6 research outputs found
Regressors in the null model which contains the same MB and MF regressors for the Active and Sham stimulation conditions.
<p>MF = model-free; MB = model-based; SE = standard error. Lag denotes the effect of time. Bold-face indicates p<.05 uncorrected for multiple comparisons.</p
Contrasts performed on the full model.
<p>MF = model-free; MB = model-based; SE = standard error; χ<sup>2</sup> = chi-square distribution; df = degrees of freedom; Lag denotes the effect of time. Bold-face indicates p<.05 uncorrected for multiple comparisons.</p
Stay probabilities as a function of reward and transition on previous trial.
<p>Participants showed a pattern of stay probabilities characteristic of hybrid model-based/model-free control (cf. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0086850#pone-0086850-g001" target="_blank">Figure 1B</a>) during both Sham and Active stimulation of dlPFC. Error bars indicate SEM.</p
Statistical power to detect true effects.
<p>We estimated statistical power in our study based on effect size estimates taken from the published literature. We could then compute the power in our study based on 22 participants and a false positive rate of 0.05 (two-sided alpha). Assuming any true effect of tDCS would have a similar magnitude as the studies shown in the figure, the current study had a power of 50–80%.</p
Model-based and model-free influences on choice.
<p>We estimated the dependence of a choice at trial <i>t</i> on reward and transition events in trials t-1 up to t-3. These regression coefficients can be interpreted as model-based and model-free influences on choice, and larger coefficients indicate a stronger influence over choice. Firstly, all regression coefficients in the plot are significantly larger than zero, suggesting that model-based and model-free systems did not just rely on events on the previous trial but rather on events as far as 3 trials in the past. We did not observe any difference between Active and Sham conditions. Error bars indicate SEM.</p
Model comparison between a null model (one set of model-based and model-free regressors for both stimulation conditions) and more complex models that allow for an effect of tDCS on model-based control, model-free control, or both, which shows the null model is significantly more plausible than any of the models that allow for an effect of tDCS on behavioral control.
<p>The second column refers to the number of regressors in the hierarchical regression at the individual subject level (cf. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0086850#pone-0086850-t001" target="_blank">Table 1</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0086850#pone-0086850-t003" target="_blank">3</a>).</p><p>BIC: Bayesian Information Criterion; AIC: Akaike’s Information Criterion.</p