Deep Brain Stimulation (DBS) is a surgical procedure that involves implanting a device, commonly referred to as a neurostimulator or brain pacemaker, into specific regions of the brain to treat various neurological conditions. DBS uses mild electrical impulses to modulate abnormal brain activity and alleviate symptoms. From a technological point of view, DBS is closely related to the field of neuroprosthetics and BCI. DBS is commonly used to manage movement disorders, including Parkinson’s disease, essential tremor, and dystonia. It has also shown promise in the treatment of other neurological and psychiatric conditions, such as epilepsy, obsessive-compulsive disorder (OCD), Tourette syndrome, and certain types of chronic pain. The exact mechanism by which DBS works is not entirely understood, but it is believed to modulate abnormal neural activity and restore more normal patterns of communication within the brain circuits. DBS is a reversible and adjustable treatment, as the stimulation parameters can be modified to achieve the desired therapeutic effect.
VISCOELASTICITY
Viscoelasticity is a property of materials that exhibit both viscous (liquid-like) and elastic (solid-like) behavior under deformation. Many biological tissues exhibit viscoelastic behavior due to their complex structures and compositions. Some examples of viscoelastic phenomena in biological tissues include:
- Creep: Creep is the gradual deformation of a material under a constant load over time. Biological tissues such as cartilage and tendons exhibit creep behavior under sustained loading.
- Stress relaxation: Stress relaxation is the gradual decrease in stress over time under constant strain. This phenomenon is observed in biological tissues such as muscles and blood vessels.
- Hysteresis: Hysteresis is the difference in stress-strain behavior between loading and unloading. Biological tissues such as ligaments and tendons exhibit hysteresis due to their viscoelastic properties.
- Frequency dependence: The mechanical properties of biological tissues may vary with the frequency of the applied load. This phenomenon is observed in soft tissues such as skin, cartilage, and fat.
- Understanding the viscoelastic properties of biological tissues is important for the development of medical devices and treatments, as well as for the design of biomechanical models of tissues and organs.
ABOUT
- The EU-funded VIBraTE ERA Chair (Grant no 101086815) will establish a Neurotechnology laboratory at the IICT. Among the objectives of the lab will be to model and investigate the properties, geometry, and mechanical effects of the interaction of the brain with the implanted electrodes. ERA Chairs are funded by the European Union to support the development of research excellence in specific scientific areas. The objective of the ERA Chair project is to attract and maintain high-quality researchers at IICT, improve research quality and impact, and enhance the institution’s research environment. The project provides funding for doctoral and postdoctoral research projects, mobility opportunities, and training activities for researchers. The project will improve the international research visibility of the IICT in the field of neurotechnology.
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- The project leader, Assoc. Prof. Dimiter Prodanov shares a position with the Interuniversity Microelectronics Centre (Imec) in Leuven, Belgium, which is one of the globally leading research organizations in the area of nanoelectronics and digital technologies. Dimiter Prodanov obtained an MD from the Medical University – Sofia in 1999 and a Ph.D. in Neuroscience from Twente University, Enschede, the Netherlands in 2006. In 2006 he was awarded a John G Nicholls fellowship from the International Brain Research Organization (IBRO) to continue his research in Neuroscience at the Catholic University of Louvain, Belgium. In 2007-2008 he conducted a postdoctoral study at the University of Liege, Belgium in the therapeutic applications of vagus nerve stimulation and pathophysiology of migraine. Since 2008 Dimiter Prodanov joined Imec as a senior scientist, where he conducted research in the development of deep brain stimulation and high-density recordings from the brain. Since 2013 Dimiter Prodanov is an affiliated researcher in Neuroelectronics Research Flanders. Assoc. Prof. Prodanov is interested in nanotechnology, computational biology, and therapeutic modulation of brain activity. His technical interests include applications of computer algebra tools and numerical algorithms to modeling biophysical phenomena and image processing. Since 2003 he is an active contributor to the public-domain imaging program ImageJ. Since 2009 he has been actively engaged in the emerging discipline of Neuroinformatics. He authored more than 60 scientific articles, 6 book chapters, and 2 patents.
INVESTIGATE
- Axis 1: “Viscoelastic coupling” will investigate the mechanical coupling between an implant and the brain tissue and its influence on extracellular matrix remodeling and gliosis. The problem will be systematically addressed starting from simple FEM brain models and only gradually adding anatomical details. Expected results will predict the influence of brain circulation, head rotation, and respiratory activity on implant displacement in realistic head geometries. Another promising direction of research will be to also investigate the above effects in fractional-order viscoelastic models using the tools of fractional calculus.
OPTIMIZE
- Axis 2: Optimization of the interface geometry will explore the interaction of electrodes, having assorted geometries – i.e. featuring (i) flanks protruding in the tissue or (ii) holes. The softness of the material plays an important role in increasing the biocompatibility, however, there seems to be a saturation of the effect.
MODEL AND INVESTIGATE
- Axis 3: “Diffusion phenomena in the brain tissue”: Diffusion in porous media, such as biological tissues, is characterized by a mixture of convective and diffusive transport which can be modeled classically by the tissue tortuosity or alternatively by the tools of fractional calculus. The presence of the foreign body (e.g. an implant) together with its mechanical interaction with the surrounding tissue eventually leads to the production and diffusion of various biochemical species. The inflammatory cells around an implant may induce a persistent gradient of soluble factors, which modulate other cells’ phenotypes.
MODEL
- Axis 4: “Effects of viscoelastic deformations on modeled brain activity” will use spiking neural network models coupled to an inhomogeneous electrical conductance model of the tissue. Modeled neurons will be displaced by a deformation field corresponding to cardiac and respiratory pulsations. The computed electrical field will be sampled in space and time, and the action potential waveforms will be correlated with the immobile condition. The displacement and electrical fields will be computed analytically (simple geometry) or simulated in FEM (more realistic geometry) depending on the complexity of the problem. Such deformations are expected to affect different spike-sorting algorithms presently used in neurophysiology.
VIEW MORE
- Axis 1: “Viscoelastic coupling” will investigate the mechanical coupling between an implant and the brain tissue and its influence on extracellular matrix remodeling and gliosis. The problem will be systematically addressed starting from simple FEM brain models and only gradually adding anatomical details. Expected results will predict the influence of brain circulation, head rotation, and respiratory activity on implant displacement in realistic head geometries. Another promising direction of research will be to also investigate the above effects in fractional-order viscoelastic models using the tools of fractional calculus.
- Axis 2: Optimization of the interface geometry will explore the interaction of electrodes, having assorted geometries – i.e. featuring (i) flanks protruding in the tissue or (ii) holes. The softness of the material plays an important role in increasing the biocompatibility, however, there seems to be a saturation of the effect.
- Axis 3: “Diffusion phenomena in the brain tissue”: Diffusion in porous media, such as biological tissues, is characterized by a mixture of convective and diffusive transport which can be modeled classically by the tissue tortuosity or alternatively by the tools of fractional calculus. The presence of the foreign body (e.g. an implant) together with its mechanical interaction with the surrounding tissue eventually leads to the production and diffusion of various biochemical species. The inflammatory cells around an implant may induce a persistent gradient of soluble factors, which modulate other cells’ phenotypes. This research axis will investigate a first-order reaction-diffusion system in two compartments featuring cylindrical geometries and will develop combined analytical/numerical approaches for quantifying this interaction. Eventually, the models will be ported to FEM solvers implementing the fractional Laplacian operator.
- Axis 4: “Effects of viscoelastic deformations on modeled brain activity” will use spiking neural network models coupled to an inhomogeneous electrical conductance model of the tissue. Modeled neurons will be displaced by a deformation field corresponding to cardiac and respiratory pulsations. The computed electrical field will be sampled in space and time, and the action potential waveforms will be correlated with the immobile condition. The displacement and electrical fields will be computed analytically (simple geometry) or simulated in FEM (more realistic geometry) depending on the complexity of the problem. Such deformations are expected to affect different spike-sorting algorithms presently used in neurophysiology.
