Heterogeneous Habenular Neuronal Ensembles during Selection of Defensive Behaviors

Abstract

Optimal selection of threat-driven defensive behaviors is paramount to an animal's survival. The lateral habenula (LHb) is a key neuronal hub coordinating behavioral responses to aversive stimuli. Yet, how individual LHb neurons represent defensive behaviors in response to threats remains unknown. Here, we show that in mice, a visual threat promotes distinct defensive behaviors, namely runaway (escape) and action-locking (immobile-like). Fiber photometry of bulk LHb neuronal activity in behaving animals reveals an increase and a decrease in calcium signal time-locked with runaway and action-locking, respectively. Imaging single-cell calcium dynamics across distinct threat-driven behaviors identify independently active LHb neuronal clusters. These clusters participate during specific time epochs of defensive behaviors. Decoding analysis of this neuronal activity reveals that some LHb clusters either predict the upcoming selection of the defensive action or represent the selected action. Thus, heterogeneous neuronal clusters in LHb predict or reflect the selection of distinct threat-driven defensive behaviors.

Keywords: calcium imaging; cluster analysis; defensive behaviors; lateral habenula.

Graphical abstract

Figure 1

Threat Exposure Promotes Divergent Defensive Strategies (A) Schematic of the looming protocol. (B) Extracted video frames depicting a mouse during looming-driven runaway (top) and action-locking (bottom). (C) Representative single mouse runaway and action-locking trials to multiple looming stimuli. (D) Top: representative track of a single mouse during runaway and action-locking trials. Bottom: strategy probability in the function of the mouse-nest distance (n_{runaway trials} = 56; n_{action-locking trials} = 23; n_mice = 11; mouse-nest distance (maximum distance = 1): runaway trials versus action-locking trials; 0.3: 4 versus 0; 0.4: 7 versus 0; 0.5: 8 versus 0; 0.6: 10 versus 2; 0.7: 11 versus 0; 0.8: 9 versus 6; 0.9: 3 versus 3; 1.0: 4 versus 12; X²₇ = 31.68; ^∗∗∗p < 0.0001, chi-square test). The lines fitting a sigmoidal distribution reports the correlation between the mouse-nest distance and the selected strategy (runaway: r = −0.883, R² = 0.78, ^∗∗p = 0.003; action-locking: r = 0.884, R² = 0.78, ^∗∗p = 0.003, Pearson correlation coefficient). (E) Left: single mouse runaway (purple) and action-locking (orange) time frame reported for each trial (dot: onset response, line: offset response). Right: pooled data (n_{runaway trials} = 56; n_{action-locking trials} = 23) for onset (runaway versus action-locking; 1.631 ± 0.14 versus 1.797 ± 0.34 s; t₇₇ = 0.53; p = 0.59, unpaired t test) and duration (runaway versus action-locking; 1.52 ± 0.14 versus 9.58 ± 2.37 s; t₇₇ = 5.29; ^∗∗∗p < 0.0001, unpaired t test) of runaway and action-locking. Data are presented with boxplots (median and 10th–90th quartile) or means ± SEMs. See also Figure S1.

Figure 2

Divergent Habenular Neuronal Dynamics Underlying Threat-Driven Behaviors (A) Top: schematic of the experiment. Bottom left: representative brain coronal section showing GCamp6f transduction and the fiber implantation track in the LHb. Bottom right: representative Ca²⁺ traces during runaway (red, top) and action-locking (blue, bottom) trials (looming, gray bar). (B) Time course of averaged traces and boxplots reporting respectively Z score (runaway = 56 trials, F_3,850 = 40.5, ^∗∗∗p < 0.0001; action-locking = 23 trials, F_1,540 = 3.122, ^∗p = 0.033; repeated measures (RM) 1-way ANOVA) and area under the curve (runaway versus action-locking, 26.14 ± 6.56 versus 3.05 ± 5.0; t₇₇ = 2.10, ^∗p = 0.039, unpaired t test) for single trials aligned to the behavioral onset. (C) Top: schematic of the experiment. Bottom: representative brain coronal section showing Jaws transduction in LHb and fiber placement above it. (D) Representative speed traces in a GFP-injected (top) and a Jaws-injected mouse (bottom) in a runaway and a no-reaction response trial, respectively. Looming exposure was paired with LHb inhibition (638 nm, 5 s, 8 mW). At right, the bar graph reports the strategy probability to the looming in the 2 groups (GFP versus Jaws, n_mice = 3 versus 3, n_trials = 45 versus 45; runaway: 30 versus 10; action-locking: 12 versus 8; no response: 3 versus 27; X²₂ = 30; ^∗∗∗p < 0.0001, chi-square test). Data are presented with boxplots (median and 10th–90th quartile) or means ± SEMs. See also Figures S2 and S3.

Figure 3

Distinct LHb Neuronal Ensembles during Defensive Behaviors (A) Top: schematic of the experiment. Bottom, pictures showing mouse with miniscope attached, GRIN lens placement, GCaMP6f expression, field of view with identified cells (maximum intensity projections), map of active LHb neurons, and respective sample traces (right). (B) Mean Ca²⁺ responses (Z score) across runaway (left) and action-locking (right) trials for 46 LHb neurons imaged within a single mouse, aligned to the onset of the behavioral reaction. Highlighted at top, the average response of a single cell (Cell: 15). Bottom, averaged time course of all cells for runaway and action-locking strategies. (C) Cluster identification by unsupervised classification during runaway (top) and action-locking (center), including all neurons recorded. Bottom, average trace across all of the neurons within the cluster. Plots are aligned to the action onset. See also Figure S4.

Figure 4

Identified LHb Neuronal Clusters Code for Behavioral Preparation and Execution (A) Single-cell activity across trials during runaway and action-locking reported as heat plots (left) and mean Z score (right). Trials are time-locked with the behavior and presented different onsets due to trial-by-trial variability in reaction time (blank spaces in the heat plots). (B) Workflow for decoding analysis of single neuron activity. The decoder was run in three different time epochs (−3 to 0 s, burgundy bar; 0–3 s, green bar; 3–6 s, yellow bar) relative to the behavioral onset. (C) Single-cell decoding accuracy above chance averaged across all recorded neurons. Red dots highlight significance above chance. Error bars reflect SEM. t₂₄₇ = 3.23 for −3 to 0 s, t₂₄₇ = 9.37 for 0–3 s, t₂₄₇ = 7.54 for 3–6 s; p values for the 3 epochs = 2.67 × 10⁻³, 1.56 × 10⁻¹⁸, and 6.84 × 10⁻¹³ after Benjamini-Hochberg multiple comparisons correction across all epochs. (D) Decoding results split by the clusters. Red dots highlight significance above chance. t₂₄₇ = (0.44, 0.12, 2.54, 1.20, 0.35, 2.58, 0.78, and 1.94) for the 8 clusters for −3 to 0 s, t₂₄₇ = (6.62, 5.03, 4.16, 4.20, 2.07, −0.19, 2.25, and 4.33) for the 8 clusters for 0–3 s, t₂₄₇ = (3.13, 8.66, 2.99, 4.43, 3.27, −2.44, 2.42, and 1.67) for the 8 clusters for 3–6 s; p values for the 3 epochs per cluster = (7.55 × 10⁻¹, 9.07 × 10⁻¹, 2.99 × 10⁻², 2.96 × 10⁻¹, 7.97 × 10⁻¹, 2.63 × 10⁻², 5.28 × 10⁻¹, and 7.91 × 10⁻²) for −3 to 0 s, (2.87 × 10⁻⁷, 4.07 × 10⁻⁵, 5.35 × 10⁻⁴, 3.39 × 10⁻⁴, 6.54 × 10⁻², 4.43 × 10⁻¹, 4.54 × 10⁻², and 1.89 × 10⁻⁴) for 0–3 s, and (7.78 × 10⁻³, 1.18 × 10⁻¹⁰, 1.12 × 10⁻², 1.89 × 10⁻⁴, 5.67 × 10⁻³, 9.84 × 10⁻¹, 3.22 × 10⁻², and 1.31 × 10⁻¹) for 3–6 s after Benjamini-Hochberg multiple comparisons correction across all clusters and epochs. See also Figure S4.