Journal
NEUROIMAGE
Volume 181, Issue -, Pages 818-830Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2018.08.039
Keywords
Dynamic causal modelling; Neural mass models; Oscillations; Basal ganglia; Motor cortex; Parkinson's disease
Funding
- European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant [795866]
- Wellcome Principal Research Fellowship [088130/Z/09/Z]
- Wellcome Trust [203147/Z/16/Z]
- Parkinson Appeal UK
- Monument Trust
- MRC Partnership award [MR/K005464/1]
- Marie Curie Actions (MSCA) [795866] Funding Source: Marie Curie Actions (MSCA)
- MRC [MR/R020418/1] Funding Source: UKRI
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We present a technical development in the dynamic causal modelling of electrophysiological responses that combines qualitatively different neural mass models within a single network. This affords the option to couple various cortical and subcortical nodes that differ in their form and dynamics. Moreover, it enables users to implement new neural mass models in a straightforward and standardized way. This generic framework hence supports flexibility and facilitates the exploration of increasingly plausible models. We illustrate this by coupling a basal ganglia-thalamus model to a (previously validated) cortical model developed specifically for motor cortex. The ensuing DCM is used to infer pathways that contribute to the suppression of beta oscillations induced by dopaminergic medication in patients with Parkinson's disease. Experimental recordings were obtained from deep brain stimulation electrodes (implanted in the subthalamic nucleus) and simultaneous magnetoencephalography. In line with previous studies, our results indicate a reduction of synaptic efficacy within the circuit between the subthalamic nucleus and external pallidum, as well as reduced efficacy in connections of the hyperdirect and indirect pathway leading to this circuit. This work forms the foundation for a range of modelling studies of the synaptic mechanisms (and pathophysiology) underlying event-related potentials and cross-spectral densities.
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