ABSTRACT
Auditory neural coding of speech-relevant temporal cues can be noninvasively probed using envelope following responses (EFRs), neural ensemble responses phase-locked to the stimulus amplitude envelope. EFRs emphasize different neural generators, such as the auditory brainstem or auditory cortex, by altering the temporal modulation rate of the stimulus. EFRs can be an important diagnostic tool to assess auditory neural coding deficits that go beyond traditional audiometric estimations. Existing approaches to measure EFRs use discrete amplitude modulated (AM) tones of varying modulation frequencies, which is time consuming and inefficient, impeding clinical translation. Here we present a faster and more efficient framework to measure EFRs across a range of AM frequencies using stimuli that dynamically vary in modulation rates, combined with spectrally specific analyses that offer optimal spectrotemporal resolution. EFRs obtained from several species (humans, Mongolian gerbils, Fischer-344 rats, and Cba/CaJ mice) showed robust, high-SNR tracking of dynamic AM trajectories (up to 800Hz in humans, and 1.4 kHz in rodents), with a fivefold decrease in recording time and thirtyfold increase in spectrotemporal resolution. EFR amplitudes between dynamic AM stimuli and traditional discrete AM tokens within the same subjects were highly correlated (94% variance explained) across species. Hence, we establish a time-efficient and spectrally specific approach to measure EFRs. These results could yield novel clinical diagnostics for precision audiology approaches by enabling rapid, objective assessment of temporal processing along the entire auditory neuraxis.
ABSTRACT
Background: Mental imagery (MI) can enhance surgical skills. Research has shown that through brain-computer interface (BCI), it is possible to provide feedback on MI strength. We hypothesized that adding BCI to MI training would enhance robotic skill acquisition compared with controls. Methods: Surgical novices were recruited. At baseline, participants completed the Mental Imagery Questionnaire (MIQ) and the Vandenburg Mental Rotation Test (MRT). Students also performed several tasks on a robotic simulator. Participants were stratified based on MIQ and robotic skill and randomized into three groups: controls, MI, and MI and BCI training. All participants completed five 2-h training sessions. One hour was devoted to practicing robotic skill on the simulator. Additionally, controls completed crosswords for one hour, the MI group completed MI training and crosswords for one hour, and the MI + BCI group completed MI training and MI-related BCI training. Following training, participants completed the same baseline assessments. A Kruskal-Wallis test was used to determine differences between groups. Mann-Whitney U tests were performed to determine specific differences between groups. Results: Twenty-seven undergraduates participated. There were post-test differences on the MRT and knot tying task. Sub-analyses revealed that the MI + BCI group significantly outperformed the other groups on knot tying. There were no appreciable differences between the control and MI groups on any measures. Conclusions: Augmenting MI training with BCI led to significantly enhanced MI and robotic skill acquisition than traditional MI or robotic training methods. To optimize surgical skill acquisition in robotic and other surgical skills curricula, educators should consider utilizing MI with BCI training.
