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Computational Model-Based Development of Novel Stimulation Algorithms

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Encyclopedia of Computational Neuroscience

Definition

In the context of this entry, the model-based development of stimulation algorithms designates a process of creation and computational testing of new techniques for control and modulation of undesirable (pathological) neuronal dynamics. Abnormal brain activity has been observed in several neurological disorders including Parkinson’s disease, essential tremor, epilepsy, tinnitus, and others. Brain stimulation is used for the therapy of patients suffering, for example, from Parkinson’s disease, epilepsy, or mental disorders. Brain stimulation is called deep brain stimulation (DBS) if structures deeply inside the brain are targeted, cortical stimulation (intracortical or epicortical) if the electrical contacts of the stimulator are positioned within the cortex or on its surface, or noninvasive transcranial stimulation if the neurons are stimulated by electrical currents induced across scalp by either external magnetic field (transcranial magnetic stimulation, TMS) or electrical...

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Abbreviations

Coordinated reset stimulation:

Coordinated reset (CR) stimulation is an effectively desynchronizing control technique, where a population of synchronized oscillators is stimulated via several stimulation sites in such a way that spatially and timely coordinated phase reset is achieved in subpopulations assigned to each of the stimulation sites. This method is suggested for counteraction of abnormal neuronal synchronization characteristic for several neurological diseases and amelioration of their symptoms. It has successively been verified in a number of experimental and clinical studies.

Deep brain stimulation:

Electrical deep brain stimulation (DBS) is the standard therapy for medically refractory movement disorders, e.g., Parkinson’s disease and essential tremor. It requires a surgical treatment, where depth electrodes are chronically implanted in target areas like the thalamic ventralis intermedius nucleus or the subthalamic nucleus. For standard DBS, electrical high-frequency (>100 Hz) stimulation is permanently delivered via depth electrodes. More sophisticated deep brain stimulation techniques are in the process of being established for clinical use.

Delayed feedback:

Delayed feedback is a method for the creation of a closed-loop forcing, where a portion of the measured output signal of a system is time delayed, linearly or nonlinearly processed, and fed back into the system. This approach is often used to control the dynamic behavior of complex systems. In this entry, delayed feedback is used to control synchronization in ensembles of coupled oscillators, e.g., neurons.

Order parameter:

The order parameter is a quantity characterizing a phase transition or phase change in the transformation of a complex system from one phase (state) to another. The order parameter is convenient for characterizing the onset and extent of synchronization in larger ensembles: Perfect phase synchronization corresponds to a large value of the order parameter, whereas an incoherent (desynchronized) state is associated with a small value of the order parameter. In synergetics it has been shown that the dynamics of complex systems may be governed by only a few order parameters.

Synchronization:

Synchronization (from Greek syn = the same, common and chronos = time) means the adjustment of rhythms of self-sustained oscillators due to their weak interaction. The interacting oscillators can be regular (periodic) or chaotic. There are several different forms of synchronization including phase, complete, generalized, and lag synchronization, etc. In this entry, we focus on phase synchronization. In the simplest form, the oscillators, rotating with the same frequency, become phase synchronized (phase locked) to each other, if the difference of their phases remains bounded, e.g., constant. In the presence of noise, phase synchronization is characterized by the presence of one or more prominent peaks of the distribution of the phase difference. Put otherwise, the oscillators adjust their rhythms, while their amplitude dynamics need not be correlated.

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Authors and Affiliations

  1. Institute of Neuroscience and Medicine – Neuromodulation (INM-7), Research Center Jülich, 52425, Jülich, Germany

    Dr. Oleksandr V. Popovych & Peter Alexander Tass

  2. Department of Neurosurgery, Stanford University, Stanford, CA, USA

    Peter Alexander Tass

  3. Department of Neuromodulation, University of Cologne, Cologne, Germany

    Peter Alexander Tass

Authors
  1. Dr. Oleksandr V. Popovych
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  2. Peter Alexander Tass
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Correspondence to Oleksandr V. Popovych .

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Editors and Affiliations

  1. Atlanta, Georgia, USA

    Dieter Jaeger

  2. Department of Biomedical Engineering, Florida International University, Miami, Florida, USA

    Ranu Jung

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Popovych, O.V., Tass, P.A. (2014). Computational Model-Based Development of Novel Stimulation Algorithms. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7320-6_124-1

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  • DOI: https://doi.org/10.1007/978-1-4614-7320-6_124-1

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  • Online ISBN: 978-1-4614-7320-6

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