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Meditation increases the depth of information processing and improves the allocation of attention in space.

van Leeuwen S, Singer W, Melloni L - Front Hum Neurosci (2012)

Bottom Line: Specifically, we investigated the effect of attentional training on the global precedence effect, i.e., faster detection of targets on a global than on a local level.Analysis of reaction times confirmed this prediction.In contrast with control group, which showed a local target selection effect only in the P1 and a global target selection effect in the P3 component, meditators showed effects of local information processing in the P1, N2, and P3 and of global processing for the N1, N2, and P3.

View Article: PubMed Central - PubMed

Affiliation: Department of Neurophysiology, Max Planck Institute for Brain Research Frankfurt am Main, Germany.

ABSTRACT
During meditation, practitioners are required to center their attention on a specific object for extended periods of time. When their thoughts get diverted, they learn to quickly disengage from the distracter. We hypothesized that learning to respond to the dual demand of engaging attention on specific objects and disengaging quickly from distracters enhances the efficiency by which meditation practitioners can allocate attention. We tested this hypothesis in a global-to-local task while measuring electroencephalographic activity from a group of eight highly trained Buddhist monks and nuns and a group of eight age and education matched controls with no previous meditation experience. Specifically, we investigated the effect of attentional training on the global precedence effect, i.e., faster detection of targets on a global than on a local level. We expected to find a reduced global precedence effect in meditation practitioners but not in controls, reflecting that meditators can more quickly disengage their attention from the dominant global level. Analysis of reaction times confirmed this prediction. To investigate the underlying changes in brain activity and their time course, we analyzed event-related potentials. Meditators showed an enhanced ability to select the respective target level, as reflected by enhanced processing of target level information. In contrast with control group, which showed a local target selection effect only in the P1 and a global target selection effect in the P3 component, meditators showed effects of local information processing in the P1, N2, and P3 and of global processing for the N1, N2, and P3. Thus, meditators seem to display enhanced depth of processing. In addition, meditation altered the uptake of information such that meditators selected target level information earlier in the processing sequence than controls. In a longitudinal experiment, we could replicate the behavioral effects, suggesting that meditation modulates attention already after a 4-day meditation retreat. Together, these results suggest that practicing meditation enhances the speed with which attention can be allocated and relocated, thus increasing the depth of information processing and reducing response latency.

No MeSH data available.


Data-driven analysis based on precedence mapping. Each head plot shows the electrodes exhibiting an effect of precedence averaged over the corresponding time period. Each panel, (A–E), shows the amplitude difference between local and global targets (local–global) averaged over the corresponding time period and electrodes. Meditators are shown in red, controls in blue. Error bars represent the SEM.
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Figure 7: Data-driven analysis based on precedence mapping. Each head plot shows the electrodes exhibiting an effect of precedence averaged over the corresponding time period. Each panel, (A–E), shows the amplitude difference between local and global targets (local–global) averaged over the corresponding time period and electrodes. Meditators are shown in red, controls in blue. Error bars represent the SEM.

Mentions: To evaluate effects not captured by the component-based ERP analysis we carried out a data-driven analysis, in which we first collapsed the data from the meditator and control group and then calculated a t-test at p = 0.01 of precedence (Local vs. Global) per time point and electrode. We applied a cluster threshold that included only those electrodes and time points that were significant over a period of 15 ms or more over at least two contiguous electrodes (Thorpe et al., 1996; Dehaene et al., 2001; Murray et al., 2001). Anterior effects (frontal electrodes) were excluded due to the potential contamination by eye movements/blinks in these regions. Figure 7 illustrates the electrodes and topographies of each of the five clusters revealed with this procedure. Precedence effects were observed over temporal electrodes (50, 56, 57, 64) between 45 and 75 ms, over frontal electrodes (11, 12, 19) between 65 and 80 ms, over right occipital electrodes (82, 83, 88, 89, 90) between 140 and 190 ms, over centroparietal electrodes (31, 52, 53, 54, 59, 60, 61, 62, 66, 70, 71, 72, 77, 78, 79, 80, 86, 87) between 255 and 290 ms, and finally over centroparietal electrodes (50, 51, 52, 53, 58, 59, 60, 61, 65, 66, 67, 69, 70, 71, 74, 76, 77, 78, 82, 83, 84, 85, 86, 89, 90, 91, 92, 96, 97) between 380 and 400 ms. Mean amplitudes per cluster were then submitted to a repeated measures ANOVA with factors precedence and group.


Meditation increases the depth of information processing and improves the allocation of attention in space.

van Leeuwen S, Singer W, Melloni L - Front Hum Neurosci (2012)

Data-driven analysis based on precedence mapping. Each head plot shows the electrodes exhibiting an effect of precedence averaged over the corresponding time period. Each panel, (A–E), shows the amplitude difference between local and global targets (local–global) averaged over the corresponding time period and electrodes. Meditators are shown in red, controls in blue. Error bars represent the SEM.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3351800&req=5

Figure 7: Data-driven analysis based on precedence mapping. Each head plot shows the electrodes exhibiting an effect of precedence averaged over the corresponding time period. Each panel, (A–E), shows the amplitude difference between local and global targets (local–global) averaged over the corresponding time period and electrodes. Meditators are shown in red, controls in blue. Error bars represent the SEM.
Mentions: To evaluate effects not captured by the component-based ERP analysis we carried out a data-driven analysis, in which we first collapsed the data from the meditator and control group and then calculated a t-test at p = 0.01 of precedence (Local vs. Global) per time point and electrode. We applied a cluster threshold that included only those electrodes and time points that were significant over a period of 15 ms or more over at least two contiguous electrodes (Thorpe et al., 1996; Dehaene et al., 2001; Murray et al., 2001). Anterior effects (frontal electrodes) were excluded due to the potential contamination by eye movements/blinks in these regions. Figure 7 illustrates the electrodes and topographies of each of the five clusters revealed with this procedure. Precedence effects were observed over temporal electrodes (50, 56, 57, 64) between 45 and 75 ms, over frontal electrodes (11, 12, 19) between 65 and 80 ms, over right occipital electrodes (82, 83, 88, 89, 90) between 140 and 190 ms, over centroparietal electrodes (31, 52, 53, 54, 59, 60, 61, 62, 66, 70, 71, 72, 77, 78, 79, 80, 86, 87) between 255 and 290 ms, and finally over centroparietal electrodes (50, 51, 52, 53, 58, 59, 60, 61, 65, 66, 67, 69, 70, 71, 74, 76, 77, 78, 82, 83, 84, 85, 86, 89, 90, 91, 92, 96, 97) between 380 and 400 ms. Mean amplitudes per cluster were then submitted to a repeated measures ANOVA with factors precedence and group.

Bottom Line: Specifically, we investigated the effect of attentional training on the global precedence effect, i.e., faster detection of targets on a global than on a local level.Analysis of reaction times confirmed this prediction.In contrast with control group, which showed a local target selection effect only in the P1 and a global target selection effect in the P3 component, meditators showed effects of local information processing in the P1, N2, and P3 and of global processing for the N1, N2, and P3.

View Article: PubMed Central - PubMed

Affiliation: Department of Neurophysiology, Max Planck Institute for Brain Research Frankfurt am Main, Germany.

ABSTRACT
During meditation, practitioners are required to center their attention on a specific object for extended periods of time. When their thoughts get diverted, they learn to quickly disengage from the distracter. We hypothesized that learning to respond to the dual demand of engaging attention on specific objects and disengaging quickly from distracters enhances the efficiency by which meditation practitioners can allocate attention. We tested this hypothesis in a global-to-local task while measuring electroencephalographic activity from a group of eight highly trained Buddhist monks and nuns and a group of eight age and education matched controls with no previous meditation experience. Specifically, we investigated the effect of attentional training on the global precedence effect, i.e., faster detection of targets on a global than on a local level. We expected to find a reduced global precedence effect in meditation practitioners but not in controls, reflecting that meditators can more quickly disengage their attention from the dominant global level. Analysis of reaction times confirmed this prediction. To investigate the underlying changes in brain activity and their time course, we analyzed event-related potentials. Meditators showed an enhanced ability to select the respective target level, as reflected by enhanced processing of target level information. In contrast with control group, which showed a local target selection effect only in the P1 and a global target selection effect in the P3 component, meditators showed effects of local information processing in the P1, N2, and P3 and of global processing for the N1, N2, and P3. Thus, meditators seem to display enhanced depth of processing. In addition, meditation altered the uptake of information such that meditators selected target level information earlier in the processing sequence than controls. In a longitudinal experiment, we could replicate the behavioral effects, suggesting that meditation modulates attention already after a 4-day meditation retreat. Together, these results suggest that practicing meditation enhances the speed with which attention can be allocated and relocated, thus increasing the depth of information processing and reducing response latency.

No MeSH data available.