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Long-term enhancement of brain function and cognition using cognitive training and brain stimulation.

Snowball A, Tachtsidis I, Popescu T, Thompson J, Delazer M, Zamarian L, Zhu T, Cohen Kadosh R - Curr. Biol. (2013)

Bottom Line: These behavioral improvements were associated with defined hemodynamic responses consistent with more efficient neurovascular coupling within the left DLPFC.These results demonstrate that, depending on the learning regime, TRNS can induce long-term enhancement of cognitive and brain functions.Such findings have significant implications for basic and translational neuroscience, highlighting TRNS as a viable approach to enhancing learning and high-level cognition by the long-term modulation of neuroplasticity.

View Article: PubMed Central - PubMed

Affiliation: Department of Experimental Psychology, University of Oxford, Oxford, OX1 3UD, UK.

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The Effect of TRNS on Arithmetic Performance(A) Calculation learning rates during training were significantly higher in the TRNS group relative to sham controls.(B) Drill learning rates during training were significantly higher in the TRNS group relative to sham controls.(C) Calculation RTs during testing were significantly faster in the TRNS group relative to sham controls for both old and new problems.(D) Drill RTs during testing did not differ between TRNS and sham groups for either old or new problems.Error bars indicate one SEM. Significant differences are marked with asterisks. See also Figure S2.
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fig2: The Effect of TRNS on Arithmetic Performance(A) Calculation learning rates during training were significantly higher in the TRNS group relative to sham controls.(B) Drill learning rates during training were significantly higher in the TRNS group relative to sham controls.(C) Calculation RTs during testing were significantly faster in the TRNS group relative to sham controls for both old and new problems.(D) Drill RTs during testing did not differ between TRNS and sham groups for either old or new problems.Error bars indicate one SEM. Significant differences are marked with asterisks. See also Figure S2.

Mentions: For assessment of skill acquisition, it is recommended that calculation and drill learning be modeled by fitting of RT data to a power law function [9] (Supplemental Experimental Procedures). This modeling allows one to quantify both initial performance (B) and learning rates (α) for each learning regime. For both calculation and drill arithmetic, there were no significant differences between the groups with regard to initial performance, indicating similar proficiency at the beginning of training (p values > 0.27). In contrast, calculation and drill learning rates were significantly higher for the transcranial random noise stimulation (TRNS) group relative to sham controls [calculation, F(1,22) = 6.75, p = 0.016; drill, F(1,22) = 10.24, p = 0.004, using initial performance as a covariate [10]; Figures 2A and 2B]. This result indicates that TRNS facilitated the speed of learning for both calculation and drill regimes.


Long-term enhancement of brain function and cognition using cognitive training and brain stimulation.

Snowball A, Tachtsidis I, Popescu T, Thompson J, Delazer M, Zamarian L, Zhu T, Cohen Kadosh R - Curr. Biol. (2013)

The Effect of TRNS on Arithmetic Performance(A) Calculation learning rates during training were significantly higher in the TRNS group relative to sham controls.(B) Drill learning rates during training were significantly higher in the TRNS group relative to sham controls.(C) Calculation RTs during testing were significantly faster in the TRNS group relative to sham controls for both old and new problems.(D) Drill RTs during testing did not differ between TRNS and sham groups for either old or new problems.Error bars indicate one SEM. Significant differences are marked with asterisks. See also Figure S2.
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fig2: The Effect of TRNS on Arithmetic Performance(A) Calculation learning rates during training were significantly higher in the TRNS group relative to sham controls.(B) Drill learning rates during training were significantly higher in the TRNS group relative to sham controls.(C) Calculation RTs during testing were significantly faster in the TRNS group relative to sham controls for both old and new problems.(D) Drill RTs during testing did not differ between TRNS and sham groups for either old or new problems.Error bars indicate one SEM. Significant differences are marked with asterisks. See also Figure S2.
Mentions: For assessment of skill acquisition, it is recommended that calculation and drill learning be modeled by fitting of RT data to a power law function [9] (Supplemental Experimental Procedures). This modeling allows one to quantify both initial performance (B) and learning rates (α) for each learning regime. For both calculation and drill arithmetic, there were no significant differences between the groups with regard to initial performance, indicating similar proficiency at the beginning of training (p values > 0.27). In contrast, calculation and drill learning rates were significantly higher for the transcranial random noise stimulation (TRNS) group relative to sham controls [calculation, F(1,22) = 6.75, p = 0.016; drill, F(1,22) = 10.24, p = 0.004, using initial performance as a covariate [10]; Figures 2A and 2B]. This result indicates that TRNS facilitated the speed of learning for both calculation and drill regimes.

Bottom Line: These behavioral improvements were associated with defined hemodynamic responses consistent with more efficient neurovascular coupling within the left DLPFC.These results demonstrate that, depending on the learning regime, TRNS can induce long-term enhancement of cognitive and brain functions.Such findings have significant implications for basic and translational neuroscience, highlighting TRNS as a viable approach to enhancing learning and high-level cognition by the long-term modulation of neuroplasticity.

View Article: PubMed Central - PubMed

Affiliation: Department of Experimental Psychology, University of Oxford, Oxford, OX1 3UD, UK.

Show MeSH