Biology subjects

Falkner, A. L.

Publications and source records attributed to Falkner, A. L..

9 recordsLinked to original sources

bioRxiv2026

Estrogen remodels large-scale cortical dynamics to promote behavioral persistence

Sex-steroid hormones remodel the brain on slow timescales of hours to days to coordinate adaptive behaviors with changing bodily physiology. Yet how this slow remodeling reorganizes and constrains neural computations that govern behavior on a moment-to-moment timescale remains poorly understood, particularly in cortical regions that support flexible social decision-making. Here we combined longitudinal high-density neural recordings, quantitative behavioral phenotyping and estrogen-receptor manipulation in female mice across low and high estrogen states. Tracking behavior and neural dynamics using this dense sampling approach revealed that high estrogen increased signatures of behavioral and neural persistence. High estrogen reversibly increased male-directed social preference and behavioral persistence, effects that were abolished by estrogen receptor alpha knockdown in the medial prefrontal cortex. In the mPFC high estrogen produced more persistent neural states that were more closely aligned with ongoing behavior, increased state discriminability, and compressed within-state dimensionality. At the single-neuron level, estrogen increased tuning selectivity, lengthened intrinsic timescales, and stabilized social representations across days, even within the same neurons tracked longitudinally. High estrogen also strengthened recurrent connectivity during the resting state, exhibiting preferential connectivity between similarly tuned ensembles. Finally, incorporating these connectivity changes into a mean-field dynamical-systems model was sufficient to reproduce increased behavioral and neural-state persistence. Together, these findings show that estrogen oscillates cortical computations across multi-day timescales, flipping the prefrontal cortex from flexible to persistent regimes that play a role in sustaining potentially costly social behaviors.

neuroscience↗

bioRxiv2025

A bifunctional optical reporter for tracking estrogen response dynamics in neurons

Estrogens are inherently dynamic signaling molecules whose fluctuations induce profound shifts in physiology and behavior. However, methods for tracking the dynamics of estrogen action in vivo 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 in vitro and in vivo, 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 in vivo, 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 in vivo 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.

neuroscience↗

bioRxiv2025

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

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 individuals 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 quantification1 to track neural activity longitudinally across a hormonal perturbation. We recorded neural population activity from neurons expressing the hormone receptor estrogen receptor alpha (ER+) as well as from local ER- 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.

neuroscience↗

bioRxiv2025

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

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.

neuroscience↗

bioRxiv2024

Aggression experience and observation promote shared behavioral and neural changes

The ability to observe the social behavior of others and use observed information to bias future action is a fundamental building block of social cognition1,2. 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 observation3, 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.

neuroscience↗

bioRxiv2023

A neural mechanism for learning from delayed postingestive feedback

Animals learn the value of foods based on their postingestive effects and thereby develop aversions to foods that are toxic1-6 and preferences to those that are nutritious7-14. 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 novel15-18, 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.

neuroscience↗

bioRxiv2022

Independent inhibitory control mechanisms for aggressive motivation and action

Social behaviors, like other motivated behaviors, frequently consist of a flexible motivated-seeking or approach phase followed by social action. Dysregulated social behavior may arise from changes to motivation, wherein individuals fail to enter a motivated seeking state, or may be in the execution of the social action itself. However, it is unclear how the brain generates and gates this flexible motivation-to-action sequence, and whether aggressive motivation and action are controlled by separate circuit mechanisms. Here, we record populations of neurons in the ventromedial hypothalamus ventrolateral area (VMHvl) of male mice at cellular resolution during "free" aggression and also during an aggression operant task, where the behaviors that precede attack are stereotyped. We find that this population encodes the temporal sequence of aggressive motivation to action and that the temporal selectivity of neurons is invariant to differences in motivated behavior. To test whether motivation and action could be independently regulated, we focused on two key inhibitory inputs to the VMHvl: a source of local inhibition (VMHvl shell) and the primary source of long-range inhibition (the medial preoptic area, MPO). While we find that the VMHvl receives broad monosynaptic inhibitory input from both inputs, optogenetic perturbation of these inputs during recording reveals temporal selectivity during aggressive motivation and action, suggesting specificity of function. Encoding models applied to population calcium recordings of these inhibitory inputs during naturalistic social interactions and during the social operant task further reveal that these inputs have different temporal dynamics during aggression: VMHvl shellvgat+ activity peaks at the start of aggressive interactions, while MPO-VMHvlvgat+ activity peaks at behaviorally aligned endpoints of aggressive interactions. Finally, using closed-loop optogenetic stimulation timed to specific phases of the aggression-operant task, we find a double-dissociation of the effects on aggressive motivation and action: activation of MPO-VMHvlvgat+, even briefly and temporally distant from the initiation of aggression, produces long-lasting motivational deficits, delaying the initiation of aggression and generating behaviors consistent with an unmotivated state. In contrast, activation of VMHvl shellvgat+ produces acute action-related deficits, causing an exit from an attack state. Fitting a Hidden Markov Model (HMM) to behavior further corroborates these findings by showing that MPO-VMHvlvgat+ stimulation prolongs a low motivation state and VMHvl shellvgat+ promotes exit from an attack state. Together, these data demonstrate how separable inhibitory circuits in the hypothalamus can independently gate the motivational and action phases of aggression through a single locus of control.

neuroscience↗

bioRxiv2020

SLEAP: Multi-animal pose tracking

The desire to understand how the brain generates and patterns behavior has driven rapid methodological innovation to quantify and model natural animal behavior. This has led to important advances in deep learning-based markerless pose estimation that have been enabled in part by the success of deep learning for computer vision applications. Here we present SLEAP (Social LEAP Estimates Animal Poses), a framework for multi-animal pose tracking via deep learning. This system is capable of simultaneously tracking any number of animals during social interactions and across a variety of experimental conditions. SLEAP implements several complementary approaches for dealing with the problems inherent in moving from single-to multi-animal pose tracking, including configurable neural network architectures, inference techniques, and tracking algorithms, enabling easy specialization and tuning for particular experimental conditions or performance requirements. We report results on multiple datasets of socially interacting animals (flies, bees, and mice) and describe how dataset-specific properties can be leveraged to determine the best configuration of SLEAP models. Using a high accuracy model (<2.8 px error on 95% of points), we were able to track two animals from full size 1024 x 1024 pixel frames at up to 320 FPS. The SLEAP framework comes with a sophisticated graphical user interface, multi-platform support, Colab-based GPU-free training and inference, and complete tutorials available, in addition to the datasets, at sleap.ai.

animal behavior and cognition↗

bioRxiv2019

PAG neurons encode a simplified action-selective signal during aggression

SummaryWhile 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 populations of neurons responding during the motivational, sensory, and action phases of aggression, and also during social interactions with the opposite sex. It has been previously unclear how the brain uses this complex multidimensional signal and generates a discrete action: the attack. Here we find that the largest posterior target of the VMHvl, the lateral periaqueductal gray (lPAG) encodes a simplified attack-selective signal during aggression. Single units in the lPAG exhibit greater selectivity for the attack action during aggression than VMHvl neurons and a subpopulation of neurons in the PAG exhibit short-latency, time-locked spiking relative to the activity of jaw muscles for biting during attack. In addition, channelrhodopsin assisted circuit mapping reveals a preferential projection from VMHvl glutamatergic cells to lPAG glutamatergic cells. Using projection-specific fiber photometry, we find that this excitatory projection conveys male-biased signals from the VMHvl to downstream glutamatergic PAG neurons that integrate ongoing male-related activity over several seconds, which suggests that action-selectivity is generated by a combination of both pre and postsynaptic filtering mechanisms.

neuroscience↗