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Paraventricular nucleus CRH neurons encode stress controllability and regulate defensive behavior selection

Nature Neuroscience volume 23, pages 398–410 (2020)Cite this article

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Abstract

In humans and rodents, the perception of control during stressful events has lasting behavioral consequences. These consequences are apparent even in situations that are distinct from the stress context, but how the brain links prior stressful experience to subsequent behaviors remains poorly understood. By assessing innate defensive behavior in a looming-shadow task, we show that the initiation of an escape response is preceded by an increase in the activity of corticotropin-releasing hormone (CRH) neurons in the paraventricular nucleus (PVN) of the hypothalamus (CRHPVN neurons). This anticipatory increase is sensitive to stressful stimuli that have high or low levels of outcome control. Specifically, experimental stress with high outcome control increases CRHPVN neuron anticipatory activity, which increases escape behavior in an unrelated context. By contrast, stress with no outcome control prevents the emergence of this anticipatory activity and decreases subsequent escape behavior. These observations indicate that CRHPVN neurons encode stress controllability and contribute to shifts between active and passive innate defensive strategies.

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Fig. 1: CRHPVN neurons modulate defensive behaviors to a looming shadow.
Fig. 2: Increase in CRHPVN neuron activity during a looming or advancing threat.
Fig. 3: CRHPVN neurons anticipate the escape response to an imminent threat.
Fig. 4: Relationship between CRHPVN neuron activity and other innate escape behaviors.
Fig. 5: Stress controllability training modifies behavior and alters plasticity at glutamate synapses.
Fig. 6: CRHPVN neurons encode stress controllability.
Fig. 7: Controllability training shifts the defensive strategy.

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Data availability

All relevant data and analysis tools are available upon reasonable request from the authors.

Code availability

Scripts used to analyze fiber photometry and detect miniscope events are deposited at https://github.com/leomol/FPA and https://github.com/leomol/MSA.

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Acknowledgements

We thank the expert technical support of C. Breiteneder, M. Tsutsui, C. Martinez and L. A. Molina. We are grateful for the support of the Cumming School of Medicine Optogenetics Core Facility. This work was supported by an operating grant to J.S.B. from the Canadian Institutes for Health Research (FDN-148440) and the Brain Canada Neurophotonics Platform. N.D. and T.-L.S. are supported by Fellowships from Alberta Innovates-Health Solutions.

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Authors and Affiliations

  1. Hotchkiss Brain Institute and Department of Physiology and Pharmacology, University of Calgary, Calgary, Alberta, Canada

    Núria Daviu, Tamás Füzesi, David G. Rosenegger, Neilen P. Rasiah, Toni-Lee Sterley, Govind Peringod & Jaideep S. Bains

  2. CSM Optogenetics Core Facility, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada

    Tamás Füzesi

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Contributions

N.D. designed and conducted experiments, analyzed data, prepared figures and wrote the manuscript. T.F. designed and conducted behavioral experiments, analyzed data and prepared figures. D.G.R. developed video and photometry analysis tools, analyzed behavioral data and reviewed the manuscript. N.P.R. and T.-L.S. conducted slice electrophysiology experiments and analyzed data. G.P. developed the accelerometer software and analysis, the artificial decoder and software for automating escape analysis. J.S.B. developed and supervised the project, analyzed data, constructed figures and wrote the manuscript.

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Correspondence to Jaideep S. Bains.

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The authors declare no competing interests.

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Peer review information Nature Neuroscience thanks Lieselot Carrette, Olivier George, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Prior experience changes defensive strategy.

a, Protocol for the second exposure to looming-shadow test. b, Behavioral analysis showing individual trials (trials/mice, n = 55, N = 11) and c, summary of all trials for the 3 behavioral outputs analyzed. d, Representation of the starting point of subject in each trial for the second exposure to the looming-shadow test. e, Data compiled and presented as fraction of trials showing a given behavior in a mouse. Escape (N = 11, Paired t-test, two tailed t(10) = 2.472, p = 0.0330, 95% CI: 1.973 to 38.03), freeze (Wilcox test, two-tailed, w = −3.000, p = 0.750), and no response (Paired t-test, two-tailed, t(10) = 3.194, p = 0.0096, 95% CI: −30.86 to −5.50). f, Representation of the starting point of subject in each trial for the photoinhibition experiment (left CRHeYFP, right CRHArch3.0). Data shown are means ± s.e.m.

Extended Data Fig. 2 Relationship between GCaMP signal and visual stimulus assessed using different parameters.

a, (i) Individual traces (gray) and mean (overlaid black) of CRHPVN activity in response to an object that tracks in a horizontal plane across the sky but does not advance (trials/mice, n = 9, N = 3). The length of the stimulus was 8 s and it was moving at a constant speed of 6 cm/s. (ii) Individual traces (gray) and mean (overlaid black) of CRHPVN activity in response to an object that remains static in a horizontal plane across the sky for the duration of the experiment (trials/mice, n = 15, N = 3) b, Individual traces (gray) and mean (overlaid green) of CRHPVN activity in response to shadow presentation corresponding to trials resulting in a freezing behavior for Naïve mice (trials/mice, n = 4, N = 3). c, Comparison between manual vs automated assessment of escape onset in the looming-shadow test (Paired t-test, two tailed, t(20) = 1.027, p = 0.3169, 95% CI −0.7580 to 0.2580). d, Average z-score of CRHPVN calcium response with individual trials time-locked to the onset of the escape when assessed manually using a frame by frame approach. Escape response indicated by dashed line and red arrow (trials/mice n = 21, N = 5). Solid lines represent average, and the shaded areas indicate SEM. Data shown are means ± s.e.m.

Extended Data Fig. 3 Avoidance behavior during controllable stress training.

Avoidance behavior in controllable group (N = 10, day 1 to day 3, repeated measure ANOVA, F(2,18) = 10.17, p = 0.0011, Bonferroni’s multiple comparisons test, Day1 vs day 2 p > 0.999, 95% CI −17.00 to 10.00. Day 2 vs day 3 p = 0.0074, 95% CI −35.00 to −8.00. Day 3 vs day 1 p = 0.0016, 95% CI −31.50 to −4.50). Data shown are means ± s.e.m.

Extended Data Fig. 4 Effects of controllability training on basal glutamate transmission and intrinsic excitability of CRHPVN neurons.

a, sEPSC amplitude and frequency for naïve, controllable and uncontrollable stress 24 h after the last training session (cells/mice, Naive = 21/4, Controllable = 16/5, Uncontrollable = 19/5; amplitude, one-way ANOVA, f(2,53) = 0.8868, p = 0.4180, Bonferroni’s multiple comparison, Naïve vs controllable p = 0.7944, 95% CI −2.966 to 7.935. Naïve vs Uncontrollable p = 0.7743, 95% CI −2.796 to 7.936. Controllable vs Uncontrollable p > 0.999, 95% CI −5.497 to 5.654; frequency, one-way ANOVA, F(2,53) = 1.405, p = 0.2544, Bonferroni’s multiple comparison, Naïve vs controllable p = 0.6639, 95% CI −4.640 to 2.188. Naïve vs Uncontrollable p = 0.6509, 95% CI −2.059 to 4.456. Controllable vs Uncontrollable p = 0.2244, 95% CI −5.915 to 1.067). b, Bar graph showing no significant changes in baseline PPR between groups (cells/mice, Controllable = 21/9, Uncontrollable = 25/10, Unpaired t-test, two-tailed, t(44) = 1.037, p = 0.3053, 95% CI −0.05364 to 0.1674). c, F-I plot shows spike frequency for each depolarizing current step (cells/mice, Naive = 18/4, Controllable = 30/5, Uncontrollable = 27/5 -2way ANOVA current step x group F(18,648) = 0.8444, p = 0.6476). Data shown are means ± s.e.m.

Extended Data Fig. 5 Peak GCaMP responses to footshock following controllable and uncontrollable stress.

a, Individual z-scores of baseline (shock onset) and footshock peak values for controllable (right, blue circles, Day 1 trials/mice = 120/6; Baseline min = −3.369, 25% = −0.1015, med = 1.118, 75% = 2.118, max = 7.730. FS peak min = −1.849, 25% = 4.602, med = 6.639, 75% = 9.195, max = 19.19; Wilcoxon signed rank test, two-tailed, W = 7248, p < 0.0001. Day 2 trials/mice = 114/6; Baseline min = −2.906, 25% = 0.4915, med = 1.593, 75% = 3.993, max = 13.14. FS peak min = −2.906, 25% = 4.155, med = 6.818, 75% = 9.533, max = 25.36; Wilcoxon signed rank test, two-tailed, W = 5430, p < 0.0001. Day 3 trials/mice = 119/6; Baseline min = −4.187, 25% = 0.5293, med = 2.544, 75% = 3.808, max = 14.82. FS peak min = −3.033, 25% = 3.302, med = 6.333, 75% = 9.212, max = 20.61; Wilcoxon signed rank test, W = 6399, p < 0.0001) and uncontrollable (orange circles, Day 1 trials/mice = 120/6; Baseline min = −5.375, 25% = −0.6542, med = 0.4421, 75% = 1.974, max = 12.61. FS peak min = −2.018, 25% = 5.927, med = 7.320, 75% = 9.287, max = 17.91; Wilcoxon signed rank test, two-tailed, W = 7230, p < 0.0001. Day 2 trials/mice = 119/6; Baseline min = −5.068, 25% = 0.6244, med = 0.3252, 75% = 1.568, max = 17.68. FS peak min = −0.218, 25% = 4.628, med = 6.598, 75% = 9.112, max = 26.66; Wilcoxon signed rank test, two-tailed, W = 7009, p < 0.0001. Day 3 trials/mice = 120/6; Baseline min = −3.594, 25% = −0.5115, med = 0.6376, 75% = 2.253, max = 16.58. FS peak min = −0.3636, 25% = 4.288, med = 6.584, 75% = 8.212, max = 33.54;Wilcoxon signed rank test, two-tailed, W = 5430, p = 0.0006) group. b, Individual delta z-scores (footshock - baseline) on day 1 (Controllable trials/mice = 120/6; min = -1.061, 25% = 3.809, med = 5.967, 75% = 8.262, max = 15.79. Uncontrollable trials/mice 120/6. min = -0.667, 25% = 4.222, med = 7.493, 75% = 8.956, max = 15.31; Mann-Whitney test, two tailed, U = 62.7, p = 0.0650), day 2 (Controllable trials/mice = 114/6; min = -1.667, 25% = 1.948, med = 4.855, 75% = 7.101, max = 19.22. Uncontrollable trials/mice = 119/6; min = -0.4561, 25% = 3.558, med = 6.533, 75% = 9.064, max = 24.63; Mann-Whitney test, two tailed, U = 5307, p = 0.0041) and day 3 (Controllable trials/mice = 120/6; min = -0.4106, 25% = 1.844, med = 3.499, 75% = 6.173, max = 17.86. Uncontrollable trials/mice = 120/6; min = -0.3787, 25% = 3.421, med = 5.809, 75% = 7.824, max = 24.80; Mann-Whitney test, two tailed, U = 5014, p < 0.0001). c, Average CRHPVN activity on day 1 for both controllable and uncontrollable groups on trial 3, 5, 15, 18 and 20 (n = 6). Data shown in the violin plots are median, 25% and 75% percentile (black bars).

Extended Data Fig. 6 Circulating corticosterone levels after controllability training.

Corticosterone levels after the last day of training of controllable (N = 10) and uncontrollable (N = 10) stress protocol (Unpaired t-test, two-tailed, t(19) = 1.586, p = 0.1301, 95% CI: -147.9 to 20.65). Data shown are means ± s.e.m.

Extended Data Fig. 7 Non-linear clustering visualization in lower dimensional space.

a, Visualization of the data matrix using non-linear clustering in a lower-dimensional space based on the 2 main features extracted from the calcium traces. From top to bottom: day 1 alone, day 2 alone, day 3 alone, all training days combined. b, Confusion matrices showing the classification accuracy (ratio of correct predictions to total predictions made) of the trained decoder from (top to bottom) day 1 to day 3.

Extended Data Fig. 8 Immobility in response to controllability training.

Immobility during: (a) baseline period (5 min before the tone presentation, unpaired t-test, two-tailed, t(10) = 1.185, p = 0.2636, 95% CI -6.161 to 20.16), (b) during tone presentation, 8 s stimulus presentation (two-way ANOVA, tone x group interaction f(4,40) = 0.5399, p = 0.7073) and (c) between tones (two-way ANOVA, tone x group interaction f(3,30) = 1.823, p = 0.1642). Inter-tone-interval (ITI) = 52 s, (N = 6 each group).Data shown are means ± s.e.m.

Extended Data Fig. 9 Additional photometry data analysis for looming shadow tests following controllability training.

a, Non-responders in uncontrollable group showing individual traces (gray) and average z-score (black) of CRHPVN calcium response during visual stimulus presentation (trials/mice = 4/3). b, Comparison between manual (frame by frame), and automated analysis of the escape reaction time (n = 26, ERT, Paired t-test, two-tailed, t(25) = 0.4067, p = 0.6877, 95% CI -0.5929 to 0.8847). c, Average z-score of CRHPVN calcium response with individual trials time-locked to the onset of the escape. Escape response indicated by dashed line and red arrow (trials/mice n = 33, N = 9). d, Individual z-score values at the baseline (white circles) and at flight response initiation (blue circles, trials/mice n = 33, N = 9; two-tailed paired t-test, t(32) = 4.025, p = 0.0003, 95% CI 0.8558 to 2.610). Solid lines represent average, and the shaded areas indicate s.e.m. Data shown are means ± s.e.m.

Extended Data Fig. 10 Compiled GCaMP data across experiments from all escape trials and all freeze trials.

a, Average z-score of CRHPVN calcium response with all individual trials time-locked to the onset of stimulus. Left panel shows all trials (naïve, controllable and uncontrollable stress; n = 55 trials) that showed an escape response; middle panel shows all trials that showed a freezing response; n = 16 trials). Right panel shows the overlaid responses from escapers and freezers during the shadow presentation. b, Cumulative distributions of z-scores at the end of shadow expansion (5 s from stimulus onset). c, z scores from escape (n = 55) and freeze (n = 16) trails at the 5 s mark of shadow presentation (two-tailed unpaired t-test, Welch’s correction; t(57.55) = 4.184, p < 0.0001, 95% CI 2.266 to 6.426). Data shown are means ± s.e.m.

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Daviu, N., Füzesi, T., Rosenegger, D.G. et al. Paraventricular nucleus CRH neurons encode stress controllability and regulate defensive behavior selection. Nat Neurosci 23, 398–410 (2020). https://doi.org/10.1038/s41593-020-0591-0

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