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The brain’s ability to associate threats with external stimuli is vital to execute essential behaviours including avoidance. Disruption of this process contributes instead to the emergence of pathological traits which are common in addiction and depression. However, the mechanisms and neural dynamics at the single-cell resolution underlying the encoding of associative learning remain elusive. Here, employing a Pavlovian discrimination task in mice we investigate how neuronal populations in the lateral habenula (LHb), a subcortical nucleus whose excitation underlies negative affect, encode the association between conditioned stimuli and a punishment (unconditioned stimulus). Large population single-unit recordings in the LHb reveal both excitatory and inhibitory responses to aversive stimuli. Additionally, local optical inhibition prevents the formation of cue discrimination during associative learning, demonstrating a critical role of LHb activity in this process. Accordingly, longitudinal in vivo two-photon imaging tracking LHb calcium neuronal dynamics during conditioning reveals an upward or downward shift of individual neurons’ CS-evoked responses. While recordings in acute slices indicate strengthening of synaptic excitation after conditioning, support vector machine algorithms suggest that postsynaptic dynamics to punishment-predictive cues represent behavioral cue discrimination. To examine the presynaptic signaling in LHb participating in learning we monitored neurotransmitter dynamics with genetically-encoded indicators in behaving mice. While glutamate, GABA, and serotonin release in LHb remain stable across associative learning, we observe enhanced acetylcholine signaling developing throughout conditioning. In summary, converging presynaptic and postsynaptic mechanisms in the LHb underlie the transformation of neutral cues in valued signals supporting cue discrimination during learning.

The lateral habenula (LHb) integrates aversive information to regulate motivated behaviors. Despite recent advances in identifying neuronal diversity at the molecular level, in vivo electrophysiological diversity of LHb neurons remains poorly understood. Understanding this diversity is essential for deciphering how information is processed in the LHb. To address this gap, we conducted in vivo electrophysiological recordings in mice and applied unsupervised clustering algorithm to analyze firing patterns. This analysis identified four distinct spontaneous firing patterns of LHb neurons, which were consistent across both anesthetized and awake states. To determine whether these firing patterns correlate with function, we recorded neuronal responses to foot shock stimulation in anesthetized mice and monitored spontaneous behavior in awake mice. We found that low-firing, bursting neurons were preferentially modulated by foot shocks in anesthetized mice and also tracked behavioral states in awake mice. Collectively, our findings indicate significant electrophysiological diversity among LHb neurons, which is associated with their modulation by aversive stimuli and behavioral state.

In the dorsolateral geniculate nucleus (dLGN) of the thalamus, stimulus-driven signals are combined with modulatory inputs such as corticothalamic (CT) feedback and behavioural state. How these shape dLGN activity remains an open question. We recorded extracellular responses in dLGN of awake mice to a movie stimulus, while photosuppressing CT feedback, and tracking locomotion and pupil size. To assess the relative impact of stimulus and modulatory inputs, we fit single neuron responses with generalized linear models. While including CT feedback and behavioural state as predictors significantly improved the model’s overall performance, the improvement was especially pronounced for a subpopulation of neurons poorly responsive to the movie stimulus. In addition, the observed impact of CT feedback was faster and more prevalent in the absence of a patterned visual stimulus. Finally, for neurons that were sensitive to CT feedback, visual stimuli could be more easily discriminated based on spiking activity when CT feedback was suppressed. Together, these results show that effects of modulatory inputs in dLGN depend on visual responsiveness and stimulus type.