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Granger causal time-dependent source connectivity in the somatosensory network.

Gao L, Sommerlade L, Coffman B, Zhang T, Stephen JM, Li D, Wang J, Grebogi C, Schelter B - Sci Rep (2015)

Bottom Line: However, the underlying neural patterns are confounded by time-dependent dynamics, non-stationarity and observational noise contamination.Source analysis confirmed that somatosensory evoked MEG was mainly generated from the contralateral primary somatosensory cortex (SI) and bilateral secondary somatosensory cortices (SII).These results are consistent with established anatomical connectivity between somatosensory regions and previous source modeling results, thereby providing empirical validation of the time-varying connectivity analysis.

View Article: PubMed Central - PubMed

Affiliation: 1] Institute of Biomedical Engineering, Key Laboratory of Biomedical Information Engineering of Education Ministry, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, P. R. China [2] State Key Laboratory of Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, P. R. China.

ABSTRACT
Exploration of transient Granger causal interactions in neural sources of electrophysiological activities provides deeper insights into brain information processing mechanisms. However, the underlying neural patterns are confounded by time-dependent dynamics, non-stationarity and observational noise contamination. Here we investigate transient Granger causal interactions using source time-series of somatosensory evoked magnetoencephalographic (MEG) elicited by air puff stimulation of right index finger and recorded using 306-channel MEG from 21 healthy subjects. A new time-varying connectivity approach, combining renormalised partial directed coherence with state space modelling, is employed to estimate fast changing information flow among the sources. Source analysis confirmed that somatosensory evoked MEG was mainly generated from the contralateral primary somatosensory cortex (SI) and bilateral secondary somatosensory cortices (SII). Transient Granger causality shows a serial processing of somatosensory information, 1) from contralateral SI to contralateral SII, 2) from contralateral SI to ipsilateral SII, 3) from contralateral SII to contralateral SI, and 4) from contralateral SII to ipsilateral SII. These results are consistent with established anatomical connectivity between somatosensory regions and previous source modeling results, thereby providing empirical validation of the time-varying connectivity analysis. We argue that the suggested approach provides novel information regarding transient cortical dynamic connectivity, which previous approaches could not assess.

No MeSH data available.


Time-frequency representations of rPDC as a measure of time-dependent Granger causal influences within the neural network between SI-l, SII-l and SII-r averaged across all the subjects. The regions circled by blue lines had significantly larger rPDC values than those in the reference interval from -100 ms to 0 ms (P < 0.01).
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f3: Time-frequency representations of rPDC as a measure of time-dependent Granger causal influences within the neural network between SI-l, SII-l and SII-r averaged across all the subjects. The regions circled by blue lines had significantly larger rPDC values than those in the reference interval from -100 ms to 0 ms (P < 0.01).

Mentions: Single-trial data of somatosensory source waveforms (SI-l, SII-l and SII-r), including 120 to 180 trials for each source of each subject, obtained from source analysis, were used in the rPDC estimation to assess the relationship among sources. The rPDC order, p, selected using Akaike’s Information Criterion (AIC), ranged from 30 to 60; the order was selected for each analysis optimally using AIC. We also projected the data in the reference interval from -100 ms to 0 ms to the representative sources. Time-varying effective connectivity patterns among somatosensory sources for the subjects, represented as time-frequency regions that have significantly increased rPDC values compared with the reference interval (P < 0.01), are summarized into the following temporally distinct groups within the post-stimulus interval around 0-320 ms (Fig. 3). Significant increases in effective connectivity are observed from SI-l to both SII-l (20-230 ms, 5-25 Hz) and SII-r (20-230 ms, 5-25 Hz), from SII-l to SI-l (90-200 ms, 5-17 Hz) and from SII-l to SII-r (220-320 ms, 5-19 Hz). The time-resolved directed network structure can be inferred from Fig. 3 and Table 2 (see also Fig. 4). The cortical information was mainly transmitted from SI-l to SII-l and to SII-r (20-230 ms, the latter one about 5 ms later than the former). Later during the post stimulus interval, the information flow was observed from SII-l to SI-l (90-200 ms) and then to SII-r (220-320 ms).


Granger causal time-dependent source connectivity in the somatosensory network.

Gao L, Sommerlade L, Coffman B, Zhang T, Stephen JM, Li D, Wang J, Grebogi C, Schelter B - Sci Rep (2015)

Time-frequency representations of rPDC as a measure of time-dependent Granger causal influences within the neural network between SI-l, SII-l and SII-r averaged across all the subjects. The regions circled by blue lines had significantly larger rPDC values than those in the reference interval from -100 ms to 0 ms (P < 0.01).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4441010&req=5

f3: Time-frequency representations of rPDC as a measure of time-dependent Granger causal influences within the neural network between SI-l, SII-l and SII-r averaged across all the subjects. The regions circled by blue lines had significantly larger rPDC values than those in the reference interval from -100 ms to 0 ms (P < 0.01).
Mentions: Single-trial data of somatosensory source waveforms (SI-l, SII-l and SII-r), including 120 to 180 trials for each source of each subject, obtained from source analysis, were used in the rPDC estimation to assess the relationship among sources. The rPDC order, p, selected using Akaike’s Information Criterion (AIC), ranged from 30 to 60; the order was selected for each analysis optimally using AIC. We also projected the data in the reference interval from -100 ms to 0 ms to the representative sources. Time-varying effective connectivity patterns among somatosensory sources for the subjects, represented as time-frequency regions that have significantly increased rPDC values compared with the reference interval (P < 0.01), are summarized into the following temporally distinct groups within the post-stimulus interval around 0-320 ms (Fig. 3). Significant increases in effective connectivity are observed from SI-l to both SII-l (20-230 ms, 5-25 Hz) and SII-r (20-230 ms, 5-25 Hz), from SII-l to SI-l (90-200 ms, 5-17 Hz) and from SII-l to SII-r (220-320 ms, 5-19 Hz). The time-resolved directed network structure can be inferred from Fig. 3 and Table 2 (see also Fig. 4). The cortical information was mainly transmitted from SI-l to SII-l and to SII-r (20-230 ms, the latter one about 5 ms later than the former). Later during the post stimulus interval, the information flow was observed from SII-l to SI-l (90-200 ms) and then to SII-r (220-320 ms).

Bottom Line: However, the underlying neural patterns are confounded by time-dependent dynamics, non-stationarity and observational noise contamination.Source analysis confirmed that somatosensory evoked MEG was mainly generated from the contralateral primary somatosensory cortex (SI) and bilateral secondary somatosensory cortices (SII).These results are consistent with established anatomical connectivity between somatosensory regions and previous source modeling results, thereby providing empirical validation of the time-varying connectivity analysis.

View Article: PubMed Central - PubMed

Affiliation: 1] Institute of Biomedical Engineering, Key Laboratory of Biomedical Information Engineering of Education Ministry, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, P. R. China [2] State Key Laboratory of Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, P. R. China.

ABSTRACT
Exploration of transient Granger causal interactions in neural sources of electrophysiological activities provides deeper insights into brain information processing mechanisms. However, the underlying neural patterns are confounded by time-dependent dynamics, non-stationarity and observational noise contamination. Here we investigate transient Granger causal interactions using source time-series of somatosensory evoked magnetoencephalographic (MEG) elicited by air puff stimulation of right index finger and recorded using 306-channel MEG from 21 healthy subjects. A new time-varying connectivity approach, combining renormalised partial directed coherence with state space modelling, is employed to estimate fast changing information flow among the sources. Source analysis confirmed that somatosensory evoked MEG was mainly generated from the contralateral primary somatosensory cortex (SI) and bilateral secondary somatosensory cortices (SII). Transient Granger causality shows a serial processing of somatosensory information, 1) from contralateral SI to contralateral SII, 2) from contralateral SI to ipsilateral SII, 3) from contralateral SII to contralateral SI, and 4) from contralateral SII to ipsilateral SII. These results are consistent with established anatomical connectivity between somatosensory regions and previous source modeling results, thereby providing empirical validation of the time-varying connectivity analysis. We argue that the suggested approach provides novel information regarding transient cortical dynamic connectivity, which previous approaches could not assess.

No MeSH data available.