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Decomposing neural synchrony: toward an explanation for near-zero phase-lag in cortical oscillatory networks.

Rajagovindan R, Ding M - PLoS ONE (2008)

Bottom Line: Recent theories have considered the importance of this phenomenon in establishing an effective communication framework among neuronal ensembles.Two factors, among possibly others, can be hypothesized to contribute to the near-zero phase-lag relationship: (1) positively correlated common input with no significant relative time delay and (2) bidirectional interaction.A rigorous mathematical theorem is used for the first time to empirically examine the factors that contribute to this phenomenon.

View Article: PubMed Central - PubMed

Affiliation: The J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, Florida, USA.

ABSTRACT

Background: Synchronized oscillation in cortical networks has been suggested as a mechanism for diverse functions ranging from perceptual binding to memory formation to sensorimotor integration. Concomitant with synchronization is the occurrence of near-zero phase-lag often observed between network components. Recent theories have considered the importance of this phenomenon in establishing an effective communication framework among neuronal ensembles.

Methodology/principal findings: Two factors, among possibly others, can be hypothesized to contribute to the near-zero phase-lag relationship: (1) positively correlated common input with no significant relative time delay and (2) bidirectional interaction. Thus far, no empirical test of these hypotheses has been possible for lack of means to tease apart the specific causes underlying the observed synchrony. In this work simulation examples were first used to illustrate the ideas. A quantitative method that decomposes the statistical interdependence between two cortical areas into a feed-forward, a feed-back and a common-input component was then introduced and applied to test the hypotheses on multichannel local field potential recordings from two behaving monkeys.

Conclusion/significance: The near-zero phase-lag phenomenon is important in the study of large-scale oscillatory networks. A rigorous mathematical theorem is used for the first time to empirically examine the factors that contribute to this phenomenon. Given the critical role that oscillatory activity is likely to play in the regulation of biological processes at all levels, the significance of the proposed method may extend beyond systems neuroscience, the level at which the present analysis is conceived and performed.

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Influence of common input on phase-lag.Scatter plot showing strong negative correlation between instantaneous causality (IC) and magnitude of phase-lag between site pairs (S1,7b) in monkeys (A) GE and (B) LU.
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pone-0003649-g004: Influence of common input on phase-lag.Scatter plot showing strong negative correlation between instantaneous causality (IC) and magnitude of phase-lag between site pairs (S1,7b) in monkeys (A) GE and (B) LU.

Mentions: For each site pair the phase-lag was estimated for each trial and the estimated value was used to sort all trials into subensembles. The phase-lag and the instantaneous causality measure for each subensemble constituted a point on a scatter plot. Figure 4 shows the result for (S1,7b) in monkeys GE and LU. Clearly, the two quantities are negatively correlated, indicating that as the instantaneous causality increases, the phase-lag decreases and, in fact, approaches zero. Spearman's rank correlation and Spearman's rank partial correlation coefficients were computed for all the site pairs and listed in Table 4 and 5. All correlation coefficients were negative. Except for (M1,7b) in monkey GE, these correlation coefficients were statistically significant at pā€Š=ā€Š0.05 level (one tail t-test) (Table 4). By partialing out the effects of the directional influences, the correlation for (M1,7b) also became significant (Table 5).


Decomposing neural synchrony: toward an explanation for near-zero phase-lag in cortical oscillatory networks.

Rajagovindan R, Ding M - PLoS ONE (2008)

Influence of common input on phase-lag.Scatter plot showing strong negative correlation between instantaneous causality (IC) and magnitude of phase-lag between site pairs (S1,7b) in monkeys (A) GE and (B) LU.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2573956&req=5

pone-0003649-g004: Influence of common input on phase-lag.Scatter plot showing strong negative correlation between instantaneous causality (IC) and magnitude of phase-lag between site pairs (S1,7b) in monkeys (A) GE and (B) LU.
Mentions: For each site pair the phase-lag was estimated for each trial and the estimated value was used to sort all trials into subensembles. The phase-lag and the instantaneous causality measure for each subensemble constituted a point on a scatter plot. Figure 4 shows the result for (S1,7b) in monkeys GE and LU. Clearly, the two quantities are negatively correlated, indicating that as the instantaneous causality increases, the phase-lag decreases and, in fact, approaches zero. Spearman's rank correlation and Spearman's rank partial correlation coefficients were computed for all the site pairs and listed in Table 4 and 5. All correlation coefficients were negative. Except for (M1,7b) in monkey GE, these correlation coefficients were statistically significant at pā€Š=ā€Š0.05 level (one tail t-test) (Table 4). By partialing out the effects of the directional influences, the correlation for (M1,7b) also became significant (Table 5).

Bottom Line: Recent theories have considered the importance of this phenomenon in establishing an effective communication framework among neuronal ensembles.Two factors, among possibly others, can be hypothesized to contribute to the near-zero phase-lag relationship: (1) positively correlated common input with no significant relative time delay and (2) bidirectional interaction.A rigorous mathematical theorem is used for the first time to empirically examine the factors that contribute to this phenomenon.

View Article: PubMed Central - PubMed

Affiliation: The J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, Florida, USA.

ABSTRACT

Background: Synchronized oscillation in cortical networks has been suggested as a mechanism for diverse functions ranging from perceptual binding to memory formation to sensorimotor integration. Concomitant with synchronization is the occurrence of near-zero phase-lag often observed between network components. Recent theories have considered the importance of this phenomenon in establishing an effective communication framework among neuronal ensembles.

Methodology/principal findings: Two factors, among possibly others, can be hypothesized to contribute to the near-zero phase-lag relationship: (1) positively correlated common input with no significant relative time delay and (2) bidirectional interaction. Thus far, no empirical test of these hypotheses has been possible for lack of means to tease apart the specific causes underlying the observed synchrony. In this work simulation examples were first used to illustrate the ideas. A quantitative method that decomposes the statistical interdependence between two cortical areas into a feed-forward, a feed-back and a common-input component was then introduced and applied to test the hypotheses on multichannel local field potential recordings from two behaving monkeys.

Conclusion/significance: The near-zero phase-lag phenomenon is important in the study of large-scale oscillatory networks. A rigorous mathematical theorem is used for the first time to empirically examine the factors that contribute to this phenomenon. Given the critical role that oscillatory activity is likely to play in the regulation of biological processes at all levels, the significance of the proposed method may extend beyond systems neuroscience, the level at which the present analysis is conceived and performed.

Show MeSH