Strategic stabilization of arousal boosts sustained attention.

Arousal and motivation interact to profoundly influence behavior. For example, experience tells us that we have some capacity to control our arousal when appropriately motivated, such as staying awake while driving a motor vehicle. However, little is known about how arousal and motivation jointly influence decision computations, including if and how animals, such as rodents, adapt their arousal state to their needs. Here, we developed and show results from an auditory, feature-based, sustained-attention task with intermittently shifting task utility. We use pupil size to estimate arousal across a wide range of states and apply tailored signal-detection theoretic, hazard function, and accumulation-to-bound modeling approaches in a large cohort of mice. We find that pupil-linked arousal and task utility both have major impacts on multiple aspects of task performance. Although substantial arousal fluctuations persist across utility conditions, mice partially stabilize their arousal near an intermediate and optimal level when task utility is high. Behavioral analyses show that multiple elements of behavior improve during high task utility and that arousal influences some, but not all, of them. Specifically, arousal influences the likelihood and timescale of sensory evidence accumulation but not the quantity of evidence accumulated per time step while attending. In sum, the results establish specific decision-computational signatures of arousal, motivation, and their interaction in attention. So doing, we provide an experimental and analysis framework for studying arousal self-regulation in neurotypical brains and in diseases such as attention-deficit/hyperactivity disorder.

Foraging Under Uncertainty Follows the Marginal Value Theorem with Bayesian Updating of Environment Representations.

Foraging theory has been a remarkably successful approach to understanding the behavior of animals in many contexts. In patch-based foraging contexts, the marginal value theorem (MVT) shows that the optimal strategy is to leave a patch when the marginal rate of return declines to the average for the environment. However, the MVT is only valid in deterministic environments whose statistics are known to the forager; naturalistic environments seldom meet these strict requirements. As a result, the strategies used by foragers in naturalistic environments must be empirically investigated. We developed a novel behavioral task and a corresponding computational framework for studying patch-leaving decisions in head-fixed and freely moving mice. We varied between-patch travel time, as well as within-patch reward depletion rate, both deterministically and stochastically. We found that mice adopt patch residence times in a manner consistent with the MVT and not explainable by simple ethologically motivated heuristic strategies. Critically, behavior was best accounted for by a modified form of the MVT wherein environment representations were updated based on local variations in reward timing, captured by a Bayesian estimator and dynamic prior. Thus, we show that mice can strategically attend to, learn from, and exploit task structure on multiple timescales simultaneously, thereby efficiently foraging in volatile environments. The results provide a foundation for applying the systems neuroscience toolkit in freely moving and head-fixed mice to understand the neural basis of foraging under uncertainty.

Cortical acetylcholine dynamics are predicted by cholinergic axon activity and behavior state.

Even under spontaneous conditions and in the absence of changing environmental demands, awake animals alternate between increased or decreased periods of alertness. These changes in brain state can occur rapidly, on a timescale of seconds, and neuromodulators such as acetylcholine (ACh) are thought to play an important role in driving these spontaneous state transitions. Here, we perform the first simultaneous imaging of ACh sensors and GCaMP-expressing axons in vivo, to examine the spatiotemporal properties of cortical ACh activity and release during spontaneous changes in behavioral state. We observed a high correlation between simultaneously recorded basal forebrain axon activity and neuromodulator sensor fluorescence around periods of locomotion and pupil dilation. Consistent with volume transmission of ACh, increases in axon activity were accompanied by increases in local ACh levels that fell off with the distance from the nearest axon. GRAB-ACh fluorescence could be accurately predicted from axonal activity alone, providing the first validation that neuromodulator axon activity is a reliable proxy for nearby neuromodulator levels. Deconvolution of fluorescence traces allowed us to account for the kinetics of the GRAB-ACh sensor and emphasized the rapid clearance of ACh for smaller transients outside of running periods. Finally, we trained a predictive model of ACh fluctuations from the combination of pupil size and running speed; this model performed better than using either variable alone, and generalized well to unseen data. Overall, these results contribute to a growing understanding of the precise timing and spatial characteristics of cortical ACh during fast brain state transitions.

Comprehensive analysis of cellular specializations that initiate parallel auditory processing pathways in mice.

The cochlear nuclear complex (CN) is the starting point for all central auditory processing and comprises a suite of neuronal cell types that are highly specialized for neural coding of acoustic signals. To examine how their striking functional specializations are determined at the molecular level, we performed single-nucleus RNA sequencing of the mouse CN to molecularly define all constituent cell types and related them to morphologically- and electrophysiologically-defined neurons using Patch-seq. We reveal an expanded set of molecular cell types encompassing all previously described major types and discover new subtypes both in terms of topographic and cell-physiologic properties. Our results define a complete cell-type taxonomy in CN that reconciles anatomical position, morphological, physiological, and molecular criteria. This high-resolution account of cellular heterogeneity and specializations from the molecular to the circuit level illustrates molecular underpinnings of functional specializations and enables genetic dissection of auditory processing and hearing disorders with unprecedented specificity.

Why study mechanisms of brain stimulation therapies? To modulate the right neurons, in the right way, at the right time.

Clinical applications of vagus nerve stimulation (VNS) are burgeoning, but mechanistic work lags behind. In this issue of Neuron, Bowles and colleagues show that VNS timed with positive reinforcement improves motor learning and cortical function by a cholinergic mechanism.

Graded recruitment of pupil-linked neuromodulation by parametric stimulation of the vagus nerve.

Vagus nerve stimulation (VNS) is thought to affect neural activity by recruiting brain-wide release of neuromodulators. VNS is used in treatment-resistant epilepsy, and is increasingly being explored for other disorders, such as depression, and as a cognitive enhancer. However, the promise of VNS is only partially fulfilled due to a lack of mechanistic understanding of the transfer function between stimulation parameters and neuromodulatory response, together with a lack of biosensors for assaying stimulation efficacy in real time. We here develop an approach to VNS in head-fixed mice on a treadmill and show that pupil dilation is a reliable and convenient biosensor for VNS-evoked cortical neuromodulation. In an 'optimal' zone of stimulation parameters, current leakage and off-target effects are minimized and the extent of pupil dilation tracks VNS-evoked basal-forebrain cholinergic axon activity in neocortex. Thus, pupil dilation is a sensitive readout of the moment-by-moment, titratable effects of VNS on brain state.

Sensory Neurobiology: A New Crossroads Deep in the Cortex.

Self-generated movements elicit concomitant sensory responses that are beneficial to ignore. Combining state-of-the-art physiology, behavior, and anatomy, a new study discovers a neural crossroads in the deepest layer of auditory cortex where pre-lick ramping activity suppresses peri-lick sound responses across layers.

Brain States: Sensory Modulations All the Way Down.

From wakefulness to sleep, and from moment to moment, the arousal state of the brain is a powerful internal context that shapes our perception and actions. Using cutting-edge imaging methods, two new studies show that arousal already sculpts visual information as it first enters the brain.

Novel Virtual Reality System for Auditory Tasks in Head-fixed Mice.

An emerging corpus of research seeks to use virtual realities (VRs) to understand the neural mechanisms underlying spatial navigation and decision making in rodents. These studies have primarily used visual stimuli to represent the virtual world. However, auditory cues play an important role in navigation for animals, especially when the visual system cannot detect objects or predators. We have developed a virtual reality environment defined exclusively by free-field acoustic landmarks for head-fixed mice. We trained animals to run in a virtual environment with 3 acoustic landmarks. We present evidence that they can learn to navigate in our context: we observed anticipatory licking and modest anticipatory slowing preceding the reward region. Furthermore, we found that animals were highly aware of changes in landmark cues: licking behavior changed dramatically when the familiar virtual environment was switched to a novel one, and then rapidly reverted to normal when the familiar virtual environment was re-introduced, all within the same session. Finally, while animals executed the task, we performed in-vivo calcium imaging in the CA1 region of the hippocampus using a modified Miniscope.org system. Our experiments point to a future in which auditory virtual reality can be used to expand our understanding of the neural bases of audition in locomoting animals and the variety of sensory cues which anchor spatial representations in a new virtual environment.

Pupil-linked phasic arousal predicts a reduction of choice bias across species and decision domains.

Decisions are often made by accumulating ambiguous evidence over time. The brain's arousal systems are activated during such decisions. In previous work in humans, we found that evoked responses of arousal systems during decisions are reported by rapid dilations of the pupil and track a suppression of biases in the accumulation of decision-relevant evidence (de Gee et al., 2017). Here, we show that this arousal-related suppression in decision bias acts on both conservative and liberal biases, and generalizes from humans to mice, and from perceptual to memory-based decisions. In challenging sound-detection tasks, the impact of spontaneous or experimentally induced choice biases was reduced under high phasic arousal. Similar bias suppression occurred when evidence was drawn from memory. All of these behavioral effects were explained by reduced evidence accumulation biases. Our results point to a general principle of interplay between phasic arousal and decision-making.

Sensation during Active Behaviors.

A substantial portion of our sensory experience happens during active behaviors such as walking around or paying attention. How do sensory systems work during such behaviors? Neural processing in sensory systems can be shaped by behavior in multiple ways ranging from a modulation of responsiveness or sharpening of tuning to a dynamic change of response properties or functional connectivity. Here, we review recent findings on the modulation of sensory processing during active behaviors in different systems: insect vision, rodent thalamus, and rodent sensory cortices. We discuss the circuit-level mechanisms that might lead to these modulations and their potential role in sensory function. Finally, we highlight the open questions and future perspectives of this exciting new field.

Pupil fluctuations track rapid changes in adrenergic and cholinergic activity in cortex.

Rapid variations in cortical state during wakefulness have a strong influence on neural and behavioural responses and are tightly coupled to changes in pupil size across species. However, the physiological processes linking cortical state and pupil variations are largely unknown. Here we demonstrate that these rapid variations, during both quiet waking and locomotion, are highly correlated with fluctuations in the activity of corticopetal noradrenergic and cholinergic projections. Rapid dilations of the pupil are tightly associated with phasic activity in noradrenergic axons, whereas longer-lasting dilations of the pupil, such as during locomotion, are accompanied by sustained activity in cholinergic axons. Thus, the pupil can be used to sensitively track the activity in multiple neuromodulatory transmitter systems as they control the state of the waking brain.

Reduced high-frequency motor neuron firing, EMG fractionation, and gait variability in awake walking ALS mice.

Amyotrophic lateral sclerosis (ALS) is a lethal neurodegenerative disease prominently featuring motor neuron (MN) loss and paralysis. A recent study using whole-cell patch clamp recording of MNs in acute spinal cord slices from symptomatic adult ALS mice showed that the fastest firing MNs are preferentially lost. To measure the in vivo effects of such loss, awake symptomatic-stage ALS mice performing self-initiated walking on a wheel were studied. Both single-unit extracellular recordings within spinal cord MN pools for lower leg flexor and extensor muscles and the electromyograms (EMGs) of the corresponding muscles were recorded. In the ALS mice, we observed absent or truncated high-frequency firing of MNs at the appropriate time in the step cycle and step-to-step variability of the EMG, as well as flexor-extensor coactivation. In turn, kinematic analysis of walking showed step-to-step variability of gait. At the MN level, the higher frequencies absent from recordings from mutant mice corresponded with the upper range of frequencies observed for fast-firing MNs in earlier slice measurements. These results suggest that, in SOD1-linked ALS mice, symptoms are a product of abnormal MN firing due at least in part to loss of neurons that fire at high frequency, associated with altered EMG patterns and hindlimb kinematics during gait.

Knockout of Foxp2 disrupts vocal development in mice.

The FOXP2 gene is important for the development of proper speech motor control in humans. However, the role of the gene in general vocal behavior in other mammals, including mice, is unclear. Here, we track the vocal development of Foxp2 heterozygous knockout (Foxp2+/-) mice and their wildtype (WT) littermates from juvenile to adult ages, and observe severe abnormalities in the courtship song of Foxp2+/- mice. In comparison to their WT littermates, Foxp2+/- mice vocalized less, produced shorter syllable sequences, and possessed an abnormal syllable inventory. In addition, Foxp2+/- song also exhibited irregular rhythmic structure, and its development did not follow the consistent trajectories observed in WT vocalizations. These results demonstrate that the Foxp2 gene is critical for normal vocal behavior in juvenile and adult mice, and that Foxp2 mutant mice may provide a tractable model system for the study of the gene's role in general vocal motor control.

Nonequivalent release sites govern synaptic depression.

Synaptic depression is prominent among synapses, but the underlying mechanisms remain uncertain. Here, we use paired patch clamp recording to study neuromuscular transmission between the caudal primary motor neuron and target skeletal muscle in zebrafish. This synapse has an unusually low number of release sites, all with high probabilities of release in response to low-frequency stimulation. During high-frequency stimulation, the synapse undergoes short-term depression and reaches steady-state levels of transmission that sustain the swimming behavior. To determine the release parameters underlying this steady state, we applied variance analysis. Our analysis revealed two functionally distinct subclasses of release sites differing by over 60-fold in rates of vesicle reloading. A slow reloading class requires seconds to recover and contributes to depression onset but not the steady-state transmission. By contrast, a fast reloading class recovers within tens of milliseconds and is solely responsible for steady-state transmission. Thus, in contrast to most current models that assign levels of steady-state depression to vesicle availability, our findings instead assign this function to nonuniform release site kinetics. The duality of active-site properties accounts for the highly nonlinear dependence of steady-state depression levels on frequency.

Waking State: Rapid Variations Modulate Neural and Behavioral Responses.

The state of the brain and body constantly varies on rapid and slow timescales. These variations contribute to the apparent noisiness of sensory responses at both the neural and the behavioral level. Recent investigations of rapid state changes in awake, behaving animals have provided insight into the mechanisms by which optimal sensory encoding and behavioral performance are achieved. Fluctuations in state, as indexed by pupillometry, impact both the "signal" (sensory evoked response) and the "noise" (spontaneous activity) of cortical responses. By taking these fluctuations into account, neural response (co)variability is significantly reduced, revealing the brain to be more reliable and predictable than previously thought.

Cortical Membrane Potential Signature of Optimal States for Sensory Signal Detection.

The neural correlates of optimal states for signal detection task performance are largely unknown. One hypothesis holds that optimal states exhibit tonically depolarized cortical neurons with enhanced spiking activity, such as occur during movement. We recorded membrane potentials of auditory cortical neurons in mice trained on a challenging tone-in-noise detection task while assessing arousal with simultaneous pupillometry and hippocampal recordings. Arousal measures accurately predicted multiple modes of membrane potential activity, including rhythmic slow oscillations at low arousal, stable hyperpolarization at intermediate arousal, and depolarization during phasic or tonic periods of hyper-arousal. Walking always occurred during hyper-arousal. Optimal signal detection behavior and sound-evoked responses, at both sub-threshold and spiking levels, occurred at intermediate arousal when pre-decision membrane potentials were stably hyperpolarized. These results reveal a cortical physiological signature of the classically observed inverted-U relationship between task performance and arousal and that optimal detection exhibits enhanced sensory-evoked responses and reduced background synaptic activity.

Brain state dependent activity in the cortex and thalamus.

Cortical and thalamocortical activity is highly state dependent, varying between patterns that are conducive to accurate sensory-motor processing, to states in which the brain is largely off-line and generating internal rhythms irrespective of the outside world. The generation of rhythmic activity occurs through the interaction of stereotyped patterns of connectivity together with intrinsic membrane and synaptic properties. One common theme in the generation of rhythms is the interaction of a positive feedback loop (e.g., recurrent excitation) with negative feedback control (e.g., inhibition, adaptation, or synaptic depression). The operation of these state-dependent activities has wide ranging effects from enhancing or blocking sensory-motor processing to the generation of pathological rhythms associated with psychiatric or neurological disorders.

Hierarchical excitatory synaptic connectivity in mouse olfactory cortex.

Topological motifs in synaptic connectivity-such as the cortical column-are fundamental to processing of information in cortical structures. However, the mesoscale topology of cortical networks beyond columns remains largely unknown. In the olfactory cortex, which lacks an obvious columnar structure, sensory-evoked patterns of activity have failed to reveal organizational principles of the network and its structure has been considered to be random. We probed the excitatory network in the mouse olfactory cortex using variance analysis of paired whole-cell recording in olfactory cortex slices. On a given trial, triggered network-wide bursts in disinhibited slices had remarkably similar time courses in widely separated and randomly selected cell pairs of pyramidal neurons despite significant trial-to-trial variability within each neuron. Simulated excitatory network models with random topologies only partially reproduced the experimental burst-variance patterns. Network models with local (columnar) or distributed subnetworks, which have been predicted as the basis of encoding odor objects, were also inconsistent with the experimental data, showing greater variability between cells than across trials. Rather, network models with power-law and especially hierarchical connectivity showed the best fit. Our results suggest that distributed subnetworks are weak or absent in the olfactory cortex, whereas a hierarchical excitatory topology may predominate. A hierarchical excitatory network organization likely underlies burst generation in this epileptogenic region, and may also shape processing of sensory information in the olfactory cortex.