Defensive behaviors are critical for animal survival. They are dynamic and adaptive, as environmental contexts, properties and intensity of threats, as well as expectations from past experiences can all modulate the form as well as the magnitude of defensive behaviors (Fanselow, 1994; Gross and Canteras, 2012; Tovote et al., 2016). Threat signals in the external environment are sensed by different sensory modalities through distinct sensory pathways to initiate appropriate defensive behaviors. Previous studies have mostly been focused on defensive behaviors initiated under stimulation of one individual sensory modality (Fanselow and LeDoux, 1999; Yilmaz and Meister, 2013). However, a danger may be associated with cues of multiple sensory modalities arriving at the same time, and the integration of information of these different modalities may profoundly influence the behavioral output. Intuitively, the presence of multisensory signals is helpful for strengthening defensive responses. However, neural circuit bases for the potential cross-modality interactions in defensive behaviors are largely unknown. In this study, we designed experiments to specifically examine whether tactile input can affect a well-established auditory-induced defensive behavior (Fanselow and LeDoux, 1999; Tovote et al., 2016). The vibrissal system is crucial to behaviors such as navigation and exploration (Carvell and Simons, 1990; Diamond et al., 2008), and rodents frequently collect information from surroundings using their whiskers (Prigg et al., 2002). We reason that it may be common for animals to use both vibrissal and auditory systems in sensing environmental dangers.

Zona incerta (ZI) is a major GABAergic subthalamic nucleus consisting of heterogeneous groups of cells. In rodents, four (rostral, ventral, dorsal, caudal) sectors of ZI can be loosely defined based on neurochemical expression patterns (Ma et al., 1997; Mitrofanis et al., 2004), and it has been suggested that different sectors might be involved in different circuits and functions (Liu et al., 2017; Plaha et al., 2008). Our recent study has shown that GABAergic neurons in the rostral sector of ZI (ZIr) play a role in reducing defensive behavior in an experience-dependent manner (Chou et al., 2018). It also raises a possibility that ZI might play a broader role in defensive behavior. ZI receives inputs from various cortical areas including the primary somatosensory cortex (SSp) (Kolmac et al., 1998; Shammah-Lagnado et al., 1985) as well as from the brainstem trigeminal nucleus that relays vibrissal information (Roger and Cadusseau, 1985; Smith, 1973). A recent study has demonstrated that deflecting whiskers directly induces neuronal activity in the ventral sector of ZI (ZIv) (Urbain and Deschênes, 2007), where parvalbumin (PV) positive neurons are enriched (Kolmac and Mitrofanis, 1999). In the present study, we investigated whether somatosensory input through whisker stimulation could modulate defensive behavior via recruiting ZIv PV+ neurons.

To test whether tactile input can affect defensive behavior, we employed a relatively simple behavioral test, sound-induced flight, following our previous studies (Xiong et al., 2015; Zingg et al., 2017). Such behavior has been observed in both freely moving and head-fixed conditions (Xiong et al., 2015; Zingg et al., 2017). In our first set of experiments, animals were head-fixed and placed on a smoothly rotatable plate (Chou et al., 2018; Liang et al., 2015). Loud noise sound (80 dB sound pressure level or SPL) elicited animal running, and the running speed was recorded in real time (Figure 1A, left). Tactile stimulation was applied by deflecting whiskers unilaterally with a cotton stick controlled by a piezo actuator (Figure 1—figure supplement 1A). In our control experiments, the whisker deflection per se did not elicit significant locomotion of animals (Figure 1—figure supplement 1B). Trials without and with tactile stimulation were interleaved. We found that tactile stimulation enhanced the running induced by noise sound (Figure 1A, right), as demonstrated by the increased peak speed (Figure 1B, Figure 1—figure supplement 1C) and total travel distance (Figure 1C, Figure 1—figure supplement 1D). The temporal profile of the behavioral response was not significantly affected, as shown by the quantifications of onset latency and time to peak (Supplementary file 1). Silencing the SSp contralateral to the whiskers being deflected by infusing a GABA receptor agonist, muscimol (Figure 1D, left), removed the difference in speed between conditions without and with whisker stimulation (Figure 1D–F), without altering the response temporal profile (Supplementary file 1). This suggests that the tactile enhancement of running is mediated mainly through SSp. To further demonstrate the tactile effect on flight behavior in freely moving animals, we used a two-chamber test following our previous study (Zingg et al., 2017). When the mouse was exposed to noise applied in one chamber, it quickly escaped to the other chamber by crossing through a narrow channel (Figure 1—figure supplement 2A). Trimming of all whiskers of the animal significantly decreased the average speed of the flight through the channel (Figure 1—figure supplement 2B), suggesting that tactile information through whiskers can indeed enhance flight behavior in a more natural condition.

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Previous studies have suggested that SSp projects to ZIv (Kolmac et al., 1998; Shammah-Lagnado et al., 1985), and that ZIv neurons respond to whisker deflections (Urbain and Deschênes, 2007). To confirm this projection, we injected AAV1-CamKII-hChR2-eYFP into SSp of PV-ires-Cre crossed with Ai14 (Cre-dependent tdTomato) reporter mice (Figure 2A). We found profuse fluorescence-labeled axons in ZIv, but few in other ZI sectors (Figure 2B). We next directly examined the effect of stimulating the SSp projection to ZIv, by placing optic fibers on top of ZIv to deliver LED light pulses (20 Hz train for 5 s) bilaterally (Figure 2C). The optogenetic activation of the SSp axons in ZIv enhanced noise-induced running (Figure 2C–E, Figure 2—figure supplement 1A–B) without affecting the response temporal profile (Supplementary file 1), but by itself had no effect on the baseline locomotion speed (Figure 2—figure supplement 1C). Infusing muscimol into ZIv bilaterally abolished the enhancement of flight response by whisker stimulation (Figure 2F–H) without affecting the response temporal profile (Supplementary file 1). Together, these results suggest that activation of the SSp-ZIv projection is sufficient and necessary for the tactile enhancement of auditory-induced flight response.

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Immuno-histological studies have suggested that PV+ neurons are a major cell type in the ventral sector of ZI (Kolmac and Mitrofanis, 1999). To test whether SSp axons innervate PV+ neurons, we performed slice whole-cell recording from ZIv PV+ neurons (labeled by tdTomato expression in PV-Cre::Ai14 animals) while optically activating ChR2-expressing SSp axons in ZI (Figure 2I). We observed that blue light pulses evoked monosynaptic excitatory postsynaptic currents (EPSCs) in most ZIv PV+ neurons recorded with tetrodotoxin (TTX) and 4-aminopyridine (4-AP) present in the bath solution. The EPSC could be blocked by an AMPA receptor blocker, 6-cyano-7-nitroquinoxaline-2,3-dione (CNQX) (Figure 2J–K). These results indicate that ZIv PV+ neurons receive direct excitatory input from SSp.

To investigate whether the PV+ neurons play a role in the tactile modulation of flight response, we injected AAV encoding Cre-dependent ChR2 or ArchT into ZI of PV-Cre::Ai14 mice (Figure 3A,D). The viral expression of opsins co-localized well with Cre-dependent tdTomato expression (Figure 3—figure supplement 1A), indicating PV-specific expression of opsins. Optogenetic manipulation of ZI PV+ neuron activity with blue (for the ChR2 group to activate) or green (for the ArchT group to suppress) LED light was interleaved with control trials in which only sound was delivered. The efficacies of ChR2 and ArchT were confirmed by slice whole-cell recordings showing that blue LED light evoked robust spiking in ChR2-expressing neurons and green LED light induced a strong hyperpolarization of the membrane potential in ArchT-expressing cells (Figure 3—figure supplement 1B–C). We found that activation of ZI PV+ neurons enhanced flight response induced by noise stimulation (Figure 3A–C, Figure 3—figure supplement 1D–E), whereas suppression of these neurons reduced the flight response (Figure 3D–F, Figure 3—figure supplement 1F–G). None of the manipulations affected the temporal profile of the behavioral response (Supplementary file 1). As a control, neither activation nor suppression of ZIv PV+ neurons alone significantly affected the baseline locomotion (Figure 3—figure supplement 2). We next expressed Cre-dependent inhibitory designer receptors exclusively-activated by designer drugs (DREADDi) (Zhu and Roth, 2014), hM4D(Gi), in ZI of PV-Cre mice, and intraperitoneally injected the DREADDi agonist, clozapine-N-oxide (CNO) (Figure 3G). The efficacy of DREADDi inhibition was confirmed by slice recording showing that CNO increased the threshold for spiking and decreased the number of spikes evoked by current injections (Figure 3—figure supplement 3). The chemogenetic silencing of ZIv PV+ neurons prevented the enhancement of noise-induced flight response by whisker stimulation (Figure 3G–I) without affecting the response temporal profile (Supplementary file 1).

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We next performed awake single-unit optrode recordings in ZI, following our previous study (Zhang et al., 2018). ZIv PV+ neurons were optogenetically identified by their time-locked spike responses to blue laser pulses (Figure 3J). We found that these neurons responded to both noise sound and whisker deflections and that concurrent whisker deflections increased the response level to noise (Figure 3K–L). This result indicates that ZIv PV+ neurons can integrate tactile and auditory inputs and that tactile input plays a faciliatory role, consistent with the behavioral results. Altogether, our results strongly suggest that the tactile enhancement of flight behavior is mediated primarily by ZIv PV+ neurons.

To identify which downstream target nucleus of ZIv PV+ neurons is involved in the behavioral modulation, we traced the projections from ZIv PV+ neurons by injecting AAV encoding Cre-dependent GFP in PV-Cre mice (Figure 4A). Consistent with previous results (Barthó et al., 2002; Trageser and Keller, 2004), we found that two targets, the medial posterior complex of thalamus (POm) and superior colliculus (SC), received the strongest projections from ZIv PV+ neurons (Figure 4B, Figure 4—figure supplement 1). We then specifically activated the ZIv PV+ projection to POm or SC by placing optic fibers on top of POm or SC, respectively, in PV-Cre mice injected with AAV encoding Cre-dependent ChR2 in ZI (Figure 4C,F). While activation of the ZIv-SC projection did not significantly change the flight speed (Figure 4C–E), that of the ZIv-POm projection significantly increased the flight speed (Figure 4F–H, Figure 4—figure supplement 2A–B), similar to the activation of ZIv PV+ neuron cell bodies. As a control, activation of the ZIv-POm projection alone did not change the baseline locomotion speed (Figure 4—figure supplement 2C). To confirm that the ZIv-POm projection is necessary for the tactile modulation, we expressed Cre-dependent hM4D(Gi) in ZI of PV-Cre mice and locally infused CNO into POm through implanted cannulas (Figure 4I). The chemogenetic silencing of the ZIv-POm projection prevented the enhancement of flight speed by whisker stimulation (Figure 4I–K). None of the manipulations affected the temporal profile of flight response (Supplementary file 1). Taken together, our results demonstrate that the projection of ZIv PV+ neurons to POm primarily mediates the enhancement of sound-induced flight behavior by tactile stimulation.

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In this study, we demonstrate that additional tactile stimulation enhances flight behavior triggered by threats such as loud noise. Both SSp and ZIv PV+neurons, which receive SSp input, are necessary for this modulation, and activation of the SSp-ZIv projection is sufficient for driving the enhancement of the behavior. We also demonstrate that activation of ZIv PV+ neurons alone can enhance the flight behavior and that inactivation of the PV+ neurons or their projections to POm blocks the tactile enhancement of the flight behavior. Together, our data suggest that tactile input through whisker deflections can modulate defensive flight via the SSp-ZIv-POm pathway.

Rodents frequently use their whiskers to locate and identify objects (O'Connor et al., 2013; Pammer et al., 2013). In complex sensory environments, whiskers are essential for them to gather information from surroundings as to guide their behaviors during exploration and navigation (Ahl, 1986; Diamond et al., 2008; Sofroniew et al., 2014; Yu et al., 2016). When escape behavior is concerned, specific somatosensory input plus loud sound may indicate the immediate proximity of a predator, and enhancement of flight at such moments will greatly increase survival chances of prey animals. In addition, information conveyed by the somatosensory system about the environment could be extremely useful for the prey animal to quickly choose an effective escape route (Diamond et al., 2008; Douglass et al., 2008). Therefore, the ability to integrate somatosensory input and modulate defensive flight behavior accordingly is beneficial for animals to avoid dangers. Here, we show that somatosensory input from whiskers can enhance auditory-induced flight response. Indeed, in freely moving mice, trimming of whiskers reduces the efficiency of their escape from a source of loud noise by crossing through a channel, indicating a faciliatory role of the tactile input.

The tactile-auditory cross-modality modulation relies on conveying somatosensory information primarily from SSp to ZI. ZI has been implicated in maintaining normal posture and locomotor functions (Edwards and Isaacs, 1991), as it sends dense projections to motor-related thalamic and brainstem nuclei (Kolmac et al., 1998; Shaw and Mitrofanis, 2002). The somatosensory input to ZI thus has a potential to influence motor functions (Périer et al., 2002; Supko et al., 1991). In this study, we show that SSp projections to ZI are mainly concentrated in ZIv, where PV+ neurons are a major cell type (Mitrofanis, 2005; Zhou et al., 2018). Consistent with this projection, PV+ neurons in ZIv receive direct excitatory input from SSp and respond to whisker deflections. Concurrent whisker deflections also increase their responses to sound, indicating that tactile-auditory integration takes place in ZIv PV+ neurons. Activating SSp-ZIv axon terminals or ZIv PV+ neurons directly enhances auditory-induced flight, while silencing the PV+ neurons abolishes the enhancement of flight by tactile stimulation. Therefore, our data demonstrate that via the SSp-ZIv pathway mediated mainly by ZIv PV+ neurons, somatosensory input can modulate motor functions in defensive behavior. Whether ZIv PV+ neurons are involved specifically in tactile-auditory integration or multisensory integration in general remains to be further investigated.

Different ZI sectors are dominated by distinct cell types (Mitrofanis, 2005; Ricardo, 1981). It has been suggested that different ZI cell types or sectors may exhibit different connectivity patterns (Mitrofanis, 2005), contributing to ZI’s multiplex roles in various physiological functions. For example, it has been shown that activation of GABAergic neurons in the rostral sector of ZI (ZIr), which are likely PV-negative, can induce binge-like eating via its projections to the periventricular nucleus of thalamus (Zhang and van den Pol, 2017), while Lhx6-expressing neurons in ZIv, which are also PV-negative, can regulate sleep through their projections to hypothalamic areas (Liu et al., 2017). Different sectors or cell types may also play different roles in defensive behavior. Indeed, we have previously shown that activation of ZIr GABAergic neurons reduces noise-induced flight via their projections to the periaqueductal gray (PAG) (Chou et al., 2018). This effect is opposite to that of activating ZIv PV+ neurons, which have few projections to PAG (Figure 4—figure supplement 1). More recently, using conditioned freezing response as a model, a study of ZIv PV+ neurons has shown that both silencing the PV+ neuron output and silencing the amygdala inhibitory input to the PV+ neurons disrupt fear memory acquisition as well as recall of remote fear memory (Zhou et al., 2018). In the current study, the behavior we examined is an innate defensive behavior. Therefore, ZIv PV+ neurons can play a role in regulating both innate and learned defensive behaviors, which are generated under different contexts and likely engage different upstream pathways. It would be interesting to investigate in the future how ZI, through interactions among its different cell-types/subdivisions, regulates behaviors in complex sensory and behavioral environments.

We have identified POm as a target of ZIv PV+ neurons that is mainly responsible for the tactile enhancement of flight behavior. Silencing of the projection from ZIv PV+ neurons to POm prevents the faciliatory effect of tactile stimulation. PV+ neurons in ZI are GABAergic (Barthó et al., 2002) and provide inhibition to their target neurons. To achieve the effect of enhancing the behavioral output, disinhibitory circuits may be involved. POm is known to project to the striatum to modulate locomotion (Ohno et al., 2012; Smith et al., 2012). The inhibitory nature of striatal neurons makes them a good candidate for engaging disinhibition of distant output responses (Grillner et al., 2005; Kreitzer and Malenka, 2008). Furthermore, we have shown previously that the noise-induced flight behavior depends on a pathway from the auditory cortex (AC) to the cortex of inferior colliculus (ICx) and then to PAG (Xiong et al., 2015). It is possible that the ZIv-POm pathway directly or indirectly connect to midbrain areas downstream of the AC-ICx-PAG pathway (Marchand and Hagino, 1983; Roseberry et al., 2016). As such, somatosensory information carried by the ZIv-POm pathway can modulate the auditory-induced behavior mediated by the AC-ICx-PAG pathway. It would be interesting to investigate in the future whether and how the POm-striatal circuit is involved in this modulation.

Overall, ZI has complex input and output connectivity patterns (Chou et al., 2018; Nicolelis et al., 1992; Roger and Cadusseau, 1985; Shammah-Lagnado et al., 1985; Zhou et al., 2018). Through convergent and divergent connectivity with various brain areas, ZI may be able to carry out multiple physiological and behavioral functions synergistically.

All experimental procedures used in this study were approved by the Animal Care and Use Committee at the University of Southern California. Male and female wild-type (C57BL/6) and transgenic (PV-ires-Cre; Ai14-tdTomato) mice aged 8–16 weeks were obtained from the Jackson Laboratory. Mice were housed on 12 hr light/dark cycle, with food and water provided ad libitum.

All data generated or analysed during this study are included in the manuscript and supporting files. The data for each figure have been provided as source data files and the code used for data analysis can be found at https://github.com/xiaolinchou/flight-speed-calculation (copy archived at https://github.com/elifesciences-publications/flight-speed-calculation).

1. 1. Ahl AS

   (1986) The role of vibrissae in behavior: a status review

   Veterinary Research Communications 10:245–268.

   https://doi.org/10.1007/BF02213989

   • PubMed
   • Google Scholar
2. 1. Barthó P
   2. Freund TF
   3. Acsády L

   (2002) Selective GABAergic innervation of thalamic nuclei from zona incerta

   European Journal of Neuroscience 16:999–1014.

   https://doi.org/10.1046/j.1460-9568.2002.02157.x

   • PubMed
   • Google Scholar
3. 1. Boyden ES
   2. Zhang F
   3. Bamberg E
   4. Nagel G
   5. Deisseroth K

   (2005) Millisecond-timescale, genetically targeted optical control of neural activity

   Nature Neuroscience 8:1263–1268.

   https://doi.org/10.1038/nn1525

   • PubMed
   • Google Scholar
4. 1. Carvell GE
   2. Simons DJ

   (1990) Biometric analyses of vibrissal tactile discrimination in the rat

   The Journal of Neuroscience 10:2638–2648.

   https://doi.org/10.1523/JNEUROSCI.10-08-02638.1990

   • PubMed
   • Google Scholar
5. 1. Chou X-lin
   2. Wang X
   3. Zhang Z-gang
   4. Shen L
   5. Zingg B
   6. Huang J
   7. Zhong W
   8. Mesik L
   9. Zhang LI
   10. Tao HW

   (2018) Inhibitory gain modulation of defense behaviors by zona incerta

   Nature Communications 9:1–12.

   https://doi.org/10.1038/s41467-018-03581-6

   • Google Scholar
6. 1. Chow BY
   2. Han X
   3. Dobry AS
   4. Qian X
   5. Chuong AS
   6. Li M
   7. Henninger MA
   8. Belfort GM
   9. Lin Y
   10. Monahan PE
   11. Boyden ES

   (2010) High-performance genetically targetable optical neural silencing by light-driven proton pumps

   Nature 463:98–102.

   https://doi.org/10.1038/nature08652

   • PubMed
   • Google Scholar
7. 1. Diamond ME
   2. von Heimendahl M
   3. Knutsen PM
   4. Kleinfeld D
   5. Ahissar E

   (2008) 'Where' and 'what' in the whisker sensorimotor system

   Nature Reviews Neuroscience 9:601–612.

   https://doi.org/10.1038/nrn2411

   • PubMed
   • Google Scholar
8. 1. Douglass AD
   2. Kraves S
   3. Deisseroth K
   4. Schier AF
   5. Engert F

   (2008) Escape behavior elicited by single, channelrhodopsin-2-evoked spikes in zebrafish somatosensory neurons

   Current Biology 18:1133–1137.

   https://doi.org/10.1016/j.cub.2008.06.077

   • PubMed
   • Google Scholar
9. 1. Edwards DA
   2. Isaacs S

   (1991) Zona incerta lesions: effects on copulation, partner-preference and other socio-sexual behaviors

   Behavioural Brain Research 44:145–150.

   https://doi.org/10.1016/S0166-4328(05)80019-1

   • PubMed
   • Google Scholar
10. 1. Fanselow MS

    (1994) Neural organization of the defensive behavior system responsible for fear

    Psychonomic Bulletin & Review 1:429–438.

    https://doi.org/10.3758/BF03210947

    • PubMed
    • Google Scholar
11. 1. Fanselow MS
    2. LeDoux JE

    (1999) Why we think plasticity underlying pavlovian fear conditioning occurs in the basolateral amygdala

    Neuron 23:229–232.

    https://doi.org/10.1016/S0896-6273(00)80775-8

    • PubMed
    • Google Scholar
12. 1. Grillner S
    2. Hellgren J
    3. Ménard A
    4. Saitoh K
    5. Wikström MA

    (2005) Mechanisms for selection of basic motor programs--roles for the striatum and pallidum

    Trends in Neurosciences 28:364–370.

    https://doi.org/10.1016/j.tins.2005.05.004

    • PubMed
    • Google Scholar
13. 1. Gross CT
    2. Canteras NS

    (2012) The many paths to fear

    Nature Reviews Neuroscience 13:651–658.

    https://doi.org/10.1038/nrn3301

    • PubMed
    • Google Scholar
14. 1. Ibrahim LA
    2. Mesik L
    3. Ji XY
    4. Fang Q
    5. Li HF
    6. Li YT
    7. Zingg B
    8. Zhang LI
    9. Tao HW

    (2016) Cross-Modality sharpening of visual cortical processing through Layer-1-Mediated inhibition and disinhibition

    Neuron 89:1031–1045.

    https://doi.org/10.1016/j.neuron.2016.01.027

    • PubMed
    • Google Scholar
15. 1. Ji XY
    2. Zingg B
    3. Mesik L
    4. Xiao Z
    5. Zhang LI
    6. Tao HW

    (2016) Thalamocortical innervation pattern in mouse auditory and visual cortex: laminar and Cell-Type specificity

    Cerebral Cortex 26:2612–2625.

    https://doi.org/10.1093/cercor/bhv099

    • PubMed
    • Google Scholar
16. 1. Kolmac CI
    2. Power BD
    3. Mitrofanis J

    (1998) Patterns of connections between zona incerta and brainstem in rats

    The Journal of Comparative Neurology 396:544–555.

    https://doi.org/10.1002/(SICI)1096-9861(19980713)396:4<544::AID-CNE10>3.0.CO;2-G

    • PubMed
    • Google Scholar
17. 1. Kolmac C
    2. Mitrofanis J

    (1999) Distribution of various neurochemicals within the zona incerta: an immunocytochemical and histochemical study

    Anatomy and Embryology 199:265–280.

    https://doi.org/10.1007/s004290050227

    • PubMed
    • Google Scholar
18. 1. Kreitzer AC
    2. Malenka RC

    (2008) Striatal plasticity and basal ganglia circuit function

    Neuron 60:543–554.

    https://doi.org/10.1016/j.neuron.2008.11.005

    • PubMed
    • Google Scholar
19. 1. Liang F
    2. Xiong XR
    3. Zingg B
    4. Ji XY
    5. Zhang LI
    6. Tao HW

    (2015) Sensory cortical control of a visually induced arrest behavior via corticotectal projections

    Neuron 86:755–767.

    https://doi.org/10.1016/j.neuron.2015.03.048

    • PubMed
    • Google Scholar
20. 1. Liu K
    2. Kim J
    3. Kim DW
    4. Zhang YS
    5. Bao H
    6. Denaxa M
    7. Lim SA
    8. Kim E
    9. Liu C
    10. Wickersham IR
    11. Pachnis V
    12. Hattar S
    13. Song J
    14. Brown SP
    15. Blackshaw S

    (2017) Lhx6-positive GABA-releasing neurons of the zona incerta promote sleep

    Nature 548:582–587.

    https://doi.org/10.1038/nature23663

    • PubMed
    • Google Scholar
21. 1. Ma TP
    2. Johnson JC
    3. Hoskins GA

    (1997) Organization of the zona incerta in the macaque: an electron microscopic study

    The Anatomical Record 249:259–275.

    https://doi.org/10.1002/(sici)1097-0185(199710)249:2<259::aid-ar14>3.0.co;2-n

    • PubMed
    • Google Scholar
22. 1. Marchand JE
    2. Hagino N

    (1983) Afferents to the periaqueductal gray in the rat. A horseradish peroxidase study

    Neuroscience 9:95–106.

    https://doi.org/10.1016/0306-4522(83)90049-0

    • PubMed
    • Google Scholar
23. 1. Mitrofanis J
    2. Ashkan K
    3. Wallace BA
    4. Benabid AL

    (2004) Chemoarchitectonic heterogeneities in the primate zona incerta: clinical and functional implications

    Journal of Neurocytology 33:429–440.

    https://doi.org/10.1023/B:NEUR.0000046573.28081.dd

    • PubMed
    • Google Scholar
24. 1. Mitrofanis J

    (2005) Some certainty for the "zone of uncertainty"? Exploring the function of the zona incerta

    Neuroscience 130:1–15.

    https://doi.org/10.1016/j.neuroscience.2004.08.017

    • PubMed
    • Google Scholar
25. 1. Nicolelis MA
    2. Chapin JK
    3. Lin RC

    (1992) Somatotopic maps within the zona incerta relay parallel GABAergic somatosensory pathways to the neocortex, superior colliculus, and brainstem

    Brain Research 577:134–141.

    https://doi.org/10.1016/0006-8993(92)90546-L

    • PubMed
    • Google Scholar
26. 1. O'Connor DH
    2. Hires SA
    3. Guo ZV
    4. Li N
    5. Yu J
    6. Sun QQ
    7. Huber D
    8. Svoboda K

    (2013) Neural coding during active somatosensation revealed using illusory touch

    Nature Neuroscience 16:958–965.

    https://doi.org/10.1038/nn.3419

    • PubMed
    • Google Scholar
27. 1. Ohno S
    2. Kuramoto E
    3. Furuta T
    4. Hioki H
    5. Tanaka YR
    6. Fujiyama F
    7. Sonomura T
    8. Uemura M
    9. Sugiyama K
    10. Kaneko T

    (2012) A morphological analysis of thalamocortical axon fibers of rat posterior thalamic nuclei: a single neuron tracing study with viral vectors

    Cerebral Cortex 22:2840–2857.

    https://doi.org/10.1093/cercor/bhr356

    • Google Scholar
28. 1. Pammer L
    2. O'Connor DH
    3. Hires SA
    4. Clack NG
    5. Huber D
    6. Myers EW
    7. Svoboda K

    (2013) The mechanical variables underlying object localization along the axis of the whisker

    Journal of Neuroscience 33:6726–6741.

    https://doi.org/10.1523/JNEUROSCI.4316-12.2013

    • PubMed
    • Google Scholar
29. 1. Périer C
    2. Tremblay L
    3. Féger J
    4. Hirsch EC

    (2002) Behavioral consequences of bicuculline injection in the subthalamic nucleus and the zona incerta in rat

    The Journal of Neuroscience 22:8711–8719.

    https://doi.org/10.1523/JNEUROSCI.22-19-08711.2002

    • PubMed
    • Google Scholar
30. 1. Petreanu L
    2. Mao T
    3. Sternson SM
    4. Svoboda K

    (2009) The subcellular organization of neocortical excitatory connections

    Nature 457:1142–1145.

    https://doi.org/10.1038/nature07709

    • PubMed
    • Google Scholar
31. 1. Plaha P
    2. Khan S
    3. Gill SS

    (2008) Bilateral stimulation of the caudal zona incerta nucleus for tremor control

    Journal of Neurology, Neurosurgery & Psychiatry 79:504–513.

    https://doi.org/10.1136/jnnp.2006.112334

    • Google Scholar
32. 1. Prigg T
    2. Goldreich D
    3. Carvell GE
    4. Simons DJ

    (2002) Texture discrimination and unit recordings in the rat whisker/barrel system

    Physiology & Behavior 77:671–675.

    https://doi.org/10.1016/S0031-9384(02)00917-4

    • PubMed
    • Google Scholar
33. 1. Ricardo JA

    (1981) Efferent connections of the subthalamic region in the rat. II. the zona incerta

    Brain Research 214:43–60.

    https://doi.org/10.1016/0006-8993(81)90437-6

    • PubMed
    • Google Scholar
34. 1. Roger M
    2. Cadusseau J

    (1985) Afferents to the zona incerta in the rat: a combined retrograde and anterograde study

    The Journal of Comparative Neurology 241:480–492.

    https://doi.org/10.1002/cne.902410407

    • PubMed
    • Google Scholar
35. 1. Roseberry TK
    2. Lee AM
    3. Lalive AL
    4. Wilbrecht L
    5. Bonci A
    6. Kreitzer AC

    (2016) Cell-Type-Specific control of brainstem locomotor circuits by basal ganglia

    Cell 164:526–537.

    https://doi.org/10.1016/j.cell.2015.12.037

    • PubMed
    • Google Scholar
36. 1. Shammah-Lagnado SJ
    2. Negrao N
    3. Silva BA
    4. Silva JA
    5. Ricardo JA

    (1985) Afferent connections of the magnocellular reticular formation: a horseradish peroxidase study in the rat

    Neuroscience 15:109–117.

    https://doi.org/10.1016/0306-4522(85)90127-7

    • Google Scholar
37. 1. Shaw V
    2. Mitrofanis J

    (2002) Anatomical evidence for somatotopic maps in the zona incerta of rats

    Anatomy and Embryology 206:119–130.

    https://doi.org/10.1007/s00429-002-0280-7

    • PubMed
    • Google Scholar
38. 1. Smith RL

    (1973) The ascending fiber projections from the principal sensory trigeminal nucleus in the rat

    The Journal of Comparative Neurology 148:423–445.

    https://doi.org/10.1002/cne.901480403

    • PubMed
    • Google Scholar
39. 1. Smith JB
    2. Mowery TM
    3. Alloway KD

    (2012) Thalamic POm projections to the dorsolateral striatum of rats: potential pathway for mediating stimulus-response associations for sensorimotor habits

    Journal of Neurophysiology 108:160–174.

    https://doi.org/10.1152/jn.00142.2012

    • PubMed
    • Google Scholar
40. 1. Sofroniew NJ
    2. Cohen JD
    3. Lee AK
    4. Svoboda K

    (2014) Natural whisker-guided behavior by head-fixed mice in tactile virtual reality

    Journal of Neuroscience 34:9537–9550.

    https://doi.org/10.1523/JNEUROSCI.0712-14.2014

    • PubMed
    • Google Scholar
41. 1. Supko DE
    2. Uretsky NJ
    3. Wallace LJ

    (1991) Activation of AMPA/kainic acid glutamate receptors in the zona incerta stimulates locomotor activity

    Brain Research 564:159–163.

    https://doi.org/10.1016/0006-8993(91)91367-A

    • PubMed
    • Google Scholar
42. 1. Tovote P
    2. Esposito MS
    3. Botta P
    4. Chaudun F
    5. Fadok JP
    6. Markovic M
    7. Wolff SB
    8. Ramakrishnan C
    9. Fenno L
    10. Deisseroth K
    11. Herry C
    12. Arber S
    13. Lüthi A

    (2016) Midbrain circuits for defensive behaviour

    Nature 534:206–212.

    https://doi.org/10.1038/nature17996

    • PubMed
    • Google Scholar
43. 1. Trageser JC
    2. Keller A

    (2004) Reducing the uncertainty: gating of peripheral inputs by zona incerta

    Journal of Neuroscience 24:8911–8915.

    https://doi.org/10.1523/JNEUROSCI.3218-04.2004

    • PubMed
    • Google Scholar
44. 1. Urbain N
    2. Deschênes M

    (2007) Motor cortex gates vibrissal responses in a thalamocortical projection pathway

    Neuron 56:714–725.

    https://doi.org/10.1016/j.neuron.2007.10.023

    • PubMed
    • Google Scholar
45. 1. Xiong XR
    2. Liang F
    3. Zingg B
    4. Ji XY
    5. Ibrahim LA
    6. Tao HW
    7. Zhang LI

    (2015) Auditory cortex controls sound-driven innate defense behaviour through corticofugal projections to inferior colliculus

    Nature Communications 6:7224.

    https://doi.org/10.1038/ncomms8224

    • PubMed
    • Google Scholar
46. 1. Yilmaz M
    2. Meister M

    (2013) Rapid innate defensive responses of mice to looming visual stimuli

    Current Biology 23:2011–2015.

    https://doi.org/10.1016/j.cub.2013.08.015

    • PubMed
    • Google Scholar
47. 1. Yu YS
    2. Graff MM
    3. Bresee CS
    4. Man YB
    5. Hartmann MJ

    (2016) Whiskers aid anemotaxis in rats

    Science Advances 2:e1600716–e1600718.

    https://doi.org/10.1126/sciadv.1600716

    • PubMed
    • Google Scholar
48. 1. Zhang GW
    2. Shen L
    3. Zhong W
    4. Xiong Y
    5. Zhang LI
    6. Tao HW

    (2018) Transforming Sensory Cues into Aversive Emotion via Septal-Habenular Pathway

    Neuron 99:1016–1028.

    https://doi.org/10.1016/j.neuron.2018.07.023

    • PubMed
    • Google Scholar
49. 1. Zhang X
    2. van den Pol AN

    (2017) Rapid binge-like eating and body weight gain driven by zona incerta GABA neuron activation

    Science 356:853–859.

    https://doi.org/10.1126/science.aam7100

    • PubMed
    • Google Scholar
50. 1. Zhou M
    2. Liang F
    3. Xiong XR
    4. Li L
    5. Li H
    6. Xiao Z
    7. Tao HW
    8. Zhang LI

    (2014) Scaling down of balanced excitation and inhibition by active behavioral states in auditory cortex

    Nature Neuroscience 17:841–850.

    https://doi.org/10.1038/nn.3701

    • PubMed
    • Google Scholar
51. 1. Zhou M
    2. Liu Z
    3. Melin MD
    4. Ng YH
    5. Xu W
    6. Südhof TC

    (2018) A central amygdala to zona incerta projection is required for acquisition and remote recall of conditioned fear memory

    Nature Neuroscience 21:1515–1519.

    https://doi.org/10.1038/s41593-018-0248-4

    • Google Scholar
52. 1. Zhu Y
    2. Wienecke CF
    3. Nachtrab G
    4. Chen X

    (2016) A thalamic input to the nucleus accumbens mediates opiate dependence

    Nature 530:219–222.

    https://doi.org/10.1038/nature16954

    • PubMed
    • Google Scholar
53. 1. Zhu H
    2. Roth BL

    (2014) Silencing synapses with DREADDs

    Neuron 82:723–725.

    https://doi.org/10.1016/j.neuron.2014.05.002

    • PubMed
    • Google Scholar
54. 1. Zingg B
    2. Chou XL
    3. Zhang ZG
    4. Mesik L
    5. Liang F
    6. Tao HW
    7. Zhang LI

    (2017) AAV-Mediated anterograde transsynaptic tagging: mapping corticocollicular Input-Defined neural pathways for defense behaviors

    Neuron 93:33–47.

    https://doi.org/10.1016/j.neuron.2016.11.045

    • PubMed
    • Google Scholar

Author details

1. Xiyue Wang

   1. Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, United States
   2. Graduate Program in Neuroscience, University of Southern California, Los Angeles, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Investigation

   Contributed equally with

   Xiaolin Chou

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-5805-0778

2. Xiaolin Chou

   1. Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, United States
   2. Graduate Program in Neuroscience, University of Southern California, Los Angeles, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Investigation

   Contributed equally with

   Xiyue Wang

   Competing interests

   No competing interests declared

3. Bo Peng

   1. Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, United States
   2. Graduate Program in Neuroscience, University of Southern California, Los Angeles, United States

   Contribution

   Data curation

   Competing interests

   No competing interests declared

4. Li Shen

   Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, United States

   Contribution

   Data curation

   Competing interests

   No competing interests declared

5. Junxiang J Huang

   1. Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, United States
   2. Graduate Program in Biomedical and Biological Sciences, University of Southern California, Los Angeles, United States

   Contribution

   Data curation

   Competing interests

   No competing interests declared

6. Li I Zhang

   1. Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, United States
   2. Department of Physiology and Neuroscience, Keck School of Medicine, University of Southern California, Los Angeles, United States

   Contribution

   Conceptualization, Funding acquisition, Writing—review and editing

   For correspondence

   liizhang@usc.edu

   Competing interests

   No competing interests declared

7. Huizhong W Tao

   1. Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, United States
   2. Department of Physiology and Neuroscience, Keck School of Medicine, University of Southern California, Los Angeles, United States

   Contribution

   Conceptualization, Funding acquisition, Writing—review and editing

   For correspondence

   htao@usc.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-3660-0513

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