Abstract
Studies on neurophysiological correlates of the functional magnetic resonance imaging (fMRI) signals reveal a strong relationship between the local field potential (LFP) acquired invasively and metabolic signal changes in fMRI experiments. Most of these studies failed to reveal an analogous relationship between metabolic signals and the spiking activity. That would allow for the prediction of the neural activity exclusively from the fMRI signals. However, the relationship between fMRI signals and spiking activity can be inferred indirectly provided that the LFPs can be used to predict the spiking activity of the area. Until now, only the LFP-spike relationship in cortical areas has been examined. Herein, we show that the spiking activity can be predicted by the LFPs acquired in a deep nucleus, namely the subthalamic nucleus (STN), using a nonlinear cascade model. The model can reproduce the spike patterns inside the motor area of the STN that represent information about the motor plans. Our findings expand the possibility of further recruiting non-invasive neuroimaging techniques to understand the activity of the STN and predict or even control movement.
Original language | English (US) |
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Article number | 114021 |
Journal | Measurement Science and Technology |
Volume | 22 |
Issue number | 11 |
DOIs | |
State | Published - Nov 2011 |
All Science Journal Classification (ASJC) codes
- Instrumentation
- Engineering (miscellaneous)
- Applied Mathematics
Keywords
- basal ganglia
- local field potentials
- subthalamic nucleus