The auditory cortex mediates the perceptual effects of acoustic temporal expectation

Rapid emergence of latent knowledge in the sensory cortex drives learning

Rapid learning confers significant advantages on animals in ecological environments. Despite the need for speed, animals appear to only slowly learn to associate rewarded actions with predictive cues1-4. This slow learning is thought to be supported by gradual changes to cue representation in the sensory cortex2,5. However, evidence is growing that animals learn more rapidly than classical performance measures suggest6,7, challenging the prevailing model of sensory cortical plasticity. Here we investigated the relationship between learning and sensory cortical representations. We trained mice on an auditory go/no-go task that dissociated the rapid acquisition of task contingencies (learning) from its slower expression (performance)7. Optogenetic silencing demonstrated that the auditory cortex drives both rapid learning and slower performance gains but becomes dispensable once mice achieve 'expert' performance. Instead of enhanced cue representations8, two-photon calcium imaging of auditory cortical neurons throughout learning revealed two higher-order signals that were causal to learning and performance. A reward-prediction signal emerged rapidly within tens of trials, was present after action-related errors early in training, and faded in expert mice. Silencing at the time of this signal impaired rapid learning, suggesting that it serves an associative role. A distinct cell ensemble encoded and controlled licking suppression that drove slower performance improvements. These ensembles were spatially clustered but uncoupled from sensory representations, indicating higher-order functional segregation within auditory cortex. Our results reveal that the sensory cortex manifests higher-order computations that separably drive rapid learning and slower performance improvements, reshaping our understanding of the fundamental role of the sensory cortex.

Hierarchical organization of the forebrain cholinergic system in rats

The basal forebrain (BF) cholinergic system (BFCS) participates in functions that are global across the brain, such as sleep-wake cycles, but also participates in capacities that are more behaviorally and anatomically specific, including sensory perception. However, how it orchestrates all the diverse local and global functions remains to be understood. To uncover the underlying organization principles, we combined data from rat brains by tracing projections from the BF to cortical areas and analyzed spatial-numerical relations of neurons to their cortical targets. The combined dataset revealed algorithmically identified and hierarchically organized three principal networks: somatosensory-motor, auditory, and visual, as defined by the sensory modality most predominant within them. These clusters of cholinergic neurons could enable the BFCS to coordinate spatially selective signaling, including the parallel modulation of multiple functionally interconnected yet diverse groups of cortical areas. This previously unseen blueprint of the hierarchy of cholinergic clusters is ready for functional testing.

Neural signatures of temporal anticipation in human cortex represent event probability density

Temporal prediction is a fundamental function of neural systems. Recent results show that humans anticipate future events by calculating probability density functions, rather than hazard rates. However, direct neural evidence for this hypothesized mechanism is lacking. We recorded neural activity using magnetoencephalography as participants anticipated auditory and visual events distributed in time. We show that temporal anticipation, measured as reaction times, approximates the event probability density function, but not hazard rate. Temporal anticipation manifests as spatiotemporally patterned activity in three anatomically and functionally distinct parieto-temporal and sensorimotor cortical areas. Each of these areas revealed a marked neural signature of anticipation: Prior to sensory cues, activity in a specific frequency range of neural oscillations, spanning alpha and beta ranges, encodes the event probability density function. These neural signals predicted reaction times to imminent sensory cues. These results demonstrate that supra-modal representations of probability density across cortex underlie the anticipation of future events.

Global to local influences on temporal expectation in marmosets and humans

Marmosets are emerging rapidly as experimental models for studying the neural bases of cognition and, importantly, for modeling disorders of human cognition, but many aspects of their mental attributes remain to be characterized. When judging elapsed time, humans implicitly use prior information to predict upcoming events and reduce perceptual and decision-making uncertainty. An influential model of temporal expectation is the hazard rate model, which posits the likelihood of an event occurring in the future, provided it has not occurred already. Here, we report that marmosets trained on a reaction time task acquire the hazard rate model of expectation, consistent with the global task structure. The model emerges progressively with learning but unexpectedly continues to be modified by local contingencies, as demonstrated by a serial effect of trial duration on responses. The combined effects of global and local task structure are well described by a multiple regression model and computationally by Bayesian updating of the hazard function. Parallel experiments in human subjects similarly demonstrate global followed by local influences on reaction times and temporal expectation. Thus, in both marmosets and humans, task history and local structure continuously update task-specific responses, surprisingly at the expense of optimal responses after the competent acquisition of an internal model.

Neural Correlates of Perceptual Plasticity in the Auditory Midbrain and Thalamus

Hearing is an active process in which listeners must detect and identify sounds, segregate and discriminate stimulus features, and extract their behavioral relevance. Adaptive changes in sound detection can emerge rapidly, during sudden shifts in acoustic or environmental context, or more slowly as a result of practice. Although we know that context- and learning-dependent changes in the sensitivity of auditory cortical (ACX) neurons support many aspects of perceptual plasticity, the contribution of subcortical auditory regions to this process is less understood. Here, we recorded single- and multiunit activity from the central nucleus of the inferior colliculus (ICC) and the ventral subdivision of the medial geniculate nucleus (MGV) of male and female Mongolian gerbils under two different behavioral contexts: as animals performed an amplitude modulation (AM) detection task and as they were passively exposed to AM sounds. Using a signal detection framework to estimate neurometric sensitivity, we found that neural thresholds in both regions improve during task performance, and this improvement is largely driven by changes in the firing rate rather than phase locking. We also found that ICC and MGV neurometric thresholds improve as animals learn to detect small AM depths during a multiday perceptual training paradigm. Finally, we revealed that in the MGV, but not the ICC, context-dependent enhancements in AM sensitivity grow stronger during perceptual training, mirroring prior observations in the ACX. Together, our results suggest that the auditory midbrain and thalamus contribute to changes in sound processing and perception over rapid and slow timescales.

Memory-based predictions prime perceptual judgments across head turns in immersive, real-world scenes

Each view of our environment captures only a subset of our immersive surroundings. Yet, our visual experience feels seamless. A puzzle for human neuroscience is to determine what cognitive mechanisms enable us to overcome our limited field of view and efficiently anticipate new views as we sample our visual surroundings. Here, we tested whether memory-based predictions of upcoming scene views facilitate efficient perceptual judgments across head turns. We tested this hypothesis using immersive, head-mounted virtual reality (VR). After learning a set of immersive real-world environments, participants (n = 101 across 4 experiments) were briefly primed with a single view from a studied environment and then turned left or right to make a perceptual judgment about an adjacent scene view. We found that participants' perceptual judgments were faster when they were primed with images from the same (vs. neutral or different) environments. Importantly, priming required memory: it only occurred in learned (vs. novel) environments, where the link between adjacent scene views was known. Further, consistent with a role in supporting active vision, priming only occurred in the direction of planned head turns and only benefited judgments for scene views presented in their learned spatiotopic positions. Taken together, we propose that memory-based predictions facilitate rapid perception across large-scale visual actions, such as head and body movements, and may be critical for efficient behavior in complex immersive environments.

Experience-driven development of decision-related representations in the auditory cortex

Associating sensory stimuli with behavioral significance induces substantial changes in stimulus representations. Recent studies suggest that primary sensory cortices not only adjust representations of task-relevant stimuli, but actively participate in encoding features of the decision-making process. We sought to determine whether this trait is innate in sensory cortices or if choice representation develops with time and experience. To trace choice representation development, we perform chronic two-photon calcium imaging in the primary auditory cortex of head-fixed mice while they gain experience in a tone detection task with a delayed decision window. Our results reveal a progressive increase in choice-dependent activity within a specific subpopulation of neurons, aligning with growing task familiarity and adapting to changing task rules. Furthermore, task experience correlates with heightened synchronized activity in these populations and the ability to differentiate between different types of behavioral decisions. Notably, the activity of this subpopulation accurately decodes the same action at different task phases. Our findings establish a dynamic restructuring of population activity in the auditory cortex to encode features of the decision-making process that develop over time and refines with experience.

Anticipatory and evoked visual cortical dynamics of voluntary temporal attention

We can often anticipate the precise moment when a stimulus will be relevant for our behavioral goals. Voluntary temporal attention, the prioritization of sensory information at task-relevant time points, enhances visual perception. However, the neural mechanisms of voluntary temporal attention have not been isolated from those of temporal expectation, which reflects timing predictability rather than relevance. Here we use time-resolved steady-state visual evoked responses (SSVER) to investigate how temporal attention dynamically modulates visual activity when temporal expectation is controlled. We recorded magnetoencephalography while participants directed temporal attention to one of two sequential grating targets with predictable timing. Meanwhile, a co-localized SSVER probe continuously tracked visual cortical modulations both before and after the target stimuli. We find that in the pre-target period, the SSVER gradually ramps up as the targets approach, reflecting temporal expectation. Furthermore, we find a low-frequency modulation of the SSVER, which shifts approximately half a cycle in phase according to which target is attended. In the post-target period, temporal attention to the first target transiently modulates the SSVER shortly after target onset. Thus, temporal attention dynamically modulates visual cortical responses via both periodic pre-target and transient post-target mechanisms to prioritize sensory information at precise moments.

Modulation of cortical representations of sensory and contextual information underlies aversive associative learning

Cortical neurons encode both sensory and contextual information, yet it remains unclear how experiences modulate these cortical representations. Here, we demonstrate that trace eyeblink conditioning (TEC), an aversive associative-learning paradigm linking conditioned (CS) with unconditioned stimuli (US), finely tunes cortical coding at both population and single-neuron levels. Initially, we show that the primary somatosensory cortex (S1) is necessary for TEC acquisition, as evidenced by local muscimol administration. At the population level, TEC enhances activity in a small subset (∼20%) of CS- or US-responsive primary neurons (rPNs) while diminishing activity in non-rPNs, including locomotion-tuned or unresponsive PNs. Crucially, TEC learning modulates the encoding of sensory versus contextual information in single rPNs: CS-responsive neurons become less responsive, while US-responsive neurons gain responses to CS. Moreover, we find that the cholinergic pathway, via nicotinic receptors, underlies TEC-induced modulations. These findings suggest that experiences dynamically tune cortical representations through cholinergic pathways.

Mechanism of Duration Perception in Artificial Brains Suggests New Model of Attentional Entrainment

While cognitive theory has advanced several candidate frameworks to explain attentional entrainment, the neural basis for the temporal allocation of attention is unknown. Here we present a new model of attentional entrainment guided by empirical evidence obtained using a cohort of 50 artificial brains. These brains were evolved in silico to perform a duration judgment task similar to one where human subjects perform duration judgments in auditory oddball paradigms. We found that the artificial brains display psychometric characteristics remarkably similar to those of human listeners and exhibit similar patterns of distortions of perception when presented with out-of-rhythm oddballs. A detailed analysis of mechanisms behind the duration distortion suggests that attention peaks at the end of the tone, which is inconsistent with previous attentional entrainment models. Instead, the new model of entrainment emphasizes increased attention to those aspects of the stimulus that the brain expects to be highly informative.

Dynamic gating of perceptual flexibility by non-classically responsive cortical neurons

The ability to flexibly respond to sensory cues in dynamic environments is essential to adaptive auditory-guided behaviors. Cortical spiking responses during behavior are highly diverse, ranging from reliable trial-averaged responses to seemingly random firing patterns. While the reliable responses of 'classically responsive' cells have been extensively studied for decades, the contribution of irregular spiking 'non-classically responsive' cells to behavior has remained underexplored despite their prevalence. Here, we show that flexible auditory behavior results from interactions between local auditory cortical circuits comprised of heterogeneous responses and inputs from secondary motor cortex. Strikingly, non-classically responsive neurons in auditory cortex were preferentially recruited during learning, specifically during rapid learning phases when the greatest gains in behavioral performance occur. Population-level decoding revealed that during rapid learning mixed ensembles comprised of both classically and non-classically responsive cells encode significantly more task information than homogenous ensembles of either type and emerge as a functional unit critical for learning. Optogenetically silencing inputs from secondary motor cortex selectively modulated non-classically responsive cells in the auditory cortex and impaired reversal learning by preventing the remapping of a previously learned stimulus-reward association. Top-down inputs orchestrated highly correlated non-classically responsive ensembles in sensory cortex providing a unique task-relevant manifold for learning. Thus, non-classically responsive cells in sensory cortex are preferentially recruited by top-down inputs to enable neural and behavioral flexibility.

Contributions of cortical neuron firing patterns, synaptic connectivity, and plasticity to task performance

Neuronal responses during behavior are diverse, ranging from highly reliable 'classical' responses to irregular 'non-classically responsive' firing. While a continuum of response properties is observed across neural systems, little is known about the synaptic origins and contributions of diverse responses to network function, perception, and behavior. To capture the heterogeneous responses measured from auditory cortex of rodents performing a frequency recognition task, we use a novel task-performing spiking recurrent neural network incorporating spike-timing-dependent plasticity. Reliable and irregular units contribute differentially to task performance via output and recurrent connections, respectively. Excitatory plasticity shifts the response distribution while inhibition constrains its diversity. Together both improve task performance with full network engagement. The same local patterns of synaptic inputs predict spiking response properties of network units and auditory cortical neurons from in vivo whole-cell recordings during behavior. Thus, diverse neural responses contribute to network function and emerge from synaptic plasticity rules.

Tactile temporal predictions: The influence of conditional probability

Predicting the timing of incoming information allows brain to optimize information processing in dynamic environments. However, the effects of temporal predictions on tactile perception are not well established. In this study, two experiments were conducted to determine how temporal predictions interact with conditional probabilities in tactile perceptual processing. In Experiment 1, we explored the range of the interval between preceding ready cues and imperative targets in which temporal prediction effects can be observed. This prediction effect was observed for intervals of 500 and 1,000 ms. In Experiment 2, we investigated the benefits of temporal predictions on tactile perception while manipulating the conditional probability (setting the stimulus onset earlier or later than the predicted moment in short and long intervals). Our results revealed that this effect became stronger as the probability of the stimulus at the predicted time point increased under short-interval conditions. Together, our results show that the difficulty of transferring processing resources increases in temporally dynamic environments, suggesting a greater subjective cost associated with maladaptive responses to temporally uncertain events.

Functional architecture of the forebrain cholinergic system in rodents

The basal forebrain cholinergic system (BFCS) participates in functions that are global across the brain, such as sleep-wake cycles, but also participates in capacities that are more behaviorally and anatomically specific, including sensory perception. To better understand the underlying organization principles of the BFCS, more and higher quality anatomical data and analysis is needed. Here, we created a "virtual Basal Forebrain", combining data from numerous rats with cortical retrograde tracer injections into a common 3D reference coordinate space and developed a "spatial density correlation" methodology to analyze patterns in BFCS cortical projection targets, revealing that the BFCS is organized into three principal networks: somatosensory-motor, auditory, and visual. Within each network, clusters of cholinergic cells with increasing complexity innervate cortical targets. These networks represent hierarchically organized building blocks that may enable the BFCS to coordinate spatially selective signaling, including parallel modulation of multiple functionally interconnected yet diverse groups of cortical areas.

Rapid emergence of latent knowledge in the sensory cortex drives learning

Rapid learning confers significant advantages to animals in ecological environments. Despite the need for speed, animals appear to only slowly learn to associate rewarded actions with predictive cues1-4. This slow learning is thought to be supported by a gradual expansion of predictive cue representation in the sensory cortex2,5. However, evidence is growing that animals learn more rapidly than classical performance measures suggest6-8, challenging the prevailing model of sensory cortical plasticity. Here, we investigated the relationship between learning and sensory cortical representations. We trained mice on an auditory go/no-go task that dissociated the rapid acquisition of task contingencies (learning) from its slower expression (performance)7. Optogenetic silencing demonstrated that the auditory cortex (AC) drives both rapid learning and slower performance gains but becomes dispensable at expert. Rather than enhancement or expansion of cue representations9, two-photon calcium imaging of AC excitatory neurons throughout learning revealed two higher-order signals that were causal to learning and performance. First, a reward prediction (RP) signal emerged rapidly within tens of trials, was present after action-related errors only early in training, and faded at expert levels. Strikingly, silencing at the time of the RP signal impaired rapid learning, suggesting it serves an associative and teaching role. Second, a distinct cell ensemble encoded and controlled licking suppression that drove the slower performance improvements. These two ensembles were spatially clustered but uncoupled from underlying sensory representations, indicating a higher-order functional segregation within AC. Our results reveal that the sensory cortex manifests higher-order computations that separably drive rapid learning and slower performance improvements, reshaping our understanding of the fundamental role of the sensory cortex.

Cortical determinants of loudness perception and auditory hypersensitivity

Parvalbumin-expressing inhibitory neurons (PVNs) stabilize cortical network activity, generate gamma rhythms, and regulate experience-dependent plasticity. Here, we observed that activation or inactivation of PVNs functioned like a volume knob in the mouse auditory cortex (ACtx), turning neural and behavioral classification of sound level up or down over a 20dB range. PVN loudness adjustments were "sticky", such that a single bout of 40Hz PVN stimulation sustainably suppressed ACtx sound responsiveness, potentiated feedforward inhibition, and behaviorally desensitized mice to loudness. Sensory sensitivity is a cardinal feature of autism, aging, and peripheral neuropathy, prompting us to ask whether PVN stimulation can persistently desensitize mice with ACtx hyperactivity, PVN hypofunction, and loudness hypersensitivity triggered by cochlear sensorineural damage. We found that a single 16-minute bout of 40Hz PVN stimulation session restored normal loudness perception for one week, showing that perceptual deficits triggered by irreversible peripheral injuries can be reversed through targeted cortical circuit interventions.

[A study of mismatched negative in normal hearing patients of different ages]

Objective:To study the characteristics of Mismatch negativity（MMN） in normal hearing patients of different ages, and to compare the MMN of normal hearing subjects at different ages to explore the differences in MMN between different ages. Methods:MMN test was performed on both ears using the classic Oddball mode. A frequency of 1 000 Hz（standard stimuli） and 2 000 Hz（deviant stimuli） was used to evoked the MMN. According to different age groups: the juvenile group（7-17 years old）, the youth group（18-44 years old）, the middle-aged group（45-59 years old）, and the elderly group（60-75 years old）, with 25 cases in each group. The MMN characteristics of normal hearing subjects in different age groups were analyzed statistically and the differences between groups were compared. All subjects underwent pure tone threshold test, tympanic reactance test and ABR test before MMN test. Results:MMN waveform could be elicited from both ears of 100 subjects. Among them, the average latency of the juvenile group was（159.70±20.34） ms while the average amplitude was（4.34±2.26） μV, For the youth group, the average latency was（166.01±28.67） ms and the average amplitude was（3.70±2.28） μV. Then in the middle-aged group, the average latency was（175.16±37.24） ms, meanwhile, the average amplitude was（2.69±0.84） μV. Finally, the elderly group has an average latency of（178.03±14.37） ms and an average amplitude of（2.11±0.70） μV. Therefore, there was no statistical difference in latency and amplitude between all groups（P>0.05）, and there was no statistical difference in latency and amplitude between left and right ears among all subjects as a whole（P>0.05）. However, when the left and right ears of all groups were compared, it was found that the latency between the left and right ears of the Juvenile group had statistical significance（P<0.05）, and the amplitude difference was not statistically significant（P>0.05）, while the latency and amplitude differences between the left and right ears of other groups had no statistical significance（P>0.05）. There were also no significant differences in latency and amplitude between men and women（P>0.05）. Conclusion:There was no statistically significant difference in the latency and amplitude of mismatched negative among normal hearing subjects of different ages, and no statistically significant difference in the MMN latency and amplitude between the left and right ears of subjects and between men and women. Therefore, the study inferred that the auditory cerebral cortex of subjects aged 7-75 years old maintained a stable state for a long time after maturity, and the latency and amplitude of mismatched negative waves were relatively stable. It is not affected by age, gender and ear side, and can stably reflect the auditory cortex function of the subjects. It has broad application prospects in clinical practice, and provides a reliable detection means for future research on the changes of the auditory cerebral cortex of patients, which is worthy of our further research and clinical promotion.

An open-source behavior controller for associative learning and memory (B-CALM)

Associative learning and memory, i.e., learning and remembering the associations between environmental stimuli, self-generated actions, and outcomes such as rewards or punishments, are critical for the well-being of animals. Hence, the neural mechanisms underlying these processes are extensively studied using behavioral tasks in laboratory animals. Traditionally, these tasks have been controlled using commercial hardware and software, which limits scalability and accessibility due to their cost. More recently, due to the revolution in microcontrollers or microcomputers, several general-purpose and open-source solutions have been advanced for controlling neuroscientific behavioral tasks. While these solutions have great strength due to their flexibility and general-purpose nature, for the same reasons, they suffer from some disadvantages including the need for considerable programming expertise, limited online visualization, or slower than optimal response latencies for any specific task. Here, to mitigate these concerns, we present an open-source behavior controller for associative learning and memory (B-CALM). B-CALM provides an integrated suite that can control a host of associative learning and memory behaviors. As proof of principle for its applicability, we show data from head-fixed mice learning Pavlovian conditioning, operant conditioning, discrimination learning, as well as a timing task and a choice task. These can be run directly from a user-friendly graphical user interface (GUI) written in MATLAB that controls many independently running Arduino Mega microcontrollers in parallel (one per behavior box). In sum, B-CALM will enable researchers to execute a wide variety of associative learning and memory tasks in a scalable, accurate, and user-friendly manner.

Differential Formation of Motor Cortical Dynamics during Movement Preparation According to the Predictability of Go Timing

The motor cortex not only executes but also prepares movement, as motor cortical neurons exhibit preparatory activity that predicts upcoming movements. In movement preparation, animals adopt different strategies in response to uncertainties existing in nature such as the unknown timing of when a predator will attack-an environmental cue informing "go." However, how motor cortical neurons cope with such uncertainties is less understood. In this study, we aim to investigate whether and how preparatory activity is altered depending on the predictability of "go" timing. We analyze firing activities of the anterior lateral motor cortex in male mice during two auditory delayed-response tasks each with predictable or unpredictable go timing. When go timing is unpredictable, preparatory activities immediately reach and stay in a neural state capable of producing movement anytime to a sudden go cue. When go timing is predictable, preparation activity reaches the movement-producible state more gradually, to secure more accurate decisions. Surprisingly, this preparation process entails a longer reaction time. We find that as preparatory activity increases in accuracy, it takes longer for a neural state to transition from the end of preparation to the start of movement. Our results suggest that the motor cortex fine-tunes preparatory activity for more accurate movement using the predictability of go timing.

The Motor of Time: Coupling Action to Temporally Predictable Events Heightens Perception

Timing and motor function share neural circuits and dynamics, which underpin their close and synergistic relationship. For instance, the temporal predictability of a sensory event optimizes motor responses to that event. Knowing when an event is likely to occur lowers response thresholds, leading to faster and more efficient motor behavior though in situations of response conflict can induce impulsive and inappropriate responding. In turn, through a process of active sensing, coupling action to temporally predictable sensory input enhances perceptual processing. Action not only hones perception of the event's onset or duration, but also boosts sensory processing of its non-temporal features such as pitch or shape. The effects of temporal predictability on motor behavior and sensory processing involve motor and left parietal cortices and are mediated by changes in delta and beta oscillations in motor areas of the brain.

Neurons in the primary visual cortex of freely moving rats encode both sensory and non-sensory task variables

Neurons in primary visual cortex (area V1) are strongly driven by both sensory stimuli and non-sensory events. However, although the representation of sensory stimuli has been well characterized, much less is known about the representation of non-sensory events. Here, we characterize the specificity and organization of non-sensory representations in rat V1 during a freely moving visual decision task. We find that single neurons encode diverse combinations of task features simultaneously and across task epochs. Despite heterogeneity at the level of single neuron response patterns, both visual and nonvisual task variables could be reliably decoded from small neural populations (5 to 40 units) throughout a trial. Interestingly, in animals trained to make an auditory decision following passive observation of a visual stimulus, some but not all task features could also be decoded from V1 activity. Our results support the view that even in V1-the earliest stage of the cortical hierarchy-bottom-up sensory information may be combined with top-down non-sensory information in a task-dependent manner.

A Cortico-Striatal Circuit for Sound-Triggered Prediction of Reward Timing

A crucial aspect of auditory perception is the ability to use sound cues to predict future events and to time actions accordingly. For example, distinct smartphone notification sounds reflect a call that needs to be answered within a few seconds, or a text that can be read later; the sound of an approaching vehicle signals when it is safe to cross the street. Other animals similarly use sounds to plan, time and execute behaviors such as hunting, evading predation and tending to offspring. However, the neural mechanisms that underlie sound-guided prediction of upcoming salient event timing are not well understood. To address this gap, we employed an appetitive sound-triggered reward time prediction behavior in head-fixed mice. We find that mice trained on this task reliably estimate the time from a sound cue to upcoming reward on the scale of a few seconds, as demonstrated by learning-dependent well-timed increases in reward-predictive licking. Moreover, mice showed a dramatic impairment in their ability to use sound to predict delayed reward when the auditory cortex was inactivated, demonstrating its causal involvement. To identify the neurophysiological signatures of auditory cortical reward-timing prediction, we recorded local field potentials during learning and performance of this behavior and found that the magnitude of auditory cortical responses to the sound prospectively encoded the duration of the anticipated sound-reward time interval. Next, we explored how and where these sound-triggered time interval prediction signals propagate from the auditory cortex to time and initiate consequent action. We targeted the monosynaptic projections from the auditory cortex to the posterior striatum and found that chemogenetic inactivation of these projections impairs animal's ability to predict sound-triggered delayed reward. Simultaneous neural recordings in the auditory cortex and posterior striatum during task performance revealed coordination of neural activity across these regions during the sound cue predicting the time interval to reward. Collectively, our findings identify an auditory cortical-striatal circuit supporting sound-triggered timing-prediction behaviors.

Flexible information representation to stabilize sensory perception despite minor external input variations

Sensory information about the environment constantly changes or varies depending on circumstances. However, once we repeatedly experience objects, our brain can perceive and recognize them as identical, even if they are slightly altered or include some diversity. We can stably perceive things without interference from minor external changes or variety. Our recent study focusing on visual perception showed that repeatedly viewing the same oriented grating stimuli enables information representation for low-contrast (or weak-intensity) orientations in the primary visual cortex. We observed low contrast-preferring neurons, whose firing rates increased by reducing the luminance contrast. The number of such neurons increased after the experience, and the neuronal population, including such neurons, can represent even low-contrast orientations. This study indicated that experience leads to flexible information representations that continuously respond to inputs of various strengths at the neuronal population level in the primary sensory cortex. In this perspective article, in addition to the above mechanism, I would discuss alternative mechanisms for perceptual stabilization. The primary sensory cortex represents external information faithfully without alterations, as well as in a state distorted by experience. Both sensory representations may cooperatively and dynamically affect hierarchical downstream, resulting in stable perception.

Learning induced neuronal identity switch in the superficial layers of the primary somatosensory cortex

During learning, multi-dimensional inputs are integrated within the sensory cortices. However, the strategies by which the sensory cortex employs to achieve learning remains poorly understood. We studied the sensory cortical neuronal coding of trace eyeblink conditioning (TEC) in head-fixed, freely running mice, where whisker deflection was used as a conditioned stimulus (CS) and an air puff to the cornea delivered after an interval was used as unconditioned stimulus (US). After training, mice learned the task with a set of stereotypical behavioral changes, most prominent ones include prolonged closure of eyelids, and increased reverse running between CS and US onset. The local blockade of the primary somatosensory cortex (S1) activities with muscimol abolished the behavior learning suggesting that S1 is required for the TEC. In naive animals, based on the response properties to the CS and US, identities of the small proportion (~20%) of responsive primary neurons (PNs) were divided into two subtypes: CR (i.e. CS-responsive) and UR neurons (i.e. US-responsive). After animals learned the task, identity of CR and UR neurons changed: while the CR neurons are less responsive to CS, UR neurons gain responsiveness to CS, a new phenomenon we defined as 'learning induced neuronal identity switch (LINIS)'. To explore the potential mechanisms underlying LINIS, we found that systemic and local (i.e. in S1) administration of the nicotinic receptor antagonist during TEC training blocked the LINIS, and concomitantly disrupted the behavior learning. Additionally, we monitored responses of two types of cortical interneurons (INs) and observed that the responses of the somatostatin-expressing (SST), but not parvalbumin-expressing (PV) INs are negatively correlated with the learning performance, suggesting that SST-INs contribute to the LINIS. Thus, we conclude that L2/3 PNs in S1 encode perceptual learning by LINIS like mechanisms, and cholinergic pathways and cortical SST interneurons are involved in the formation of LINIS.

Dynamics of cortical contrast adaptation predict perception of signals in noise

Neurons throughout the sensory pathway adapt their responses depending on the statistical structure of the sensory environment. Contrast gain control is a form of adaptation in the auditory cortex, but it is unclear whether the dynamics of gain control reflect efficient adaptation, and whether they shape behavioral perception. Here, we trained mice to detect a target presented in background noise shortly after a change in the contrast of the background. The observed changes in cortical gain and behavioral detection followed the dynamics of a normative model of efficient contrast gain control; specifically, target detection and sensitivity improved slowly in low contrast, but degraded rapidly in high contrast. Auditory cortex was required for this task, and cortical responses were not only similarly affected by contrast but predicted variability in behavioral performance. Combined, our results demonstrate that dynamic gain adaptation supports efficient coding in auditory cortex and predicts the perception of sounds in noise.

Auditory cortex ensembles jointly encode sound and locomotion speed to support sound perception during movement

The ability to process and act upon incoming sounds during locomotion is critical for survival and adaptive behavior. Despite the established role that the auditory cortex (AC) plays in behavior- and context-dependent sound processing, previous studies have found that auditory cortical activity is on average suppressed during locomotion as compared to immobility. While suppression of auditory cortical responses to self-generated sounds results from corollary discharge, which weakens responses to predictable sounds, the functional role of weaker responses to unpredictable external sounds during locomotion remains unclear. In particular, whether suppression of external sound-evoked responses during locomotion reflects reduced involvement of the AC in sound processing or whether it results from masking by an alternative neural computation in this state remains unresolved. Here, we tested the hypothesis that rather than simple inhibition, reduced sound-evoked responses during locomotion reflect a tradeoff with the emergence of explicit and reliable coding of locomotion velocity. To test this hypothesis, we first used neural inactivation in behaving mice and found that the AC plays a critical role in sound-guided behavior during locomotion. To investigate the nature of this processing, we used two-photon calcium imaging of local excitatory auditory cortical neural populations in awake mice. We found that locomotion had diverse influences on activity of different neurons, with a net suppression of baseline-subtracted sound-evoked responses and neural stimulus detection, consistent with previous studies. Importantly, we found that the net inhibitory effect of locomotion on baseline-subtracted sound-evoked responses was strongly shaped by elevated ongoing activity that compressed the response dynamic range, and that rather than reflecting enhanced "noise," this ongoing activity reliably encoded the animal's locomotion speed. Decoding analyses revealed that locomotion speed and sound are robustly co-encoded by auditory cortical ensemble activity. Finally, we found consistent patterns of joint coding of sound and locomotion speed in electrophysiologically recorded activity in freely moving rats. Together, our data suggest that rather than being suppressed by locomotion, auditory cortical ensembles explicitly encode it alongside sound information to support sound perception during locomotion.

Sleep-like changes in neural processing emerge during sleep deprivation in early auditory cortex

Insufficient sleep is commonplace in modern lifestyle and can lead to grave outcomes, yet the changes in neuronal activity accumulating over hours of extended wakefulness remain poorly understood. Specifically, which aspects of cortical processing are affected by sleep deprivation (SD), and whether they also affect early sensory regions, remain unclear. Here, we recorded spiking activity in the rat auditory cortex along with polysomnography while presenting sounds during SD followed by recovery sleep. We found that frequency tuning, onset responses, and spontaneous firing rates were largely unaffected by SD. By contrast, SD decreased entrainment to rapid (≥20 Hz) click trains, increased population synchrony, and increased the prevalence of sleep-like stimulus-induced silent periods, even when ongoing activity was similar. Recovery NREM sleep was associated with similar effects as SD with even greater magnitude, while auditory processing during REM sleep was similar to vigilant wakefulness. Our results show that processes akin to those in NREM sleep invade the activity of cortical circuits during SD, even in the early sensory cortex.

Unexpected sound omissions are signaled in human posterior superior temporal gyrus: an intracranial study

Context modulates sensory neural activations enhancing perceptual and behavioral performance and reducing prediction errors. However, the mechanism of when and where these high-level expectations act on sensory processing is unclear. Here, we isolate the effect of expectation absent of any auditory evoked activity by assessing the response to omitted expected sounds. Electrocorticographic signals were recorded directly from subdural electrode grids placed over the superior temporal gyrus (STG). Subjects listened to a predictable sequence of syllables, with some infrequently omitted. We found high-frequency band activity (HFA, 70-170 Hz) in response to omissions, which overlapped with a posterior subset of auditory-active electrodes in STG. Heard syllables could be distinguishable reliably from STG, but not the identity of the omitted stimulus. Both omission- and target-detection responses were also observed in the prefrontal cortex. We propose that the posterior STG is central for implementing predictions in the auditory environment. HFA omission responses in this region appear to index mismatch-signaling or salience detection processes.

Basal Forebrain Modulation of Olfactory Coding In Vivo

Sensory perception is one of the most fundamental brain functions, allowing individuals to properly interact and adapt to a constantly changing environment. This process requires the integration of bottom-up and topdown neuronal activity, which is centrally mediated by the basal forebrain, a brain region that has been linked to a series of cognitive processes such as attention and alertness. Here, we review the latest research using optogenetic approaches in rodents and in vivo electrophysiological recordings that are shedding light on the role of this region, in regulating olfactory processing and decisionmaking. Moreover, we summarize evidence highlighting the anatomical and physiological differences in the basal forebrain of individuals with autism spectrum disorder, which could underpin the sensory perception abnormalities they exhibit, and propose this research line as a potential opportunity to understand the neurobiological basis of this disorder.

Coherent mapping of position and head direction across auditory and visual cortex

Neurons in primary visual cortex (V1) may not only signal current visual input but also relevant contextual information such as reward expectancy and the subject's spatial position. Such contextual representations need not be restricted to V1 but could participate in a coherent mapping throughout sensory cortices. Here, we show that spiking activity coherently represents a location-specific mapping across auditory cortex (AC) and lateral, secondary visual cortex (V2L) of freely moving rats engaged in a sensory detection task on a figure-8 maze. Single-unit activity of both areas showed extensive similarities in terms of spatial distribution, reliability, and position coding. Importantly, reconstructions of subject position based on spiking activity displayed decoding errors that were correlated between areas. Additionally, we found that head direction, but not locomotor speed or head angular velocity, was an important determinant of activity in AC and V2L. By contrast, variables related to the sensory task cues or to trial correctness and reward were not markedly encoded in AC and V2L. We conclude that sensory cortices participate in coherent, multimodal representations of the subject's sensory-specific location. These may provide a common reference frame for distributed cortical sensory and motor processes and may support crossmodal predictive processing.

Attention in flux

Selective attention comprises essential infrastructural functions supporting cognition-anticipating, prioritizing, selecting, routing, integrating, and preparing signals to guide adaptive behavior. Most studies have examined its consequences, systems, and mechanisms in a static way, but attention is at the confluence of multiple sources of flux. The world advances, we operate within it, our minds change, and all resulting signals progress through multiple pathways within the dynamic networks of our brains. Our aim in this review is to raise awareness of and interest in three important facets of how timing impacts our understanding of attention. These include the challenges posed to attention by the timing of neural processing and psychological functions, the opportunities conferred to attention by various temporal structures in the environment, and how tracking the time courses of neural and behavioral modulations with continuous measures yields surprising insights into the workings and principles of attention.

Multimodal processing in face-to-face interactions: A bridging link between psycholinguistics and sensory neuroscience

In face-to-face communication, humans are faced with multiple layers of discontinuous multimodal signals, such as head, face, hand gestures, speech and non-speech sounds, which need to be interpreted as coherent and unified communicative actions. This implies a fundamental computational challenge: optimally binding only signals belonging to the same communicative action while segregating signals that are not connected by the communicative content. How do we achieve such an extraordinary feat, reliably, and efficiently? To address this question, we need to further move the study of human communication beyond speech-centred perspectives and promote a multimodal approach combined with interdisciplinary cooperation. Accordingly, we seek to reconcile two explanatory frameworks recently proposed in psycholinguistics and sensory neuroscience into a neurocognitive model of multimodal face-to-face communication. First, we introduce a psycholinguistic framework that characterises face-to-face communication at three parallel processing levels: multiplex signals, multimodal gestalts and multilevel predictions. Second, we consider the recent proposal of a lateral neural visual pathway specifically dedicated to the dynamic aspects of social perception and reconceive it from a multimodal perspective ("lateral processing pathway"). Third, we reconcile the two frameworks into a neurocognitive model that proposes how multiplex signals, multimodal gestalts, and multilevel predictions may be implemented along the lateral processing pathway. Finally, we advocate a multimodal and multidisciplinary research approach, combining state-of-the-art imaging techniques, computational modelling and artificial intelligence for future empirical testing of our model.

Spatiotemporal and sensory modality attention processing with domain-specific representations in frontoparietal areas

The frontoparietal network (FPN), including bilateral frontal eye field, inferior parietal sulcus, and supplementary motor area, has been linked to attention processing, including spatiotemporal and sensory modality domains. However, it is unclear whether FPN encodes representations of these domains that are generalizable across subdomains. We decomposed multivariate patterns of functional magnetic resonance imaging activity from 20 participants into domain-specific components and identified latent multivariate representations that generalized across subdomains. The 30 experimental conditions were organized into unimodal-bimodal and spatial-temporal models. We found that brain areas in the FPN, form the primary network that modulated during attention across domains. However, the activation patterns of areas within the FPN were reorganized according to the specific attentional demand, especially when pay attention to different sensory, suggesting distinct regional neural representations associated with specific attentional processes within FPN. In addition, there were also other domain-specific areas outside the FPN, such as the dorsolateral prefrontal cortex. Our conclusion is that, according to the results of the analysis of representation similarity, 2 types of activated brain regions, related to attention domain detailed information processing and general information processing, can be revealed.

Neural basis of anticipation and premature impulsive action in the frontal cortex

Planning motor actions can improve behavioral performance; however, it can also lead to premature actions. Although the anterior lateral motor cortex (ALM) is known to be important for correct motor planning, it is currently unknown how it contributes to premature impulsive motor output. This was addressed using whole-cell voltage recordings from layer 2/3 pyramidal neurons within the ALM while mice performed a cued sensory association task. Here, a robust voltage response was evoked during the auditory cue, which was greater during incorrect premature behavior than during correct performance in the task. Optogenetically suppressing ALM during the cued sensory association task led to enhanced behavior, with fewer, and more delayed, premature responses and faster correct responses. Taken together, our findings extend the current known roles of the ALM, illustrating that ALM plays an important role in impulsive behavior by encoding and influencing premature motor output.

The neural bases for timing of durations

Durations are defined by a beginning and an end, and a major distinction is drawn between durations that start in the present and end in the future ('prospective timing') and durations that start in the past and end either in the past or the present ('retrospective timing'). Different psychological processes are thought to be engaged in each of these cases. The former is thought to engage a clock-like mechanism that accurately tracks the continuing passage of time, whereas the latter is thought to engage a reconstructive process that utilizes both temporal and non-temporal information from the memory of past events. We propose that, from a biological perspective, these two forms of duration 'estimation' are supported by computational processes that are both reliant on population state dynamics but are nevertheless distinct. Prospective timing is effectively carried out in a single step where the ongoing dynamics of population activity directly serve as the computation of duration, whereas retrospective timing is carried out in two steps: the initial generation of population state dynamics through the process of event segmentation and the subsequent computation of duration utilizing the memory of those dynamics.

Neural mechanisms underlying the temporal organization of naturalistic animal behavior

Naturalistic animal behavior exhibits a strikingly complex organization in the temporal domain, with variability arising from at least three sources: hierarchical, contextual, and stochastic. What neural mechanisms and computational principles underlie such intricate temporal features? In this review, we provide a critical assessment of the existing behavioral and neurophysiological evidence for these sources of temporal variability in naturalistic behavior. Recent research converges on an emergent mechanistic theory of temporal variability based on attractor neural networks and metastable dynamics, arising via coordinated interactions between mesoscopic neural circuits. We highlight the crucial role played by structural heterogeneities as well as noise from mesoscopic feedback loops in regulating flexible behavior. We assess the shortcomings and missing links in the current theoretical and experimental literature and propose new directions of investigation to fill these gaps.

Implicit Versus Explicit Timing-Separate or Shared Mechanisms?

Time implicitly shapes cognition, but time is also explicitly represented, for instance, in the form of durations. Parsimoniously, the brain could use the same mechanisms for implicit and explicit timing. Yet, the evidence has been equivocal, revealing both joint versus separate signatures of timing. Here, we directly compared implicit and explicit timing using magnetoencephalography, whose temporal resolution allows investigating the different stages of the timing processes. Implicit temporal predictability was induced in an auditory paradigm by a manipulation of the foreperiod. Participants received two consecutive task instructions: discriminate pitch (indirect measure of implicit timing) or duration (direct measure of explicit timing). The results show that the human brain efficiently extracts implicit temporal statistics of sensory environments, to enhance the behavioral and neural responses to auditory stimuli, but that those temporal predictions did not improve explicit timing. In both tasks, attentional orienting in time during predictive foreperiods was indexed by an increase in alpha power over visual and parietal areas. Furthermore, pretarget induced beta power in sensorimotor and parietal areas increased during implicit compared to explicit timing, in line with the suggested role for beta oscillations in temporal prediction. Interestingly, no distinct neural dynamics emerged when participants explicitly paid attention to time, compared to implicit timing. Our work thus indicates that implicit timing shapes the behavioral and sensory response in an automatic way and is reflected in oscillatory neural dynamics, whereas the translation of implicit temporal statistics to explicit durations remains somewhat inconclusive, possibly because of the more abstract nature of this task.

Expectations of the timing and intensity of a stimulus propagate to the auditory periphery through the medial olivocochlear reflex

Expectations concerning the timing of a stimulus enhance attention at the time at which the event occurs, which confers significant sensory and behavioral benefits. Herein, we show that temporal expectations modulate even the sensory transduction in the auditory periphery via the descending pathway. We measured the medial olivocochlear reflex (MOCR), a sound-activated efferent feedback that controls outer hair cell motility and optimizes the dynamic range of the sensory system. MOCR was noninvasively assessed using otoacoustic emissions. We found that the MOCR was enhanced by a visual cue presented at a fixed interval before a sound but was unaffected if the interval was changing between trials. The MOCR was also observed to be stronger when the learned timing expectation matched with the timing of the sound but remained unvaried when these two factors did not match. This implies that the MOCR can be voluntarily controlled in a stimulus- and goal-directed manner. Moreover, we found that the MOCR was enhanced by the expectation of a strong but not a weak, sound intensity. This asymmetrical enhancement could facilitate antimasking and noise protective effects without disrupting the detection of faint signals. Therefore, the descending pathway conveys temporal and intensity expectations to modulate auditory processing.

Parallel processing in speech perception with local and global representations of linguistic context

Speech processing is highly incremental. It is widely accepted that human listeners continuously use the linguistic context to anticipate upcoming concepts, words, and phonemes. However, previous evidence supports two seemingly contradictory models of how a predictive context is integrated with the bottom-up sensory input: Classic psycholinguistic paradigms suggest a two-stage process, in which acoustic input initially leads to local, context-independent representations, which are then quickly integrated with contextual constraints. This contrasts with the view that the brain constructs a single coherent, unified interpretation of the input, which fully integrates available information across representational hierarchies, and thus uses contextual constraints to modulate even the earliest sensory representations. To distinguish these hypotheses, we tested magnetoencephalography responses to continuous narrative speech for signatures of local and unified predictive models. Results provide evidence that listeners employ both types of models in parallel. Two local context models uniquely predict some part of early neural responses, one based on sublexical phoneme sequences, and one based on the phonemes in the current word alone; at the same time, even early responses to phonemes also reflect a unified model that incorporates sentence-level constraints to predict upcoming phonemes. Neural source localization places the anatomical origins of the different predictive models in nonidentical parts of the superior temporal lobes bilaterally, with the right hemisphere showing a relative preference for more local models. These results suggest that speech processing recruits both local and unified predictive models in parallel, reconciling previous disparate findings. Parallel models might make the perceptual system more robust, facilitate processing of unexpected inputs, and serve a function in language acquisition.

Reaction Time Sensitivity to Spectrotemporal Modulations of Sound

We tested whether sensitivity to acoustic spectrotemporal modulations can be observed from reaction times for normal-hearing and impaired-hearing conditions. In a manual reaction-time task, normal-hearing listeners had to detect the onset of a ripple (with density between 0-8 cycles/octave and a fixed modulation depth of 50%), that moved up or down the log-frequency axis at constant velocity (between 0-64 Hz), in an otherwise-unmodulated broadband white-noise. Spectral and temporal modulations elicited band-pass filtered sensitivity characteristics, with fastest detection rates around 1 cycle/oct and 32 Hz for normal-hearing conditions. These results closely resemble data from other studies that typically used the modulation-depth threshold as a sensitivity criterion. To simulate hearing-impairment, stimuli were processed with a 6-channel cochlear-implant vocoder, and a hearing-aid simulation that introduced separate spectral smearing and low-pass filtering. Reaction times were always much slower compared to normal hearing, especially for the highest spectral densities. Binaural performance was predicted well by the benchmark race model of binaural independence, which models statistical facilitation of independent monaural channels. For the impaired-hearing simulations this implied a "best-of-both-worlds" principle in which the listeners relied on the hearing-aid ear to detect spectral modulations, and on the cochlear-implant ear for temporal-modulation detection. Although singular-value decomposition indicated that the joint spectrotemporal sensitivity matrix could be largely reconstructed from independent temporal and spectral sensitivity functions, in line with time-spectrum separability, a substantial inseparable spectral-temporal interaction was present in all hearing conditions. These results suggest that the reaction-time task yields a valid and effective objective measure of acoustic spectrotemporal-modulation sensitivity.

Three Water Restriction Schedules Used in Rodent Behavioral Tasks Transiently Impair Growth and Differentially Evoke a Stress Hormone Response without Causing Dehydration

Water restriction is commonly used to motivate rodents to perform behavioral tasks; however, its effects on hydration and stress hormone levels are unknown. Here, we report daily body weight and bi-weekly packed red blood cell volume and corticosterone (CORT) in adult male rats across 80 days for three commonly used water restriction schedules. We also assessed renal adaptation to water restriction using postmortem histologic evaluation of renal medulla. A control group received ad libitum water. After one week of water restriction, rats on all restriction schedules resumed similar levels of growth relative to the control group. Normal hydration was observed, and water restriction did not drive renal adaptation. An intermittent restriction schedule was associated with an increase in CORT relative to the control group. However, intermittent restriction evokes a stress response which could affect behavioral and neurobiological results. Our results also suggest that stable motivation in behavioral tasks may only be achieved after one week of restriction.

Cross-modal perceptual enhancement of unisensory targets is uni-directional and does not affect temporal expectations

Temporal structures in the environment can shape temporal expectations (TE); and previous studies demonstrated that TEs interact with multisensory interplay (MSI) when multisensory stimuli are presented synchronously. Here, we tested whether other types of MSI - evoked by asynchronous yet temporally flanking irrelevant stimuli - result in similar performance patterns. To this end, we presented sequences of 12 stimuli (10 Hz) which consisted of auditory (A), visual (V) or alternating auditory-visual stimuli (e.g. A-V-A-V-…) with either auditory or visual targets (Exp. 1). Participants discriminated target frequencies (auditory pitch or visual spatial frequency) embedded in these sequences. To test effects of TE, the proportion of early and late temporal target positions was manipulated run-wise. Performance for unisensory targets was affected by temporally flanking distractors, with auditory temporal flankers selectively improving visual target perception (Exp. 1). However, no effect of temporal expectation was observed. Control experiments (Exp. 2-3) tested whether this lack of TE effect was due to the higher presentation frequency in Exp. 1 relative to previous experiments. Importantly, even at higher stimulation frequencies redundant multisensory targets (Exp. 2-3) reliably modulated TEs. Together, our results indicate that visual target detection was enhanced by MSI. However, this cross-modal enhancement - in contrast to the redundant target effect - was still insufficient to generate TEs. We posit that unisensory target representations were either instable or insufficient for the generation of TEs while less demanding MSI still occurred; highlighting the need for robust stimulus representations when generating temporal expectations.

Self-generation and sound intensity interactively modulate perceptual bias, but not perceptual sensitivity

The ability to distinguish self-generated stimuli from those caused by external sources is critical for all behaving organisms. Although many studies point to a sensory attenuation of self-generated stimuli, recent evidence suggests that motor actions can result in either attenuated or enhanced perceptual processing depending on the environmental context (i.e., stimulus intensity). The present study employed 2-AFC sound detection and loudness discrimination tasks to test whether sound source (self- or externally-generated) and stimulus intensity (supra- or near-threshold) interactively modulate detection ability and loudness perception. Self-generation did not affect detection and discrimination sensitivity (i.e., detection thresholds and Just Noticeable Difference, respectively). However, in the discrimination task, we observed a significant interaction between self-generation and intensity on perceptual bias (i.e. Point of Subjective Equality). Supra-threshold self-generated sounds were perceived softer than externally-generated ones, while at near-threshold intensities self-generated sounds were perceived louder than externally-generated ones. Our findings provide empirical support to recent theories on how predictions and signal intensity modulate perceptual processing, pointing to interactive effects of intensity and self-generation that seem to be driven by a biased estimate of perceived loudness, rather by changes in detection and discrimination sensitivity.

Minimal interplay between explicit knowledge, dynamics of learning and temporal expectations in different, complex uni- and multisensory contexts

While temporal expectations (TE) generally improve reactions to temporally predictable events, it remains unknown how the learning of temporal regularities (one time point more likely than another time point) and explicit knowledge about temporal regularities contribute to performance improvements; and whether any contributions generalise across modalities. Here, participants discriminated the frequency of diverging auditory, visual or audio-visual targets embedded in auditory, visual or audio-visual distractor sequences. Temporal regularities were manipulated run-wise (early vs. late target within sequence). Behavioural performance (accuracy, RT) plus measures from a computational learning model all suggest that learning of temporal regularities occurred but did not generalise across modalities, and that dynamics of learning (size of TE effect across runs) and explicit knowledge have little to no effect on the strength of TE. Remarkably, explicit knowledge affects performance-if at all-in a context-dependent manner: Only under complex task regimes (here, unknown target modality) might it partially help to resolve response conflict while it is lowering performance in less complex environments.

Context dependency of time-based event-related expectations for different modalities

Expectations about the temporal occurrence of events (when) are often tied with the expectations about certain event-related properties (what and where) happening at these time points. For instance, slowly waking up in the morning we expect our alarm clock to go off; however, the longer we do not hear it the more likely we already missed it. However, most current evidence for complex time-based event-related expectations (TBEEs) is based on the visual modality. Here we tested whether implicit TBEEs can act cross-modally. To this end, visual and auditory stimulus streams were presented which contained early and late targets embedded among distractors (to maximise temporal target uncertainty). Foreperiod-modality-contingencies were manipulated run-wise: visual targets either occurred early in 80% of trials and auditory targets occurred late in 80% of trials or vice versa. Participants showed increased sensitivity for expected auditory early/visual late targets which increased over time while the opposite pattern was observed for visual early/auditory late targets. A benefit in reaction times was only found for auditory early trials. Together, this pattern of results suggests that implicit context-dependent TBEEs for auditory targets after short foreperiods (be they correct or not) dominated and determined which modality became more expected at the late position irrespective of the veridical statistical regularity. Hence, TBEEs in cross-modal and uncertain environments are context-dependent, shaped by the dominant modality in temporal tasks (i.e., auditory) and only boost performance cross-modally when expectations about the event after the short foreperiod match with the run-wise context (i.e., auditory early/visual late).

Behavioral Approaches to Study Top-Down Influences on Active Listening

The massive network of descending corticofugal projections has been long-recognized by anatomists, but their functional contributions to sound processing and auditory-guided behaviors remain a mystery. Most efforts to characterize the auditory corticofugal system have been inductive; wherein function is inferred from a few studies employing a wide range of methods to manipulate varying limbs of the descending system in a variety of species and preparations. An alternative approach, which we focus on here, is to first establish auditory-guided behaviors that reflect the contribution of top-down influences on auditory perception. To this end, we postulate that auditory corticofugal systems may contribute to active listening behaviors in which the timing of bottom-up sound cues can be predicted from top-down signals arising from cross-modal cues, temporal integration, or self-initiated movements. Here, we describe a behavioral framework for investigating how auditory perceptual performance is enhanced when subjects can anticipate the timing of upcoming target sounds. Our first paradigm, studied both in human subjects and mice, reports species-specific differences in visually cued expectation of sound onset in a signal-in-noise detection task. A second paradigm performed in mice reveals the benefits of temporal regularity as a perceptual grouping cue when detecting repeating target tones in complex background noise. A final behavioral approach demonstrates significant improvements in frequency discrimination threshold and perceptual sensitivity when auditory targets are presented at a predictable temporal interval following motor self-initiation of the trial. Collectively, these three behavioral approaches identify paradigms to study top-down influences on sound perception that are amenable to head-fixed preparations in genetically tractable animals, where it is possible to monitor and manipulate particular nodes of the descending auditory pathway with unparalleled precision.

Mesoscale cortical dynamics reflect the interaction of sensory evidence and temporal expectation during perceptual decision-making

How sensory evidence is transformed across multiple brain regions to influence behavior remains poorly understood. We trained mice in a visual change detection task designed to separate the covert antecedents of choices from activity associated with their execution. Wide-field calcium imaging across the dorsal cortex revealed fundamentally different dynamics of activity underlying these processes. Although signals related to execution of choice were widespread, fluctuations in sensory evidence in the absence of overt motor responses triggered a confined activity cascade, beginning with transient modulation of visual cortex and followed by sustained recruitment of the secondary and primary motor cortex. Activation of the motor cortex by sensory evidence was modulated by animals' expectation of when the stimulus was likely to change. These results reveal distinct activation timescales of specific cortical areas by sensory evidence during decision-making and show that recruitment of the motor cortex depends on the interaction of sensory evidence and temporal expectation.

A cortical circuit mechanism for structural knowledge-based flexible sensorimotor decision-making

Making flexible decisions based on prior knowledge about causal environmental structures is a hallmark of goal-directed cognition in mammalian brains. Although several association brain regions, including the orbitofrontal cortex (OFC), have been implicated, the precise neuronal circuit mechanisms underlying knowledge-based decision-making remain elusive. Here, we established an inference-based auditory categorization task where mice performed within-session flexible stimulus re-categorization by inferring the changing task rules. We constructed a reinforcement learning model to recapitulate the inference-based flexible behavior and quantify the hidden variables associated with task structural knowledge. Combining two-photon population imaging and projection-specific optogenetics, we found that auditory cortex (ACx) neurons encoded the hidden task rule variable, which requires feedback input from the OFC. Silencing OFC-ACx input specifically disrupted re-categorization behavior. Direct imaging from OFC axons in the ACx revealed task state-related feedback signals, supporting the knowledge-based updating mechanism. Our data reveal a cortical circuit mechanism underlying structural knowledge-based flexible decision-making.

State-Dependent Regulation of Cortical Processing Speed via Gain Modulation

To thrive in dynamic environments, animals must be capable of rapidly and flexibly adapting behavioral responses to a changing context and internal state. Examples of behavioral flexibility include faster stimulus responses when attentive and slower responses when distracted. Contextual or state-dependent modulations may occur early in the cortical hierarchy and may be implemented via top-down projections from corticocortical or neuromodulatory pathways. However, the computational mechanisms mediating the effects of such projections are not known. Here, we introduce a theoretical framework to classify the effects of cell type-specific top-down perturbations on the information processing speed of cortical circuits. Our theory demonstrates that perturbation effects on stimulus processing can be predicted by intrinsic gain modulation, which controls the timescale of the circuit dynamics. Our theory leads to counterintuitive effects, such as improved performance with increased input variance. We tested the model predictions using large-scale electrophysiological recordings from the visual hierarchy in freely running mice, where we found that a decrease in single-cell intrinsic gain during locomotion led to an acceleration of visual processing. Our results establish a novel theory of cell type-specific perturbations, applicable to top-down modulation as well as optogenetic and pharmacological manipulations. Our theory links connectivity, dynamics, and information processing via gain modulation.SIGNIFICANCE STATEMENT To thrive in dynamic environments, animals adapt their behavior to changing circumstances and different internal states. Examples of behavioral flexibility include faster responses to sensory stimuli when attentive and slower responses when distracted. Previous work suggested that contextual modulations may be implemented via top-down inputs to sensory cortex coming from higher brain areas or neuromodulatory pathways. Here, we introduce a theory explaining how the speed at which sensory cortex processes incoming information is adjusted by changes in these top-down projections, which control the timescale of neural activity. We tested our model predictions in freely running mice, revealing that locomotion accelerates visual processing. Our theory is applicable to internal modulation as well as optogenetic and pharmacological manipulations and links circuit connectivity, dynamics, and information processing.

Rotational dynamics reduce interference between sensory and memory representations

Cognition depends on integrating sensory percepts with the memory of recent stimuli. However, the distributed nature of neural coding can lead to interference between sensory and memory representations. Here, we show that the brain mitigates such interference by rotating sensory representations into orthogonal memory representations over time. To study how sensory inputs and memories are represented, we recorded neurons from the auditory cortex of mice as they implicitly learned sequences of sounds. We found that the neural population represented sensory inputs and the memory of recent stimuli in two orthogonal dimensions. The transformation of sensory information into a memory was facilitated by a combination of 'stable' neurons, which maintained their selectivity over time, and 'switching' neurons, which inverted their selectivity over time. Together, these neural responses rotated the population representation, transforming sensory inputs into memory. Theoretical modeling showed that this rotational dynamic is an efficient mechanism for generating orthogonal representations, thereby protecting memories from sensory interference.