two-color-multifiber-photometry-recordings-social-behavior-network

Two-color Multifiber Photometry Recordings of the Social Behavior Network in Mice

Fiber photometry, the bulk recording of signals through a fiber optic cable, is a useful method for recording calcium activity from groups of neurons in ...

Princeton University

Although the ventromedial hypothalamus ventrolateral area (VMHvl) is now well established as a critical locus for the generation of conspecific aggression, its role is complex, with neurons responding during multiple phases of social interactions with both males and females. It has been previously unclear how the brain uses this complex multidimensional signal and coordinates a discrete action: the attack. Here, we find a hypothalamic-midbrain circuit that represents hierarchically organized social signals during aggression. Optogenetic-assisted circuit mapping reveals a preferential projection from VMHvl to lPAG cells, and inactivation of downstream lPAG populations results in aggression-specific deficits. lPAG neurons are selective for attack action and exhibit short-latency, time-locked spiking relative to the activity of jaw muscles during biting. Last, we find that this projection conveys male-biased signals from the VMHvl to downstream lPAG neurons that are sensitive to features of ongoing activity, suggesting that action selectivity is generated by a combination of pre- and postsynaptic mechanisms.

Hierarchical Representations of Aggression in a Hypothalamic-Midbrain Circuit.

Balancing anxiety and social desire.

Sex differences are commonly observed in behaviors that are closely linked to adaptive function, but sex differences can also be observed in behavioral "building blocks" such as locomotor activity and reward processing. Modern neuroscientific inquiry, in pursuit of generalizable principles of functioning across sexes, has often ignored these more subtle sex differences in behavioral building blocks that may result from differences in these behavioral building blocks. A frequent assumption is that there is a default (often male) way to perform a behavior. This approach misses fundamental drivers of individual variability within and between sexes. Incomplete behavioral descriptions of both sexes can lead to an overreliance on reduced "single-variable" readouts of complex behaviors, the design of which may be based on male-biased samples. Here, we advocate that the incorporation of new machine-learning tools for collecting and analyzing multimodal "big behavior" data allows for a more holistic and richer approach to the quantification of behavior in both sexes. These new tools make behavioral description more robust and replicable across laboratories and species, and may open up new lines of neuroscientific inquiry by facilitating the discovery of novel behavioral states. Having more accurate measures of behavioral diversity in males and females could serve as a hypothesis generator for where and when we should look in the brain for meaningful neural differences.

Quantifying Sex Differences in Behavior in the Era of "Big" Data.

While aggression is often conceptualized as a highly stereotyped, innate behavior, individuals within a species exhibit a surprising amount of variability in the frequency, intensity, and targets of their aggression. While differences in genetics are a source of some of this variation across individuals (estimates place the heritability of behavior at around 25-30%), a critical driver of variability is previous life experience. A wide variety of social experiences, including sexual, parental, and housing experiences can facilitate "persistent" aggressive states, suggesting that these experiences engage a common set of synaptic and molecular mechanisms that act on dedicated neural circuits for aggression. It has long been known that sex steroid hormones are powerful modulators of behavior, and also, that levels of these hormones are themselves modulated by experience. Several recent studies have started to unravel how experience-dependent hormonal changes during adulthood can create a cascade of molecular, synaptic, and circuit changes that enable behavioral persistence through circuit level remodeling. Here, we propose that sex steroid hormones facilitate persistent aggressive states by changing the relationship between neural activity and an aggression "threshold".

Neural mechanisms of persistent aggression.

The desire to understand how the brain generates and patterns behavior has driven rapid methodological innovation in tools to quantify natural animal behavior. While advances in deep learning and computer vision have enabled markerless pose estimation in individual animals, extending these to multiple animals presents unique challenges for studies of social behaviors or animals in their natural environments. Here we present Social LEAP Estimates Animal Poses (SLEAP), a machine learning system for multi-animal pose tracking. This system enables versatile workflows for data labeling, model training and inference on previously unseen data. SLEAP features an accessible graphical user interface, a standardized data model, a reproducible configuration system, over 30 model architectures, two approaches to part grouping and two approaches to identity tracking. We applied SLEAP to seven datasets across flies, bees, mice and gerbils to systematically evaluate each approach and architecture, and we compare it with other existing approaches. SLEAP achieves greater accuracy and speeds of more than 800 frames per second, with latencies of less than 3.5 ms at full 1,024 × 1,024 image resolution. This makes SLEAP usable for real-time applications, which we demonstrate by controlling the behavior of one animal on the basis of the tracking and detection of social interactions with another animal.

SLEAP: A deep learning system for multi-animal pose tracking.

Publisher Correction: SLEAP: A deep learning system for multi-animal pose tracking.

Chronic stress can have lasting adverse consequences in some individuals, yet others are resilient to the same stressor. Susceptible and resilient individuals exhibit differences in the intrinsic properties of mesolimbic dopamine (DA) neurons after the stressful experience is over. However, the causal links between DA, behaviour during stress and individual differences in resilience are unknown. Here we recorded behaviour in mice simultaneously with DA neuron activity in projections to the nucleus accumbens (NAc) (which signals reward) and the tail striatum (TS) (which signals threat) during social defeat. Supervised and unsupervised behavioural quantification revealed that during stress, resilient and susceptible mice use different behavioural strategies and have distinct activity patterns in DA terminals in the NAc (but not the TS). Neurally, resilient mice have greater activity near the aggressor, including at the onset of fighting back. Conversely, susceptible mice have greater activity at the offset of attacks and onset of fleeing. We also performed optogenetic stimulation of NAc-projecting DA neurons in open loop (randomly timed) during defeat or timed to specific behaviours using real-time behavioural classification. Both open-loop and fighting-back-timed activation promoted resilience and reorganized behaviour during defeat towards resilience-associated patterns. Together, these data provide a link between DA neural activity, resilience and resilience-associated behaviour during the experience of stress.

Behavioural and dopaminergic signatures of resilience.

Animals learn the value of foods based on their postingestive effects and thereby develop aversions to foods that are toxic and preferences to those that are nutritious. However, it remains unclear how the brain is able to assign credit to flavors experienced during a meal with postingestive feedback signals that can arise after a substantial delay. Here, we reveal an unexpected role for postingestive reactivation of neural flavor representations in this temporal credit assignment process. To begin, we leverage the fact that mice learn to associate novel, but not familiar, flavors with delayed gastric malaise signals to investigate how the brain represents flavors that support aversive postingestive learning. Surveying cellular resolution brainwide activation patterns reveals that a network of amygdala regions is unique in being preferentially activated by novel flavors across every stage of the learning process: the initial meal, delayed malaise, and memory retrieval. By combining high-density recordings in the amygdala with optogenetic stimulation of genetically defined hindbrain malaise cells, we find that postingestive malaise signals potently and specifically reactivate amygdalar novel flavor representations from a recent meal. The degree of malaise-driven reactivation of individual neurons predicts strengthening of flavor responses upon memory retrieval, leading to stabilization of the population-level representation of the recently consumed flavor. In contrast, meals without postingestive consequences degrade neural flavor representations as flavors become familiar and safe. Thus, our findings demonstrate that interoceptive reactivation of amygdalar flavor representations provides a neural mechanism to resolve the temporal credit assignment problem inherent to postingestive learning.

A neural mechanism for learning from delayed postingestive feedback.

Social behaviors often consist of a motivational phase followed by action. Here we show that neurons in the ventromedial hypothalamus ventrolateral area (VMHvl) of mice encode the temporal sequence of aggressive motivation to action. The VMHvl receives local inhibitory input (VMHvl shell) and long-range input from the medial preoptic area (MPO) with functional coupling to neurons with specific temporal profiles. Encoding models reveal that during aggression, VMHvl shell activity peaks at the start of an attack, whereas activity from the MPO-VMHvl input peaks at specific interaction endpoints. Activation of the MPO-VMHvl input promotes and prolongs a low motivation state, whereas activation of VMHvl shell results in action-related deficits, acutely terminating attack. Moreover, stimulation of MPO-VMHvl input is positively valenced and anxiolytic. Together, these data demonstrate how distinct inhibitory inputs to the hypothalamus can independently gate the motivational and action phases of aggression through a single locus of control.

Independent inhibitory control mechanisms for aggressive motivation and action.

Some individuals are susceptible to chronic stress, and others are more resilient. While many brain regions implicated in learning are dysregulated after stress, little is known about whether and how neural teaching signals during stress differ between susceptible and resilient individuals. Here, we seek to determine if activity in the lateral habenula (LHb), which encodes a negative teaching signal, differs between susceptible and resilient mice during stress to produce different outcomes. After (but not before) chronic social defeat stress, the LHb is active when susceptible mice are in proximity of the aggressor strain. During stress, activity is higher in susceptible mice during aggressor interactions, and activation biases mice toward susceptibility. This manipulation generates a persistent and widespread increase in the balance of subcortical vs. cortical activity in susceptible mice. Taken together, our results indicate that heightened activity in the LHb during stress produces lasting brainwide and behavioral substrates of susceptibility.

Heightened lateral habenula activity during stress produces brainwide and behavioral substrates of susceptibility.

The ability to observe the social behavior of others and use observed information to bias future action is a fundamental building block of social cognition. A foundational question is whether social observation and experience engage common circuit mechanisms that enable behavioral change. While classic studies on social learning have shown that aggressive behaviors can be learned through observation, it remains unclear whether aggression observation promotes persistent neural changes that generalize to new contexts. Here, to directly compare the effects of aggression experience and observation at brain-wide scale, we develop a strategy to perform large-scale cell-type specific recordings across subcortical networks for social behavior control and learning. We record longitudinally while animals "train" through direct experience or observation, then probe shared differences in behavior and neural activity in a novel "hard" aggression context. Using supervised and unsupervised methods for behavioral quantification, we detect unique signatures of a shared behavioral strategy not present in animals with no training. During observation, we find widespread activation that mimics experience in networks for behavior generation, with critical differences in signals associated with reward and threat learning. After observation, we observe that changes persist into the novel aggression context, with increased similarity in the neural dynamics between experience and observation groups. Network-level modeling reveals persistent shared changes to a core aggression network, with widespread decoupling of inhibition from a key hypothalamic output region. This demonstrates that "experience-like" activity during observation can recruit a shared plasticity mechanism that biases behavior toward adaptive defensive strategies in new contexts.

Aggression experience and observation promote shared behavioral and neural changes.

Animals learn the value of foods on the basis of their postingestive effects and thereby develop aversions to foods that are toxic and preferences to those that are nutritious. However, it remains unclear how the brain is able to assign credit to flavours experienced during a meal with postingestive feedback signals that can arise after a substantial delay. Here we reveal an unexpected role for the postingestive reactivation of neural flavour representations in this temporal credit-assignment process. To begin, we leverage the fact that mice learn to associate novel, but not familiar, flavours with delayed gastrointestinal malaise signals to investigate how the brain represents flavours that support aversive postingestive learning. Analyses of brain-wide activation patterns reveal that a network of amygdala regions is unique in being preferentially activated by novel flavours across every stage of learning (consumption, delayed malaise and memory retrieval). By combining high-density recordings in the amygdala with optogenetic stimulation of malaise-coding hindbrain neurons, we show that delayed malaise signals selectively reactivate flavour representations in the amygdala from a recent meal. The degree of malaise-driven reactivation of individual neurons predicts the strengthening of flavour responses upon memory retrieval, which in turn leads to stabilization of the population-level representation of the recently consumed flavour. By contrast, flavour representations in the amygdala degrade in the absence of unexpected postingestive consequences. Thus, we demonstrate that postingestive reactivation and plasticity of neural flavour representations may support learning from delayed feedback.

Gonadal sex steroid hormones regulate internal states, social drive, perception of external cues, and learning and memory. Fluctuating hormones influence mood and emotional states, enabling flexibility in instinctive behaviors and cognitive decisions. Conversely, elevated hormone levels help sustain emotional states and behavioral choices, ensuring the precise execution of costly social behaviors within optimal time windows to maximize reproductive success. While decades of work have shed light on the cellular and molecular mechanisms by which sex hormones alter neural excitability and circuit architecture, recent work has begun to tie many of these changes to principles of computation using the tools of systems neuroscience. Here, we will outline the mechanisms by which sex steroid hormones alter neural functioning at the molecular and cellular level and highlight recent work that points towards changes in specific computational functions, including the generation and maintenance of neural and behavioral persistence.

Hormonal regulation of behavioral and emotional persistence: Novel insights from a systems-level approach to neuroendocrinology.

In naturalistic conditions, animals must routinely make ongoing self-motivated choices about whether to initiate interactions with same or opposite-sex partners and whether to re-initiate social contact when interactions have ended. However, it remains unclear what governs these choices, and whether they are motivated by drive states that exhibit signatures of moment-to-moment social satiety when these interactions have ended. Here, to explicitly test this at the behavioral level, we designed a novel fully-automated two-choice social operant paradigm where individuals can choose between same and opposite-sex social rewards and rewards are delivered for interaction with systematically varying durations. We trained cohorts of both sexes on this task and quantified the patterns of choices. We used choice latency as a metric to infer moment-to-moment satiety to test whether increased interaction duration leads to increased moment-to-moment satiety. We find that although both males and females have stable choice biases across sessions, with males showing consistent opposite sex biases, only males exhibit behavioral signatures of moment-to-moment social satiety and are sensitive to the duration of interaction. Using a simple normative model to capture patterns of social choice, we observe that behavior is better fit by a model that has a single evolving social drive and choice bias, rather than a model with multiple, independent drives for same and opposite-sex interactions. Together, our data reveal behavioral signatures of social satiety and offer new insights into the underlying homeostatic and motivational drives that govern social choices.

An automated two-choice social operant task for probing moment-to-moment changes in social satiety.

Deciding whether and when to engage in social interaction depends on external factors including the location of the interaction and the identity of the social partner (the social "context") as well as internal factors such as an individual's hormonal state. However, we lack a mechanistic understanding of how external and internal variables coordinate social action through networks of hormone-sensitive neurons. In particular, while gonadal hormones have long been suggested to coordinate territorial behaviors, direct evidence of how this coordination occurs has been lacking. To answer this, we combined large-scale neural recordings with large-scale unsupervised behavioral quantification to track neural activity longitudinally across a hormonal perturbation. We recorded neural population activity from neurons expressing the hormone receptor estrogen receptor alpha (ERɑ+) as well as from local ERɑ- neurons across the subcortical Social Behavior Network (SBN) and compared neural responses and behavior across social contexts with varied partners and territories. Using a comprehensive behavioral quantification strategy, we observe that patterns of social action and their underlying neural dynamics differentiate social partner and territory in both sexes. We find that each context has a unique behavioral action code, and that territory naturally rescales the partner-specific social action code in the hormonally intact state. However, when levels of circulating gonadal hormones are reduced, we observe that patterns of behavior during interactions in the home territory in males are disrupted, and that these changes can be rescued by testosterone replacement. Critically, hormonal perturbation disrupts territorial rescaling in a population-specific manner. Together, these data demonstrate how a loss of circulating hormones alters the relationship between social context and social action to disrupt context-specific social decision making.

Context rescales a social action code in a hormone-sensitive network.

Estrogens are inherently dynamic signaling molecules whose fluctuations induce profound shifts in physiology and behavior. However, methods for tracking the dynamics of estrogen action  are limited and not tissue-specific, making it difficult to directly relate dynamics to ongoing physiological, behavioral, and neural changes. Traditionally, estrogen sensitive cells have been identified by metrics such as receptor expression or radioactive ligand binding, but these measures do not capture the dynamic nature of hormone response. In addition, current methods for assessing the dynamics of estrogens in an individual, including microdialysis and vaginal cytology, lack temporal and spatial resolution. To address this need we developed a bifunctional reporter called neuro-seeER (neuronal see Estrogen Response) that can be used to track changes in exogenous and endogenous estrogen dynamics  and  including longitudinally in behaving animals. We confirmed that the fluorescent response requires estrogen receptor expression, is specific to activation with estradiol, and is consistent with the timescale of transcriptional induction. Neuro-seeER expression in the hypothalamus of Esr1-Cre mice revealed dynamic labeling of estrogen-responsive cells following treatment with exogenous estradiol, and fluorescence-aided cell sorting followed by RNA-sequencing confirmed that high neuro-seeER response is associated with enriched expression of genes associated with endogenous estrogen responses. Using a novel "snapshot" photometry method to track the dynamics longitudinally  we demonstrate that we can robustly detect exogenous estrogen response across multiple hypothalamic sites simultaneously. Finally, we demonstrate that this tool is uniquely suited to capturing endogenous estrogen response dynamics  across the long timescale of the estrous cycle, revealing individual differences in neural estrogen dynamics. Together, these findings reveal unexpected cellular and temporal heterogeneity of the transcriptional response and demonstrate the feasibility of tracking the dynamics of hormonal response alongside additional neural, cell signaling, or behavioral measures.

Article	Year
Hierarchical Representations of Aggression in a Hypothalamic-Midbrain Circuit. Neuron\| PubMed ID: 32164875	2020
Balancing anxiety and social desire. Nature neuroscience\| PubMed ID: 33674751	2021
Quantifying Sex Differences in Behavior in the Era of "Big" Data. Cold Spring Harbor perspectives in biology\| PubMed ID: 34607831	2022
Neural mechanisms of persistent aggression. Current opinion in neurobiology\| PubMed ID: 35344844	2022
SLEAP: A deep learning system for multi-animal pose tracking. Nature methods\| PubMed ID: 35379947	2022
Publisher Correction: SLEAP: A deep learning system for multi-animal pose tracking. Nature methods\| PubMed ID: 35468969	2022
Behavioural and dopaminergic signatures of resilience. Nature\| PubMed ID: 36261520	2022
A neural mechanism for learning from delayed postingestive feedback. bioRxiv : the preprint server for biology\| PubMed ID: 37873112	2024
Independent inhibitory control mechanisms for aggressive motivation and action. Nature neuroscience\| PubMed ID: 38347201	2024
Heightened lateral habenula activity during stress produces brainwide and behavioral substrates of susceptibility. Neuron\| PubMed ID: 39393349	2024
Aggression experience and observation promote shared behavioral and neural changes. bioRxiv : the preprint server for biology\| PubMed ID: 39763843	2024
A neural mechanism for learning from delayed postingestive feedback. Nature\| PubMed ID: 40175547	2025
Hormonal regulation of behavioral and emotional persistence: Novel insights from a systems-level approach to neuroendocrinology. Neurobiology of learning and memory\| PubMed ID: 40436262	2025
An automated two-choice social operant task for probing moment-to-moment changes in social satiety. bioRxiv : the preprint server for biology\| PubMed ID: 40791340	2025
Context rescales a social action code in a hormone-sensitive network. bioRxiv : the preprint server for biology\| PubMed ID: 41040254	2025
A bifunctional optical reporter for tracking estrogen response dynamics in neurons. bioRxiv : the preprint server for biology\| PubMed ID: 41427375	2025

Annegret L. Falkner

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