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Divergent projections of the paraventricular nucleus of the thalamus mediate the selection of passive and active defensive behaviors

Nature Neuroscience volume 24, pages 1429–1440 (2021)Cite this article

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Abstract

The appropriate selection of passive and active defensive behaviors in threatening situations is essential for survival. Previous studies have shown that passive defensive responses depend on activity of the central nucleus of the amygdala (CeA), whereas active ones primarily rely on the nucleus accumbens (NAc). However, the mechanisms underlying flexible switching between these two types of responses remain unknown. Here we show in mice that the paraventricular thalamus (PVT) mediates the selection of defensive behaviors through its interaction with the CeA and the NAc. We show that the PVT–CeA pathway drives conditioned freezing responses, whereas the PVT–NAc pathway is inhibited during freezing and, instead, signals active avoidance events. Optogenetic manipulations revealed that activity in the PVT–CeA or PVT–NAc pathway biases behavior toward the selection of passive or active defensive responses, respectively. These findings provide evidence that the PVT mediates flexible switching between opposing defensive behaviors.

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Fig. 1: pPVTD2R projections to NAc and CeA are partially segregated.
Fig. 2: pPVTD2R neurons control active avoidance and are inhibited during freezing.
Fig. 3: pPVTD2R–NAc axon terminals signal active avoidance.
Fig. 4: NAc-projecting neurons of the pPVT signal active avoidance.
Fig. 5: Optogenetic inhibition of pPVTD2R–NAc axon terminals decreases active avoidance and increases freezing.
Fig. 6: Fiber photometry imaging of GCaMP7s fluorescence from the CeA terminals of pPVTD2R neurons in the 2AA task.
Fig. 7: Optogenetic inhibition pPVTD2R–CeA axon terminals increases active avoidance and reduces freezing.
Fig. 8: pPVTD2R projections to the NAc and the CeA flexibly bias the selection of defensive behaviors.

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Data availability

All the data that support the findings presented in this study are available from the corresponding author upon reasonable request. Source data are provided with this paper and are publicly available at the following repository: https://github.com/Penzolab/Source-Data-07092021.git.

Code availability

R code used to analyze active avoidance behavior and photometric signal is available at the following repository: https://github.com/Penzolab/Data-analysis-of-Two-way-active-avoidance-task.git.

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Acknowledgements

We thank former NIMH postbac N. Ringelberg for gathering preliminary findings that encouraged some aspects of the present study. In addition, we thank the NIMH IRP Rodent Behavioral Core for their support with the development of the custom apparatus for the 2AA task, the NIMH IRP Systems Neuroscience Imaging Resource for their support with the quantification of the rabies data and M. Hoon (NICHD) and F. Do Monte (UT Health) for offering scientific and writing feedback. This work was supported by the NIMH Intramural Research Program (1ZIAMH002950, to M.A.P.; MH002951 and MH002952, to Y.C.).

Author information

Authors and Affiliations

  1. Unit on the Neurobiology of Affective Memory, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA

    Jun Ma, Morgan Kindel, B. Sofia Beas & Mario A. Penzo

  2. Central Nervous System Diseases Research, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riß, Germany

    Johann du Hoffmann

  3. Rodent Behavioral Core, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA

    Johann du Hoffmann & Yogita Chudasama

  4. Section on Behavioral Neuroscience, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA

    Yogita Chudasama

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Contributions

J.M. performed all experiments. M.K. assisted with histological procedures and analyzed the monosynaptic rabies tracing data. B.S.B. assisted with the monosynaptic rabies tracing experiments. J.d.H. developed custom tools for analyzing behavior and calcium signals. J.M. and J.d.H. analyzed the data. Y.C. contributed to funding acquisition and writing. J.M. and M.A.P. designed the study, interpreted results and wrote the paper.

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Correspondence to Mario A. Penzo.

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

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Extended data

Extended Data Fig. 1 pPVTD2R neuron activity during fear conditioning and retrieval.

a, Representative image of GCaMP6s expression in pPVTD2R neurons and optical fiber placements (n = 6 mice). b, Experimental paradigm. c-e, Freezing behavior during the habituation (c), conditioning (d) and retrieval (e) sessions. f-h, Average calcium responses during the habituation (f), conditioning (g) and retrieval (h) sessions. i-k, Quantification of calcium signal during habituation (i), conditioning (j) and retrieval (k) sessions. AUC, One-way ANOVA followed by two-stage linear step-up procedure of Benjamini, Krieger and Yekutieli. Habituation: n = 20 Trials; F(2, 57) = 0.1. Conditioning: n = 30 Trials; F(2, 87) = 2.17. Retrieval: n = 48 Trials; F(2, 141) = 7.7; group comparisons, pre-CS vs CS ***P = 0.0006, CS vs post-CS **P = 0.0012. l, Average calcium responses during early (Trials 1-3; left) and late (Trials 4-5; right) conditioning trials. m, Quantification of calcium signal during the first 5 s following the onset of CS during conditioning sessions. AUC, Two-way ANOVA followed by two-stage linear step-up procedure of Benjamini, Krieger and Yekutieli, n = 12 Trials; F(4, 112) = 1.49. Group comparisons: Early, 1 s vs 4 s P = 0.054, 1 s vs 5 s *P = 0.021; Late, 1 s vs 3 s **P = 0.0043, 1 s vs 4 s ***P = 0.0003, 1 s vs 5 s ***P < 0.001, 2 s vs 5 s **P = 0.0035, 3 s vs 5 s *P = 0.049. n, Calcium signal during US presentation in the late trials is higher than the early trials (n = 6 mice; two-tailed paired Student’s t-test, P = 0.054). o, Top: Heatmaps showing calcium responses of Conditioning Trials 1-5 from individual subjects, respectively. Bottom: Average calcium responses of the top panels. All data in figure shown as mean ± s.e.m.

Source data

Extended Data Fig. 2 The activity of pPVTD2R neurons is positively correlated with movement during the CS following fear memory retrieval.

a, Calcium responses of individual retrieval trials aligned by percentage CS freezing (See Methods) (right). n = 6 mice, 8 trials per mouse. b, Left: Linear regression of CS calcium signal and freezing percentage for each trial. Right: Average CS calcium signal for each group (L, n = 20 trials; M, n = 16 trials; H, n = 12 trials). AUC, F(2, 45) = 3.3, one-way ANOVA followed by two-stage linear step-up procedure of Benjamini, Krieger and Yekutieli. Group comparisons, L vs H, *P = 0.013. c, Average calcium responses (top), average movement index (middle) and linear regression of average calcium signal and movement index during the CS (bottom) for each group. d, Comparison of calcium signal (left) and movement index (right) for each group (L, n = 20 trials; M, n = 16 trials; H, n = 12 trials). AUC, two-way ANOVA followed by two-stage linear step-up procedure of Benjamini, Krieger and Yekutieli. Calcium signal: F(4, 90) = 3.37; movement index: F(4, 90) = 3.6; for group comparisons ***P < 0.001, *P < 0.05. e-f, Average movement index (e) and linear regression of average calcium signal and movement index during the CS (f) for the habituation session. g, Individual subjects contributing to each group. h, Calcium responses of Trials 1-8 and average in bottom panels. i, Quantification of calcium signal during the Trials 1-8. AUC, One-way ANOVA followed by two-stage linear step-up procedure of Benjamini, Krieger and Yekutieli. n = 6; Trial 1, F(2, 10) = 1.36; Trial 2, F(2, 10) = 4.55; Trial 3, F(2, 10) = 0.092; Trial 4, F(2, 10) = 1.55; Trial 5, F(2, 10) = 0.74; Trial 6, F(2, 10) = 2.83; Trial 7, F(2, 10) = 4.94; Trial 8, F(2, 10) = 2.71; for group comparisons *P < 0.05. j, Linear regression of average calcium signal and movement index from Trials 1-8. All data in figure shown as mean ± s.e.m.

Source data

Extended Data Fig. 3 The activity of pPVTD2R neurons in the 2AA task, related to Fig. 2.

a, Latency to avoid and freezing time during the ITI across days (n = 5 mice). b, Left: Linear regression of peak calcium signal and freezing time during the CS for avoidance (blue; A; R2 = 0.069, P = 0.0043) and failure trials (red; F; R2 = 0.15, P < 0.001). Right: Linear regression of average calcium signal and freezing time during the CS for avoidance (blue; A; R2 = 0.17, P < 0.001) and failure trials (red; F; R2 = 0.24, P < 0.001). c, Quantification of the latency to freezing after CS onset for avoidance and failure trials. Left: Counts of the freezing latency. Right: cumulative probability plots for the Left panel. Avoidance, n = 56 Events; Failure, n = 109 Events. d, Quantification of the latency to escape after CS onset for avoidance and failure trials. Left: Counts of the escape latency. Right: cumulative probability plots for the Left panel. Avoidance, n = 118; Failure, n = 122 Trials. All data in figure shown as mean ± s.e.m.

Source data

Extended Data Fig. 4 Optogenetic inhibition of pPVTD2R neurons in the 2AA task.

a, Representative image from a mouse expressing Halo-mCherry in pPVTD2R neurons and implanted with an optical fiber. b, Fiber placements (Ctl, n = 8 mice; Halo, n = 9 mice). c, Schematic of the 2AA task. d-g, Avoidance rate (d), latency to avoid (e) and freezing time during the CS (f) and the ITI (g) across training days for each group. h, Left: Freezing time during the ITI. Right: Normalization to Day 1 for each group. ITI freezing in s, two-way ANOVA followed by two-stage linear step-up procedure of Benjamini, Krieger and Yekutieli. F(2, 30) = 0.36, Non-significant. i, Linear regression of the changes in freezing behavior across test sessions as a function of changes in avoidance behavior. j. Moving distance in the open field. Ctl, n = 8 mice; Halo, n = 5 mice. k, Schematic of the viral vector strategy and optical fiber placement used for optogenetic silencing of pPVTD2R neurons in the 2AA task. l, Fiber placements (Ctl, n = 6 mice; Halo, n = 7). m-p, Avoidance rate (m), latency to avoid (n) and freezing time during the CS (o) and the ITI (p) across training days in both Ctl and Halo groups. q-t, Left: Effect of optogenetic inhibition of pPVTD2Rneurons during the ITI on avoidance rate (q), the latency to avoid (r) and freezing time during the CS (s) and the ITI (t). Right: Normalization to Day 1 for each group. Two-way ANOVA followed by two-stage linear step-up procedure of Benjamini, Krieger and Yekutieli. Avoidance rate, F(5, 80) = 9.05; latency to avoid, F(5, 80) = 4.52; CS freezing, F(5, 80) = 1.17; ITI freezing, F(5, 80) = 0.44; non-significant change among each group comparison. All data in figure shown as mean ± s.e.m.

Source data

Extended Data Fig. 5 Optogenetic inhibition of pPVT–NAc axon terminals in the 2AA task.

a, Schematic of the viral vector strategy and optical fiber placement for optogenetic silencing of pPVT–NAc axon terminals in the 2AA task. b, Fiber placements (Ctl, n = 13 mice; Halo, n = 11 mice). c-f, Avoidance rate (c), latency to avoid (d) and freezing time during the CS (e) and ITI (f) across training sessions for each group. g-j, Left: Avoidance rate (g), latency to avoid (h), freezing time during the CS (i) and the ITI (j) during optogenetic inhibition of pPVT–NAc axon terminals. Right: Normalization to Day 1 for each group. Two-way ANOVA followed by two-stage linear step-up procedure of Benjamini, Krieger and Yekutieli. Avoidance rate: F(2, 44) = 4.89; group comparisons, Halo, Day 1 vs Day 2 *P = 0.013. Latency to avoid: F(2, 44) = 2.88; group comparisons, Halo, Day 1 vs Day 2 *P = 0.024. CS freezing: F(2, 44) = 1.1. ITI freezing: F(2, 44) = 0.46; non-significant change among other group comparison. k, Linear regression of the changes in freezing behavior across test sessions as a function of changes in avoidance behavior. l-o, Left: Optogenetic inhibition of pPVT–NAc axon terminals during the ITI has little effect on avoidance rate (l), the latency to avoid (m) and freezing time during the CS (n) and the ITI (o). Right: Normalization to Day 1 for each group. Ctl, n = 7 mice; Halo, n = 4 mice. Two-way ANOVA followed by two-stage linear step-up procedure of Benjamini, Krieger and Yekutieli. Avoidance rate, F(2, 18) = 0.16; latency to avoid, F(2, 18) = 0.22; CS freezing, F(2, 18) = 0.037; ITI freezing, F(2, 18) = 0.48, Halo, Day 2 vs Day 3 *P = 0.022; non-significant change among other group comparison. p. Moving distance in the open field. Ctl, n = 9 mice; Halo, n = 8 mice. All data in figure shown as mean ± s.e.m.

Source data

Extended Data Fig. 6 Optogenetic inhibition of pPVT–CeA axon terminals in the 2AA task.

a, Schematic of the viral vector strategy and optical fiber placement for optogenetic silencing of pPVT–CeA axon terminals in the 2AA task. b, Fiber placements (Ctl, n = 11 mice; Halo, n = 12 mice). c-f, Avoidance rate (c), latency to avoid (d) and freezing time during the CS (e) and ITI (f) across training sessions for each group. g-j, Left: Avoidance rate (g), latency to avoid (h) and freezing time during the CS (i) and the ITI (j) of optogenetic inhibition of pPVT–CeA axon terminals. Right: Normalization to Day 1 for each group. Two-way ANOVA followed by two-stage linear step-up procedure of Benjamini, Krieger and Yekutieli. Avoidance rate: F(2, 42) = 3.27. Latency to avoid: F(2, 42) = 5.35. CS freezing: F(2, 42) = 2.77. ITI freezing: F(2, 42) = 1.67. For group comparisons **P < 0.01, *P < 0.05. k, Linear regression of the changes in freezing behavior across test sessions as a function of changes in avoidance behavior. l-o, Left: Avoidance rate (l), the latency to avoid (m) and freezing time during the CS (n) and the ITI (o) during optogenetic inhibition of pPVT–CeA axon terminals during the ITI. Right: Normalization to Day 1 for each group. Ctl, n = 6 mice; Halo, n = 10 mice. Two-way ANOVA followed by two-stage linear step-up procedure of Benjamini, Krieger and Yekutieli. Avoidance rate, F(2, 28) = 0.0052; latency to avoid, F(2, 28) = 0.22; CS freezing, F(2, 28) = 0.61; ITI freezing, F(2, 28) = 0.086; non-significant change among each group comparison. p. Moving distance in the open field. Ctl, n = 8 mice; Halo, n = 9 mice. All data in figure shown as mean ± s.e.m.

Source data

Extended Data Fig. 7 Optogenetic inhibition of pPVTD2R–CeA axon terminals in the 2AA task, related to Fig. 7.

a, Freezing time during the ITI across training days in both Ctl and Halo groups. n = 9 mice per group. b, Left: Optogenetic inhibition of pPVTD2R–CeA axon terminals gradually reduces freezing time during the the ITI. Right: Normalization to Day 1 for each group. Two-way ANOVA followed by two-stage linear step-up procedure of Benjamini, Krieger and Yekutieli. F(5, 80) = 0.44; group comparisons, Ctl, Day 1 vs Day 6 ***P = 0.0006, Day 2 vs Day 6 *P = 0.011, Day 3 vs Day 6 **P = 0.0074, Day 4 vs Day 6 *P = 0.048; Halo, Day 1 vs Day 6 *P = 0.017. c, Linear regression of the changes in freezing behavior between Test Day 1 and other test sessions as a function of changes in avoidance behavior. All data in figure shown as mean ± s.e.m.

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Extended Data Fig. 8 Optogenetic stimulation of pPVTD2R–NAc or pPVTD2R–CeA axon terminals in the 2AA task.

a, Schematic of the viral vector strategy and optical fiber placement for optogenetic stimulation of pPVTD2R–NAc axon terminals in the 2AA task. b, Fiber placements (Ctl, n = 8 mice; ChR, n = 12 mice). c-f, Avoidance rate (c), latency to avoid (d) and freezing time during the CS (e) and ITI (f) across training sessions for each group. g-j, Top: Avoidance rate (g), latency to avoid (h) and freezing time during the CS (i) and the ITI (j) during optogenetic stimulation of pPVTD2R–NAc axon terminals. Bottom: Normalization to Day 1 for each group. Two-way ANOVA followed by two-stage linear step-up procedure of Benjamini, Krieger and Yekutieli. Avoidance rate: F(2, 36) = 6.21. Latency to avoid: F(2, 36) = 3.34. CS freezing: F(2, 36) = 0.16; ITI freezing: F(2, 36) = 0.21. For group comparisons **P < 0.01, *P < 0.05 k, Linear regression of the changes in freezing behavior across test sessions as a function of changes in avoidance behavior. l, Schematic of the viral vector strategy and optical fiber placement for optogenetic stimulating of pPVTD2R–CeA axon terminals in the 2AA task. m, Fiber placements (Ctl, n = 7 mice; ChR, n = 10 mice). n-q, Avoidance rate (n), latency to avoid (o) and freezing time during the CS (p) and ITI (q) across training sessions for both groups. r-u, Top: Avoidance rate (r), latency to avoid (s) and freezing time during the CS (t) and the ITI (u) during optogenetic stimulation of pPVTD2R–CeA axon terminals. Bottom: Normalization to Day 1 for each group. Two-way ANOVA followed by two-stage linear step-up procedure of Benjamini, Krieger and Yekutieli. Avoidance rate: F(2, 30) = 5.43. Latency to avoid: F(2, 30) = 1.89. CS freezing: F(2, 30) = 0.88; ITI freezing: F(2, 30) = 0.66. For group comparisons **P < 0.01, *P < 0.05. v, Linear regression of the changes in freezing behavior across test sessions as a function of changes in avoidance behavior. All data in figure shown as mean ± s.e.m.

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Extended Data Fig. 9 Optogenetic inhibition of pPVTD2R–NAc or pPVTD2R–CeA axon terminals in the 2AA task, related to Fig. 8.

a, Optical fiber placements (n = 8 mice per group). b, Freezing time during the ITI across training sessions for both Ctl and Halo groups. c, Left: Effect of optogenetic inhibition of pPVTD2R–NAc axon terminals (Day 2) and pPVTD2R–CeA axon terminals (Day 3) on ITI freezing. Right: Normalization to Day 1 for each group. Two-way ANOVA followed by two-stage linear step-up procedure of Benjamini, Krieger and Yekutieli. F(3, 42) = 1.08; Halo, Day 1 vs Day 2 *P = 0.032. d, Linear regression of the changes in freezing behavior across test sessions as a function of changes in avoidance behavior. All data in figure shown as mean ± s.e.m.

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Extended Data Fig. 10 Monosynaptic inputs of NAc– and CeA–projecting neurons of the pPVT.

a, Schematic of the viral vector strategy to trace the inputs to NAc–projectors or CeA–projectors in pPVT. b, Representative images showing the rabies starter cells (Rabies-GFP and TVA-mCherry double-labelled cells) in pPVT neurons. c, Quantification of monosynaptic inputs to NAc–projectors or CeA–projectors in pPVT. NAc–projectors, n = 3 mice; CeA–projectors, n = 2 mice. To normalize retrogradely labeled (GFP+) cells between subjects, a connectivity index for each brain region was computed by dividing the number of retrogradely labeled cells by the number of starter cells (See Methods).

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Supplementary information

Reporting Summary

Supplementary Video 1

Fiber photometry signal from pPVTD2R neurons from a sample subject. One exemplary avoidance trial and one exemplary failure trial are shown in the video.

Supplementary Video 2

Fiber photometry signal from pPVT–NAc neurons from a sample subject. One exemplary avoidance trial and one exemplary failure trial are shown in the video.

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Ma, J., du Hoffmann, J., Kindel, M. et al. Divergent projections of the paraventricular nucleus of the thalamus mediate the selection of passive and active defensive behaviors. Nat Neurosci 24, 1429–1440 (2021). https://doi.org/10.1038/s41593-021-00912-7

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