1Successful navigation in complex acoustic scenes requires focusing on relevant 2 sounds while ignoring irrelevant distractors. It has been argued that the ability to 3 track stimulus statistics and generate predictions supports the choice what to 4 attend and what to ignore. However, the role of these predictions about future 5 auditory events in drafting decisions remains elusive. While most psychophysical 6 studies in humans indicate that expected stimuli serve as implicit cues attracting 7 attention, most work studying physiological auditory processing in animals 8 highlights the detection of unexpected, surprising stimuli. Here, we tested whether 9 in the mouse, target probability is used as an implicit cue attracting attention or 10 whether detection is biased towards low-probability deviants using an auditory 11 detection task. We implemented a probabilistic choice model to investigate 12 whether a possible dependence on stimulus statistics arises from short term serial 13 correlations or from integration over longer periods. Our results demonstrate that 14 adapt their behavior according to the stimulus statistics (Bargones and Werner, 39 1994a; Gordon Z. Greenberg and Larkin, 1968). This form of selective auditory 40 attention does not require awareness of the subject and is driven by unconscious 41 expectations (Wolmetz and Elhilali, 2016). Within this framework, the 42 improvement of detectability is based on the expectation as an implicit cue and 43 serves as an internal reward-maximizing strategy that drives the attention towards 44 the expectation (Girshick et al., 2011). 45 While most psychophysical studies indicate that expected stimuli serve as implicit 46 cues attracting attention, most work studying the physiology of auditory 47 processing highlights the detection of unexpected, surprising stimuli. Stimuli are 48 more salient when presented rarely to the auditory system and thus might be 49 easier to detect due to pre-attentive mechanisms (Malmierca et al., 2015; Pérez-50 González et al., 2005; Tiitinen et al., 1994). Within this framework, the evaluation 51 of stimulus statistics serves to detect novelty, emphasizing changes in the auditory 52 scene rather than enabling tracking of task relevant information. 53 Thus, tracking of stimulus probability influences auditory processing in two 54 contrary ways: on the physiological level, low-probability sounds elicit maximal 55 responses, but during listening tasks, relevant high-probability sounds appear to 56 attract attention, improving their detectability. While physiological evidence for 57 deviant detection spans all the way from animal models to humans (Heilbron and 58 Chait, 2017; Khouri and Nelken, 2015), behavioral assessment of the effects of 59 target probability is largely restricted to humans. In order to understand the neural 60 mechanisms underlying predictive coding, animal models such as rodents in 61 which both physiology and behavior can be studied are needed. 62 Although rodents serve as widely used animal models to study audi...

Successful navigation in complex acoustic scenes requires focusing on relevant sounds while ignoring irrelevant distractors. It has been argued that the ability to track stimulus statistics and generate predictions supports the choice of what to attend and what to ignore. However, the role of these predictions about future auditory events in drafting decisions remains elusive. While most psychophysical studies in humans indicate that expected stimuli are more easily detected, most work studying physiological auditory processing in animals highlights the detection of unexpected, surprising stimuli. Here, we tested whether in the mouse, high target probability results in enhanced detectability or whether detection is biased towards low-probability deviants using an auditory detection task. We implemented a probabilistic choice model to investigate whether a possible dependence on stimulus statistics arises from short-term serial correlations or from integration over longer periods. Our results demonstrate that target detectability in mice decreases with increasing probability, contrary to humans. We suggest that mice indeed track probability over a timescale of at least several minutes but do not use this information in the same way as humans do: instead of maximizing reward by focusing on high-probability targets, the saliency of a target is determined by surprise.