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. 2011 Feb 14;54(4):2950-9.
doi: 10.1016/j.neuroimage.2010.10.046. Epub 2010 Oct 23.

Linking inter-individual differences in neural activation and behavior to intrinsic brain dynamics

Affiliations

Linking inter-individual differences in neural activation and behavior to intrinsic brain dynamics

Maarten Mennes et al. Neuroimage. .

Abstract

The brain's energy economy excessively favors intrinsic, spontaneous neural activity over extrinsic, evoked activity, presumably to maintain its internal organization. Emerging hypotheses capable of explaining such an investment posit that the brain's intrinsic functional architecture encodes a blueprint for its repertoire of responses to the external world. Yet, there is little evidence directly linking intrinsic and extrinsic activity in the brain. Here we relate differences among individuals in the magnitude of task-evoked activity during performance of an Eriksen flanker task, to spontaneous oscillatory phenomena observed during rest. Specifically, we focused on the amplitude of low-frequency oscillations (LFO, 0.01-0.1 Hz) present in the BOLD signal. LFO amplitude measures obtained during rest successfully predicted the magnitude of task-evoked activity in a variety of regions that were all activated during performance of the flanker task. In these regions, higher LFO amplitude at rest predicted higher task-evoked activity. LFO amplitude measures obtained during rest were also found to have robust predictive value for behavior. In midline cingulate regions, LFO amplitudes predicted not only the speed and consistency of performance but also the magnitude of the behavioral congruency effect embedded in the flanker task. These results support the emerging hypothesis that the brain's repertoire of responses to the external world are represented and updated in the brain's intrinsic functional architecture.

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Figures

Figure 1
Figure 1. Amplitude of low-frequency oscillations (LFO) observed in the BOLD signal during rest predicted task-evoked activation
A. Regions exhibiting a significant relationship between resting state fractional amplitude of low-frequency fluctuations (fALFF) and overall (Congruent + Incongruent > Baseline) activity evoked by the flanker task. Yellow: Regions exhibiting a significant resting state fALFF/task-evoked activity relationship. Red: regions exhibiting significant overall (Congruent + Incongruent > Baseline) task-evoked activation. Blue: regions exhibiting significant overall task-evoked deactivation. B. Regression lines for all clusters exhibiting a significant linear relationship between resting state fALFF and overall task-evoked activity. Inset shows the regression lines for all significant clusters, while the scatter plot illustrates the actual relationship for the regression line shown in black in the inset. C. Comparison of regions in which either resting state fALFF or resting state functional connectivity (RSFC) significantly predicted overall task-evoked activity. Regions (shown in yellow) in which resting state fALFF predicted overall (Congruent + Incongruent > Baseline) task-evoked activity were located within regions of significant overall task-evoked activation. Regions (shown in green) in which RSFC predicted overall task-evoked activity were mainly located in transition zones between significant overall task-evoked activation and deactivation (see Mennes et al., 2010). We observed only 7% overlap (shown in violet) between the results obtained for fALFF and those observed for RSFC. Red: Significant overall flanker task activation (Congruent + Incongruent > Baseline). Blue: Significant overall flanker task deactivation.
Figure 2
Figure 2. Resting state fALFF predicted behavioral performance during the Eriksen flanker task
For both congruent (green background) and incongruent (rose background) trials in the flanker task, areas depicted in blue indicate regions in which higher resting state fALFF was associated with better performance, i.e., lower mean reaction time (mean RT; Top) or smaller coefficient of variation (CV; [standard deviation/mean RT]; Bottom). Areas depicted in yellow/orange indicate regions in which higher resting state fALFF was associated with more variable performance (higher CV). We observed no regions that showed a significant relationship between resting state fALFF and mean RT for the congruent trials. Resting state fALFF also predicted behavioral performance associated with the congruency effect (brown background; [mean RT incongruent – mean RT congruent]/mean RT congruent; see also Figure 4). Areas depicted in blue indicate regions in which higher resting state fALFF was associated with a smaller congruency effect. Areas depicted in yellow/orange indicate regions in which higher resting state fALFF was associated with a larger effect of congruency on mean RT. Results for resting state ALFF predicting behavioral performance are shown in Supplementary Figure S3. Results for task-evoked activity predicting behavioral performance are shown in Supplementary Figure S4. Results for fALFF predicting behavioral performance when mean RT and CV were included in one model are shown in Supplementary Figure S7.
Figure 3
Figure 3. Overlap between regions exhibiting a resting state fALFF/behavior relationship as well as a resting state fALFF/task-evoked activity relationship
Top: Regions exhibiting both a relationship between resting state fALFF and coefficient of variation (CV) for the congruent trials as well as a relationship between resting state fALFF and task-evoked activity associated with the congruent trials of the flanker task (Congruent > Baseline). Bottom: Regions exhibiting both a relationship between resting state fALFF and mean reaction time (mean RT) for the incongruent trials as well as a relationship between resting state fALFF and task-evoked activity associated with the incongruent trials of the flanker task (Incongruent > Baseline). MNI coordinates for the region overlapping between the top and bottom surface maps are x=2, y=20, z=38. Graphs on the right illustrate the linear relationships between resting state fALFF and behavior and resting state fALFF and task-evoked activity for the regions shown on the brains on the left. Given the marked difference in values between behavior and task-evoked activity, graphs are shown separately for each measure. However, fALFF, shown on the x-axis, is the same for the behavior and the task-evoked activity graphs.
Figure 4
Figure 4. Intrinsic properties of medial wall structures, but extrinsic properties of lateral prefrontal cortical areas predicted behavioral performance associated with the congruency effect
Regions exhibiting a significant positive (violet) or negative (green) relationship between resting state fALFF and the behavioral congruency effect ([mean RT incongruent – mean RT congruent]/mean RT congruent) were mainly found in the medial wall. In contrast, regions exhibiting a significant relationship (positive, red; negative, blue) between task-evoked activity observed for the congruency effect (Incongruent > Congruent) and the behavioral congruency effect were mainly located in lateral frontal-parietal cortex.

References

    1. Andersson JLR, Jenkinson M, Smith SM. TR07JA2 : Non-linear registration, aka Spatial normalisation. FMRIB Analysis Group Technical Reports. 2007 http://www.fmrib.ox.ac.uk/analysis/techrep/
    1. Barnes A, Bullmore ET, Suckling J. Endogenous human brain dynamics recover slowly following cognitive effort. PLoS One. 2009;4:e6626. - PMC - PubMed
    1. Beckmann CF, DeLuca M, Devlin JT, Smith SM. Investigations into resting-state connectivity using independent component analysis. Philos Trans R Soc Lond B Biol Sci. 2005;360:1001–1013. - PMC - PubMed
    1. Bellec P, Rosa-Neto P, Lyttelton OC, Benali H, Evans AC. Multi-level bootstrap analysis of stable clusters in resting-state fMRI. Neuroimage. 2010;51:1126–1139. - PubMed
    1. Biswal B, Yetkin FZ, Haughton VM, Hyde JS. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med. 1995;34:537–541. - PubMed

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