Figure 2.

Schematic diagram of expected effects of activating aging neuronal gain control through cognitive training and non-invasive brain stimulation. Comparable to Figure 1A the y-axis indicates the activation value of units of the artificial neural network. The activation value as bounded by the sigmoidal activation function is between 0 and 1. The x-axis denotes incoming excitatory or inhibitory inputs, which ranged from −10 to +10. The s-shaped logistic activation function transforms the net inputs into the strength of an output signal. The responsivity of a unit to inhibitory or excitatory inputs is modulated by the slope of the function, which is regulated by the gain parameter (see Li et al., 2001). Reducing the slope flattens the activation function and the unit becomes less responsive, whereas steepening the slope of the function enhances the responsivity.