Internal State
internal state
Brain-Wide Compositionality and Learning Dynamics in Biological Agents
Biological agents continually reconcile the internal states of their brain circuits with incoming sensory and environmental evidence to evaluate when and how to act. The brains of biological agents, including animals and humans, exploit many evolutionary innovations, chiefly modularity—observable at the level of anatomically-defined brain regions, cortical layers, and cell types among others—that can be repurposed in a compositional manner to endow the animal with a highly flexible behavioral repertoire. Accordingly, their behaviors show their own modularity, yet such behavioral modules seldom correspond directly to traditional notions of modularity in brains. It remains unclear how to link neural and behavioral modularity in a compositional manner. We propose a comprehensive framework—compositional modes—to identify overarching compositionality spanning specialized submodules, such as brain regions. Our framework directly links the behavioral repertoire with distributed patterns of population activity, brain-wide, at multiple concurrent spatial and temporal scales. Using whole-brain recordings of zebrafish brains, we introduce an unsupervised pipeline based on neural network models, constrained by biological data, to reveal highly conserved compositional modes across individuals despite the naturalistic (spontaneous or task-independent) nature of their behaviors. These modes provided a scaffolding for other modes that account for the idiosyncratic behavior of each fish. We then demonstrate experimentally that compositional modes can be manipulated in a consistent manner by behavioral and pharmacological perturbations. Our results demonstrate that even natural behavior in different individuals can be decomposed and understood using a relatively small number of neurobehavioral modules—the compositional modes—and elucidate a compositional neural basis of behavior. This approach aligns with recent progress in understanding how reasoning capabilities and internal representational structures develop over the course of learning or training, offering insights into the modularity and flexibility in artificial and biological agents.
Neural mechanisms governing the learning and execution of avoidance behavior
The nervous system orchestrates adaptive behaviors by intricately coordinating responses to internal cues and environmental stimuli. This involves integrating sensory input, managing competing motivational states, and drawing on past experiences to anticipate future outcomes. While traditional models attribute this complexity to interactions between the mesocorticolimbic system and hypothalamic centers, the specific nodes of integration have remained elusive. Recent research, including our own, sheds light on the midline thalamus's overlooked role in this process. We propose that the midline thalamus integrates internal states with memory and emotional signals to guide adaptive behaviors. Our investigations into midline thalamic neuronal circuits have provided crucial insights into the neural mechanisms behind flexibility and adaptability. Understanding these processes is essential for deciphering human behavior and conditions marked by impaired motivation and emotional processing. Our research aims to contribute to this understanding, paving the way for targeted interventions and therapies to address such impairments.
Feedback control in the nervous system: from cells and circuits to behaviour
The nervous system is fundamentally a closed loop control device: the output of actions continually influences the internal state and subsequent actions. This is true at the single cell and even the molecular level, where “actions” take the form of signals that are fed back to achieve a variety of functions, including homeostasis, excitability and various kinds of multistability that allow switching and storage of memory. It is also true at the behavioural level, where an animal’s motor actions directly influence sensory input on short timescales, and higher level information about goals and intended actions are continually updated on the basis of current and past actions. Studying the brain in a closed loop setting requires a multidisciplinary approach, leveraging engineering and theory as well as advances in measuring and manipulating the nervous system. I will describe our recent attempts to achieve this fusion of approaches at multiple levels in the nervous system, from synaptic signalling to closed loop brain machine interfaces.
Inter-tissue signals modify food-seeking behavior in C. elegans
Animals modify their behavioral outputs in response to changes in external and internal environments. We use the nematode, C. elegans to probe the pathways linking changes in internal states like hunger with behavior. We find that acute food deprivation alters the localization of two transcription factors, likely releasing an insulin-like peptide from the intestine, which in turn modifies chemosensory neurons and alters behavior. These results present a model for how inter-tissue signals to generate flexible behaviors via gut-brain signaling.
Unchanging and changing: hardwired taste circuits and their top-down control
The taste system detects 5 major categories of ethologically relevant stimuli (sweet, bitter, umami, sour and salt) and accordingly elicits acceptance or avoidance responses. While these taste responses are innate, the taste system retains a remarkable flexibility in response to changing external and internal contexts. Taste chemicals are first recognized by dedicated taste receptor cells (TRCs) and then transmitted to the cortex via a multi-station relay. I reasoned that if I could identify taste neural substrates along this pathway, it would provide an entry to decipher how taste signals are encoded to drive innate response and modulated to facilitate adaptive response. Given the innate nature of taste responses, these neural substrates should be genetically identifiable. I therefore exploited single-cell RNA sequencing to isolate molecular markers defining taste qualities in the taste ganglion and the nucleus of the solitary tract (NST) in the brainstem, the two stations transmitting taste signals from TRCs to the brain. How taste information propagates from the ganglion to the brain is highly debated (i.e., does taste information travel in labeled-lines?). Leveraging these genetic handles, I demonstrated one-to-one correspondence between ganglion and NST neurons coding for the same taste. Importantly, inactivating one ‘line’ did not affect responses to any other taste stimuli. These results clearly showed that taste information is transmitted to the brain via labeled lines. But are these labeled lines aptly adapted to the internal state and external environment? I studied the modulation of taste signals by conflicting taste qualities in the concurrence of sweet and bitter to understand how adaptive taste responses emerge from hardwired taste circuits. Using functional imaging, anatomical tracing and circuit mapping, I found that bitter signals suppress sweet signals in the NST via top-down modulation by taste cortex and amygdala of NST taste signals. While the bitter cortical field provides direct feedback onto the NST to amplify incoming bitter signals, it exerts negative feedback via amygdala onto the incoming sweet signal in the NST. By manipulating this feedback circuit, I showed that this top-down control is functionally required for bitter evoked suppression of sweet taste. These results illustrate how the taste system uses dedicated feedback lines to finely regulate innate behavioral responses and may have implications for the context-dependent modulation of hardwired circuits in general.
Synergy of color and motion vision for detecting approaching objects in Drosophila
I am working on color vision in Drosophila, identifying behaviors that involve color vision and understanding the neural circuits supporting them (Longden 2016). I have a long-term interest in understanding how neural computations operate reliably under changing circumstances, be they external changes in the sensory context, or internal changes of state such as hunger and locomotion. On internal state-modulation of sensory processing, I have shown how hunger alters visual motion processing in blowflies (Longden et al. 2014), and identified a role for octopamine in modulating motion vision during locomotion (Longden and Krapp 2009, 2010). On responses to external cues, I have shown how one kind of uncertainty in the motion of the visual scene is resolved by the fly (Saleem, Longden et al. 2012), and I have identified novel cells for processing translation-induced optic flow (Longden et al. 2017). I like working with colleagues who use different model systems, to get at principles of neural operation that might apply in many species (Ding et al. 2016, Dyakova et al. 2015). I like work motivated by computational principles - my background is computational neuroscience, with a PhD on models of memory formation in the hippocampus (Longden and Willshaw, 2007).
NMC4 Keynote:
The brain represents the external world through the bottleneck of sensory organs. The network of hierarchically organized neurons is thought to recover the causes of sensory inputs to reconstruct the reality in the brain in idiosyncratic ways depending on individuals and their internal states. How can we understand the world model represented in an individual’s brain, or the neuroverse? My lab has been working on brain decoding of visual perception and subjective experiences such as imagery and dreaming using machine learning and deep neural network representations. In this talk, I will outline the progress of brain decoding methods and present how subjective experiences are externalized as images and how they could be shared across individuals via neural code conversion. The prospects of these approaches in basic science and neurotechnology will be discussed.
Toward Naturalistic Paradigms of Agency
Voluntary control of behavior requires the ability to dynamically integrate internal states and external evidence to achieve one’s goals. However, neuroscientific studies of intentional action and critical philosophical commentary of that research have taken a rather narrow turn in recent years, focussing on the neural precursors of spontaneous simple actions as potential realizers of intentions. In this session, we show how the debate can benefit from incorporating other types of experimental approaches, focussing on agency in dynamic contexts.
A brain circuit for curiosity
Motivational drives are internal states that can be different even in similar interactions with external stimuli. Curiosity as the motivational drive for novelty-seeking and investigating the surrounding environment is for survival as essential and intrinsic as hunger. Curiosity, hunger, and appetitive aggression drive three different goal-directed behaviors—novelty seeking, food eating, and hunting— but these behaviors are composed of similar actions in animals. This similarity of actions has made it challenging to study novelty seeking and distinguish it from eating and hunting in nonarticulating animals. The brain mechanisms underlying this basic survival drive, curiosity, and novelty-seeking behavior have remained unclear. In spite of having well-developed techniques to study mouse brain circuits, there are many controversial and different results in the field of motivational behavior. This has left the functions of motivational brain regions such as the zona incerta (ZI) still uncertain. Not having a transparent, nonreinforced, and easily replicable paradigm is one of the main causes of this uncertainty. Therefore, we chose a simple solution to conduct our research: giving the mouse freedom to choose what it wants—double freeaccess choice. By examining mice in an experimental battery of object free-access double-choice (FADC) and social interaction tests—using optogenetics, chemogenetics, calcium fiber photometry, multichannel recording electrophysiology, and multicolor mRNA in situ hybridization—we uncovered a cell type–specific cortico-subcortical brain circuit of the curiosity and novelty-seeking behavior. We found in mice that inhibitory neurons in the medial ZI (ZIm) are essential for the decision to investigate an object or a conspecific. These neurons receive excitatory input from the prelimbic cortex to signal the initiation of exploration. This signal is modulated in the ZIm by the level of investigatory motivation. Increased activity in the ZIm instigates deep investigative action by inhibiting the periaqueductal gray region. A subpopulation of inhibitory ZIm neurons expressing tachykinin 1 (TAC1) modulates the investigatory behavior.
Measuring behavior to measure the brain
Animals produce behavior by responding to a mixture of cues that arise both externally (sensory) and internally (neural dynamics and states). These cues are continuously produced and can be combined in different ways depending on the needs of the animal. However, the integration of these external and internal cues remains difficult to understand in natural behaviors. To address this gap, we have developed an unsupervised method to identify internal states from behavioral data, and have applied it to the study of a dynamic social interaction. During courtship, Drosophila melanogaster males pattern their songs using cues from their partner. This sensory-driven behavior dynamically modulates courtship directed at their partner. We use our unsupervised method to identify how the animal integrates sensory information into distinct underlying states. We then use this to identify the role of courtship neurons in either integrating incoming information or directing the production of the song, roles that were previously hidden. Our results reveal how animals compose behavior from previously unidentified internal states, a necessary step for quantitative descriptions of animal behavior that link environmental cues, internal needs, neuronal activity, and motor outputs.
A Changing View of Vision: From Molecules to Behavior in Zebrafish
All sensory perception and every coordinated movement, as well as feelings, memories and motivation, arise from the bustling activity of many millions of interconnected cells in the brain. The ultimate function of this elaborate network is to generate behavior. We use zebrafish as our experimental model, employing a diverse array of molecular, genetic, optical, connectomic, behavioral and computational approaches. The goal of our research is to understand how neuronal circuits integrate sensory inputs and internal state and convert this information into behavioral responses.
Hypothalamic control of internal states underlying social behaviors in mice
Social interactions such as mating and fighting are driven by internal emotional states. How can we study internal states of an animal when it cannot tell us its subjective feelings? Especially when the meaning of the animal’s behavior is not clear to us, can we understand the underlying internal states of the animal? In this talk, I will introduce our recent work in which we used male mounting behavior in mice as an example to understand the underlying internal state of the animals. In many animal species, males exhibit mounting behavior toward females as part of the mating behavior repertoire. Interestingly, males also frequently show mounting behavior toward other males of the same species. It is not clear what the underlying motivation is - whether it is reproductive in nature or something distinct. Through detailed analysis of video and audio recordings during social interactions, we found that while male-directed and female-directed mounting behaviors are motorically similar, they can be distinguished by both the presence of ultrasonic vocalization during female-directed mounting (reproductive mounting) and the display of aggression following male-directed mounting (aggressive mounting). Using optogenetics, we further identified genetically defined neural populations in the medial preoptic area (MPOA) that mediate reproductive mounting and the ventrolateral ventromedial hypothalamus (VMHvl) that mediate aggressive mounting. In vivo microendocsopic imaging in MPOA and VMHvl revealed distinct neural ensembles that mainly encode either a reproductive or an aggressive state during which male or female directed mounting occurs. Together, these findings demonstrate that internal states are represented in the hypothalamus and that motorically similar behaviors exhibited under different contexts may reflect distinct internal states.
Food for Thought: How internal states shape foraging behavior
Fish Feelings: Emotional states in larval zebrafish
I’ll give an overview of internal - or motivational - states in larval zebrafish. Specifically we will focus on the role of the Oxytocin system in regulating the detection of, and behavioral responses to, conspecifics. The appeal here is that Oxytocin has likely conserved roles across all vertebrates, including humans, and that the larval zebrafish allows us to study some of the general principles across the brain but nonetheless at cellular resolution. This allows us to propose mechanistic models of emotional states.
Conflict or complement: Parallel memories control behaviour in Drosophila
Drosophila can learn to associate odours with reward or punishment and the resulting memories direct odour-specific approach or avoidance behaviours. Recent progress has revealed a straightforward model for learning in which reinforcing dopaminergic neurons assign valence to odour representations in the neural ensemble of the mushroom bodies. Dopamine directed synaptic depression alters the route of odour-driven activity through the mushroom body output network. This circuit configuration and influence of internal state guide the expression of appropriate behaviour. Importantly, learned behaviour is flexible and can be updated as the fly accumulates additional experience. Our latest studies demonstrate that well-informed behaviour is guided by combining parallel conflicting and complementary memories of opposite valence.
Arousal modulates retinal output
Neural responses in the visual system are usually not purely visual but depend on behavioural and internal states such as arousal. This dependence is seen both in primary visual cortex (V1) and in subcortical brain structures receiving direct retinal input. In this talk, I will show that modulation by behavioural state arises as early as in the output of the retina.To measure retinal activity in the awake, intact brain, we imaged the synaptic boutons of retinal axons in the superficial superior colliculus (sSC) of mice. The activity of about half of the boutons depended not only on vision but also on running speed and pupil size, regardless of retinal illumination. Arousal typically reduced the boutons’ visual responses to preferred direction and their selectivity for direction and orientation.Arousal may affect activity in retinal boutons by presynaptic neuromodulation. To test whether the effects of arousal occur already in the retina, we recorded from retinal axons in the optic tract. We found that, in darkness, more than one third of the recorded axons was significantly correlated with running speed. Arousal had similar effects postsynaptically, in sSC neurons, independent of activity in V1, the other main source of visual inputs to colliculus. Optogenetic inactivation of V1 generally decreased activity in collicular neurons but did not diminish the effects of arousal. These results indicate that arousal modulates activity at every stage of the visual system. In the future, we will study the purpose and the underlying mechanisms of behavioural modulation in the early visual system
Light-bacteria interactions
In 1676, using candle light and a small glass sphere as the lens, van Leeuwenhoek discovered the microscopic world of living microorganisms. Today, using lasers, spatial light modulators, digital cameras and computers, we study the statistical and fluid mechanics of microswimmers in ways that were unimaginable only 50 years ago. With light we can image swimming bacteria in 3D, apply controllable force fields or sculpt their 3D environment. In addition to shaping the physical world outside cells we can use light to control the internal state of genetically modified bacteria. I will review our recent work with light-bacteria interactions, going from some fundamental problems in the fluid and statistical mechanics of microswimmers to the use of bacteria as propellers for micro-machines or as a "living" paint controlled by light.
Safety in numbers: how animals use motion of others as threat or safety cues
Our work concerns the general problem of adaptive behaviour in response to predatory threats, and of the neural mechanisms underlying a choice between strategies. When faced with a threat, an animal must decide whether to freeze, reducing its chances of being noticed, or to flee to the safety of a refuge. Animals from fish to primates choose between these two alternatives when confronted by an attacking predator, a choice that largely depends on the context in which the threat occurs. Recent work has made strides identifying the pre-motor circuits, and their inputs, which control freezing behaviour in rodents, but how contextual information is integrated to guide this choice is still far from understood. The social environment is a potent contextual modulator of defensive behaviours of animals in a group. Indeed, anti-predation strategies are believed to be a major driving force for the evolution of sociality. We recently found that fruit flies in response to visual looming stimuli, simulating a large object on collision course, make rapid freeze/flee choices accompanied by lasting changes in the fly’s internal state, reflected in altered cardiac activity. In this talk, I will discuss our work on how flies process contextual cues, focusing on the social environment, to guide their behavioural response to a threat. We have identified a social safety cue, resumption of activity, and visual projection neurons involved in processing this cue. Given the knowledge regarding sensory detection of looming threats and descending neuron involved in the expression of freezing, we are now in a unique position to understand how information about a threat is integrated with cues from the social environment to guide the choice of whether to freeze.
Leveraging olfaction to understand how the brain and the body generate social behavior
Courtship behavior is an innate model for many types of brain computations including sensory detection, learning and memory, and internal state modulation. Despite the robustness of the behavior, we have little understanding of the underlying neural circuits and mechanisms. The Stowers’ lab is leveraging the ability of specialized olfactory cues, pheromones, to specifically activate and therefore identify and study courtship circuits in the mouse. We are interested in identifying general circuit principles (specific brain nodes and information flow) that are common to all individuals, in order to additionally study how experience, gender, age, and internal state modulate and personalize behavior. We are solving two parallel sensory to motor courtship circuits, that promote social vocal calling and scent marking, to study information processing of behavior as a complete unit instead of restricting focus to a single brain region. We expect comparing and contrasting the coding logic of two courtship motor behaviors will begin to shed light on general principles of how the brain senses context, weighs experience and responds to internal state to ultimately decide appropriate action.
Untangling the web of behaviours used to produce spider orb webs
Many innate behaviours are the result of multiple sensorimotor programs that are dynamically coordinated to produce higher-order behaviours such as courtship or architecture construction. Extendend phenotypes such as architecture are especially useful for ethological study because the structure itself is a physical record of behavioural intent. A particularly elegant and easily quantifiable structure is the spider orb-web. The geometric symmetry and regularity of these webs have long generated interest in their behavioural origin. However, quantitative analyses of this behaviour have been sparse due to the difficulty of recording web-making in real-time. To address this, we have developed a novel assay enabling real-time, high-resolution tracking of limb movements and web structure produced by the hackled orb-weaver Uloborus diversus. With its small brain size of approximately 100,000 neurons, the spider U. diversus offers a tractable model organism for the study of complex behaviours. Using deep learning frameworks for limb tracking, and unsupervised behavioural clustering methods, we have developed an atlas of stereotyped movement motifs and are investigating the behavioural state transitions of which the geometry of the web is an emergent property. In addition to tracking limb movements, we have developed algorithms to track the web’s dynamic graph structure. We aim to model the relationship between the spider’s sensory experience on the web and its motor decisions, thereby identifying the sensory and internal states contributing to this sensorimotor transformation. Parallel efforts in our group are establishing 2-photon in vivo calcium imaging protocols in this spider, eventually facilitating a search for neural correlates underlying the internal and sensory state variables identified by our behavioural models. In addition, we have assembled a genome, and are developing genetic perturbation methods to investigate the genetic underpinnings of orb-weaving behaviour. Together, we aim to understand how complex innate behaviours are coordinated by underlying neuronal and genetic mechanisms.
Integration of infant sensory cues and internal states for maternal motivated behaviors
COSYNE 2022
Integration of infant sensory cues and internal states for maternal motivated behaviors
COSYNE 2022
How internal states shape sensorimotor mapping in zebrafish larvae
COSYNE 2025
Visual loom features drive shifts in behavioral choices and internal states in larval zebrafish
FENS Forum 2024