Waking State: Rapid Variations Modulate Neural and Behavioral Responses

Spatiotemporally heterogeneous coordination of cholinergic and neocortical activity

Variation in an animal's behavioral state is linked to fluctuations in brain activity and cognitive ability. In the neocortex, state-dependent circuit dynamics may reflect neuromodulatory influences such as that of acetylcholine (ACh). Although early literature suggested that ACh exerts broad, homogeneous control over cortical function, recent evidence indicates potential anatomical and functional segregation of cholinergic signaling. In addition, it is unclear whether states as defined by different behavioral markers reflect heterogeneous cholinergic and cortical network activity. Here, we perform simultaneous, dual-color mesoscopic imaging of both ACh and calcium across the neocortex of awake mice to investigate their relationships with behavioral variables. We find that higher arousal, categorized by different motor behaviors, is associated with spatiotemporally dynamic patterns of cholinergic modulation and enhanced large-scale network correlations. Overall, our findings demonstrate that ACh provides a highly dynamic and spatially heterogeneous signal that links fluctuations in behavior to functional reorganization of cortical networks.

Precise movement-based predictions in the mouse auditory cortex

Many of the sensations experienced by an organism are caused by their own actions, and accurately anticipating both the sensory features and timing of self-generated stimuli is crucial to a variety of behaviors. In the auditory cortex, neural responses to self-generated sounds exhibit frequency-specific suppression, suggesting that movement-based predictions may be implemented early in sensory processing. However, it remains unknown whether this modulation results from a behaviorally specific and temporally precise prediction, nor is it known whether corresponding expectation signals are present locally in the auditory cortex. To address these questions, we trained mice to expect the precise acoustic outcome of a forelimb movement using a closed-loop sound-generating lever. Dense neuronal recordings in the auditory cortex revealed suppression of responses to self-generated sounds that was specific to the expected acoustic features, to a precise position within the movement, and to the movement that was coupled to sound during training. Prediction-based suppression was concentrated in L2/3 and L5, where deviations from expectation also recruited a population of prediction-error neurons that was otherwise unresponsive. Recording in the absence of sound revealed abundant movement signals in deep layers that were biased toward neurons tuned to the expected sound, as well as expectation signals that were present throughout the cortex and peaked at the time of expected auditory feedback. Together, these findings identify distinct populations of auditory cortical neurons with movement, expectation, and error signals consistent with a learned internal model linking an action to its specific acoustic outcome.

Influence of data sampling methods on the representation of neural spiking activity in vivo

In vivo single-unit recordings distinguish the basal spiking properties of neurons in different experimental settings and disease states. Here, we examined over 300 spike trains recorded from Purkinje cells and cerebellar nuclei neurons to test whether data sampling approaches influence the extraction of rich descriptors of firing properties. Our analyses included neurons recorded in awake and anesthetized control mice, and disease models of ataxia, dystonia, and tremor. We find that recording duration circumscribes overall representations of firing rate and pattern. Notably, shorter recording durations skew estimates for global firing rate variability toward lower values. We also find that only some populations of neurons in the same mouse are more similar to each other than to neurons recorded in different mice. These data reveal that recording duration and approach are primary considerations when interpreting task-independent single neuron firing properties. If not accounted for, group differences may be concealed or exaggerated.

Multimodal analysis demonstrating the shaping of functional gradients in the marmoset brain

The discovery of functional gradients introduce a new perspective in understanding the cortical spectrum of intrinsic dynamics, as it captures major axes of functional connectivity in low-dimensional space. However, how functional gradients arise and dynamically vary remains poorly understood. In this study, we investigated the biological basis of functional gradients using awake resting-state fMRI, retrograde tracing and gene expression datasets in marmosets. We found functional gradients in marmosets showed a sensorimotor-to-visual principal gradient followed by a unimodal-to-multimodal gradient, resembling functional gradients in human children. Although strongly constrained by structural wirings, functional gradients were dynamically modulated by arousal levels. Utilizing a reduced model, we uncovered opposing effects on gradient dynamics by structural connectivity (inverted U-shape) and neuromodulatory input (U-shape) with arousal fluctuations, and dissected the contribution of individual neuromodulatory receptors. This study provides insights into biological basis of functional gradients by revealing the interaction between structural connectivity and ascending neuromodulatory system.

Key role of neuronal diversity in structured reservoir computing

Chaotic time series have been captured by reservoir computing models composed of a recurrent neural network whose output weights are trained in a supervised manner. These models, however, are typically limited to randomly connected networks of homogeneous units. Here, we propose a new class of structured reservoir models that incorporates a diversity of cell types and their known connections. In a first version of the model, the reservoir was composed of mean-rate units separated into pyramidal, parvalbumin, and somatostatin cells. Stability analysis of this model revealed two distinct dynamical regimes, namely, (i) an inhibition-stabilized network (ISN) where strong recurrent excitation is balanced by strong inhibition and (ii) a non-ISN network with weak excitation. These results were extended to a leaky integrate-and-fire model that captured different cell types along with their network architecture. ISN and non-ISN reservoir networks were trained to relay and generate a chaotic Lorenz attractor. Despite their increased performance, ISN networks operate in a regime of activity near the limits of stability where external perturbations yield a rapid divergence in output. The proposed framework of structured reservoir computing opens avenues for exploring how neural microcircuits can balance performance and stability when representing time series through distinct dynamical regimes.

Wide-Field Calcium Imaging of Neuronal Network Dynamics In Vivo

A central tenet of neuroscience is that sensory, motor, and cognitive behaviors are generated by the communications and interactions among neurons, distributed within and across anatomically and functionally distinct brain regions. Therefore, to decipher how the brain plans, learns, and executes behaviors requires characterizing neuronal activity at multiple spatial and temporal scales. This includes simultaneously recording neuronal dynamics at the mesoscale level to understand the interactions among brain regions during different behavioral and brain states. Wide-field Ca²⁺ imaging, which uses single photon excitation and improved genetically encoded Ca²⁺ indicators, allows for simultaneous recordings of large brain areas and is proving to be a powerful tool to study neuronal activity at the mesoscopic scale in behaving animals. This review details the techniques used for wide-field Ca²⁺ imaging and the various approaches employed for the analyses of the rich neuronal-behavioral data sets obtained. Also discussed is how wide-field Ca²⁺ imaging is providing novel insights into both normal and altered neural processing in disease. Finally, we examine the limitations of the approach and new developments in wide-field Ca²⁺ imaging that are bringing new capabilities to this important technique for investigating large-scale neuronal dynamics.

Lateral septum modulates cortical state to tune responsivity to threat stimuli

Sudden unexpected environmental changes capture attention and, when perceived as potentially dangerous, evoke defensive behavioral states. Perturbations of the lateral septum (LS) can produce extreme hyperdefensiveness even to innocuous stimuli, but how this structure influences stimulus-evoked defensive responses and threat perception remains unclear. Here, we show that Crhr2-expressing neurons in mouse LS exhibit phasic activation upon detection of threatening but not rewarding stimuli. Threat-stimulus-driven activity predicts the probability but not vigor or type of defensive behavior evoked. Although necessary for and sufficient to potentiate stimulus-triggered defensive responses, LSCrhr2 neurons do not promote specific behaviors. Rather, their stimulation elicits negative valence and physiological arousal. Moreover, LSCrhr2 activity tracks brain state fluctuations and drives cortical activation and rapid awakening in the absence of threat. Together, our findings suggest that LS directs bottom-up modulation of cortical function to evoke preparatory defensive internal states and selectively enhance responsivity to threat-related stimuli.

Reduced activity of parvalbumin-positive interneurons in the posterior parietal cortex causes visually dominant multisensory decisions in freely navigating mice

Multisensory integration is vital for animals to make optimal decisions in a complicated sensory environment. However, the neural mechanisms for flexible multisensory behaviors are not well understood. Here, we found that mice exhibit auditory-dominant decisions in the head-fixed and stationary state and switch to make visual-dominant decisions in the freely navigating state to resolve audiovisual conflicts. To understand the neural mechanism of the state-dependent switch in multisensory decisions, we performed in vivo calcium imaging of parvalbumin-expressing (PV⁺) inhibitory neurons in the posterior parietal cortex (PPC), which are known to mediate auditory dominance in the resolution of audiovisual conflicts, in mice on the treadmill. In the stationary state, the PPC PV⁺ neurons showed similar amounts of evoked activity in responses to auditory and visual stimuli and enhanced responses to the multisensory audiovisual stimuli. Conversely, when mice were running on a treadmill, the PV⁺ neurons lost auditory responses and did not show any multisensory enhancement in their activity. When we optogenetically activated the PPC PV⁺ neurons in mice freely navigating the T-maze, the mice made more auditory-dominant decisions without changes in unisensory decisions. Our data demonstrate that the PPC PV⁺ neurons lost their ability to integrate auditory information with the visual one during active navigation. This modulation of the PPC PV⁺ neuron activity is critical for animals to make adaptive multisensory decisions according to their behavioral states.

Rule-based and stimulus-based cues bias auditory decisions via different computational and physiological mechanisms

Expectations, such as those arising from either learned rules or recent stimulus regularities, can bias subsequent auditory perception in diverse ways. However, it is not well understood if and how these diverse effects depend on the source of the expectations. Further, it is unknown whether different sources of bias use the same or different computational and physiological mechanisms. We examined how rule-based and stimulus-based expectations influenced behavior and pupil-linked arousal, a marker of certain forms of expectation-based processing, of human subjects performing an auditory frequency-discrimination task. Rule-based cues consistently biased choices and response times (RTs) toward the more-probable stimulus. In contrast, stimulus-based cues had a complex combination of effects, including choice and RT biases toward and away from the frequency of recently presented stimuli. These different behavioral patterns also had: 1) distinct computational signatures, including different modulations of key components of a novel form of a drift-diffusion decision model and 2) distinct physiological signatures, including substantial bias-dependent modulations of pupil size in response to rule-based but not stimulus-based cues. These results imply that different sources of expectations can modulate auditory processing via distinct mechanisms: one that uses arousal-linked, rule-based information and another that uses arousal-independent, stimulus-based information to bias the speed and accuracy of auditory perceptual decisions.

Prior information about upcoming stimuli can bias our perception of those stimuli. Whether different sources of prior information bias perception in similar or distinct ways is not well understood. We compared the influence of two kinds of prior information on tone-frequency discrimination: rule-based cues, in the form of explicit information about the most-likely identity of the upcoming tone; and stimulus-based cues, in the form of sequences of tones presented before the to-be-discriminated tone. Although both types of prior information biased auditory decision-making, they demonstrated distinct behavioral, computational, and physiological signatures. Our results suggest that the brain processes prior information in a form-specific manner rather than utilizing a general-purpose prior. Such form-specific processing has implications for understanding decision biases real-world contexts, in which prior information comes from many different sources and modalities.

Awake perception is associated with dedicated neuronal assemblies in the cerebral cortex

Neural activity in the sensory cortex combines stimulus responses and ongoing activity, but it remains unclear whether these reflect the same underlying dynamics or separate processes. In the present study, we show in mice that, during wakefulness, the neuronal assemblies evoked by sounds in the auditory cortex and thalamus are specific to the stimulus and distinct from the assemblies observed in ongoing activity. By contrast, under three different anesthetics, evoked assemblies are indistinguishable from ongoing assemblies in the cortex. However, they remain distinct in the thalamus. A strong remapping of sensory responses accompanies this dynamic state change produced by anesthesia. Together, these results show that the awake cortex engages dedicated neuronal assemblies in response to sensory inputs, which we suggest is a network correlate of sensory perception.

Filipchuk et al. show that when awake mice perceive sounds, the auditory cortex produces sound-specific neuronal assemblies distinct from its ongoing activity, whereas under anesthesia sound-evoked assemblies are indistinguishable from ongoing activity.

Active neural coordination of motor behaviors with internal states

The brain continuously coordinates skeletomuscular movements with internal physiological states like arousal, but how is this coordination achieved? One possibility is that the brain simply reacts to changes in external and/or internal signals. Another possibility is that it is actively coordinating both external and internal activities. We used functional ultrasound imaging to capture a large medial section of the brain, including multiple cortical and subcortical areas, in marmoset monkeys while monitoring their spontaneous movements and cardiac activity. By analyzing the causal ordering of these different time series, we found that information flowing from the brain to movements and heart-rate fluctuations were significantly greater than in the opposite direction. The brain areas involved in this external versus internal coordination were spatially distinct, but also extensively interconnected. Temporally, the brain alternated between network states for this regulation. These findings suggest that the brain's dynamics actively and efficiently coordinate motor behavior with internal physiology.

Versatile treadmill system for measuring locomotion and neural activity in head-fixed mice

Here, we present a protocol for using a versatile treadmill system to measure locomotion and neural activity at high temporal resolution in head-fixed mice. We first describe the assembly of the treadmill system. We then detail surgical implantation of the headplate on the mouse skull, followed by habituation of mice to locomotion on the treadmill system. The system is compact, movable, and simple to synchronize with other data streams, making it ideal for monitoring brain activity in diverse behavioral frameworks. For complete details on the use and execution of this protocol, please refer to Rasmussen et al. (2019).

Arousal impacts distributed hubs modulating the integration of brain functional connectivity

Even when subjects are at rest, it is thought that brain activity is organized into distinct brain states during which reproducible patterns are observable. Yet, it is unclear how to define or distinguish different brain states. A potential source of brain state variation is arousal, which may play a role in modulating functional interactions between brain regions. Here, we use simultaneous resting state functional magnetic resonance imaging (fMRI) and pupillometry to study the impact of arousal levels indexed by pupil area on the integration of large-scale brain networks. We employ a novel sparse dictionary learning-based method to identify hub regions participating in between-network integration stratified by arousal, by measuring k-hubness, the number (k) of functionally overlapping networks in each brain region. We show evidence of a brain-wide decrease in between-network integration and inter-subject variability at low relative to high arousal, with differences emerging across regions of the frontoparietal, default mode, motor, limbic, and cerebellum networks. State-dependent changes in k-hubness relate to the actual patterns of network integration within these hubs, suggesting a brain state transition from high to low arousal characterized by global synchronization and reduced network overlaps. We demonstrate that arousal is not limited to specific brain areas known to be directly associated with arousal regulation, but instead has a brain-wide impact that involves high-level between-network communications. Lastly, we show a systematic change in pairwise fMRI signal correlation structures in the arousal state-stratified data, and demonstrate that the choice of global signal regression could result in different conclusions in conventional graph theoretical analysis and in the analysis of k-hubness when studying arousal modulations. Together, our results suggest the presence of global and local effects of pupil-linked arousal modulations on resting state brain functional connectivity.

State-Dependent Modulation of Activity in Distinct Layer 6 Corticothalamic Neurons in Barrel Cortex of Awake Mice

Layer 6 corticothalamic (L6 CT) neurons are in a strategic position to control sensory input to the neocortex, yet we understand very little about their functions. Apart from studying their anatomic, physiological, and synaptic properties, most recent efforts have focused on the activity-dependent influences CT cells can exert on thalamic and cortical neurons through causal optogenetic manipulations. However, few studies have attempted to study them during behavior. To address this gap, we performed juxtacellular recordings from optogenetically identified CT neurons in whisker-related primary somatosensory cortex (wS1) of awake, head-fixed mice (either sex) free to rest quietly or self-initiate bouts of whisking and locomotion. We found a rich diversity of response profiles exhibited by CT cells. Their spiking patterns were either modulated by whisking-related behavior (∼28%) or not (∼72%). Whisking-responsive neurons exhibited both increases (activated-type) and decreases in firing rates (suppressed-type) that aligned with whisking onset better than locomotion. We also encountered responsive neurons with preceding modulations in firing rate before whisking onset. Overall, whisking better explained these changes in rates than overall changes in arousal. Whisking-unresponsive CT cells were generally quiet, with many having low spontaneous firing rates (sparse-type) and others being completely silent (silent-type). Remarkably, the sparse firing CT population preferentially spiked at the state transition point when pupil diameter constricted, and the mouse entered quiet wakefulness. Thus, our results demonstrate that L6 CT cells in wS1 show diverse spiking patterns, perhaps subserving distinct functional roles related to precisely timed responses during complex behaviors and transitions between discrete waking states.SIGNIFICANCE STATEMENT Layer 6 corticothalamic neurons provide a massive input to the sensory thalamus and local connectivity within cortex, but their role in thalamocortical processing remains unclear because of difficulty accessing and isolating their activity. Although several recent optogenetic studies reveal that the net influence of corticothalamic actions, suppression versus enhancement, depends critically on the rate these neurons fire, the factors that influence their spiking are poorly understood, particularly during wakefulness. Using the well-established Ntsr1-Cre line to target this elusive population in the whisker somatosensory cortex of awake mice, we found that corticothalamic neurons show diverse state-related responses and modulations in firing rate. These results suggest separate corticothalamic populations can differentially influence thalamocortical excitability during rapid state transitions in awake, behaving animals.

Visual-area-specific tonic modulation of GABA release by endocannabinoids sets the activity and coordination of neocortical principal neurons

Perisomatic inhibition of pyramidal neurons (PNs) coordinates cortical network activity during sensory processing, and this role is mainly attributed to parvalbumin-expressing basket cells (BCs). However, cannabinoid receptor type 1 (CB1)-expressing interneurons are also BCs, but the connectivity and function of these elusive but prominent neocortical inhibitory neurons are unclear. We find that their connectivity pattern is visual area specific. Persistently active CB1 signaling suppresses GABA release from CB1 BCs in the medial secondary visual cortex (V2M), but not in the primary visual cortex (V1). Accordingly, in vivo, tonic CB1 signaling is responsible for higher but less coordinated PN activity in the V2M than in the V1. These differential firing dynamics in the V1 and V2M can be captured by a computational network model that incorporates visual-area-specific properties. Our results indicate a differential CB1-mediated mechanism controlling PN activity, suggesting an alternative connectivity scheme of a specific GABAergic circuit in different cortical areas.

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CB1⁺ basket cells exhibit visual-area-specific morphology and connectivity patterns

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Tonic CB1 signaling underlies high pyramidal neurons (PN) activity in V2M but not V1

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Tonic CB1 signaling differentially modulates PN-correlated activity in V1 and V2M

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Numerical simulations capture specific CB1-dependent firing dynamics of V1 and V2M

The emergence and influence of internal states

Animal behavior is shaped by a variety of "internal states"-partially hidden variables that profoundly shape perception, cognition, and action. The neural basis of internal states, such as fear, arousal, hunger, motivation, aggression, and many others, is a prominent focus of research efforts across animal phyla. Internal states can be inferred from changes in behavior, physiology, and neural dynamics and are characterized by properties such as pleiotropy, persistence, scalability, generalizability, and valence. To date, it remains unclear how internal states and their properties are generated by nervous systems. Here, we review recent progress, which has been driven by advances in behavioral quantification, cellular manipulations, and neural population recordings. We synthesize research implicating defined subsets of state-inducing cell types, widespread changes in neural activity, and neuromodulation in the formation and updating of internal states. In addition to highlighting the significance of these findings, our review advocates for new approaches to clarify the underpinnings of internal brain states across the animal kingdom.

Functional States Shape the Spatiotemporal Representation of Local and Cortex-wide Neural Activity in Mouse Sensory Cortex

The spatiotemporal representation of neural activity during rest and upon sensory stimulation in cortical areas is highly dynamic, and may be predominantly governed by cortical state. On the mesoscale level, intrinsic neuronal activity ranges from a persistent state, generally associated with a sustained depolarization of neurons, to a bimodal, slow-wave like state with bursts of neuronal activation, alternating with silent periods. These different activity states are prevalent under certain types of sedatives, or are associated with specific behavioral or vigilance conditions. Neurophysiological experiments assessing circuit activity, usually assume a constant underlying state, yet reports of variability of neuronal responses under seemingly constant conditions are common in the field. Even when a certain type of neural activity or cortical state can stably be maintained over time, the associated response properties are highly relevant for explaining experimental outcomes. Here we describe the spatiotemporal characteristics of ongoing activity and sensory evoked responses under two predominant functional states in the sensory cortices of mice: persistent activity (PA) and slow wave activity (SWA). Using electrophysiological recordings, and local and wide-field calcium recordings, we examine whether spontaneous and sensory evoked neuronal activity propagate throughout the cortex in a state dependent manner. We find that PA and SWA differ in their spatiotemporal characteristics which determine the cortical network's response to a sensory stimulus. During PA state, sensory stimulation elicits gamma-based short-latency responses which precisely follow each stimulation pulse and are prone to adaptation upon higher stimulation frequencies. Sensory responses during SWA are more variable, dependent on refractory periods following spontaneous slow waves. While spontaneous slow waves propagated in anterior-posterior direction in a majority of observations, the direction of propagation of stimulus-elicited wave depends on the sensory modality. These findings suggest that cortical state explains variance and should be considered when investigating multi-scale correlates of functional neurocircuit activity.

Distractibility and impulsivity neural states are distinct from selective attention and modulate the implementation of spatial attention

In the context of visual attention, it has been classically assumed that missing the response to a target or erroneously selecting a distractor occurs as a consequence of the (miss)allocation of attention in space. In the present paper, we challenge this view and provide evidence that, in addition to encoding spatial attention, prefrontal neurons also encode a distractibility-to-impulsivity state. Using supervised dimensionality reduction techniques in prefrontal neuronal recordings in monkeys, we identify two partially overlapping neuronal subpopulations associated either with the focus of attention or overt behaviour. The degree of overlap accounts for the behavioral gain associated with the good allocation of attention. We further describe the neural variability accounting for distractibility-to-impulsivity behaviour by a two dimensional state associated with optimality in task and responsiveness. Overall, we thus show that behavioral performance arises from the integration of task-specific neuronal processes and pre-existing neuronal states describing task-independent behavioral states.

Failing to detect relevant information has been assumed to be a consequence of misallocation of attention. Here, the authors present findings showing that optimal behavioral performance results from the absence of interference between internal neural states and attention control.

Motivational and Valence-Related Modulation of Sleep/Wake Behavior are Mediated by Midbrain Dopamine and Uncoupled from the Homeostatic and Circadian Processes

Motivation and its hedonic valence are powerful modulators of sleep/wake behavior, yet its underlying mechanism is still poorly understood. Given the well-established role of midbrain dopamine (mDA) neurons in encoding motivation and emotional valence, here, neuronal mechanisms mediating sleep/wake regulation are systematically investigated by DA neurotransmission. It is discovered that mDA mediates the strong modulation of sleep/wake states by motivational valence. Surprisingly, this modulation can be uncoupled from the classically employed measures of circadian and homeostatic processes of sleep regulation. These results establish the experimental foundation for an additional new factor of sleep regulation. Furthermore, an electroencephalographic marker during wakefulness at the theta range is identified that can be used to reliably track valence-related modulation of sleep. Taken together, this study identifies mDA signaling as an important neural substrate mediating sleep modulation by motivational valence.

Cell-type-specific silence in thalamocortical circuits precedes hippocampal sharp-wave ripples

Evidence suggests that the hippocampus conveys memory-related neural patterns across distributed cortical circuits during high-frequency oscillations called sharp-wave ripples (SWRs). We investigate how circuit activity in the retrosplenial cortex (RSC), a primary hippocampal target, could aid in processing SWR-related input. Using patch-clamp recordings from awake mice, we find that SWR-aligned membrane potential modulation is widespread but weak, and that spiking responses are sparse. However, using cell-type-specific two-photon Ca²⁺ imaging and optogenetics, we show that, 1-2 s before SWRs, superficial inhibition and thalamocortical input in RSC is reduced. We propose that pyramidal dendrites experience decreased local inhibition and subcortical interference in a seconds-long time window preceding SWRs. This may aid communication of weak and sparse SWR-aligned excitation between the hippocampus and neocortex and promote the strengthening of memory-related connections.

Brain state limits propagation of neural signals in laminar cortical circuits

Brain state fluctuates throughout the course of the day. Whether and how these fluctuations impact signal propagation in the brain remains unknown. Here, we used optogenetic stimulation during different brain states to show that the coupling between neurons modulates the spread of signals across cortical circuits in a state-dependent manner. Our results indicate that brain state influences how far electrical signals travel in neocortex and suggest a revision of computational models relying on robust signal propagation across neural networks.

Our perception of the environment relies on the efficient propagation of neural signals across cortical networks. During the time course of a day, neural responses fluctuate dramatically as the state of the brain changes to possibly influence how electrical signals propagate across neural circuits. Despite the importance of this issue, how patterns of spiking activity propagate within neuronal circuits in different brain states remains unknown. Here, we used multielectrode laminar arrays to reveal that brain state strongly modulates the propagation of neural activity across the layers of early visual cortex (V1). We optogenetically induced synchronized state transitions within a group of neurons and examined how far electrical signals travel during wakefulness and rest. Although optogenetic stimulation elicits stronger neural responses during wakefulness relative to rest, signals propagate only weakly across the cortical column during wakefulness, and the extent of spread is inversely related to arousal level. In contrast, the light-induced population activity vigorously propagates throughout the entire cortical column during rest, even when neurons are in a desynchronized wake-like state prior to light stimulation. Mechanistically, the influence of global brain state on the propagation of spiking activity across laminar circuits can be explained by state-dependent changes in the coupling between neurons. Our results impose constraints on the conclusions of causal manipulation studies attempting to influence neural function and behavior, as well as on previous computational models of perception assuming robust signal propagation across cortical layers and areas.

Not so spontaneous: Multi-dimensional representations of behaviors and context in sensory areas

Sensory areas are spontaneously active in the absence of sensory stimuli. This spontaneous activity has long been studied; however, its functional role remains largely unknown. Recent advances in technology, allowing large-scale neural recordings in the awake and behaving animal, have transformed our understanding of spontaneous activity. Studies using these recordings have discovered high-dimensional spontaneous activity patterns, correlation between spontaneous activity and behavior, and dissimilarity between spontaneous and sensory-driven activity patterns. These findings are supported by evidence from developing animals, where a transition toward these characteristics is observed as the circuit matures, as well as by evidence from mature animals across species. These newly revealed characteristics call for the formulation of a new role for spontaneous activity in neural sensory computation.

Structural connections between the noradrenergic and cholinergic system shape the dynamics of functional brain networks

Complex cognitive abilities are thought to arise from the ability of the brain to adaptively reconfigure its internal network structure as a function of task demands. Recent work has suggested that this inherent flexibility may in part be conferred by the widespread projections of the ascending arousal systems. While the different components of the ascending arousal system are often studied in isolation, there are anatomical connections between neuromodulatory hubs that we hypothesise are crucial for mediating key features of adaptive network dynamics, such as the balance between integration and segregation. To test this hypothesis, we estimated the strength of structural connectivity between key hubs of the noradrenergic and cholinergic arousal systems (the locus coeruleus [LC] and nucleus basalis of Meynert [nbM], respectively). We then asked whether the strength of structural LC and nbM inter-connectivity was related to individual differences in the emergent, dynamical signatures of functional integration measured from resting state fMRI data, such as network and attractor topography. We observed a significant positive relationship between the strength of white-matter connections between the LC and nbM and the extent of network-level integration following BOLD signal peaks in LC relative to nbM activity. In addition, individuals with denser white-matter streamlines interconnecting neuromodulatory hubs also demonstrated a heightened ability to shift to novel brain states. These results suggest that individuals with stronger structural connectivity between the noradrenergic and cholinergic systems have a greater capacity to mediate the flexible network dynamics required to support complex, adaptive behaviour. Furthermore, our results highlight the underlying static features of the neuromodulatory hubs can impose some constraints on the dynamic features of the brain.

Awake Mouse fMRI and Pupillary Recordings in the Ultra-High Magnetic Field

Awake rodent fMRI is becoming a promising non-invasive brain imaging module when investigating large-scale brain function given behavioral tasks. Previous studies have either applied sedatives during scanning or pre-treatment of anesthetics, e.g., isoflurane, to reduce the motion of animals, which could confound the brain function of "awake" states in rodents. Here, we have established a long training awake mouse fMRI-pupillometry paradigm/setup without the initial use of anesthesia. To validate the awake mouse fMRI platform, evoked BOLD-fMRI was performed to identify brain activation in the visual cortex, dorsal lateral geniculate nuclei, and superior colliculus. Furthermore, pupil signal fluctuation was investigated during scanning, showing a less dilated pupil after 5-8 weeks of intermittent training. Thus, using the awake mouse fMRI with real-time pupillometry provides a longitudinal functional mapping tool to study fully conscious mice.

Rapid Effects of Vagus Nerve Stimulation on Sensory Processing Through Activation of Neuromodulatory Systems

After sensory information is encoded into neural signals at the periphery, it is processed through multiple brain regions before perception occurs (i.e., sensory processing). Recent work has begun to tease apart how neuromodulatory systems influence sensory processing. Vagus nerve stimulation (VNS) is well-known as an effective and safe method of activating neuromodulatory systems. There is a growing body of studies confirming VNS has immediate effects on sensory processing across multiple sensory modalities. These immediate effects of VNS on sensory processing are distinct from the more well-documented method of inducing lasting neuroplastic changes to the sensory pathways through repeatedly delivering a brief VNS burst paired with a sensory stimulus. Immediate effects occur upon VNS onset, often disappear upon VNS offset, and the modulation is present for all sensory stimuli. Conversely, the neuroplastic effect of pairing sub-second bursts of VNS with a sensory stimulus alters sensory processing only after multiple pairing sessions, this alteration remains after cessation of pairing sessions, and the alteration selectively affects the response properties of neurons encoding the specific paired sensory stimulus. Here, we call attention to the immediate effects VNS has on sensory processing. This review discusses existing studies on this topic, provides an overview of the underlying neuromodulatory systems that likely play a role, and briefly explores the potential translational applications of using VNS to rapidly regulate sensory processing.

A transcriptomic axis predicts state modulation of cortical interneurons

Transcriptomics has revealed that cortical inhibitory neurons exhibit a great diversity of fine molecular subtypes^1-6, but it is not known whether these subtypes have correspondingly diverse patterns of activity in the living brain. Here we show that inhibitory subtypes in primary visual cortex (V1) have diverse correlates with brain state, which are organized by a single factor: position along the main axis of transcriptomic variation. We combined in vivo two-photon calcium imaging of mouse V1 with a transcriptomic method to identify mRNA for 72 selected genes in ex vivo slices. We classified inhibitory neurons imaged in layers 1-3 into a three-level hierarchy of 5 subclasses, 11 types and 35 subtypes using previously defined transcriptomic clusters³. Responses to visual stimuli differed significantly only between subclasses, with cells in the Sncg subclass uniformly suppressed, and cells in the other subclasses predominantly excited. Modulation by brain state differed at all hierarchical levels but could be largely predicted from the first transcriptomic principal component, which also predicted correlations with simultaneously recorded cells. Inhibitory subtypes that fired more in resting, oscillatory brain states had a smaller fraction of their axonal projections in layer 1, narrower spikes, lower input resistance and weaker adaptation as determined in vitro⁷, and expressed more inhibitory cholinergic receptors. Subtypes that fired more during arousal had the opposite properties. Thus, a simple principle may largely explain how diverse inhibitory V1 subtypes shape state-dependent cortical processing.

Building bridges: simultaneous multimodal neuroimaging approaches for exploring the organization of brain networks

Brain organization is evident across spatiotemporal scales as well as from structural and functional data. Yet, translating from micro- to macroscale (vice versa) as well as between different measures is difficult. Reconciling disparate observations from different modes is challenging because each specializes within a restricted spatiotemporal milieu, usually has bounded organ coverage, and has access to different contrasts. True intersubject biological heterogeneity, variation in experiment implementation (e.g., use of anesthesia), and true moment-to-moment variations in brain activity (maybe attributable to different brain states) also contribute to variability between studies. Ultimately, for a deeper and more actionable understanding of brain organization, an ability to translate across scales, measures, and species is needed. Simultaneous multimodal methods can contribute to bettering this understanding. We consider four modes, three optically based: multiphoton imaging, single-photon (wide-field) imaging, and fiber photometry, as well as magnetic resonance imaging. We discuss each mode as well as their pairwise combinations with regard to the definition and study of brain networks.

GluN3A excitatory glycine receptors control adult cortical and amygdalar circuits

GluN3A is an atypical glycine-binding subunit of NMDA receptors (NMDARs) whose actions in the brain are mostly unknown. Here, we show that the expression of GluN3A subunits controls the excitability of mouse adult cortical and amygdalar circuits via an unusual signaling mechanism involving the formation of excitatory glycine GluN1/GluN3A receptors (eGlyRs) and their tonic activation by extracellular glycine. eGlyRs are mostly extrasynaptic and reside in specific neuronal populations, including the principal cells of the basolateral amygdala (BLA) and SST-positive interneurons (SST-INs) of the neocortex. In the BLA, tonic eGlyR currents are sensitive to fear-conditioning protocols, are subject to neuromodulation by the dopaminergic system, and control the stability of fear memories. In the neocortex, eGlyRs control the in vivo spiking of SST-INs and the behavior-dependent modulation of cortical activity. GluN3A-containing eGlyRs thus represent a novel and widespread signaling modality in the adult brain, with attributes that strikingly depart from those of conventional NMDARs.

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In mice, GluN3A is expressed by SST-INs in the cortex and pyramidal neurons in the BLA

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GluN3A assembles as excitatory glycine GluN1/GluN3A receptors (eGlyRs)

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eGlyRs detect extracellular glycine levels and generate tonic excitatory currents

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eGlyRs tune the function of SST-INs in cortex and alter the formation of fear memories in BLA

Pupillometry as an integrated readout of distinct attentional networks

The course of pupillary constriction and dilation provides an easy-to-access, inexpensive, and noninvasive readout of brain activity. We propose a new taxonomy of factors affecting the pupil and link these to associated neural underpinnings in an ascending hierarchy. In addition to two well-established low-level factors (light level and focal distance), we suggest two further intermediate-level factors, alerting and orienting, and a higher-level factor, executive functioning. Alerting, orienting, and executive functioning - including their respective underlying neural circuitries - overlap with the three principal attentional networks, making pupil size an integrated readout of distinct states of attention. As a now widespread technique, pupillometry is ready to provide meaningful applications and constitutes a viable part of the psychophysiological toolbox.

Neural correlates of blood flow measured by ultrasound

Functional ultrasound imaging (fUSI) is an appealing method for measuring blood flow and thus infer brain activity, but it relies on the physiology of neurovascular coupling and requires extensive signal processing. To establish to what degree fUSI trial-by-trial signals reflect neural activity, we performed simultaneous fUSI and neural recordings with Neuropixels probes in awake mice. fUSI signals strongly correlated with the slow (<0.3 Hz) fluctuations in the local firing rate and were closely predicted by the smoothed firing rate of local neurons, particularly putative inhibitory neurons. The optimal smoothing filter had a width of ∼3 s, matched the hemodynamic response function of awake mice, was invariant across mice and stimulus conditions, and was similar in the cortex and hippocampus. fUSI signals also matched neural firing spatially: firing rates were as highly correlated across hemispheres as fUSI signals. Thus, blood flow measured by ultrasound bears a simple and accurate relationship to neuronal firing.

State-dependent effects of neural stimulation on brain function and cognition

Invasive and non-invasive brain stimulation methods are widely used in neuroscience to establish causal relationships between distinct brain regions and the sensory, cognitive and motor functions they subserve. When combined with concurrent brain imaging, such stimulation methods can reveal patterns of neuronal activity responsible for regulating simple and complex behaviours at the level of local circuits and across widespread networks. Understanding how fluctuations in physiological states and task demands might influence the effects of brain stimulation on neural activity and behaviour is at the heart of how we use these tools to understand cognition. Here we review the concept of such 'state-dependent' changes in brain activity in response to neural stimulation, and consider examples from research on altered states of consciousness (for example, sleep and anaesthesia) and from task-based manipulations of selective attention and working memory. We relate relevant findings from non-invasive methods used in humans to those obtained from direct electrical and optogenetic stimulation of neuronal ensembles in animal models. Given the widespread use of brain stimulation as a research tool in the laboratory and as a means of augmenting or restoring brain function, consideration of the influence of changing physiological and cognitive states is crucial for increasing the reliability of these interventions.

Translaminar recurrence from layer 5 suppresses superficial cortical layers

Information flow in the sensory cortex has been described as a predominantly feedforward sequence with deep layers as the output structure. Although recurrent excitatory projections from layer 5 (L5) to superficial L2/3 have been identified by anatomical and physiological studies, their functional impact on sensory processing remains unclear. Here, we use layer-selective optogenetic manipulations in the primary auditory cortex to demonstrate that feedback inputs from L5 suppress the activity of superficial layers regardless of the arousal level, contrary to the prediction from their excitatory connectivity. This suppressive effect is predominantly mediated by translaminar circuitry through intratelencephalic neurons, with an additional contribution of subcortical projections by pyramidal tract neurons. Furthermore, L5 activation sharpened tone-evoked responses of superficial layers in both frequency and time domains, indicating its impact on cortical spectro-temporal integration. Together, our findings establish a translaminar inhibitory recurrence from deep layers that sharpens feature selectivity in superficial cortical layers.

Pupil-linked Arousal Signals in the Midbrain Superior Colliculus

The orienting response evoked by the appearance of a salient stimulus is modulated by arousal; however, neural underpinnings for the interplay between orienting and arousal are not well understood. The superior colliculus (SC), causally involved in multiple components of the orienting response including gaze and attention shifts, receives not only multisensory and cognitive inputs but also arousal-regulated inputs from various cortical and subcortical structures. To investigate the impact of moment-by-moment fluctuations in arousal on orienting saccade responses, we used microstimulation of the monkey SC to trigger saccade responses, and we used pupil size and velocity to index the level of arousal at stimulation onset because these measures correlate with changes in brain states and locus coeruleus activity. Saccades induced by SC microstimulation correlated with prestimulation pupil velocity, with higher pupil velocities on trials without evoked saccades than with evoked saccades. In contrast, prestimulation absolute pupil size did not correlate with saccade behavior. However, pupil velocity correlated with evoked saccade latency and metrics. Together, our results demonstrated that small fluctuations in arousal, indexed by pupil velocity, can modulate the saccade response evoked by SC microstimulation in awake behaving monkeys.

Walking strides direct rapid and flexible recruitment of visual circuits for course control in Drosophila

Flexible mapping between activity in sensory systems and movement parameters is a hallmark of motor control. This flexibility depends on the continuous comparison of short-term postural dynamics and the longer-term goals of an animal, thereby necessitating neural mechanisms that can operate across multiple timescales. To understand how such body-brain interactions emerge across timescales to control movement, we performed whole-cell patch recordings from visual neurons involved in course control in Drosophila. We show that the activity of leg mechanosensory cells, propagating via specific ascending neurons, is critical for stride-by-stride steering adjustments driven by the visual circuit, and, at longer timescales, it provides information about the moving body’s state to flexibly recruit the visual circuit for course control. Thus, our findings demonstrate the presence of an elegant stride-based mechanism operating at multiple timescales for context-dependent course control. We propose that this mechanism functions as a general basis for the adaptive control of locomotion.

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HS cells receive stride-coupled signals via ascending neurons

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The stride-coupled signals reflect an internal motor context

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Motor context modulates HS cells at multiple timescales

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HS cells drive rapid steering depending on motor context

Spectral Fingerprints of Cortical Neuromodulation

Pupil size has been established as a versatile marker of noradrenergic and cholinergic neuromodulation, which has profound effects on neuronal processing, cognition, and behavior. However, little is known about the cortical control and effects of pupil-linked neuromodulation. Here, we show that pupil dynamics are tightly coupled to temporally, spectrally, and spatially specific modulations of local and large-scale cortical population activity in the human brain. We quantified the dynamics of band-limited cortical population activity in resting human subjects using magnetoencephalography and investigated how neural dynamics were linked to simultaneously recorded pupil dynamics. Our results show that pupil-linked neuromodulation does not merely affect cortical population activity in a stereotypical fashion. Instead, we identified three frontal, precentral, and occipitoparietal networks, in which local population activity with distinct spectral profiles in the theta, beta, and alpha bands temporally preceded and followed changes in pupil size. Furthermore, we found that amplitude coupling at ∼16 Hz in a large-scale frontoparietal network predicted pupil dynamics. Our results unravel network-specific spectral fingerprints of cortical neuromodulation in the human brain that likely reflect both the causes and effects of neuromodulation.SIGNIFICANCE STATEMENT Brain function is constantly affected by modulatory neurotransmitters. Pupil size has been established as a versatile marker of noradrenergic and cholinergic neuromodulation. However, because the cortical correlates of pupil dynamics are largely unknown, fundamental questions remain unresolved. Which cortical networks control pupil-linked neuromodulation? Does neuromodulation affect cortical activity in a stereotypical or region-specific fashion? To address this, we quantified the dynamics of cortical population activity in human subjects using magnetoencephalography. We found that pupil dynamics are coupled to highly specific modulations of local and large-scale cortical activity in the human brain. We identified four cortical networks with distinct spectral profiles that temporally predicted and followed pupil size dynamics. These effects likely reflect both the cortical control and effect of neuromodulation.

Distinct ensembles in the noradrenergic locus coeruleus are associated with diverse cortical states

Brainstem locus coeruleus (LC) noradrenergic neurons produce an arousal-related state characterized by a broadband increase in high-frequency oscillations. This perspective was built upon electrical or optogenetic stimulation that artificially activates LC neurons synchronously. This has led to the conceptual model that LC activation is associated with a single cortical state. Here, we show that natural, spontaneously occurring LC single-unit activity consists of ensembles with largely nonoverlapping activation dynamics. Spontaneous activations of different LC ensembles are associated with different cortical states. Our results suggest that the role of the LC in controlling a single type of cortical state associated with arousal is an oversimplification. Instead, ensembles of LC neurons may control a diverse multitude of cortical states.

The noradrenergic locus coeruleus (LC) is a controller of brain and behavioral states. Activating LC neurons en masse by electrical or optogenetic stimulation promotes a stereotypical “activated” cortical state of high-frequency oscillations. However, it has been recently reported that spontaneous activity of LC cell pairs has sparse yet structured time-averaged cross-correlations, which is unlike the highly synchronous neuronal activity evoked by stimulation. Therefore, LC population activity could consist of distinct multicell ensembles each with unique temporal evolution of activity. We used nonnegative matrix factorization (NMF) to analyze large populations of simultaneously recorded LC single units in the rat LC. NMF identified ensembles of spontaneously coactive LC neurons and their activation time courses. Since LC neurons selectively project to specific forebrain regions, we hypothesized that distinct ensembles activate during different cortical states. To test this hypothesis, we calculated band-limited power and spectrograms of local field potentials in cortical area 24a aligned to spontaneous activations of distinct LC ensembles. A diversity of state modulations occurred around activation of different LC ensembles, including a typical activated state with increased high-frequency power as well as other states including decreased high-frequency power. Thus—in contrast to the stereotypical activated brain state evoked by en masse LC stimulation—spontaneous activation of distinct LC ensembles is associated with a multitude of cortical states.

Arousal elevation drives the development of oscillatory vocal output

Adult behaviors, such as vocal production, often exhibit temporal regularity. In contrast, their immature forms are more irregular. We ask whether the coupling of motor behaviors with arousal changes give rise to temporal regularity. Do they drive the transition from variable to regular motor output over the course of development? We used marmoset monkey vocal production to explore this putative influence of arousal on the nonlinear changes in their developing vocal output patterns. Based on a detailed analysis of vocal and arousal dynamics in marmosets, we put forth a general model incorporating arousal and auditory-feedback loops for spontaneous vocal production. Using this model, we show that a stable oscillation can emerge as the baseline arousal increases, predicting the transition from stochastic to periodic oscillations observed during marmoset vocal development. We further provide a solution for how this model can explain vocal development as the joint consequence of energetic growth and social feedback. Together, we put forth a plausible mechanism for the development of arousal-mediated adaptive behavior.

Arousal state affects perceptual decision-making by modulating hierarchical sensory processing in a large-scale visual system model

Arousal levels strongly affect task performance. Yet, what arousal level is optimal for a task depends on its difficulty. Easy task performance peaks at higher arousal levels, whereas performance on difficult tasks displays an inverted U-shape relationship with arousal, peaking at medium arousal levels, an observation first made by Yerkes and Dodson in 1908. It is commonly proposed that the noradrenergic locus coeruleus system regulates these effects on performance through a widespread release of noradrenaline resulting in changes of cortical gain. This account, however, does not explain why performance decays with high arousal levels only in difficult, but not in simple tasks. Here, we present a mechanistic model that revisits the Yerkes-Dodson effect from a sensory perspective: a deep convolutional neural network augmented with a global gain mechanism reproduced the same interaction between arousal state and task difficulty in its performance. Investigating this model revealed that global gain states differentially modulated sensory information encoding across the processing hierarchy, which explained their differential effects on performance on simple versus difficult tasks. These findings offer a novel hierarchical sensory processing account of how, and why, arousal state affects task performance.

The role of melanopsin photoreception on visual attention linked pupil responses

A decision during a visual task is marked by a task‐evoked pupil dilation (TEPD) that is linked to the global cortical arousal state. Melanopsin expressing intrinsically photosensitive retinal ganglion cells (ipRGCs) form the afferent pathway for this pupil response. Melanopsin activation also influences mood and arousal and increases activity in decision‐making brain areas that receive direct ipRGC projections. Here, an optical photostimulation method controlled the excitations of all five photoreceptor classes in the human eye to isolate melanopsin‐mediated photoreception. We hypothesised that the TEPD can be driven by directing active visual covert attention through the ipRGC pathway. When observers are completely certain of the stimulus presence, melanopsin‐directed stimulation produces a TEPD of similar amplitude to a cone‐directed stimulation, with their combination producing larger amplitudes. This dilation is satisfactorily modelled by linear addition with a higher melanopsin weighting in ipRGCs. Visual reaction times were longest in response to melanopsin‐directed lights. Next, we asked whether the afferent photoreceptor input and decision certainty, controlled by priming the observer's a priori expectation, interact to drive the TEPD. Signal detection analysis showed that by fixing the predecision certainty (bias), the phasic arousal and TEPD amplitude vary with observer criterion (c′) and sensitivity (d′) but not with preferential activation of melanopsin. The signature feature of the melanopsin response during attention was a biphasic TEPD. We conclude that active covert attention can be modulated by visual information mediated via ipRGCs, but that phasic arousal responses marked using the TEPD are not increased by higher levels of melanopsin activation.

Pupil Correlates of Decision Variables in Mice Playing a Competitive Mixed-Strategy Game

In a competitive game involving an animal and an opponent, the outcome is contingent on the choices of both players. To succeed, the animal must continually adapt to competitive pressure, or else risk being exploited and lose out on rewards. In this study, we demonstrate that head-fixed male mice can be trained to play the iterative competitive game "matching pennies" against a virtual computer opponent. We find that the animals' performance is well described by a hybrid computational model that includes Q-learning and choice kernels. Comparing between matching pennies and a non-competitive two-armed bandit task, we show that the tasks encourage animals to operate at different regimes of reinforcement learning. To understand the involvement of neuromodulatory mechanisms, we measure fluctuations in pupil size and use multiple linear regression to relate the trial-by-trial transient pupil responses to decision-related variables. The analysis reveals that pupil responses are modulated by observable variables, including choice and outcome, as well as latent variables for value updating, but not action selection. Collectively, these results establish a paradigm for studying competitive decision-making in head-fixed mice and provide insights into the role of arousal-linked neuromodulation in the decision process.

Temporal dynamics of auditory bistable perception correlated with fluctuation of baseline pupil size

A dynamic neural network change, accompanied by cognitive shifts such as internal perceptual alternation in bistable stimuli, is reconciled by the discharge of noradrenergic locus coeruleus neurons. Transient pupil dilation as a consequence of the reconciliation with the neural network in bistable perception has been reported to precede the reported perceptual alternation. Here, we found that baseline pupil size, an index of temporal fluctuation of arousal level over a longer range of timescales than that for the transient pupil changes, relates to the frequency of perceptual alternation in auditory bistability. Baseline pupil size was defined as the mean pupil diameter over a period of 1 s prior to the task requirement (i.e., before the observation period for counting the perceptual alternations in Experiment 1 and reporting whether participants experienced the perceptual alternations in Experiment 2). The results showed that the baseline pupil size monotonically increased with an increasing number of perceptual alternations and its occurrence probability. Furthermore, a cross‐correlation analysis indicates that baseline pupil size predicted perceptual alternation at least 35 s before the behavioral response and that the overall correspondence between pupil size and perceptual alternation was maintained over a sustained time window of 45 s at minimum. The overall results suggest that variability of baseline pupil size reflects the stochastic dynamics of arousal fluctuation in the brain related to bistable perception.

Brain Infraslow Activity Correlates With Arousal Levels

The functional role of the brain’s infraslow activity (ISA, 0.01–0.1 Hz) in human behavior has yet to be elucidated. To date, it has been shown that the brain’s ISA correlates with behavioral performance; task performance is more likely to increase when executed at a specific ISA phase. However, it is unclear how the ISA correlates behavioral performance. We hypothesized that the ISA phase correlation of behavioral performance is mediated by arousal. Our data analysis results showed that the electroencephalogram (EEG) ISA phase was correlated with the galvanic skin response (GSR) amplitude, a measure of the arousal level. Furthermore, subjects whose EEG ISA phase correlated with the GSR amplitude more strongly also showed greater EEG ISA modulation during meditation, which implies an intimate relationship between brain ISA and arousal. These results may help improve understanding of the functional role of the brain’s ISA.

Deficient Recurrent Cortical Processing in Congenital Deafness

The influence of sensory experience on cortical feedforward and feedback interactions has rarely been studied in the auditory cortex. Previous work has documented a dystrophic effect of deafness in deep cortical layers, and a reduction of interareal couplings between primary and secondary auditory areas in congenital deafness which was particularly pronounced in the top-down direction (from the secondary to the primary area). In the present study, we directly quantified the functional interaction between superficial (supragranular, I to III) and deep (infragranular, V and VI) layers of feline’s primary auditory cortex A1, and also between superficial/deep layers of A1 and a secondary auditory cortex, namely the posterior auditory field (PAF). We compared adult hearing cats under acoustic stimulation and cochlear implant (CI) stimulation to adult congenitally deaf cats (CDC) under CI stimulation. Neuronal activity was recorded from auditory fields A1 and PAF simultaneously with two NeuroNexus electrode arrays. We quantified the spike field coherence (i.e., the statistical dependence of spike trains at one electrode with local field potentials on another electrode) using pairwise phase consistency (PPC). Both the magnitude as well as the preferred phase of synchronization was analyzed. The magnitude of PPC was significantly smaller in CDCs than in controls. Furthermore, controls showed no significant difference between the preferred phase of synchronization between supragranular and infragranular layers, both in acoustic and electric stimulation. In CDCs, however, there was a large difference in the preferred phase between supragranular and infragranular layers. These results demonstrate a loss of synchrony and for the first time directly document a functional decoupling of the interaction between supragranular and infragranular layers of the primary auditory cortex in congenital deafness. Since these are key for the influence of top-down to bottom-up computations, the results suggest a loss of recurrent cortical processing in congenital deafness and explain the outcomes of previous studies by deficits in intracolumnar microcircuitry.

Functional Coupling of the Locus Coeruleus Is Linked to Successful Cognitive Control

The locus coeruleus (LC) is a brainstem structure that sends widespread efferent projections throughout the mammalian brain. The LC constitutes the major source of noradrenaline (NE), a modulatory neurotransmitter that is crucial for fundamental brain functions such as arousal, attention, and cognitive control. This role of the LC-NE is traditionally not believed to reflect functional influences on the frontoparietal network or the striatum, but recent advances in chemogenetic manipulations of the rodent brain have challenged this notion. However, demonstrations of LC-NE functional connectivity with these areas in the human brain are surprisingly sparse. Here, we close this gap. Using an established emotional stroop task, we directly compared trials requiring response conflict control with trials that did not require this, but were matched for visual stimulus properties, response modality, and controlled for pupil dilation differences across both trial types. We found that LC-NE functional coupling with the parietal cortex and regions of the striatum is substantially enhanced during trials requiring response conflict control. Crucially, the strength of this functional coupling was directly related to individual reaction time differences incurred by conflict resolution. Our data concur with recent rodent findings and highlight the importance of converging evidence between human and nonhuman neurophysiology to further understand the neural systems supporting adaptive and maladaptive behavior in health and disease.

Activity-dependent modulation of NMDA receptors by endogenous zinc shapes dendritic function in cortical neurons

NMDA receptors (NMDARs) have been proposed to control single-neuron computations in vivo. However, whether specific mechanisms regulate the function of such receptors and modulate input-output transformations performed by cortical neurons under in vivo-like conditions is understudied. Here, we report that in layer 2/3 pyramidal neurons (L2/3 PNs), repeated synaptic stimulation results in an activity-dependent decrease in NMDAR function by vesicular zinc. Such a mechanism shifts the threshold for dendritic non-linearities and strongly reduces LTP. Modulation of NMDARs is cell and pathway specific, being present selectively in L2/3-L2/3 connections but absent in inputs originating from L4 neurons. Numerical simulations highlight that activity-dependent modulation of NMDARs influences dendritic computations, endowing L2/3 PN dendrites with the ability to sustain non-linear integrations constant across different regimes of synaptic activity like those found in vivo. Our results unveil vesicular zinc as an important endogenous modulator of dendritic function in cortical PNs.

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Vesicular zinc release downregulates function of synaptic NMDARs in cortical neurons

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Zinc modulation of NMDARs is activity dependent, pathway and cell specific

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Endogenous zinc controls dendritic non-linearities and synaptic plasticity in L2/3 PNs

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Modulation of NMDARs normalizes dendritic function during ongoing synaptic activity

Hearing in Complex Environments: Auditory Gain Control, Attention, and Hearing Loss

Listening in noisy or complex sound environments is difficult for individuals with normal hearing and can be a debilitating impairment for those with hearing loss. Extracting meaningful information from a complex acoustic environment requires the ability to accurately encode specific sound features under highly variable listening conditions and segregate distinct sound streams from multiple overlapping sources. The auditory system employs a variety of mechanisms to achieve this auditory scene analysis. First, neurons across levels of the auditory system exhibit compensatory adaptations to their gain and dynamic range in response to prevailing sound stimulus statistics in the environment. These adaptations allow for robust representations of sound features that are to a large degree invariant to the level of background noise. Second, listeners can selectively attend to a desired sound target in an environment with multiple sound sources. This selective auditory attention is another form of sensory gain control, enhancing the representation of an attended sound source while suppressing responses to unattended sounds. This review will examine both “bottom-up” gain alterations in response to changes in environmental sound statistics as well as “top-down” mechanisms that allow for selective extraction of specific sound features in a complex auditory scene. Finally, we will discuss how hearing loss interacts with these gain control mechanisms, and the adaptive and/or maladaptive perceptual consequences of this plasticity.

Coupling of pupil- and neuronal population dynamics reveals diverse influences of arousal on cortical processing

Fluctuations in arousal, controlled by subcortical neuromodulatory systems, continuously shape cortical state, with profound consequences for information processing. Yet, how arousal signals influence cortical population activity in detail has so far only been characterized for a few selected brain regions. Traditional accounts conceptualize arousal as a homogeneous modulator of neural population activity across the cerebral cortex. Recent insights, however, point to a higher specificity of arousal effects on different components of neural activity and across cortical regions. Here, we provide a comprehensive account of the relationships between fluctuations in arousal and neuronal population activity across the human brain. Exploiting the established link between pupil size and central arousal systems, we performed concurrent magnetoencephalographic (MEG) and pupillographic recordings in a large number of participants, pooled across three laboratories. We found a cascade of effects relative to the peak timing of spontaneous pupil dilations: Decreases in low-frequency (2-8 Hz) activity in temporal and lateral frontal cortex, followed by increased high-frequency (>64 Hz) activity in mid-frontal regions, followed by monotonic and inverted U relationships with intermediate frequency-range activity (8-32 Hz) in occipito-parietal regions. Pupil-linked arousal also coincided with widespread changes in the structure of the aperiodic component of cortical population activity, indicative of changes in the excitation-inhibition balance in underlying microcircuits. Our results provide a novel basis for studying the arousal modulation of cognitive computations in cortical circuits.