The emergence and influence of internal states

State-dependent dynamics of cuttlefish mantle activity

Cuttlefish skin is a powerful rendering device, capable of producing extraordinary changes in visual appearance over a broad range of temporal scales. This unique ability is typically associated with camouflage; however, cuttlefish often produce skin patterns that do not appear connected with the surrounding environment, such as fast large-scale fluctuations with wave-like characteristics. Little is known about the functional significance of these dynamic patterns. In this study, we developed novel tools for analyzing pattern dynamics, and demonstrate their utility for detecting changes in feeding state that occur without concomitant changes in sensory stimulation. Under these conditions, we found that the dynamic properties of specific pattern components differ for different feeding states, despite no measurable change in the overall expression of those components. Therefore, these dynamic changes are not detectable by conventional analyses focusing on pattern expression, requiring analytical tools specifically targeted to pattern dynamics.

Development of neural circuits for social motion perception in schooling fish

The collective behavior of animal groups emerges from the interactions among individuals. These social interactions produce the coordinated movements of bird flocks and fish schools, but little is known about their developmental emergence and neurobiological foundations. By characterizing the visually based schooling behavior of the micro glassfish Danionella cerebrum, we found that social development progresses sequentially, with animals first acquiring the ability to aggregate, followed by postural alignment with social partners. This social maturation was accompanied by the development of neural populations in the midbrain that were preferentially driven by visual stimuli that resemble the shape and movements of schooling fish. Furthermore, social isolation over the course of development impaired both schooling behavior and the neural encoding of social motion in adults. This work demonstrates that neural populations selective for the form and motion of conspecifics emerge with the experience-dependent development of collective movement.

Satiety controls behavior in Hydra through an interplay of pre-enteric and central nervous system-like neuron populations

Hunger and satiety can have an influence on decision-making, sensory processing, and motor behavior by altering the internal state of the brain. This process necessitates the integration of peripheral sensory stimuli into the central nervous system. Here, we show how animals without a central nervous system such as the cnidarian Hydra measure and integrate satiety into neuronal circuits and which specific neuronal populations are involved. We demonstrate that this simple nervous system, previously referred to as diffuse, has an endodermal subpopulation (N4) similar to the enteric nervous system (feeding-associated behavior) and an ectodermal population (N3) that performs central nervous system-like functions (physiology/motor). This view of a supposedly simple nervous system could open an important window into the origin of more complex nervous systems.

Measuring the replicability of our own research

In the study of transgenic mouse models of neurodevelopmental and neurodegenerative disorders, we use batteries of tests to measure deficits in behaviour and from the results of these tests, we make inferences about the mental states of the mice that we interpret as deficits in "learning", "memory", "anxiety", "depression", etc. This paper discusses the problems of determining whether a particular transgenic mouse is a valid mouse model of disease X, the problem of background strains, and the question of whether our behavioural tests are measuring what we say they are. The problem of the reliability of results is then discussed: are they replicable between labs and can we replicate our results in our own lab? This involves the study of intra- and inter- experimenter reliability. The variables that influence replicability and the importance of conducting a complete behavioural phenotype: sensory, motor, cognitive and social emotional behaviour are discussed. Then the thorny question of failure to replicate is examined: Is it a curse or a blessing? Finally, the role of failure in research and what it tells us about our research paradigms is examined.

Studying dominance and aggression requires ethologically relevant paradigms

Although aggression is associated with several psychiatric disorders, there is no effective treatment nor a rigorous definition for "pathological aggression". Mice make a valuable model for studying aggression. They have a dynamic social structure that depends on the habitat and includes reciprocal interactions between the mice's aggression levels, social dominance hierarchy (SDH), and resource allocation. Nevertheless, the classical behavioral tests for territorial aggression and SDH in mice are reductive and have limited ethological and translational relevance. Recent work has explored the use of semi-natural environments to simultaneously study dominance-related behaviors, resource allocation, and aggressive behavior. Semi-natural setups allow experimental control of the environment combined with manipulations of neural activity. We argue that these setups can help bridge the translational gap in aggression research toward discovering neuronal mechanisms underlying maladaptive aggression.

Dynamic skin behaviors in cephalopods

The coleoid cephalopods (cuttlefish, octopus, and squid) are a group of soft-bodied mollusks that exhibit a wealth of complex behaviors, including dynamic camouflage, object mimicry, skin-based visual communication, and dynamic body patterns during sleep. Many of these behaviors are visually driven and engage the animals' color changing skin, a pixelated display that is directly controlled by neurons projecting from the brain. Thus, cephalopod skin provides a direct readout of neural activity in the brain. During camouflage, cephalopods recreate on their skin an approximation of what they see, providing a window into perceptual processes in the brain. Additionally, cephalopods communicate their internal state during social encounters using innate skin patterns, and create waves of pigmentation on their skin during periods of arousal. Thus, by leveraging the visual displays of cephalopods, we can gain insight into how the external world is represented in the brain and how this representation is transformed into a recapitulation of the world on the skin. Here, we describe the rich skin behaviors of the coleoid cephalopods, what is known about cephalopod neuroanatomy, and how advancements in gene editing, machine learning, optical imaging, and electrophysiological tools may provide an opportunity to explore the neural bases of these fascinating behaviors.

Memory Trace for Fear Extinction: Fragile yet Reinforceable

Fear extinction is a biological process in which learned fear behavior diminishes without anticipated reinforcement, allowing the organism to re-adapt to ever-changing situations. Based on the behavioral hypothesis that extinction is new learning and forms an extinction memory, this new memory is more readily forgettable than the original fear memory. The brain's cellular and synaptic traces underpinning this inherently fragile yet reinforceable extinction memory remain unclear. Intriguing questions are about the whereabouts of the engram neurons that emerged during extinction learning and how they constitute a dynamically evolving functional construct that works in concert to store and express the extinction memory. In this review, we discuss recent advances in the engram circuits and their neural connectivity plasticity for fear extinction, aiming to establish a conceptual framework for understanding the dynamic competition between fear and extinction memories in adaptive control of conditioned fear responses.

Understanding collective behavior through neurobiology

A variety of organisms exhibit collective movement, including schooling fish and flocking birds, where coordinated behavior emerges from the interactions between group members. Despite the prevalence of collective movement in nature, little is known about the neural mechanisms producing each individual's behavior within the group. Here we discuss how a neurobiological approach can enrich our understanding of collective behavior by determining the mechanisms by which individuals interact. We provide examples of sensory systems for social communication during collective movement, highlight recent discoveries about neural systems for detecting the position and actions of social partners, and discuss opportunities for future research. Understanding the neurobiology of collective behavior can provide insight into how nervous systems function in a dynamic social world.

Different state-dependence of population codes across cortex

During perceptual decision-making, behavioral performance varies with changes in internal states such as arousal, motivation, and strategy. Yet it is unknown how these internal states affect information coding across cortical regions involved in differing aspects of sensory perception and decision-making. We recorded neural activity from the primary auditory cortex (AC) and posterior parietal cortex (PPC) in mice performing a navigation-based sound localization task. We then modeled transitions in the behavioral strategies mice used during task performance. Mice transitioned between three latent performance states with differing decision-making strategies: an 'optimal' state and two 'sub-optimal' states characterized by choice bias and frequent errors. Performance states strongly influenced population activity patterns in association but not sensory cortex. Surprisingly, activity of individual PPC neurons was better explained by external inputs and behavioral variables during suboptimal behavioral performance than in the optimal performance state. Furthermore, shared variability across neurons (coupling) in PPC was strongest in the optimal state. In AC, shared variability was similarly weak across all performance states. Together, these findings indicate that neural activity in association cortex is more strongly linked to internal state than in sensory cortex.

Simultaneous, cortex-wide dynamics of up to 1 million neurons reveal unbounded scaling of dimensionality with neuron number

The brain's remarkable properties arise from the collective activity of millions of neurons. Widespread application of dimensionality reduction to multi-neuron recordings implies that neural dynamics can be approximated by low-dimensional "latent" signals reflecting neural computations. However, can such low-dimensional representations truly explain the vast range of brain activity, and if not, what is the appropriate resolution and scale of recording to capture them? Imaging neural activity at cellular resolution and near-simultaneously across the mouse cortex, we demonstrate an unbounded scaling of dimensionality with neuron number in populations up to 1 million neurons. Although half of the neural variance is contained within sixteen dimensions correlated with behavior, our discovered scaling of dimensionality corresponds to an ever-increasing number of neuronal ensembles without immediate behavioral or sensory correlates. The activity patterns underlying these higher dimensions are fine grained and cortex wide, highlighting that large-scale, cellular-resolution recording is required to uncover the full substrates of neuronal computations.

SAUSI: a novel assay for measuring social anxiety and motivation

Social anxiety is one of the most prevalent mental health disorders, though the underlying neurobiology is poorly understood. Progress in understanding the etiology of social anxiety has been hindered by the lack of comprehensive tools to assess social anxiety in model systems. Here, we created a new behavioral task - Selective Access to Unrestricted Social Interaction (SAUSI), which combines elements of social motivation, hesitancy, decision-making, and free interaction to enable the wholistic assessment of social anxiety-like behaviors in mice. Using this novel assay, we found that social isolation-induced social anxiety-like behaviors in female mice are largely driven by increases in social fear, social hesitancy, and altered ultrasonic vocalizations. Deep learning analyses were able to computationally identify a unique behavioral footprint underlying the state produced by social isolation, demonstrating the compatibility of modern computational approaches with SAUSI. Finally, we compared the results of SAUSI to traditionally social assays including the 3-chamber sociability assay and the resident intruder task. This revealed that behavioral changes induced by isolation were highly context dependent, and that while fragments of social anxiety measured in SAUSI were replicable across other tasks, a wholistic assessment was not obtainable from these alternative assays. Our findings debut a novel task for the behavioral toolbox - one which overcomes limitations of previous assays, allowing for both social choice as well as free interaction, and offers a new approach for assessing social anxiety in rodents.

Understanding the factors regulating host-microbiome interactions using Caenorhabditis elegans

The Human Microbiome Project was a research programme that successfully identified associations between microbial species and healthy or diseased individuals. However, a major challenge identified was the absence of model systems for studying host-microbiome interactions, which would increase our capacity to uncover molecular interactions, understand organ-specificity and discover new microbiome-altering health interventions. Caenorhabditis elegans has been a pioneering model organism for over 70 years but was largely studied in the absence of a microbiome. Recently, ecological sampling of wild nematodes has uncovered a large amount of natural genetic diversity as well as a slew of associated microbiota. The field has now explored the interactions of C. elegans with its associated gut microbiome, a defined and non-random microbial community, highlighting its suitability for dissecting host-microbiome interactions. This core microbiome is being used to study the impact of host genetics, age and stressors on microbiome composition. Furthermore, single microbiome species are being used to dissect molecular interactions between microbes and the animal gut. Being amenable to health altering genetic and non-genetic interventions, C. elegans has emerged as a promising system to generate and test new hypotheses regarding host-microbiome interactions, with the potential to uncover novel paradigms relevant to other systems. This article is part of the theme issue 'Sculpting the microbiome: how host factors determine and respond to microbial colonization'.

Fluctuating landscapes and heavy tails in animal behavior

Animal behavior is shaped by a myriad of mechanisms acting on a wide range of scales, which hampers quantitative reasoning and the identification of general principles. Here, we combine data analysis and theory to investigate the relationship between behavioral plasticity and heavy-tailed statistics often observed in animal behavior. Specifically, we first leverage high-resolution recordings of C. elegans locomotion to show that stochastic transitions among long-lived behaviors exhibit heavy-tailed first passage time distributions and correlation functions. Such heavy tails can be explained by slow adaptation of behavior over time. This particular result motivates our second step of introducing a general model where we separate fast dynamics on a quasi-stationary multi-well potential, from non-ergodic, slowly varying modes. We then show that heavy tails generically emerge in such a model, and we provide a theoretical derivation of the resulting functional form, which can become a power law with exponents that depend on the strength of the fluctuations. Finally, we provide direct support for the generality of our findings by testing them in a C. elegans mutant where adaptation is suppressed and heavy tails thus disappear, and recordings of larval zebrafish swimming behavior where heavy tails are again prevalent.

Top-down modulation of visual cortical stimulus encoding and gamma independent of firing rates

Neurons in primary visual cortex integrate sensory input with signals reflecting the animal's internal state to support flexible behavior. Internal variables, such as expectation, attention, or current goals, are imposed in a top-down manner via extensive feedback projections from higher-order areas. We optogenetically activated a high-order visual area, area 21a, in the lightly anesthetized cat (OptoTD), while recording from neuronal populations in V1. OptoTD induced strong, up to several fold, changes in gamma-band synchronization together with much smaller changes in firing rate, and the two effects showed no correlation. OptoTD effects showed specificity for the features of the simultaneously presented visual stimuli. OptoTD-induced changes in gamma synchronization, but not firing rates, were predictive of simultaneous changes in the amount of encoded stimulus information. Our findings suggest that one important role of top-down signals is to modulate synchronization and the information encoded by populations of sensory neurons.

Serotonergic modulation of vigilance states in zebrafish and mice

Vigilance refers to being alertly watchful or paying sustained attention to avoid potential threats. Animals in vigilance states reduce locomotion and have an enhanced sensitivity to aversive stimuli so as to react quickly to dangers. Here we report that an unconventional 5-HT driven mechanism operating at neural circuit level which shapes the internal state underlying vigilance behavior in zebrafish and male mice. The neural signature of internal vigilance state was characterized by persistent low-frequency high-amplitude neuronal synchrony in zebrafish dorsal pallium and mice prefrontal cortex. The neuronal synchronization underlying vigilance was dependent on intense release of 5-HT induced by persistent activation of either DRN 5-HT neuron or local 5-HT axon terminals in related brain regions via activation of 5-HTR7. Thus, we identify a mechanism of vigilance behavior across species that illustrates the interplay between neuromodulators and neural circuits necessary to shape behavior states.

Whole-brain neural substrates of behavioral variability in the larval zebrafish

Animals engaged in naturalistic behavior can exhibit a large degree of behavioral variability even under sensory invariant conditions. Such behavioral variability can include not only variations of the same behavior, but also variability across qualitatively different behaviors driven by divergent cognitive states, such as fight-or-flight decisions. However, the neural circuit mechanisms that generate such divergent behaviors across trials are not well understood. To investigate this question, here we studied the visual-evoked responses of larval zebrafish to moving objects of various sizes, which we found exhibited highly variable and divergent responses across repetitions of the same stimulus. Given that the neuronal circuits underlying such behaviors span sensory, motor, and other brain areas, we built a novel Fourier light field microscope which enables high-resolution, whole-brain imaging of larval zebrafish during behavior. This enabled us to screen for neural loci which exhibited activity patterns correlated with behavioral variability. We found that despite the highly variable activity of single neurons, visual stimuli were robustly encoded at the population level, and the visual-encoding dimensions of neural activity did not explain behavioral variability. This robustness despite apparent single neuron variability was due to the multi-dimensional geometry of the neuronal population dynamics: almost all neural dimensions that were variable across individual trials, i.e. the "noise" modes, were orthogonal to those encoding for sensory information. Investigating this neuronal variability further, we identified two sparsely-distributed, brain-wide neuronal populations whose pre-motor activity predicted whether the larva would respond to a stimulus and, if so, which direction it would turn on a single-trial level. These populations predicted single-trial behavior seconds before stimulus onset, indicating they encoded time-varying internal modulating behavior, perhaps organizing behavior over longer timescales or enabling flexible behavior routines dependent on the animal's internal state. Our results provide the first whole-brain confirmation that sensory, motor, and internal variables are encoded in a highly mixed fashion throughout the brain and demonstrate that de-mixing each of these components at the neuronal population level is critical to understanding the mechanisms underlying the brain's remarkable flexibility and robustness.

Molecular control of temporal integration matches decision-making to motivational state

Motivations bias our responses to stimuli, producing behavioral outcomes that match our needs and goals. We describe a mechanism behind this phenomenon: adjusting the time over which stimulus-derived information is permitted to accumulate toward a decision. As a Drosophila copulation progresses, the male becomes less likely to continue mating through challenges. We show that a set of Copulation Decision Neurons (CDNs) flexibly integrates information about competing drives to mediate this decision. Early in mating, dopamine signaling restricts CDN integration time by potentiating CaMKII activation in response to stimulatory inputs, imposing a high threshold for changing behaviors. Later into mating, the timescale over which the CDNs integrate termination-promoting information expands, increasing the likelihood of switching behaviors. We suggest scalable windows of temporal integration at dedicated circuit nodes as a key but underappreciated variable in state-based decision-making.

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.

Fantastic beasts and how to study them: rethinking experimental animal behavior

Humans have been trying to understand animal behavior at least since recorded history. Recent rapid development of new technologies has allowed us to make significant progress in understanding the physiological and molecular mechanisms underlying behavior, a key goal of neuroethology. However, there is a tradeoff when studying animal behavior and its underlying biological mechanisms: common behavior protocols in the laboratory are designed to be replicable and controlled, but they often fail to encompass the variability and breadth of natural behavior. This Commentary proposes a framework of 10 key questions that aim to guide researchers in incorporating a rich natural context into their experimental design or in choosing a new animal study system. The 10 questions cover overarching experimental considerations that can provide a template for interspecies comparisons, enable us to develop studies in new model organisms and unlock new experiments in our quest to understand behavior.

Neuroendocrine gene expression coupling of interoceptive bacterial food cues to foraging behavior of C. elegans

Animal internal state is modulated by nutrient intake, resulting in behavioral responses to changing food conditions. The neural mechanisms by which internal states are generated and maintained are not well understood. Here, we show that in the nematode Caenorhabditis elegans, distinct cues from bacterial food - interoceptive signals from the ingestion of bacteria and gustatory molecules sensed from nearby bacteria - act antagonistically on the expression of the neuroendocrine TGF-beta ligand DAF-7 from the ASJ pair of sensory neurons to modulate foraging behavior. A positive-feedback loop dependent on the expression of daf-7 from the ASJ neurons acts to promote transitions between roaming and dwelling foraging states and influence the persistence of roaming states. SCD-2, the C. elegans ortholog of mammalian anaplastic lymphoma kinase (ALK), which has been implicated in the central control of metabolism of mammals, functions in the AIA interneurons to regulate foraging behavior and cell-non-autonomously control the expression of DAF-7 from the ASJ neurons. Our data establish how a dynamic neuroendocrine daf-7 expression feedback loop regulated by SCD-2 functions to couple sensing and ingestion of bacterial food to foraging behavior. We further suggest that this neuroendocrine feedback loop underlies previously characterized exploratory behaviors in C. elegans. Our data suggest that the expression of daf-7 from the ASJ neurons contributes to and is correlated with an internal state of 'unmet need' that regulates exploratory foraging behavior in response to bacterial cues in diverse physiological contexts.

Simultaneous, cortex-wide and cellular-resolution neuronal population dynamics reveal an unbounded scaling of dimensionality with neuron number

The brain's remarkable properties arise from collective activity of millions of neurons. Widespread application of dimensionality reduction to multi-neuron recordings implies that neural dynamics can be approximated by low-dimensional "latent" signals reflecting neural computations. However, what would be the biological utility of such a redundant and metabolically costly encoding scheme and what is the appropriate resolution and scale of neural recording to understand brain function? Imaging the activity of one million neurons at cellular resolution and near-simultaneously across mouse cortex, we demonstrate an unbounded scaling of dimensionality with neuron number. While half of the neural variance lies within sixteen behavior-related dimensions, we find this unbounded scaling of dimensionality to correspond to an ever-increasing number of internal variables without immediate behavioral correlates. The activity patterns underlying these higher dimensions are fine-grained and cortex-wide, highlighting that large-scale recording is required to uncover the full neural substrates of internal and potentially cognitive processes.

Synchronized LFP rhythmicity in the social brain reflects the context of social encounters

Mammalian social behavior is highly context-sensitive. Yet, little is known about the mechanisms that modulate social behavior according to its context. Recent studies have revealed a network of mostly limbic brain regions which regulates social behavior. We hypothesize that coherent theta and gamma rhythms reflect the organization of this network into functional sub-networks in a context-dependent manner. To test this concept, we simultaneously record local field potential (LFP) from multiple social brain regions in adult male mice performing three social discrimination tasks. While LFP rhythmicity across all tasks is dominated by a global internal state, the pattern of theta coherence between the various regions reflect the behavioral task more than other variables. Moreover, Granger causality analysis implicate the ventral dentate gyrus as a main player in coordinating the context-specific rhythmic activity. Thus, our results suggest that the pattern of coordinated rhythmic activity within the network reflects the subject's social context.

Sensory neurons couple arousal and foraging decisions in Caenorhabditis elegans

Foraging animals optimize feeding decisions by adjusting both common and rare behavioral patterns. Here, we characterize the relationship between an animal's arousal state and a rare decision to leave a patch of bacterial food. Using long-term tracking and behavioral state classification, we find that food leaving decisions in Caenorhabditis elegans are coupled to arousal states across multiple timescales. Leaving emerges probabilistically over minutes from the high arousal roaming state, but is suppressed during the low arousal dwelling state. Immediately before leaving, animals have a brief acceleration in speed that appears as a characteristic signature of this behavioral motif. Neuromodulatory mutants and optogenetic manipulations that increase roaming have a coupled increase in leaving rates, and similarly acute manipulations that inhibit feeding induce both roaming and leaving. By contrast, inactivating a set of chemosensory neurons that depend on the cGMP-gated transduction channel TAX-4 uncouples roaming and leaving dynamics. In addition, tax-4-expressing sensory neurons promote lawn-leaving behaviors that are elicited by feeding inhibition. Our results indicate that sensory neurons responsive to both internal and external cues play an integrative role in arousal and foraging decisions.

Multiple neuronal populations control the eating behavior in Hydra and are responsive to microbial signals

Although recent studies indicate the impact of microbes on the central nervous systems and behavior, it remains unclear how the relationship between the functionality of the nervous system, behavior, and the microbiota evolved. In this work, we analyzed the eating behavior of Hydra, a host that has a simple nervous system and a low-complexity microbiota. To identify the neuronal subpopulations involved, we used a subpopulation-specific cell ablation system and calcium imaging. The role of the microbiota was uncovered by manipulating the diversity of the natural microbiota. We show that different neuronal subpopulations are functioning together to control eating behavior. Animals with a drastically reduced microbiome had severe difficulties in mouth opening due to a significantly increased level of glutamate. This could be reversed by adding a full complement of the microbiota. In summary, we provide a mechanistic explanation of how Hydra's nervous system controls eating behavior and what role microbes play in this.

Reward Modulates Visual Responses in the Superficial Superior Colliculus of Mice

The processing of sensory input is constantly adapting to behavioral demands and internal states. The drive to obtain reward, e.g., searching for water when thirsty, is a strong behavioral demand and associating the reward with its source, a certain environment or action, is paramount for survival. Here, we show that water reward increases subsequent visual activity in the superficial layers of the superior colliculus (SC), which receive direct input from the retina and belong to the earliest stages of visual processing. We trained mice of either sex to perform a visual decision task and recorded the activity of neurons in the SC using two-photon calcium imaging and high-density electrophysiological recordings. Responses to visual stimuli in around 20% of visually responsive neurons in the superficial SC were affected by reward delivered in the previous trial. Reward mostly increased visual responses independent from modulations due to pupil size changes. The modulation of visual responses by reward could not be explained by movements like licking. It was specific to responses to the following visual stimulus, independent of slow fluctuations in neural activity and independent of how often the stimulus was previously rewarded. Electrophysiological recordings confirmed these results and revealed that reward affected the early phase of the visual response around 80 ms after stimulus onset. Modulation of visual responses by reward, but not pupil size, significantly improved the performance of a population decoder to detect visual stimuli, indicating the relevance of reward modulation for the visual performance of the animal.SIGNIFICANCE STATEMENT To learn which actions lead to food, water, or safety, it is necessary to integrate the receiving of reward with sensory stimuli related to the reward. Cortical stages of sensory processing have been shown to represent stimulus-reward associations. Here, we show, however, that reward influences neurons at a much earlier stage of sensory processing, the superior colliculus (SC), receiving direct input from the retina. Visual responses were increased shortly after the animal received the water reward, which led to an improved stimulus signal in the population of these visual neurons. Reward modulation of early visual responses may thus improve perception of visual environments predictive of reward.

Synaptic plasticity through a naturalistic lens

From the myriad of studies on neuronal plasticity, investigating its underlying molecular mechanisms up to its behavioral relevance, a very complex landscape has emerged. Recent efforts have been achieved toward more naturalistic investigations as an attempt to better capture the synaptic plasticity underpinning of learning and memory, which has been fostered by the development of in vivo electrophysiological and imaging tools. In this review, we examine these naturalistic investigations, by devoting a first part to synaptic plasticity rules issued from naturalistic in vivo-like activity patterns. We next give an overview of the novel tools, which enable an increased spatio-temporal specificity for detecting and manipulating plasticity expressed at individual spines up to neuronal circuit level during behavior. Finally, we put particular emphasis on works considering brain-body communication loops and macroscale contributors to synaptic plasticity, such as body internal states and brain energy metabolism.

A thalamocortical pathway controlling impulsive behavior

Planning and anticipating motor actions enables movements to be quickly and accurately executed. However, if anticipation is not properly controlled, it can lead to premature impulsive actions. Impulsive behavior is defined as actions that are poorly conceived and are often risky and inappropriate. Historically, impulsive behavior was thought to be primarily controlled by the frontal cortex and basal ganglia. More recently, two additional brain regions, the ventromedial (VM) thalamus and the anterior lateral motor cortex (ALM), have been shown to have an important role in mice. Here, we explore this newly discovered role of the thalamocortical pathway and suggest cellular mechanisms that may be involved in driving the cortical activity that contributes to impulsive behavior.

Neuroendocrine Gene Expression Coupling of Interoceptive Bacterial Food Cues to Foraging Behavior of C. elegans

Animal internal state is modulated by nutrient intake, resulting in behavioral responses to changing food conditions. The neural mechanisms by which internal states are generated and maintained are not well understood. Here, we show that in the nematode Caenorhabditis elegans, distinct cues from bacterial food - interoceptive signals from the ingestion of bacteria and gustatory molecules sensed from nearby bacteria - act antagonistically on the expression of the neuroendocrine TGF-beta ligand DAF-7 from the ASJ pair of sensory neurons to modulate foraging behavior. A positive-feedback loop dependent on the expression of daf-7 from the ASJ neurons acts to promote transitions between roaming and dwelling foraging states and influence the persistence of roaming states. SCD-2, the C. elegans ortholog of mammalian Anaplastic Lymphoma Kinase (ALK), which has been implicated in the central control of metabolism of mammals, functions in the AIA interneurons to regulate foraging behavior and cell-non-autonomously control the expression of DAF-7 from the ASJ neurons. Our data establish how a dynamic neuroendocrine daf-7 expression feedback loop regulated by SCD-2 functions to couple sensing and ingestion of bacterial food to foraging behavior. We further suggest that this neuroendocrine feedback loop underlies previously characterized exploratory behaviors in C. elegans. Our data suggest that the expression of daf-7 from the ASJ neurons contributes to and is correlated with an internal state of "unmet need" that regulates exploratory foraging behavior in response to bacterial cues in diverse physiological contexts.

Neuropeptide Signaling is Required to Implement a Line Attractor Encoding a Persistent Internal Behavioral State

Internal states drive survival behaviors, but their neural implementation is not well understood. Recently we identified a line attractor in the ventromedial hypothalamus (VMH) that represents an internal state of aggressiveness. Line attractors can be implemented by recurrent connectivity and/or neuromodulatory signaling, but evidence for the latter is scant. Here we show that neuropeptidergic signaling is necessary for line attractor dynamics in this system, using a novel approach that integrates cell type-specific, anatomically restricted CRISPR/Cas9-based gene editing with microendoscopic calcium imaging. Co-disruption of receptors for oxytocin and vasopressin in adult VMH Esr1 + neurons that control aggression suppressed attack, reduced persistent neural activity and eliminated line attractor dynamics, while only modestly impacting neural activity and sex- or behavior-tuning. These data identify a requisite role for neuropeptidergic signaling in implementing a behaviorally relevant line attractor. Our approach should facilitate mechanistic studies in neuroscience that bridge different levels of biological function and abstraction.

Defensive responses: behaviour, the brain and the body

Most animals live under constant threat from predators, and predation has been a major selective force in shaping animal behaviour. Nevertheless, defence responses against predatory threats need to be balanced against other adaptive behaviours such as foraging, mating and recovering from infection. This behavioural balance in ethologically relevant contexts requires adequate integration of internal and external signals in a complex interplay between the brain and the body. Despite this complexity, research has often considered defensive behaviour as entirely mediated by the brain processing threat-related information obtained via perception of the external environment. However, accumulating evidence suggests that the endocrine, immune, gastrointestinal and reproductive systems have important roles in modulating behavioural responses to threat. In this Review, we focus on how predatory threat defence responses are shaped by threat imminence and review the circuitry between subcortical brain regions involved in mediating defensive behaviours. Then, we discuss the intersection of peripheral systems involved in internal states related to infection, hunger and mating with the neurocircuits that underlie defence responses against predatory threat. Through this process, we aim to elucidate the interconnections between the brain and body as an integrated network that facilitates appropriate defensive responses to threat and to discuss the implications for future behavioural research.

Development of neural circuits for social motion perception in schooling fish

Many animals move in groups, where collective behavior emerges from the interactions amongst individuals. These social interactions produce the coordinated movements of bird flocks and fish schools, but little is known about their developmental emergence and neurobiological foundations. By characterizing the visually-based schooling behavior of the micro glassfish Danionella cerebrum, here we found that social development progresses sequentially, with animals first acquiring the ability to aggregate, followed by postural alignment with social partners. This social maturation was accompanied by the development of neural populations in the midbrain and forebrain that were preferentially driven by visual stimuli that resemble the shape and movements of schooling fish. The development of these neural circuits enables the social coordination required for collective movement.

Fluctuating landscapes and heavy tails in animal behavior

Animal behavior is shaped by a myriad of mechanisms acting on a wide range of scales. This immense variability hampers quantitative reasoning and renders the identification of universal principles elusive. Through data analysis and theory, we here show that slow non-ergodic drives generally give rise to heavy-tailed statistics in behaving animals. We leverage high-resolution recordings of C. elegans locomotion to extract a self-consistent reduced order model for an inferred reaction coordinate, bridging from sub-second chaotic dynamics to long-lived stochastic transitions among metastable states. The slow mode dynamics exhibits heavy-tailed first passage time distributions and correlation functions, and we show that such heavy tails can be explained by dynamics on a time-dependent potential landscape. Inspired by these results, we introduce a generic model in which we separate faster mixing modes that evolve on a quasi-stationary potential, from slower non-ergodic modes that drive the potential landscape, and reflect slowly varying internal states. We show that, even for simple potential landscapes, heavy tails emerge when barrier heights fluctuate slowly and strongly enough. In particular, the distribution of first passage times and the correlation function can asymptote to a power law, with related exponents that depend on the strength and nature of the fluctuations. We support our theoretical findings through direct numerical simulations.

Persistent modulatory actions and task switching in the feeding network of Aplysia

The activity of multifunctional networks is configured by neuromodulators that exert persistent effects. This raises a question, does this impact the ability of a network to switch from one type of activity to another? We review studies that have addressed this question in the Aplysia feeding circuit. Task switching in this system occurs "asymmetrically." When there is a switch from egestion to ingestion neuromodulation impedes switching (creates a "negative bias"). When there is a switch from ingestion to egestion the biasing is "positive." Ingestion promotes subsequent egestion. We contrast mechanisms responsible for the two types of biasing and show that the observed asymmetry is a consequence of the fact that there is more than one set of egestive circuit parameters.

Ventral CA1 Population Codes for Anxiety

The ventral hippocampus is a critical node in the distributed brain network that controls anxiety. Using miniature microscopy and calcium imaging, we recorded ventral CA1 (vCA1) neurons in freely moving mice as they explored variants of classic behavioral assays for anxiety. Unsupervised behavioral segmentation revealed clusters of behavioral motifs that corresponded to exploratory and vigilance-like states. We discovered multiple vCA1 population codes that represented the anxiogenic features of the environment, such as bright light and openness, as well as the moment-to-moment anxiety state of the animals. These population codes possessed distinct generalization properties: neural representations of anxiogenic features were different for open field and elevated plus/zero maze tasks, while neural representations of moment-to-moment anxiety state were similar across both experimental contexts. Our results suggest that anxiety is not tied to the aversive compartments of these mazes but is rather defined by a behavioral state and its corresponding population code that generalizes across environments.

Toggling between food-seeking and self-preservation behaviors via hypothalamic response networks

Motivated behaviors are often studied in isolation to assess labeled lines of neural connections underlying innate actions. However, in nature, multiple systems compete for expression of goal-directed behaviors via complex neural networks. Here, we examined flexible survival decisions in animals tasked with food seeking under predation threat. We found that predator exposure rapidly induced physiological, neuronal, and behavioral adaptations in mice highlighted by reduced food seeking and consumption contingent on current threat level. Diminishing conflict via internal state or external environment perturbations shifted feeding strategies. Predator introduction and/or selective manipulation of danger-responsive cholecystokinin (Cck) cells of the dorsal premammilary nucleus (PMd) suppressed hunger-sensitive Agouti-related peptide (AgRP) neurons, providing a mechanism for threat-evoked hypophagia. Increased caloric need enhanced food seeking under duress through AgRP pathways to the bed nucleus of the stria terminalis (BNST) and/or lateral hypothalamus (LH). Our results suggest oscillating interactions between systems underlying self-preservation and food seeking to promote optimal behavior.

Brain-wide representations of behavior spanning multiple timescales and states in C. elegans

Changes in an animal's behavior and internal state are accompanied by widespread changes in activity across its brain. However, how neurons across the brain encode behavior and how this is impacted by state is poorly understood. We recorded brain-wide activity and the diverse motor programs of freely moving C. elegans and built probabilistic models that explain how each neuron encodes quantitative behavioral features. By determining the identities of the recorded neurons, we created an atlas of how the defined neuron classes in the C. elegans connectome encode behavior. Many neuron classes have conjunctive representations of multiple behaviors. Moreover, although many neurons encode current motor actions, others integrate recent actions. Changes in behavioral state are accompanied by widespread changes in how neurons encode behavior, and we identify these flexible nodes in the connectome. Our results provide a global map of how the cell types across an animal's brain encode its behavior.

The neurobiology of insulin-like growth factor I: From neuroprotection to modulation of brain states

After decades of research in the neurobiology of IGF-I, its role as a prototypical neurotrophic factor is undisputed. However, many of its actions in the adult brain indicate that this growth factor is not only involved in brain development or in the response to injury. Following a three-layer assessment of its role in the central nervous system, we consider that at the cellular level, IGF-I is indeed a bona fide neurotrophic factor, modulating along ontogeny the generation and function of all the major types of brain cells, contributing to sculpt brain architecture and adaptive responses to damage. At the circuit level, IGF-I modulates neuronal excitability and synaptic plasticity at multiple sites, whereas at the system level, IGF-I intervenes in energy allocation, proteostasis, circadian cycles, mood, and cognition. Local and peripheral sources of brain IGF-I input contribute to a spatially restricted, compartmentalized, and timed modulation of brain activity. To better define these variety of actions, we consider IGF-I a modulator of brain states. This definition aims to reconcile all aspects of IGF-I neurobiology, and may provide a new conceptual framework in the design of future research on the actions of this multitasking neuromodulator in the brain.

Context and the functional use of information in insect sensory ecology

Context-specific behaviors emerge from the interaction between an animal's internal state and its external environment. Although the importance of context is acknowledged in the field of insect sensory ecology, there is a lack of synthesis on this topic stemming from challenges in conceptualizing 'context'. We address this challenge by gleaning over the recent findings on the sensory ecology of mosquitoes and other insect pollinators. We discuss internal states and their temporal dynamics, from those lasting minutes to hours (host-seeking) to those lasting days to weeks (diapause, migration). Of the many patterns reviewed, at least three were common to all taxa studied. First, different sensory cues gain prominence depending on the insect's internal state. Second, similar sensory circuits between related species can result in different behavioral outcomes. And third, ambient conditions can dramatically alter internal states and behaviors.

Isolation of Projection-Specific and Behavior-Relevant Amygdala Circuit for RNA Sequencing

One of the most sought-after topics in neuroscience is to understand how the environment regulates the activity and function of neural circuitry and subsequently influences relevant behaviors. In response to alterations in the environment, the neural circuits undergo adaptive changes ranging from gene expression changes to altered cellular function. Performing sequencing of the transcriptome involved in these behavior-related circuits will provide clues to accurately dissect the detailed mechanisms of related behavior. Here, we describe methods for marking and collecting the ventral hippocampus-projecting basolateral amygdala neurons, which have been repeatedly implicated in regulation of anxiety-like behavior, and subsequently constructing a library ready for sequencing. Specifically, the reported approaches include adeno-associated virus injection, acute brain slice isolation, cell suspension preparation, cell extraction, and cDNA library construction. By utilizing the techniques described here, researchers can comprehensively investigate the transcriptional levels of neural clusters embedded in particular circuits and discover potential pathogenic and therapeutic targets for behavior-relevant disorders. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Tagging of behavior-related neural circuits Basic Protocol 2: Isolation and capture of fluorescent-positive cells Basic Protocol 3: Foundation of sequencing library.

Why is everyone talking about brain state?

The rapid and coordinated propagation of neural activity across the brain provides the foundation for complex behavior and cognition. Technical advances across neuroscience subfields have advanced understanding of these dynamics, but points of convergence are often obscured by semantic differences, creating silos of subfield-specific findings. In this review we describe how a parsimonious conceptualization of brain state as the fundamental building block of whole-brain activity offers a common framework to relate findings across scales and species. We present examples of the diverse techniques commonly used to study brain states associated with physiology and higher-order cognitive processes, and discuss how integration across them will enable a more comprehensive and mechanistic characterization of the neural dynamics that are crucial to survival but are disrupted in disease.

Behavioral dissection of hunger states in Drosophila

Hunger is a motivational drive that promotes feeding, and it can be generated by the physiological need to consume nutrients as well as the hedonic properties of food. Brain circuits and mechanisms that regulate feeding have been described, but which of these contribute to the generation of motive forces that drive feeding is unclear. Here, we describe our first efforts at behaviorally and neuronally distinguishing hedonic from homeostatic hunger states in Drosophila melanogaster and propose that this system can be used as a model to dissect the molecular mechanisms that underlie feeding motivation. We visually identify and quantify behaviors exhibited by hungry flies and find that increased feeding duration is a behavioral signature of hedonic feeding motivation. Using a genetically encoded marker of neuronal activity, we find that the mushroom body (MB) lobes are activated by hedonic food environments, and we use optogenetic inhibition to implicate a dopaminergic neuron cluster (protocerebral anterior medial [PAM]) to α'/β' MB circuit in hedonic feeding motivation. The identification of discrete hunger states in flies and the development of behavioral assays to measure them offers a framework to begin dissecting the molecular and circuit mechanisms that generate motivational states in the brain.

Astrocytes: integrators of arousal state and sensory context

The integration of external information with the internal state of the body is central to the survival of virtually every multicellular organism. However, a complete picture of the mechanisms that govern this process is lacking. In this opinion article, we synthesize evidence demonstrating that astrocytes sense the momentary arousal state - through neuromodulator release - as well as the sensory inputs - through local synaptic activity - and respond to them with changes in calcium (Ca2+) signaling. We hypothesize that astrocytes integrate sensory signals with the internal state and that this process is necessary to secure optimal behavior. Finally, we argue that dysfunctional astrocytic Ca2+ signaling could be an underlying factor in disorders characterized by disrupted sensory processing.

Systematic evaluation of a predator stress model of depression in mice using a hierarchical 3D-motion learning framework

Investigation of the neurobiology of depression in humans depends on animal models that attempt to mimic specific features of the human disorder. However, frequently-used paradigms based on social stress cannot be easily applied to female mice which has led to a large sex bias in preclinical studies of depression. Furthermore, most studies focus on one or only a few behavioral assessments, with time and practical considerations prohibiting a comprehensive evaluation. In this study, we demonstrate that predator stress effectively induced depression-like behaviors in both male and female mice. By comparing predator stress and social defeat models, we observed that the former elicited a higher level of behavioral despair and the latter elicited more robust social avoidance. Furthermore, the use of machine learning (ML)-based spontaneous behavioral classification can distinguish mice subjected to one type of stress from another, and from non-stressed mice. We show that related patterns of spontaneous behaviors correspond to depression status as measured by canonical depression-like behaviors, which illustrates that depression-like symptoms can be predicted by ML-classified behavior patterns. Overall, our study confirms that the predator stress induced phenotype in mice is a good reflection of several important aspects of depression in humans and illustrates that ML-supported analysis can simultaneously evaluate multiple behavioral alterations in different animal models of depression, providing a more unbiased and holistic approach for the study of neuropsychiatric disorders.

A leaky integrate-and-fire computational model based on the connectome of the entire adult Drosophila brain reveals insights into sensorimotor processing

The forthcoming assembly of the adult Drosophila melanogaster central brain connectome, containing over 125,000 neurons and 50 million synaptic connections, provides a template for examining sensory processing throughout the brain. Here, we create a leaky integrate-and-fire computational model of the entire Drosophila brain, based on neural connectivity and neurotransmitter identity, to study circuit properties of feeding and grooming behaviors. We show that activation of sugar-sensing or water-sensing gustatory neurons in the computational model accurately predicts neurons that respond to tastes and are required for feeding initiation. Computational activation of neurons in the feeding region of the Drosophila brain predicts those that elicit motor neuron firing, a testable hypothesis that we validate by optogenetic activation and behavioral studies. Moreover, computational activation of different classes of gustatory neurons makes accurate predictions of how multiple taste modalities interact, providing circuit-level insight into aversive and appetitive taste processing. Our computational model predicts that the sugar and water pathways form a partially shared appetitive feeding initiation pathway, which our calcium imaging and behavioral experiments confirm. Additionally, we applied this model to mechanosensory circuits and found that computational activation of mechanosensory neurons predicts activation of a small set of neurons comprising the antennal grooming circuit that do not overlap with gustatory circuits, and accurately describes the circuit response upon activation of different mechanosensory subtypes. Our results demonstrate that modeling brain circuits purely from connectivity and predicted neurotransmitter identity generates experimentally testable hypotheses and can accurately describe complete sensorimotor transformations.

On the origin of appetite: GLWamide in jellyfish represents an ancestral satiety neuropeptide

Food intake is regulated by internal state. This function is mediated by hormones and neuropeptides, which are best characterized in popular model species. However, the evolutionary origins of such feeding-regulating neuropeptides are poorly understood. We used the jellyfish Cladonema to address this question. Our combined transcriptomic, behavioral, and anatomical approaches identified GLWamide as a feeding-suppressing peptide that selectively inhibits tentacle contraction in this jellyfish. In the fruit fly Drosophila, myoinhibitory peptide (MIP) is a related satiety peptide. Surprisingly, we found that GLWamide and MIP were fully interchangeable in these evolutionarily distant species for feeding suppression. Our results suggest that the satiety signaling systems of diverse animals share an ancient origin.

Negative energy balance hinders prosocial helping behavior

The internal state of an animal, including homeostatic requirements, modulates its behavior. Negative energy balance stimulates hunger, thus promoting a range of actions aimed at obtaining food. While these survival actions are well established, the influence of the energy status on prosocial behavior remains unexplored. We developed a paradigm to assess helping behavior in which a free mouse was faced with a conspecific trapped in a restrainer. We measured the willingness of the free mouse to liberate the confined mouse under diverse metabolic conditions. Around 42% of ad libitum-fed mice exhibited a helping behavior, as evidenced by the reduction in the latencies to release the trapped cagemate. This behavior was independent of subsequent social contact reward and was associated with changes in corticosterone indicative of emotional contagion. This decision-making process was coupled with reduced blood glucose excursions and higher Adenosine triphosphate (ATP):Adenosine diphosphate (ADP) ratios in the forebrain of helper mice, suggesting that it was a highly energy-demanding process. Interestingly, chronic (food restriction and type 2 diabetes) and acute (chemogenetic activation of hunger-promoting AgRP neurons) situations mimicking organismal negative energy balance and enhanced appetite attenuated helping behavior toward a distressed conspecific. To investigate similar effects in humans, we estimated the influence of glycated hemoglobin (a surrogate of long-term glycemic control) on prosocial behavior (namely charity donation) using the Understanding Society dataset. Our results evidenced that organismal energy status markedly influences helping behavior and that hypothalamic AgRP neurons are at the interface of metabolism and prosocial behavior.

A single neuron in C. elegans orchestrates multiple motor outputs through parallel modes of transmission

Animals generate a wide range of highly coordinated motor outputs, which allows them to execute purposeful behaviors. Individual neuron classes in the circuits that generate behavior have a remarkable capacity for flexibility, as they exhibit multiple axonal projections, transmitter systems, and modes of neural activity. How these multi-functional properties of neurons enable the generation of highly coordinated behaviors remains unknown. Here we show that the HSN neuron in C. elegans evokes multiple motor programs over different timescales to enable a suite of behavioral changes during egg-laying. Using HSN activity perturbations and in vivo calcium imaging, we show that HSN acutely increases egg-laying and locomotion while also biasing the animals towards low-speed dwelling behavior over longer timescales. The acute effects of HSN on egg-laying and high-speed locomotion are mediated by separate sets of HSN transmitters and different HSN axonal projections. The long-lasting effects on dwelling are mediated by HSN release of serotonin that is taken up and re-released by NSM, another serotonergic neuron class that directly evokes dwelling. Our results show how the multi-functional properties of a single neuron allow it to induce a coordinated suite of behaviors and also reveal for the first time that neurons can borrow serotonin from one another to control behavior.

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.

Serotonin has an eye for detail

In this issue of Neuron, Reggiani et al.¹ show that serotonin and arousal suppress retinal inputs to the thalamus with opposing feature sensitivity, providing an elegant means for neuromodulation to selectively filter early visual processing.

From perception to behavior: The neural circuits underlying prey hunting in larval zebrafish

A key challenge for neural systems is to extract relevant information from the environment and make appropriate behavioral responses. The larval zebrafish offers an exciting opportunity for studying these sensing processes and sensory-motor transformations. Prey hunting is an instinctual behavior of zebrafish that requires the brain to extract and combine different attributes of the sensory input and form appropriate motor outputs. Due to its small size and transparency the larval zebrafish brain allows optical recording of whole-brain activity to reveal the neural mechanisms involved in prey hunting and capture. In this review we discuss how the larval zebrafish brain processes visual information to identify and locate prey, the neural circuits governing the generation of motor commands in response to prey, how hunting behavior can be modulated by internal states and experience, and some outstanding questions for the field.