Many animals live in complex social groups. To survive, it is essential to know who to avoid and who to interact. Although naïve mice are naturally attracted to any adult conspecifics, a single defeat experience could elicit social avoidance towards the aggressor for days. The neural mechanisms underlying the behavior switch from social approach to social avoidance remains incompletely understood. Here, we identify oxytocin neurons in the retrochiasmatic supraoptic nucleus (SOROXT) and oxytocin receptor (OXTR) expressing cells in the anterior subdivision of ventromedial hypothalamus, ventrolateral part (aVMHvlOXTR) as a key circuit motif for defeat-induced social avoidance learning. After defeat, aVMHvlOXTR cells drastically increase their responses to aggressor cues. This response change is functionally important as optogenetic activation of aVMHvlOXTR cells elicits time-locked social avoidance towards a benign social target whereas inactivating the cells suppresses defeat-induced social avoidance. Furthermore, OXTR in the aVMHvl is itself essential for the behavior change. Knocking out OXTR in the aVMHvl or antagonizing the receptor during defeat, but not during post-defeat social interaction, impairs defeat-induced social avoidance. aVMHvlOXTR receives its private supply of oxytocin from SOROXT cells. SOROXT is highly activated by the noxious somatosensory inputs associated with defeat. Oxytocin released from SOROXT depolarizes aVMHvlOXTR cells and facilitates their synaptic potentiation, and hence, increases aVMHvlOXTR cell responses to aggressor cues. Ablating SOROXT cells impairs defeat-induced social avoidance learning whereas activating the cells promotes social avoidance after a subthreshold defeat experience. Altogether, our study reveals an essential role of SOROXT-aVMHvlOXTR circuit in defeat-induced social learning and highlights the importance of hypothalamic oxytocin system in social ranking and its plasticity.

Human movement disorders and pharmacological studies have long suggested molecular dopamine modulates the pace of the internal clock. But how does the endogenous dopaminergic system influence the timing of our movements? We examined the relationship between dopaminergic signaling and the timing of reward-related, self-timed movements in mice. Animals were trained to initiate licking after a self-timed interval following a start cue; reward was delivered if the animal’s first lick fell within a rewarded window (3.3-7 s). The first-lick timing distributions exhibited the scalar property, and we leveraged the considerable variability in these distributions to determine how the activity of the dopaminergic system related to the animals’ timing. Surprisingly, dopaminergic signals ramped-up over seconds between the start-timing cue and the self-timed movement, with variable dynamics that predicted the movement/reward time, even on single trials. Steeply rising signals preceded early initiation, whereas slowly rising signals preceded later initiation. Higher baseline signals also predicted earlier self-timed movement. Optogenetic activation of dopamine neurons during self-timing did not trigger immediate movements, but rather caused systematic early-shifting of the timing distribution, whereas inhibition caused late-shifting, as if dopaminergic manipulation modulated the moment-to-moment probability of unleashing the planned movement. Consistent with this view, the dynamics of the endogenous dopaminergic signals quantitatively predicted the moment-by-moment probability of movement initiation. We conclude that ramping dopaminergic signals, potentially encoding dynamic reward expectation, probabilistically modulate the moment-by-moment decision of when to move. (Based on work from Hamilos et al., eLife, 2021).

Optogenetics is a powerful tool that allows experimentalists to perturb neural circuits. What can we learn about a network from observing its response to perturbations? I will first describe the results of optogenetic activation of inhibitory neurons in mice cortex, and show that the results are consistent with inhibition stabilization. I will then move to experiments in which excitatory neurons are activated optogenetically, with or without visual inputs, in mice and monkeys. In some conditions, these experiments show a surprising result that the distribution of firing rates is not significantly changed by stimulation, even though firing rates of individual neurons are strongly modified. I will show in which conditions a network model of excitatory and inhibitory neurons can reproduce this feature.

The ability to keep track of one’s location in space is a critical behavior for animals navigating to and from a salient location, and its computational basis is now beginning to be unraveled. Here, we tracked flies in a ring-shaped channel as they executed bouts of search triggered by optogenetic activation of sugar receptors. Unlike experiments in open field arenas, which produce highly tortuous search trajectories, our geometrically constrained paradigm enabled us to monitor flies’ decisions to move toward or away from the fictive food. Our results suggest that flies use path integration to remember the location of a food site even after it has disappeared, and flies can remember the location of a former food site even after walking around the arena one or more times. To determine the behavioral algorithms underlying Drosophila search, we developed multiple state transition models and found that flies likely accomplish path integration by combining odometry and compass navigation to keep track of their position relative to the fictive food. Our results indicate that whereas flies re-zero their path integrator at food when only one feeding site is present, they adjust their path integrator to a central location between sites when experiencing food at two or more locations. Together, this work provides a simple experimental paradigm and theoretical framework to advance investigations of the neural basis of path integration.

Seizures can emerge from multiple or large foci in temporal lobe epilepsy (TLE), complicating focally targeted strategies such as surgical resection or the modulation of the activity of specific hippocampal neuronal populations through genetic or optogenetic techniques. Here, we evaluate a strategy in which optogenetic activation of medial septal GABAergic neurons (MSGNs), which provide extensive projections throughout the hippocampus, is used to control seizures. We found that MSGNs were structurally and functionally resilient in the chronic intrahippocampal kainate mouse model of TLE, which as is often the case in human TLE patients, presents with hippocampal sclerosis. Optogenetic stimulation of MSGNs modulated oscillations across the rostral to caudal extent of the hippocampus in epileptic conditions. Chronic wireless optogenetic stimulation of MSGNs, upon electrographic detection of spontaneous hippocampal seizures, resulted in reduced seizure durations. We propose MSGNs as a novel target for optogenetic control of seizures in TLE.

Olfactory navigation provides a tractable model for studying the circuit basis of sensori-motor transformations and goal-directed behaviour. Macroscopic organisms typically navigate in odor plumes that provide a noisy and uncertain signal about the location of an odor source. Work in many species has suggested that animals accomplish this task by combining temporal processing of dynamic odor information with an estimate of wind direction. Our lab has been using adult walking Drosophila to understand both the computational algorithms and the neural circuits that support navigation in a plume of attractive food odor. We developed a high-throughput paradigm to study behavioural responses to temporally-controlled odor and wind stimuli. Using this paradigm we found that flies respond to a food odor (apple cider vinegar) with two behaviours: during the odor they run upwind, while after odor loss they perform a local search. A simple computational model based one these two responses is sufficient to replicate many aspects of fly behaviour in a natural turbulent plume. In on-going work, we are seeking to identify the neural circuits and biophysical mechanisms that perform the computations delineated by our model. Using electrophysiology, we have identified mechanosensory neurons that compute wind direction from movements of the two antennae and central mechanosensory neurons that encode wind direction are are involved in generating a stable downwind orientation. Using optogenetic activation, we have traced olfactory circuits capable of evoking upwind orientation and offset search from the periphery, through the mushroom body and lateral horn, to the central complex. Finally, we have used optogenetic activation, in combination with molecular manipulation of specific synapses, to localize temporal computations performed on the odor signal to olfactory transduction and transmission at specific synapses. Our work illustrates how the tools available in fruit fly can be applied to dissect the mechanisms underlying a complex goal-directed behaviour.