期刊
NATURE BIOMEDICAL ENGINEERING
卷 5, 期 4, 页码 -出版社
NATURE PORTFOLIO
DOI: 10.1038/s41551-020-00666-w
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资金
- Army Research Office [W911NF-16-1-0368]
- UK Ministry of Defence
- UK Engineering and Physical Research Council under the Multidisciplinary University Research Initiative
- US National Institutes of Health BRAIN [R01-NS104923]
- Defense Advanced Research Projects Agency [W911NF-14-2-0043]
- Army Research Office contracting office in support of the DARPA SUBNETS programme
Dynamic input-output models have been developed to predict the multiregional dynamics of brain networks in response to varying patterns of microstimulation. The activities of brain networks can be modulated by changes in stimulation amplitude and frequency, with variations in prediction accuracy and estimated response strength across brain regions. This research may enable precise neuromodulation for disease treatment and help investigate the functional organization of large-scale brain networks.
Direct electrical stimulation can modulate the activity of brain networks for the treatment of several neurological and neuropsychiatric disorders and for restoring lost function. However, precise neuromodulation in an individual requires the accurate modelling and prediction of the effects of stimulation on the activity of their large-scale brain networks. Here, we report the development of dynamic input-output models that predict multiregional dynamics of brain networks in response to temporally varying patterns of ongoing microstimulation. In experiments with two awake rhesus macaques, we show that the activities of brain networks are modulated by changes in both stimulation amplitude and frequency, that they exhibit damping and oscillatory response dynamics, and that variabilities in prediction accuracy and in estimated response strength across brain regions can be explained by an at-rest functional connectivity measure computed without stimulation. Input-output models of brain dynamics may enable precise neuromodulation for the treatment of disease and facilitate the investigation of the functional organization of large-scale brain networks.
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