Dataset Information

Optimized temporal pattern of brain stimulation designed by computational evolution.

ABSTRACT: Brain stimulation is a promising therapy for several neurological disorders, including Parkinson's disease. Stimulation parameters are selected empirically and are limited to the frequency and intensity of stimulation. We varied the temporal pattern of deep brain stimulation to ameliorate symptoms in a parkinsonian animal model and in humans with Parkinson's disease. We used model-based computational evolution to optimize the stimulation pattern. The optimized pattern produced symptom relief comparable to that from standard high-frequency stimulation (a constant rate of 130 or 185 Hz) and outperformed frequency-matched standard stimulation in a parkinsonian rat model and in patients. Both optimized and standard high-frequency stimulation suppressed abnormal oscillatory activity in the basal ganglia of rats and humans. The results illustrate the utility of model-based computational evolution of temporal patterns to increase the efficiency of brain stimulation in treating Parkinson's disease and thereby reduce the energy required for successful treatment below that of current brain stimulation paradigms.

SUBMITTER: Brocker DT

PROVIDER: S-EPMC5516784 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Optimized temporal pattern of brain stimulation designed by computational evolution.

Brocker David T DT Swan Brandon D BD So Rosa Q RQ Turner Dennis A DA Gross Robert E RE Grill Warren M WM

Science translational medicine 20170101 371

Brain stimulation is a promising therapy for several neurological disorders, including Parkinson's disease. Stimulation parameters are selected empirically and are limited to the frequency and intensity of stimulation. We varied the temporal pattern of deep brain stimulation to ameliorate symptoms in a parkinsonian animal model and in humans with Parkinson's disease. We used model-based computational evolution to optimize the stimulation pattern. The optimized pattern produced symptom relief com ...[more]

PMID: 28053151

Similar Datasets

Project description:Transcranial alternating current stimulation (tACS) is a noninvasive method used to modulate activity of superficial brain regions. Deeper and more steerable stimulation could potentially be achieved using transcranial temporal interference stimulation (tTIS): two high-frequency alternating fields interact to produce a wave with an envelope frequency in the range thought to modulate neural activity. Promising initial results have been reported for experiments with mice. In this study we aim to better understand the electric fields produced with tTIS and examine its prospects in humans through simulations with murine and human head models. A murine head finite element model was used to simulate previously published experiments of tTIS in mice. With a total current of 0.776 mA, tTIS electric field strengths up to 383 V/m were reached in the modeled mouse brain, affirming experimental results indicating that suprathreshold stimulation is possible in mice. Using a detailed anisotropic human head model, tTIS was simulated with systematically varied electrode configurations and input currents to investigate how these parameters influence the electric fields. An exhaustive search with 88 electrode locations covering the entire head (146M current patterns) was employed to optimize tTIS for target field strength and focality. In all analyses, we investigated maximal effects and effects along the predominant orientation of local neurons. Our results showed that it was possible to steer the peak tTIS field by manipulating the relative strength of the two input fields. Deep brain areas received field strengths similar to conventional tACS, but with less stimulation in superficial areas. Maximum field strengths in the human model were much lower than in the murine model, too low to expect direct stimulation effects. While field strengths from tACS were slightly higher, our results suggest that tTIS is capable of producing more focal fields and allows for better steerability. Finally, we present optimal four-electrode current patterns to maximize tTIS in regions of the pallidum (0.37 V/m), hippocampus (0.24 V/m) and motor cortex (0.57 V/m).

Project description:BACKGROUND:Dysregulated gene expression patterns have been reported in several mental disorders. Limited by the difficulty of obtaining samples, psychiatric molecular mechanism research still relies heavily on clues from genetics studies. By using reference data from brain expression studies, multiple types of comprehensive gene expression pattern analysis have been performed on psychiatric genetic results. These systems-level spatial-temporal expression pattern analyses provided evidence on specific brain regions, developmental stages and molecular pathways that are possibly involved in psychiatric pathophysiology. At present, there is no online tool for such systematic analysis, which hinders the applications of analysis by non-informatics researchers such as experimental biologists and clinical molecular biologists. RESULTS:We developed the BEST web server to support Brain Expression Spatio-Temporal pattern analysis. There are three highlighted features of BEST: 1) visualization: it generates user-friendly visual results that are easy to interpret, including heatmaps, Venn diagrams, gene co-expression networks and cluster-based Manhattan gene plots; these results illustrate the complex spatio-temporal expression patterns, including expression quantification and correlation between genes; 2) integration: it provides comprehensive human brain spatio-temporal expression patterns by integrating data from currently available databases; 3) multi-dimensionality: it analyses input genes as both a whole set and several subsets (clusters) which are enriched according to co-expression patterns, and it also presents the correlation between genetic and expression data. CONCLUSIONS:To the best of our knowledge, BEST is the first data tool to support comprehensive human brain spatial-temporal expression pattern analysis. It helps to bridge disease-related genetic studies and mechanism studies, provides clues for key gene and molecular system identification, and supports the analysis of disease sensitive brain region and age stages. BEST is freely available at http://best.psych.ac.cn.

Dataset Information

Optimized temporal pattern of brain stimulation designed by computational evolution.

Publications

Optimized temporal pattern of brain stimulation designed by computational evolution.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets