Reversal of age-related neural timing delays with training

Abstract

Neural slowing is commonly noted in older adults, with consequences for sensory, motor, and cognitive domains. One of the deleterious effects of neural slowing is impairment of temporal resolution; older adults, therefore, have reduced ability to process the rapid events that characterize speech, especially in noisy environments. Although hearing aids provide increased audibility, they cannot compensate for deficits in auditory temporal processing. Auditory training may provide a strategy to address these deficits. To that end, we evaluated the effects of auditory-based cognitive training on the temporal precision of subcortical processing of speech in noise. After training, older adults exhibited faster neural timing and experienced gains in memory, speed of processing, and speech-in-noise perception, whereas a matched control group showed no changes. Training was also associated with decreased variability of brainstem response peaks, suggesting a decrease in temporal jitter in response to a speech signal. These results demonstrate that auditory-based cognitive training can partially restore age-related deficits in temporal processing in the brain; this plasticity in turn promotes better cognitive and perceptual skills.

Fig. 1.

Flow of participants randomly assigned to auditory training or active control groups.

Fig. 2.

The stimulus waveform [da] (gray) and the grand average response waveform to the [da] presented in quiet (n = 67) at pretest (black).

Fig. 3.

Changes in the neural response to [da] for peaks occurring every 10 ms (corresponding to the 100 Hz pitch of the stimulus) are displayed for the auditory training (red; n = 35) and active control (blue; n = 32) groups in quiet (Upper) and noise (Lower). The brackets indicate the transition and steady-state regions of the [da]. Improvements in timing were noted in the auditory training but not in the active control group. *P < 0.05, ***P < 0.001; Error bars: ±1 SE.

Fig. 4.

Individual average timing changes for the formant transition (Left) and steady-state vowel (Right) in the auditory training (Upper) and active control (Lower) groups for neural responses to speech in noise. *P < 0.05, ***P < 0.001.

Fig. 5.

Quiet-to-noise timing shift differences. Responses in quiet and noise were cross-correlated to obtain an objective measure of timing (lag). (A) Before training, the expected noise-induced timing shift is observed, with the response in noise (black) lagging behind the response in quiet (gray) by 0.2–0.3 ms (shown in an individual participant). (B) After training, this individual’s response in noise (red) now overlays the response in quiet (pink) with minimal apparent lag. (C) Lag changes in each participant in the auditory training group, indicating a significant group change from pre- to posttest. (D) Mean group lag changes. *P < 0.01; error bars: ±1 SE.

Fig. 6.

Improvements in speech-in-noise perception, short-term memory, and processing speed were only observed in the auditory training group. **P < 0.01 group × test interactions; error bars: ±1 SE.