Dissecting the role of the hippocampal-prefrontal circuit in anxiety

The ventral hippocampus (vHPC), medial prefrontal cortex (mPFC), and basolateral amygdala (BLA) are each required for the expression of anxiety-like behavior. Yet the role of each individual element of the circuit is unclear. The projection from the vHPC to the mPFC has been implicated in anxiety-related neural synchrony and spatial representations of aversion. The role of this projection was examined using multi-site neural recordings combined with optogenetic terminal inhibition. Inhibition of vHPC input to the mPFC disrupted anxiety and mPFC representations of aversion, and reduced theta synchrony in a pathway-, frequency- and task-specific manner. Moreover, bilateral, but not unilateral, inhibition altered physiological correlates of anxiety in the BLA, mimicking a safety-like state. These results reveal a specific role for the vHPC-mPFC projection in anxiety-related behavior and the spatial representation of aversive information within the mPFC. Moreover, these data suggested that theta-frequency input from the vHPC plays a causal role in anxiety-like behavior. Next, it was investigated whether optogenetic stimulation of the vHPC-mPFC at a theta frequency was sufficient to increase anxiety. Stimulating the vHPC input to the mPFC with a sinusoidal light pattern at 8 Hz significantly increased anxiety behavior. The anxiogenic effect of vHPC terminal stimulation was frequency- (8 Hz but not 20 Hz) and pattern- (sinusoids but not pulses) specific. To understand how pulses and sinusoidal light modulate mPFC neurons differentially, mPFC pyramidal neurons were recorded both in vitro and in vivo while stimulating vHPC terminals with the same sinusoidal or pulsatile patterns. In vitro, sinusoidal stimulation increased the rate of spontaneous EPSCs, while pulses evoked strong, stimulus-locked EPSCs. In vivo, sinusoidal stimulation of vHPC terminals increased the phase-locking of mPFC single unit spiking to the optical stimulation pattern without changing overall firing rates. Together, these results suggest that sinusoidal stimulation at 8 Hz enhances theta-frequency activity in mPFC neurons as well as anxiety-related behavior. Moreover, they suggest that theta-frequency components of neural activity play a privileged role in vHPC-mPFC communication and hippocampal-dependent forms of anxiety

AlphaTracker: a multi-animal tracking and behavioral analysis tool

Computer vision has emerged as a powerful tool to elevate behavioral research. This protocol describes a computer vision machine learning pipeline called AlphaTracker, which has minimal hardware requirements and produces reliable tracking of multiple unmarked animals, as well as behavioral clustering. AlphaTracker pairs a top-down pose-estimation software combined with unsupervised clustering to facilitate behavioral motif discovery that will accelerate behavioral research. All steps of the protocol are provided as open-source software with graphic user interfaces or implementable with command-line prompts. Users with a graphical processing unit (GPU) can model and analyze animal behaviors of interest in less than a day. AlphaTracker greatly facilitates the analysis of the mechanism of individual/social behavior and group dynamics

Nature

The ability to associate temporally segregated information and assign positive or negative valence to environmental cues is paramount for survival. Studies have shown that different basolateral amygdala (BLA) projections are potentiated following reward or punishment learning1–7. However, we do not yet understand how valence specific information is routed to the BLA neurons with the appropriate downstream projections. Nor do we understand how to reconcile the subsecond timescales of synaptic plasticity8–11 with the longer timescales separating the predictive cues from their outcomes. Here, we demonstrate that neurotensin (NT) neurons in the paraventricular nucleus of the thalamus (PVT) projecting to the BLA (PVT-BLA:NT) mediate valence assignment by exerting concentration-dependent modulation in BLA during associative learning. We found that optogenetic activation of the PVT-BLA:NT projection promotes reward learning, while PVT-BLA projection-specific Nt gene knockout augments punishment learning. Using genetically encoded calcium and NT sensors, we further revealed that both calcium dynamics within the PVT-BLA:NT projection and NT concentrations in the BLA are enhanced after reward learning and reduced after punishment learning. Finally, we showed that CRISPR-mediated knockout of the Nt gene in the PVT-BLA pathway blunts BLA neural dynamics and attenuates the preference to active behavioral strategies to reward and punishment predictive cues. Taken together, we have identified NT as a neuropeptide that signals valence in the BLA, and showed that NT is a critical neuromodulator that orchestrates positive and negative valence assignment in amygdala neurons by extending valence-specific plasticity to behaviorally-relevant timescales

Lessons from the Stories of Women in Neuroscience.

Women have been contributing to the field of neuroscience since its inception, but their accomplishments are often overlooked. Lack of recognition, among other issues, has led to progressively fewer women at each academic stage; although half of neuroscience graduate students are women, women comprise less than one-third of neuroscience faculty, and even fewer full professors. Those who reach this level continue to struggle to get their work recognized. Women from historically excluded backgrounds are even more starkly underrepresented and face added challenges related to racial, ethnic, and other biases. To increase the visibility of women in neuroscience, promote their voices, and learn about their career journeys, we created Stories of Women in Neuroscience (Stories of WiN). Stories of WiN shares the scientific and personal stories of women neuroscientists with diverse backgrounds, identities, research interests, and at various career stages. From >70 women highlighted thus far, a major theme has emerged: there is not a single archetype of a woman neuroscientist, nor a single path to "success." Yet, through these diverse experiences run common threads, such as the importance of positive early research experiences, managing imposter syndrome, the necessity of work-life balance, and the challenges of fitting into-or resisting-the "scientist mold" within a patriarchal, racialized academic system. These commonalities reveal important considerations for supporting women neuroscientists. Through the lens of women highlighted by Stories of WiN, we explore the similarities among their journeys and detail specific actionable items to help encourage, support, and sustain women in neuroscience

A systematic review and meta-analysis of how social memory is studied

Abstract Social recognition is crucial for survival in social species, and necessary for group living, selective reproduction, pair bonding, and dominance hierarchies. Mice and rats are the most commonly used animal models in social memory research, however current paradigms do not account for the complex social dynamics they exhibit in the wild. To assess the range of social memories being studied, we conducted a systematic analysis of neuroscience articles testing the social memory of mice and rats published within the past two decades and analyzed their methods. Our results show that despite these rodent’s rich social memory capabilities, the majority of social recognition papers explore short-term memories and short-term familiarity levels with minimal exposure between subject and familiar stimuli—a narrow type of social memory. We have identified several key areas currently understudied or underrepresented: kin relationships, mates, social ranks, sex variabilities, and the effects of aging. Additionally, reporting on social stimulus variables such as housing history, strain, and age, is limited, which may impede reproducibility. Overall, our data highlight large gaps in the diversity of social memories studied and the effects social variables have on social memory mechanisms

AlphaTracker: a multi-animal tracking and behavioral analysis tool.

Computer vision has emerged as a powerful tool to elevate behavioral research. This protocol describes a computer vision machine learning pipeline called AlphaTracker, which has minimal hardware requirements and produces reliable tracking of multiple unmarked animals, as well as behavioral clustering. AlphaTracker pairs a top-down pose-estimation software combined with unsupervised clustering to facilitate behavioral motif discovery that will accelerate behavioral research. All steps of the protocol are provided as open-source software with graphic user interfaces or implementable with command-line prompts. Users with a graphical processing unit (GPU) can model and analyze animal behaviors of interest in less than a day. AlphaTracker greatly facilitates the analysis of the mechanism of individual/social behavior and group dynamics