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Dynamic causal modelling for functional near-infrared spectroscopy.

Tak S, Kempny AM, Friston KJ, Leff AP, Penny WD - Neuroimage (2015)

Bottom Line: Specifically, we present a generative model of how observed fNIRS data are caused by interactions among hidden neuronal states.Inversion of this generative model, using an established Bayesian framework (variational Laplace), then enables inference about changes in directed connectivity at the neuronal level.Using experimental data acquired during motor imagery and motor execution tasks, we show that directed (i.e., effective) connectivity from the supplementary motor area to the primary motor cortex is negatively modulated by motor imagery, and this suppressive influence causes reduced activity in the primary motor cortex during motor imagery.

View Article: PubMed Central - PubMed

Affiliation: Wellcome Trust Centre for Neuroimaging, University College London, 12 Queen Square, London WC1N 3BG, UK. Electronic address: s.tak@ucl.ac.uk.

No MeSH data available.


Model with estimated parameters of effective connectivity. The units of connections are the rates (Hz) of neural population changes. Black and red dotted lines indicate intrinsic and extrinsic connections modulated by motor imagery, respectively. The results indicate that while all motor stimuli positively affect the regional activity in primary motor cortex (M1), motor imagery negatively modulates connection from supplementary motor area (SMA) to M1, resulting in the suppressive influence of SMA on M1. These results are consistent with the findings of previous fMRI studies (Kasess et al., 2008; Gerardin et al., 2000).
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f0035: Model with estimated parameters of effective connectivity. The units of connections are the rates (Hz) of neural population changes. Black and red dotted lines indicate intrinsic and extrinsic connections modulated by motor imagery, respectively. The results indicate that while all motor stimuli positively affect the regional activity in primary motor cortex (M1), motor imagery negatively modulates connection from supplementary motor area (SMA) to M1, resulting in the suppressive influence of SMA on M1. These results are consistent with the findings of previous fMRI studies (Kasess et al., 2008; Gerardin et al., 2000).

Mentions: Fig. 7 shows the parameter estimates as a network model. The results indicate that while all motor stimuli positively affect the regional activity in M1, motor imagery negatively modulates the connection from SMA to M1, resulting in the suppressive influence of SMA on M1. Quantitatively, the strength of connectivity from SMA to M1, − 0.49 is significantly reduced by motor imagery, − 0.77. This suppressive influence causes reduced activity in M1 during motor imagery. Interestingly, we also found that motor imagery positively modulates the connection from M1 to SMA.


Dynamic causal modelling for functional near-infrared spectroscopy.

Tak S, Kempny AM, Friston KJ, Leff AP, Penny WD - Neuroimage (2015)

Model with estimated parameters of effective connectivity. The units of connections are the rates (Hz) of neural population changes. Black and red dotted lines indicate intrinsic and extrinsic connections modulated by motor imagery, respectively. The results indicate that while all motor stimuli positively affect the regional activity in primary motor cortex (M1), motor imagery negatively modulates connection from supplementary motor area (SMA) to M1, resulting in the suppressive influence of SMA on M1. These results are consistent with the findings of previous fMRI studies (Kasess et al., 2008; Gerardin et al., 2000).
© Copyright Policy - CC BY-NC-ND
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4401444&req=5

f0035: Model with estimated parameters of effective connectivity. The units of connections are the rates (Hz) of neural population changes. Black and red dotted lines indicate intrinsic and extrinsic connections modulated by motor imagery, respectively. The results indicate that while all motor stimuli positively affect the regional activity in primary motor cortex (M1), motor imagery negatively modulates connection from supplementary motor area (SMA) to M1, resulting in the suppressive influence of SMA on M1. These results are consistent with the findings of previous fMRI studies (Kasess et al., 2008; Gerardin et al., 2000).
Mentions: Fig. 7 shows the parameter estimates as a network model. The results indicate that while all motor stimuli positively affect the regional activity in M1, motor imagery negatively modulates the connection from SMA to M1, resulting in the suppressive influence of SMA on M1. Quantitatively, the strength of connectivity from SMA to M1, − 0.49 is significantly reduced by motor imagery, − 0.77. This suppressive influence causes reduced activity in M1 during motor imagery. Interestingly, we also found that motor imagery positively modulates the connection from M1 to SMA.

Bottom Line: Specifically, we present a generative model of how observed fNIRS data are caused by interactions among hidden neuronal states.Inversion of this generative model, using an established Bayesian framework (variational Laplace), then enables inference about changes in directed connectivity at the neuronal level.Using experimental data acquired during motor imagery and motor execution tasks, we show that directed (i.e., effective) connectivity from the supplementary motor area to the primary motor cortex is negatively modulated by motor imagery, and this suppressive influence causes reduced activity in the primary motor cortex during motor imagery.

View Article: PubMed Central - PubMed

Affiliation: Wellcome Trust Centre for Neuroimaging, University College London, 12 Queen Square, London WC1N 3BG, UK. Electronic address: s.tak@ucl.ac.uk.

No MeSH data available.