recovers from motor impairment during the first months after stroke. The integrity of fiber tracts connecting movement areas of the brain with spine and muscles (i.e., of the so-called cortico-spinal tract, CST) and repair processes around the damaged brain cortex were found to key factors for motor improvement within the first 3 months. Furthermore, new treatment approaches have become available that can influence neural processes that may be important for recovery. Hence, we can now start to apply treatments which induce specific repair processes in patient subgroups that are likely to benefit. This has the potential to obtain causal and customised treatment of motor handicap.

This project proposes to test two therapy concepts resulting from recent advances in the understanding of motor plasticity in patients with subacute stroke.

In a first component of the project, we will perform non-invasive stimulation by applying a small direct current to the scalp of patients with stroke (a technique called “transcranial direct current stimulation”). This treatment will be tested in patients with light to moderate motor handicap and with at least partial integrity of the CST. We hypothesize that if this treatment is started within 4 weeks after stroke onset, it enhances repair processes in the cortex and leads to improved clinical motor recovery.

In a second part of the project, we will test a treatment in patients with severe motor handicap and severe damage to the CST. A brain-computer interface system will detect when patients activate their movement areas of the brain by trying to move their paralyzed arm. This will trigger an electrical stimulation of the arm muscles and lead to a movement. We hypothesize that, if this treatment is applied within 4 weeks after stroke, it helps restore CST fibers and improve recovery of patients with severe handicap.

We hope that our approach can influence more selectively and efficiently repair processes that are critical for recovery and that it leads to robust effects on motor recovery even in patients with severe motor deficits.

Latest News

  • Akhil Surapaneni’s poster wins the Larry Abraham Excellence in Rehabilitation Research Award
  • Brain-Powered Wheelchair Shows Real-World Promise
  • UT Researchers Develop Electrode to Rehabilitate Stroke Patients at Home
  • Stable Electrodes for Long-Term, Wearable Brain-Machine Interface
  • José Del R. Millán Nominated as a Dell Medical School Visionary

Latest Journal Publications

Beraldo, G., Tonin, L., Cesta, A., Menegatti, E., Millán, J.d.R. (2023). Validation of Shared Intelligence Approach for Teleoperating Telepresence Robots Through Inaccurate Interfaces. In: Petrovic, I., Menegatti, E., Marković, I. (eds) Intelligent Autonomous Systems 17. IAS 2022. Lecture Notes in Networks and Systems, vol 577. Springer, Cham.

Luca Tonin, Serafeim Perdikis, Taylan Deniz Kuzu, Jorge Pardo, Bastien Orset, Kyuhwa Lee, Mirko Aach, Thomas Armin Schildhauer, Ramón Martínez-Olivera, José del R. Millán. Learning to control a BMI-driven wheelchair for people with severe tetraplegia. iScience. 2022. 105418.

Ju-Chun Hsieh, Hussein Alawieh, Yang Li, Fumiaki Iwane, Linran Zhao, […]. A highly stable electrode with low electrode-skin impedance for wearable brain-computer interface. Biosensors and Bioelectronics. 2022, 114756.

JH. Jeong, JH. Cho, YE. Lee, SH. Lee, GH. Shin, YS. Kweon,  J.d.R. Millán, KR. Müller, SW Lee. 2020 International brain-computer interface competition: A review. Front Hum Neurosci. 2022 Jul, 22(16):898300.

F. Dell’Agnola, P.-K. Jao, R. Chavarriaga, J.d.R. Millán, D. Floreano, D. Atienza. (2022). Machine-Learning Based Monitoring of Cognitive Workload in Rescue Missions with Drones. in IEEE J. of Biomedical and Health Informatics,2022 Sep, 26(9):4751-4762.


For a complete list of publications go to our Publications page!

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