Abstract
Detecting regular patterns in the environment, a process known as statistical learning, is essential for survival. Neuronal adaptation is a key mechanism in the detection of patterns that are continuously repeated across short (seconds to minutes) temporal windows. Here, we found in mice that a subcortical structure in the auditory midbrain was sensitive to patterns that were repeated discontinuously, in a temporally sparse manner, across windows of minutes to hours. Using a combination of behavioral, electrophysiological, and molecular approaches, we found changes in neuronal response gain that varied in mechanism with the degree of sound predictability and resulted in changes in frequency coding. Analysis of population activity (structural tuning) revealed an increase in frequency classification accuracy in the context of increased overlap in responses across frequencies. The increase in accuracy and overlap was paralleled at the behavioral level in an increase in generalization in the absence of diminished discrimination. Gain modulation was accompanied by changes in gene and protein expression, indicative of long-term plasticity. Physiological changes were largely independent of corticofugal feedback, and no changes were seen in upstream cochlear nucleus responses, suggesting a key role of the auditory midbrain in sensory gating. Subsequent behavior demonstrated learning of predictable and random patterns and their importance in auditory conditioning. Using longer timescales than previously explored, the combined data show that the auditory midbrain codes statistical learning of temporally sparse patterns, a process that is critical for the detection of relevant stimuli in the constant soundscape that the animal navigates through.
Highlights
As we interact with the environment, our brain is constantly detecting patterns—i.e., regularities—in the sensory world
Statistical learning of sparse patterns is important for grammatical learning or musical sensitivity in humans [5,6], both of which are achieved through exposures that occur across days to years
We found that the number of Vglut2 puncta in the dorsal (“adjacent”) area was similar between groups, while GABA vesicular transporter (VGAT) was significantly reduced in the predictable group
Summary
As we interact with the environment, our brain is constantly detecting patterns—i.e., regularities—in the sensory world. This capacity allows us to recognize surrounding stimuli and make predictions necessary for survival. Statistical learning of sparse patterns is important for grammatical learning or musical sensitivity in humans [5,6], both of which are achieved through exposures that occur across days to years. This type of learning is likely to involve long-term plasticity mechanisms, different from neuronal adaptation
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
