Biology subjects

Milinski, L.

Publications and source records attributed to Milinski, L..

5 recordsLinked to original sources

bioRxiv2026

Sleep immediately after noise overexposure worsens tinnitus in mice

Subjective tinnitus is the most common auditory phantom perception in the absence of an acoustic stimulus yet there is no cure nor widely effective treatment to date. Previously, we suggested that sleep may contribute to tinnitus development after a triggering event, such as noise overexposure (NOE). Here, we investigated the effect of natural sleep on tinnitus development following NOE in mice. One group of mice was kept awake for 6 hours immediately after NOE, whereas a control group could sleep ad libitum. Tinnitus and hearing loss were assessed before and after NOE by determining gap prepulse inhibition of the acoustic startle reflex (GPIAS) and by recording auditory brainstem responses (ABRs). Only mice that were allowed to sleep in the first six hours after NOE developed a significant change in the GPIAS ratio one week after NOE, indicative of tinnitus. Habituation to the startle stimulus was largely similar between both groups, except that at eight weeks after NOE, when GPIAS ratio had returned to baseline levels in both groups, the sleep deprived group showed less habituation to the startle stimulus. Notably, animals in neither group showed significantly elevated ABR thresholds after NOE, yet the control group showed signs of elevated evoked activity in the auditory brainstem one week after NOE. These findings demonstrate that sleep early after noise overexposure may amplify subsequent tinnitus development. Our results suggest that sleep represents a temporal window that may be harnessed for potential modulation or mitigation of noise-induced hearing loss and tinnitus-related impairments.

neuroscience↗

bioRxiv2024

Cortical evoked activity is modulated by the sleep state in a ferret model of tinnitus. A case study.

Subjective tinnitus is a phantom auditory perception in the absence of an actual acoustic stimulus. It affects 15% of the global population and can be associated with disturbed sleep, poor mental health and quality of life. To date, there is no effective treatment for tinnitus. We used adult ferrets exposed to mild noise trauma as an animal model of tinnitus. We assessed the phantom percept using two operant paradigms sensitive to tinnitus, silent gap detection and silence detection, before and up to six months after the mild acoustic trauma. The integrity of the auditory brainstem was assessed over the same period using auditory brainstem response recordings. Following noise overexposure, ferrets developed lasting, frequency-specific impairments in operant behaviour and evoked brainstem activity. To explore the interaction between sleep and tinnitus, in addition to tracking the behavioural markers of noise-induced tinnitus and hearing impairment after noise overexposure, we evaluated sleep-wake architecture and spontaneous and auditory-evoked EEG activity across vigilance states. Behavioural performance and auditory-evoked activity measurements after noise overexposure suggested distinct degrees of tinnitus and hearing impairment between individuals. Animals that developed signs of tinnitus consistently developed sleep impairments, suggesting a link between the emergence of noise-induced tinnitus and sleep disruption. However, neural markers of tinnitus were reduced during sleep, suggesting that sleep may transiently mitigate tinnitus. These results reveal the importance of sleep-wake states in tinnitus and suggest that understanding the neurophysiological link between sleep and tinnitus may provide a new angle for research into the causes of phantom percepts and inform future treatments.

neuroscience↗

bioRxiv2021

Somnotate: A robust automated sleep stage classifier that exceeds human performance and identifies ambiguous states in mice

Electrophysiological recordings from freely behaving animals are a widespread and powerful mode of investigation in sleep research. These recordings generate large amounts of data that require sleep stage annotation (polysomnography), in which the data is parcellated according to three vigilance states: awake, rapid eye movement (REM) sleep, and non-REM (NREM) sleep. Manual and computational annotation methods currently ignore intermediate states because the classification features become ambiguous. However, these intermediate states contain important information regarding vigilance state dynamics. Here, we present a new classifier, "Somnotate", which produces automated annotation accuracies that exceed human expert performance on mouse electrophysiological data, is robust to errors in the training data, compatible with different recording configurations, and maintains high performance during experimental interventions. Somnotate is a probabilistic classifier based on a combination of linear discriminant analysis (LDA) with a hidden Markov model (HMM). A unique feature of Somnotate is that it quantifies and reports the certainty of its annotations, enabling the experimenter to identify ambiguous recording periods in a principled manner. We leverage this feature to identify epochs that exhibit intermediate vigilance states, revealing that many of these cluster around state transitions, whereas others correspond to failed attempts to transition. We show that the success rates of different transitions can be experimentally manipulated and explain previously observed sleep patterns. Somnotate can thus facilitate the study of sleep stage transitions and offers new insight into the mechanisms underlying sleep-wake dynamics. Author summaryTypically, the three different vigilance states - awake, REM sleep, and non-REM sleep - exhibit distinct features that are readily recognised in electrophysiological recordings. However, particularly around vigilance state transitions, epochs often exhibit features from more than one state. These intermediate vigilance states pose challenges for existing manual and automated classification methods, and are hence often ignored. Here, we present Somnotate - an open-source, highly accurate and robust sleep stage classifier, which supports research into intermediate states and sleep stage dynamics. Somnotate quantifies and reports the certainty of its annotations, enabling the experimenter to identify abnormal epochs in a principled manner. We use this feature to identify intermediate states and to detect unsuccessful attempts to switch between vigilance states. This provides new insights into the mechanisms of vigilance state transitions in mice, and creates new opportunities for future experiments.

neuroscience↗

bioRxiv2021

Sound disrupts sleep-associated brain oscillations inrodents according to its meaning

Sleep is essential but poses a risk to the animal. Filtering acoustic information according to its relevance, a process generally known as sensory gating, is crucial during sleep to ensure a balance between rest and danger detection. The mechanisms of this sensory gating and its specificity are not understood. Here, we tested the effect that sounds of different meaning had on sleep-associated ongoing oscillations. We recorded EEG and EMG from mice during rapid-eye movement (REM) and non-REM (NREM) sleep while presenting sounds with or without behavioural relevance. We found that sound presentation per se, in the form of an unfamiliar neutral sound, elicited a weak or no change in the sleep-dependent EEG power during NREM and REM sleep. In contrast, the presentation of a sound previously conditioned in an aversive task, elicited a clear and fast decrease in the sleep-dependent EEG power during both sleep phases, suggesting a transition to lighter sleep without awakening. The observed changes generally weakened over training days and were not present in animals that failed to learn. Interestingly, the effect could be generalized to unfamiliar neutral sounds if presented following conditioned training, an effect that depended on sleep phase and sound type. The data demonstrate that sounds are differentially gated during sleep depending on their meaning and that this process is reflected in disruption of sleep-associated brain oscillations without an effect on behavioural arousal.

neuroscience↗

bioRxiv2020

Waking experience modulates sleep need in mice

Homeostatic regulation of sleep is reflected in the maintenance of a daily balance between sleep and wake. Although numerous internal and external factors can influence sleep, it is unclear whether and to what extent the process that keeps track of time spent awake is determined by the content of the waking experience. We hypothesised that alterations in environmental conditions may elicit different types of wakefulness, which will in turn influence both the capacity to sustain continuous wakefulness as well the rates of accumulating sleep pressure. To address this, we performed two experiments, where we compared wakefulness dominated by novel object exploration with either (i) the effects of voluntary wheel running (Experiment 1) or (ii) performance in a simple touchscreen task (Experiment 2). We find that voluntary wheel running results in longer wake episodes, as compared with exploratory behaviour; yet it does not lead to higher levels of EEG slow wave activity (SWA) during subsequent sleep. On the other hand, engagement in a touchscreen task, motivated by a food reward, results in lower SWA during subsequent sleep, as compared to exploratory wakefulness, even though the total duration of wakefulness was similar. Overall, our study suggests that sleep-wake behaviour is highly flexible within an individual, and that the homeostatic process that keeps track of time spent awake is sensitive to the nature of the waking experience. We therefore conclude that sleep dynamics are determined, to a large degree, by the interaction between the organism and the environment.

neuroscience↗