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In a group of 20 elderly (mean age 62.1 years) right-handed individuals, we applied transcranial direct current stimulation (tDCS; 20 minutes, 1 mA) over the right temporoparietal cortex, while subjects acquired the correct position of buildings on a street map using an associative learning paradigm.

Using Instagram data from 166 individuals, we applied machine learning tools to successfully identify markers of depression.

To account for the repeated measures within individuals, we applied multilevel logistic regression [ 19].

To search for possible close relative pairs among the individuals, we applied software KING (version 1.4) [ 92] to analyze the entire dataset.

To determine the extent of human full length L1 polymorphism between unrelated individuals, we applied SIMPLE to seven individual genomic DNA samples from non-related Caucasian individuals to assess the degree of full-length L1 polymorphism between these individuals.

For the primary analysis, using the unrelated individuals, we applied the multivariate MAGWAS approach (Brown et al. 2012b), sensitive to any pattern of variation of cytotoxicity measurements due to genotype.

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To take into account correlation among the repeated observations within an individual, we applied linear mixed-effect regression models in examining the differences in BMI change across the baseline BMI categories and periods with an interaction term of baseline BMI × period and their main effects included in the model.

Additionally, in order to verify whether the power law observed in the recency rank distribution is rooted on the temporal semantics of individuals' trajectories, we applied our rank-based approach to randomized versions of both empirical datasets (D1 and D2).

For individual data, we applied two design matrices, the Time design matrix and the Orientation design matrix, to estimate the beta values for each duration and orientation parameter of S1.

Our method allows for the simultaneous detection of 34 parameters from tens of thousands of individual synapses.CONCLUSION: We applied Mass Synaptometry to analyze 34 parameters simultaneously on more than 390,000 synaptosomes from 13 human brain samples.

To control for satisfactory precision with respect to individual metabolites, we applied a test to ensure that the data correlated well with known experimental factors.

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