Development of a menopause-specific questionnaire: Content and face validation using a modified Delphi technique.

Saccades move our retina with high speed across the visual scene and bring a target object from the visual periphery into foveal vision. Because these ballistic movements are so fast, visual information obtained during the eye movement cannot be used to apply changes to the trajectory of the current saccade. Instead, saccade accuracy has to be evaluated after eye movement, and potential errors are used to adjust future saccades. It is hypothesized that this post-saccadic evaluation of saccade accuracy requires that the object near the fovea first has to be recognized as the target object that has been selected before movement onset (; ; ), and that this process considers position as well as surface feature information about the objects in the scene (). The pre-saccadic target object is assumed to be defined by a specific combination of features, for example, its position, shape, or color. This feature combination might be stored in visuospatial working memory, and, after the saccade, be compared with the feature information extracted from the object near the fovea. If its features and the features stored in the visuospatial working memory match, the post-saccadic target recognition is supposed to be successful, and trans-saccadic object correspondence might be established (; ; ; ). Post-saccadic target recognition enables the evaluation of saccade accuracy. It is a prerequisite for detecting a post-saccadic error and is therefore necessary to determine whether any adaptive modifications should be made to future saccades. Adaptive changes are required if the saccade fails to align the fovea with the target object, as is the case, for example, in nerve palsy (; ). However, such a post-saccadic error can also be induced artificially. This can be done by repeatedly manipulating the position of the target object during the saccade. The target object can be shifted in or against saccade direction. The saccade then under- or overshoots the target object, respectively (). The target shift remains undetected because of saccadic suppression of displacement (; ). This phenomenon might be supported by a strong prior assumption of a stable external world during saccadic eye movements (; ; ), which is only abandoned if the discrepancies between the pre- and post-saccadic images are too large (; ). Despite participants being unaware of the intra-saccadic manipulation, adaptive changes to the saccade amplitude develop and gradually decrease the post-saccadic distance between the fovea and the target object (). This learning process is termed saccadic adaptation. Its time course is often modeled with an exponential function because, after a rapid initial change to the amplitude, the process continues to develop more slowly until a new steady state is reached (; ; ). Even after this new steady state has been reached, saccadic adaptation does not compensate for the full extent of the intra-saccadic target displacement (; ; ). Another important hallmark of saccadic adaptation is its effect on the perceived position of objects. Before the repeated exposure to intra-saccadic target displacements, the spatial position of a localization stimulus presented during the saccade preparation period is reported accurately. However, after exposure to the double-step paradigm, the perceived location of objects shifts in the direction of the target displacement, ultimately leading to a localization error (; ; ; ; ; ; ). This effect pertains both to objects that are presented during fixation and during saccade preparation, but is more pronounced for the latter (; ; ). The nature of the error signal underlying saccadic adaptation has been debated. Initially, the visual error was proposed. It describes the post-saccadic distance between the target object and the fovea. The visual error was rejected because it is not consistent with the natural saccade hypometria (; ) and the incomplete adjustment of the saccade amplitude to the intra-saccadic target displacement (; ; ; ). Thus, another error signal was proposed: the prediction error. According to this approach, an error is identified if the predicted and actual retinal eccentricity of the target object do not match (; ; ; ). The prediction is supposed to rely on an estimate of the pending saccade, derived from the efference copy (; ; ; ). However, the prediction error presents with several weaknesses. 1) Once the learning process is complete and a steady state has been reached, the prediction error should be nullified. During this state, the predicted post-saccadic target position and the actual position of the displaced target should match. However, demonstrated that this is not the case. 2) If the estimated and actual post-saccadic retinal target eccentricity are the same, learning has optimized the prediction. However, because the magnitude of this post-saccadic retinal target eccentricity is irrelevant, optimized predictions do not necessarily correspond with optimized saccade accuracy. 3