Motor learning is the process of improving task execution according to some measure of performance. This can be divided into skill learning, a model-free process, and adaptation, a model-based process. Prior studies have indicated that adaptation results from two complementary learning systems with parallel organization. This report attempted to answer the question of whether a similar interaction leads to savings, a model-free process that is described as faster relearning when experiencing something familiar. This was tested in a two-week reaching task conducted on a robotic arm capable of perturbing movements. The task was designed so that the two sessions differed in their history of errors. By measuring the change in the learning rate, the savings was determined at various points. The results showed that the history of errors successfully modulated savings. Thus, this supports the notion that the two complementary systems interact to develop savings. Additionally, this report was part of a larger study that will explore the organizational structure of the complementary systems as well as the neural basis of this motor learning.

The cocktail party effect describes the brain’s natural ability to attend to a specific voice or audio source in a crowded room. Researchers have recently attempted to recreate this ability in hearing aid design using brain signals from invasive electrocorticography electrodes. The present study aims to find neural signatures of auditory attention to achieve this same goal with noninvasive electroencephalographic (EEG) methods. Five human participants participated in an auditory attention task. Participants listened to a series of four syllables followed by a fifth syllable (probe syllable). Participants were instructed to indicate whether or not the probe syllable was one of the four syllables played immediately before the probe syllable. Trials of this task were separated into conditions of playing the syllables in silence (Signal) and in background noise (Signal With Noise), and both behavioral and EEG data were recorded. EEG signals were analyzed with event-related potential and time-frequency analysis methods. The behavioral data indicated that participants performed better on the task during the “Signal” condition, which aligns with the challenges demonstrated in the cocktail party effect. The EEG analysis showed that the alpha band’s (9-13 Hz) inter-trial coherence could potentially indicate characteristics of the attended speech signal. These preliminary results suggest that EEG time-frequency analysis has the potential to reveal the neural signatures of auditory attention, which may allow for the design of a noninvasive, EEG-based hearing aid.