Modulation of metastable ensemble dynamics explains optimal coding at moderate arousal in auditory cortex.

Performance during perceptual decision-making exhibits an inverted-U relationship with arousal, but the underlying network mechanisms remain unclear. Here, we recorded from auditory cortex (A1) of behaving mice during passive tone presentation, while tracking arousal via pupillometry. We found that tone discriminability in A1 ensembles was optimal at intermediate arousal, revealing a population-level neural correlate of the inverted-U relationship. We explained this arousal-dependent coding using a spiking network model with a clustered architecture. Specifically, we show that optimal stimulus discriminability is achieved near a transition between a multi-attractor phase with metastable cluster dynamics (low arousal) and a single-attractor phase (high arousal). Additional signatures of this transition include arousal-induced reductions of overall neural variability and the extent of stimulus-induced variability quenching, which we observed in the empirical data. Altogether, this study elucidates computational principles underlying interactions between pupil-linked arousal, sensory processing, and neural variability, and suggests a role for phase transitions in explaining nonlinear modulations of cortical computations.

Decision-making dynamics are predicted by arousal and uninstructed movements.

During sensory-guided behavior, an animal's decision-making dynamics unfold through sequences of distinct performance states, even while stimulus-reward contingencies remain static. Little is known about the factors that underlie these changes in task performance. We hypothesize that these decision-making dynamics can be predicted by externally observable measures, such as uninstructed movements and changes in arousal. Here, using computational modeling of visual and auditory task performance data from mice, we uncovered lawful relationships between transitions in strategic task performance states and an animal's arousal and uninstructed movements. Using hidden Markov models applied to behavioral choices during sensory discrimination tasks, we find that animals fluctuate between minutes-long optimal, sub-optimal, and disengaged performance states. Optimal state epochs are predicted by intermediate levels, and reduced variability, of pupil diameter and movement. Our results demonstrate that externally observable uninstructed behaviors can predict optimal performance states and suggest that mice regulate their arousal during optimal performance.

Pan-cortical 2-photon mesoscopic imaging and neurobehavioral alignment in awake, behaving mice.

The flow of neural activity across the neocortex during active sensory discrimination is constrained by task-specific cognitive demands, movements, and internal states. During behavior, the brain appears to sample from a broad repertoire of activation motifs. Understanding how these patterns of local and global activity are selected in relation to both spontaneous and task-dependent behavior requires in-depth study of densely sampled activity at single neuron resolution across large regions of cortex. In a significant advance toward this goal, we developed procedures to record mesoscale 2-photon Ca2+ imaging data from two novel in vivo preparations that, between them, allow simultaneous access to nearly all of the mouse dorsal and lateral neocortex. As a proof of principle, we aligned neural activity with both behavioral primitives and high-level motifs to reveal the existence of large populations of neurons that coordinated their activity across cortical areas with spontaneous changes in movement and/or arousal. The methods we detail here facilitate the identification and exploration of widespread, spatially heterogeneous neural ensembles whose activity is related to diverse aspects of behavior.

The h-current controls cortical recurrent network activity through modulation of dendrosomatic communication.

A fundamental feature of the cerebral cortex is the ability to rapidly turn on and off maintained activity within ensembles of neurons through recurrent excitation balanced by inhibition. Here we demonstrate that reduction of the h-current, which is especially prominent in pyramidal cell dendrites, strongly increases the ability of local cortical networks to generate maintained recurrent activity. Reduction of the h-current resulted in hyperpolarization and increase in input resistance of both the somata and apical dendrites of layer 5 pyramidal cells, while strongly increasing the dendrosomatic transfer of low (<20 Hz) frequencies, causing an increased responsiveness to dynamic clamp-induced recurrent network-like activity injected into the dendrites and substantially increasing the duration of spontaneous Up states. We propose that modulation of the h-current may strongly control the ability of cortical networks to generate recurrent persistent activity and the formation and dissolution of neuronal ensembles.

Decision-making dynamics are predicted by arousal and uninstructed movements.

During sensory-guided behavior, an animal's decision-making dynamics unfold through sequences of distinct performance states, even while stimulus-reward contingencies remain static. Little is known about the factors that underlie these changes in task performance. We hypothesize that these decision-making dynamics can be predicted by externally observable measures, such as uninstructed movements and changes in arousal. Here, combining behavioral experiments in mice with computational modeling, we uncovered lawful relationships between transitions in strategic task performance states and an animal's arousal and uninstructed movements. Using hidden Markov models applied to behavioral choices during sensory discrimination tasks, we found that animals fluctuate between minutes-long optimal, sub-optimal and disengaged performance states. Optimal state epochs were predicted by intermediate levels, and reduced variability, of pupil diameter, along with reduced variability in face movements and locomotion. Our results demonstrate that externally observable uninstructed behaviors can predict optimal performance states, and suggest mice regulate their arousal during optimal performance.

Cholinergic and noradrenergic axonal activity contains a behavioral-state signal that is coordinated across the dorsal cortex.

Fluctuations in brain and behavioral state are supported by broadly projecting neuromodulatory systems. In this study, we use mesoscale two-photon calcium imaging to examine spontaneous activity of cholinergic and noradrenergic axons in awake mice in order to determine the interaction between arousal/movement state transitions and neuromodulatory activity across the dorsal cortex at distances separated by up to 4 mm. We confirm that GCaMP6s activity within axonal projections of both basal forebrain cholinergic and locus coeruleus noradrenergic neurons track arousal, indexed as pupil diameter, and changes in behavioral engagement, as reflected by bouts of whisker movement and/or locomotion. The broad coordination in activity between even distant axonal segments indicates that both of these systems can communicate, in part, through a global signal, especially in relation to changes in behavioral state. In addition to this broadly coordinated activity, we also find evidence that a subpopulation of both cholinergic and noradrenergic axons may exhibit heterogeneity in activity that appears to be independent of our measures of behavioral state. By monitoring the activity of cholinergic interneurons in the cortex, we found that a subpopulation of these cells also exhibit state-dependent (arousal/movement) activity. These results demonstrate that cholinergic and noradrenergic systems provide a prominent and broadly synchronized signal related to behavioral state, and therefore may contribute to state-dependent cortical activity and excitability.

Visual thalamocortical mechanisms of waking state-dependent activity and alpha oscillations.

The brain exhibits distinct patterns of recurrent activity closely related to behavioral state. The neural mechanisms that underlie state-dependent activity in the awake animal are incompletely understood. Here, we demonstrate that two types of state-dependent activity, rapid arousal/movement-related signals and a 3-5 Hz alpha-like rhythm, in the primary visual cortex (V1) of mice strongly correlate with activity in the visual thalamus. Inactivation of V1 does not interrupt arousal/movement signals in most visual thalamic neurons, but it abolishes the 3-5 Hz oscillation. Silencing of the visual thalamus similarly eradicates the alpha-like rhythm and perturbs arousal/movement-related activation in V1. Intracellular recordings in thalamic neurons reveal the 3-5 Hz oscillation to be associated with rhythmic low-threshold Ca2+ spikes. Our results indicate that thalamocortical interactions through ionotropic signaling, together with cell-intrinsic properties of thalamocortical cells, play a crucial role in shaping state-dependent activity in V1 of the awake animal.

Neuromodulation of Brain State and Behavior.

Neural activity and behavior are both notoriously variable, with responses differing widely between repeated presentation of identical stimuli or trials. Recent results in humans and animals reveal that these variations are not random in their nature, but may in fact be due in large part to rapid shifts in neural, cognitive, and behavioral states. Here we review recent advances in the understanding of rapid variations in the waking state, how variations are generated, and how they modulate neural and behavioral responses in both mice and humans. We propose that the brain has an identifiable set of states through which it wanders continuously in a nonrandom fashion, owing to the activity of both ascending modulatory and fast-acting corticocortical and subcortical-cortical neural pathways. These state variations provide the backdrop upon which the brain operates, and understanding them is critical to making progress in revealing the neural mechanisms underlying cognition and behavior.

Movement and Performance Explain Widespread Cortical Activity in a Visual Detection Task.

Recent studies in mice reveal widespread cortical signals during task performance; however, the various task-related and task-independent processes underlying this activity are incompletely understood. Here, we recorded wide-field neural activity, as revealed by GCaMP6s, from dorsal cortex while simultaneously monitoring orofacial movements, walking, and arousal (pupil diameter) of head-fixed mice performing a Go/NoGo visual detection task and examined the ability of task performance and spontaneous or task-related movements to predict cortical activity. A linear model was able to explain a significant fraction (33-55% of variance) of widefield dorsal cortical activity, with the largest factors being movements (facial, walk, eye), response choice (hit, miss, false alarm), and arousal and indicate that a significant fraction of trial-to-trial variability arises from both spontaneous and task-related changes in state (e.g., movements, arousal). Importantly, secondary motor cortex was highly correlated with lick rate, critical for optimal task performance (high d'), and was the first region to significantly predict the lick response on target trials. These findings suggest that secondary motor cortex is critically involved in the decision and performance of learned movements and indicate that a significant fraction of trial-to-trial variation in cortical activity results from spontaneous and task-related movements and variations in behavioral/arousal state.

Distinct Waking States for Strong Evoked Responses in Primary Visual Cortex and Optimal Visual Detection Performance.

Variability in cortical neuronal responses to sensory stimuli and in perceptual decision making performance is substantial. Moment-to-moment fluctuations in waking state or arousal can account for much of this variability. Yet, this variability is rarely characterized across the full spectrum of waking states, leaving the characteristics of the optimal state for sensory processing unresolved. Using pupillometry in concert with extracellular multiunit and intracellular whole-cell recordings, we found that the magnitude and reliability of visually evoked responses in primary visual cortex (V1) of awake, passively behaving male mice increase as a function of arousal and are largest during sustained locomotion periods. During these high-arousal, sustained locomotion periods, cortical neuronal membrane potential was at its most depolarized and least variable. Contrastingly, behavioral performance of mice on two distinct visual detection tasks was generally best at a range of intermediate arousal levels, but worst during high arousal with locomotion. These results suggest that large, reliable responses to visual stimuli in V1 occur at a distinct arousal level from that associated with optimal visual detection performance. Our results clarify the relation between neuronal responsiveness and the continuum of waking states, and suggest new complexities in the relation between primary sensory cortical activity and behavior.SIGNIFICANCE STATEMENT Cortical sensory processing strongly depends on arousal. In the mouse visual system, locomotion (associated with high arousal) has previously been shown to enhance the sensory responses of neurons in primary visual cortex (V1). Yet, arousal fluctuates on a moment-to-moment basis, even during quiescent periods. The characteristics of V1 sensory processing across the continuum of arousal are unclear. Furthermore, the arousal level corresponding to optimal visual detection performance is unknown. We show that the magnitude and reliability of sensory-evoked V1 responses are monotonic increasing functions of arousal, and largest during locomotion. Visual detection behavior, however, is suboptimal during high arousal with locomotion, and usually best during intermediate arousal. Our study provides a more complete picture of the dependence of V1 sensory processing on arousal.

Mechanisms of decreased cholinergic arousal in focal seizures: In vivo whole-cell recordings from the pedunculopontine tegmental nucleus.

Focal limbic seizures often impair consciousness/awareness with major negative impact on quality of life. Recent work has shown that limbic seizures depress brainstem arousal systems, including reduced action potential firing in a key node: cholinergic neurons of the pedunculopontine tegmental nucleus (PPT). In vivo whole-cell recordings have not previously been achieved in PPT, but are used here with the goal of elucidating the mechanisms of reduced PPT cholinergic neuronal activity. An established model of focal limbic seizures was used in rats following brief hippocampal stimulation under light anesthesia. Whole-cell in vivo recordings were obtained from PPT neurons using custom-fabricated 9-10 mm tapered patch pipettes, and cholinergic neurons were identified histologically. Average membrane potential, input resistance, membrane potential fluctuations and variance were analyzed during seizures. A subset of PPT neurons exhibited reduced firing and hyperpolarization during seizures and stained positive for choline acetyltransferase. These PPT neurons showed a mean membrane potential hyperpolarization of -3.82 mV (±0.81 SEM, P < .05) during seizures, and also showed significantly increased input resistance, fewer excitatory post-synaptic potential (EPSP)-like events (P < .05), and reduced membrane potential variance (P < .01). The combination of increased input resistance, decreased EPSP-like events and decreased variance weigh against active ictal inhibition and support withdrawal of excitatory input as the dominant mechanism of decreased activity of cholinergic neurons in the PPT. Further identifying synaptic mechanisms of depressed arousal during seizures may lead to new treatments to improve ictal and postictal cognition.

Distinct Functional Groups Emerge from the Intrinsic Properties of Molecularly Identified Entorhinal Interneurons and Principal Cells.

Inhibitory interneurons are an important source of synaptic inputs that may contribute to network mechanisms for coding of spatial location by entorhinal cortex (EC). The intrinsic properties of inhibitory interneurons in the EC of the mouse are mostly undescribed. Intrinsic properties were recorded from known cell types, such as, stellate and pyramidal cells and 6 classes of molecularly identified interneurons (regulator of calcineurin 2, somatostatin, serotonin receptor 3a, neuropeptide Y neurogliaform (NGF), neuropeptide Y non-NGF, and vasoactive intestinal protein) in acute brain slices. We report a broad physiological diversity between and within cell classes. We also found differences in the ability to produce postinhibitory rebound spikes and in the frequency and amplitude of incoming EPSPs. To understand the source of this intrinsic variability we applied hierarchical cluster analysis to functionally classify neurons. These analyses revealed physiologically derived cell types in EC that mostly corresponded to the lines identified by biomarkers with a few unexpected and important differences. Finally, we reduced the complex multidimensional space of intrinsic properties to the most salient five that predicted the cellular biomolecular identity with 81.4% accuracy. These results provide a framework for the classification of functional subtypes of cortical neurons by their intrinsic membrane properties.

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.

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.

Simulating Cortical Feedback Modulation as Changes in Excitation and Inhibition in a Cortical Circuit Model.

Cortical feedback pathways are hypothesized to distribute context-dependent signals during flexible behavior. Recent experimental work has attempted to understand the mechanisms by which cortical feedback inputs modulate their target regions. Within the mouse whisker sensorimotor system, cortical feedback stimulation modulates spontaneous activity and sensory responsiveness, leading to enhanced sensory representations. However, the cellular mechanisms underlying these effects are currently unknown. In this study we use a simplified neural circuit model, which includes two recurrent excitatory populations and global inhibition, to simulate cortical modulation. First, we demonstrate how changes in the strengths of excitation and inhibition alter the input-output processing responses of our model. Second, we compare these responses with experimental findings from cortical feedback stimulation. Our analyses predict that enhanced inhibition underlies the changes in spontaneous and sensory evoked activity observed experimentally. More generally, these analyses provide a framework for relating cellular and synaptic properties to emergent circuit function and dynamic modulation.

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.

Competing Neural Ensembles in Motor Cortex Gate Goal-Directed Motor Output.

Unit recordings in behaving animals have revealed the transformation of sensory to motor representations in cortical neurons. However, we still lack basic insights into the mechanisms by which neurons interact to generate such transformations. Here, we study cortical circuits related to behavioral control in mice engaged in a sensory detection task. We recorded neural activity using extracellular and intracellular techniques and analyzed the task-related neural dynamics to reveal underlying circuit processes. Within motor cortex, we find two populations of neurons that have opposing spiking patterns in anticipation of movement. From correlation analyses and circuit modeling, we suggest that these dynamics reflect neural ensembles engaged in a competition. Furthermore, we demonstrate how this competitive circuit may convert a transient, sensory stimulus into a motor command. Together, these data reveal cellular and circuit processes underlying behavioral control and establish an essential framework for future studies linking cellular activity to behavior.

Cortical Interneuron Subtypes Vary in Their Axonal Action Potential Properties.

The role of interneurons in cortical microcircuits is strongly influenced by their passive and active electrical properties. Although different types of interneurons exhibit unique electrophysiological properties recorded at the soma, it is not yet clear whether these differences are also manifested in other neuronal compartments. To address this question, we have used voltage-sensitive dye to image the propagation of action potentials into the fine collaterals of axons and dendrites in two of the largest cortical interneuron subtypes in the mouse: fast-spiking interneurons, which are typically basket or chandelier neurons; and somatostatin containing interneurons, which are typically regular spiking Martinotti cells. We found that fast-spiking and somatostatin-expressing interneurons differed in their electrophysiological characteristics along their entire dendrosomatoaxonal extent. The action potentials generated in the somata and axons, including axon collaterals, of somatostatin-expressing interneurons are significantly broader than those generated in the same compartments of fast-spiking inhibitory interneurons. In addition, action potentials back-propagated into the dendrites of somatostatin-expressing interneurons much more readily than fast-spiking interneurons. Pharmacological investigations suggested that axonal action potential repolarization in both cell types depends critically upon Kv1 channels, whereas the axonal and somatic action potentials of somatostatin-expressing interneurons also depend on BK Ca(2+)-activated K(+) channels. These results indicate that the two broad classes of interneurons studied here have expressly different subcellular physiological properties, allowing them to perform unique computational roles in cortical circuit operations. SIGNIFICANCE STATEMENT: Neurons in the cerebral cortex are of two major types: excitatory and inhibitory. The proper balance of excitation and inhibition in the brain is critical for its operation. Neurons contain three main compartments: dendritic, somatic, and axonal. How the neurons receive information, process it, and pass on new information depends upon how these three compartments operate. While it has long been assumed that axons are simply for conducting information from the cell body to the synapses, here we demonstrate that the axons of different types of interneurons, the inhibitory cells, possess differing electrophysiological properties. This result implies that differing types of interneurons perform different tasks in the cortex, not only through their anatomical connections, but also through how their axons operate.

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.