Parkinson’s disease is a condition affecting the human brain that becomes worse over time. The most common symptoms are tremors, muscle spasms and movements that are much slower than normal; all of which decrease an individual’s quality of life. Although there is currently no cure, the brain structures involved in Parkinson’s disease are known. These are collectively termed the basal ganglia, and are often targeted to treat the symptoms of Parkinson’s disease. For example, electrically stimulating the subthalamic nucleus (STN), one part of the basal ganglia, reduces muscle tremors and stiffness.

Pain is another common symptom in Parkinson’s disease. Patients often report strange burning or stabbing sensations with no obvious physical cause. They are also likely to be more sensitive to painful stimuli and have a lower pain threshold than normal. This suggested that the brain circuits that allow us to perceive and process pain could be somehow involved in Parkinson’s disease. Indeed, stimulating the STN is known to relieve pain in Parkinson’s disease, as well as the muscle symptoms, but exactly how the STN might link up with the brain’s ‘pain network’ remains poorly understood. Pautrat et al. therefore set out to explore the connection between pain networks and the STN, and determine its potential role in Parkinson’s disease.

First, the electrical activity of nerve cells in the STN of rats was measured, which revealed that these cells do respond to mildly painful sensations. Experiments using dyes to label cells in both the STN and brain structures known to transmit painful signals showed that the STN was indeed directly linked to the brain’s pain network. Moreover, rats with a STN that did not work properly also responded abnormally to painful stimuli, confirming that the STN did indeed influence their perception of pain. Finally, Pautrat et al. repeated their measurements of electrical activity in the STN, this time using rats that lacked the same group of nerve cells affected in the basal ganglia of patients with Parkinson’s disease. Such rats are commonly used to model the disease in laboratory experiments. In these rats, the STN cells responded very strongly to painful stimuli, suggesting that problems with the STN could be causing some of the pain symptoms in Parkinson’s disease.

This work reveals a new role for the STN in controlling responses to pain, both in health and disease. Pautrat et al. hope that their results will inspire research into more effective treatments of nerve pain in both Parkinson’s disease and other neurodegenerative conditions.

Pain is highly prevalent in Parkinson’s disease (PD) and includes primary symptoms assumed to originate from a dysfunction of the central nervous system. Patients describe bizarre and unexplained painful sensations such as burning, stabbing, aching, itching or tingling sensations, predominating on the more affected side (Schestatsky et al., 2007). These symptoms are not directly related to the pain caused by the motor symptoms (Ha and Jankovic, 2012). Sensitivity to noxious stimulation is also increased in patients with PD, with or without pain symptoms (Berardelli et al., 2012; Brefel-Courbon et al., 2013; Tinazzi et al., 2008), and their nociceptive threshold is altered (Chudler and Dong, 1995; Conte et al., 2013; Djaldetti et al., 2004). Although it is well known that PD affects the basal ganglia, there is to date no clear description of a link between the basal ganglia and the cerebral network involved in pain. Interestingly, deep brain stimulation of the subthalamic nucleus (STN-DBS) in PD, a valuable and effective therapeutic technique for motor symptoms (Krack et al., 2003; Limousin et al., 1998), has also been shown to reduce pain (Cury et al., 2014; Hanagasi et al., 2011; Kim et al., 2008; Klingelhoefer et al., 2014). By contrast, the effects of dopamine replacement therapy on the pain symptoms in PD are controversial, with some investigations reporting an improvement, no effect or an aggravation of pain symptoms or nociceptive thresholds (Conte et al., 2013; Dellapina et al., 2011). These variable results of dopamine replacement therapy indicate a role for other systems in the pain symptoms observed in PD. Importantly in the present context, it has been demonstrated that pain relief following STN-DBS is superior to that following dopaminergic treatment, further positioning STN as a crucial structure in pain symptoms in PD and their relief (Sürücü et al., 2013).

The mechanism by which STN-DBS improves pain in PD patients remains unclear, which raises a fundamental question about the link between the subthalamic nucleus (STN) and pain. Preliminary evidence suggests that noxious stimulation can modulate background activity in the STN, at least in the Parkinsonian brain (Belasen et al., 2016; Heise et al., 2008). As a consequence, the STN could be linked to a nociceptive network involved in the perception of noxious stimuli, although this has yet to be explored fully. Despite the classical description of a sensory territory in the STN (Alexander et al., 1986) and the functional impact that STN sensory responses could have on the basal ganglia (Baunez et al., 2011), there is a paucity of information in the literature regarding the type of sensory stimuli that activate this structure and the afferent sensory source(s) (Coizet et al., 2009; Hammond et al., 1978; Matsumura et al., 1992). Two major subcortical central targets for ascending nociceptive information from the spinal cord are potential relays for nociceptive information to the STN: the superior colliculus (SC) and the parabrachial nucleus (PBN) (Hylden et al., 1989; Craig, 1995; Klop et al., 2005; McHaffie et al., 1989).

We have shown that the SC, a highly conserved but evolutionarily ancient subcortical multi-sensory structure, directly projects to the STN and is the primary, if not exclusive, source of visual input into the STN (Coizet et al., 2009; Tokuno et al., 1994). This projection shows that subcortical hyper-direct pathways exist between brainstem sensorimotor structures and the STN which predate, from an evolutionary perspective, those from the cortex — thus reinforcing the position of the STN as a critical input structure processing short latency visual signals in the basal ganglia (Baunez et al., 2011). The substantia nigra pars compacta (SNc) is also on the input side of the basal ganglia and we have shown that SNc receives nociceptive-related afferents from the PBN (Coizet et al., 2010), raising the possibility that the STN may also receive such inputs.

It is interesting to note that the STN is well known to project heavily to basal ganglia output structures such as the substantia nigra pars reticulata (SNr) (Alexander et al., 1986; Gurney et al., 2001), which in turn projects to the SC and PBN (Schneider, 1986; Deniau and Chevalier, 1992), linking the STN, SNr and SC/PBN anatomically. With the STN in a position to modulate a nociceptive network involving the SC/PBN, the elevated activity in the STN in Parkinsonism (Bergman et al., 1994; Albin et al., 1995) could underlie some of the unexplained pain symptoms in this disease, with STN-DBS acting (at least in part) locally to achieve its analgesic effects. Nociceptive processing in the STN would also be consistent with the nucleus’s role as part of the brain’s interrupt circuitry (Jahanshahi et al., 2015), terminating behaviors that achieve negative outcomes, of which pain is a clear example.

Therefore, the main objective of the present work was to characterize the link between STN and nociception, answering the following questions:

• Does the STN process nociceptive information? We explored the possibility that noxious stimulation could induce nociceptive responses in the rat STN with in vivo electrophysiology.

• Is the STN linked to a nociceptive network? We tested the potential role of the SC and PBN in the transmission of nociceptive information to the STN, both physiologically and, in the case of the PBN, anatomically.

• Can manipulation of the integrity of the STN change nociceptive responses measured behaviorally? We tested STN-lesioned and sham-operated rats using a hotplate test.

• Finally, to examine the hypothesis that STN dysfunction could underlie some of the pain symptoms observed in PD, we evaluated whether STN nociceptive responses were abnormal in a rat model of PD.

We present convergent evidence that the STN is functionally linked to a nociceptive network and that STN nociceptive responses are affected in Parkinsonism. The objectives above are summarized in Figure 1.

Figure 1

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The present study demonstrates for the first time that a large majority of STN neurons exhibit various mono- or multi-phasic responses to noxious stimulation, consistent with the hypothesis that one of the functions of the STN is to interrupt behavior when appropriate (Jahanshahi et al., 2015); in this case, to select a more appropriate action to try to relieve the noxious sensation. STN nociceptive responses mainly had a short latency (~20–40 ms) and could be recorded all over the structure. We have shown that most of the responsive cells are nociceptive-specific, as only few of them also respond to non-noxious somatosensory stimulation. In addition, we found that we could differentiate three types of STN neurons, which showed an increase, a decrease or no change, respectively, in their baseline firing rate upon introduction of the noxious stimulation. The spontaneous firing rate of STN ‘down’ cells was significantly higher than that of the two other groups, suggesting the possibility of a separate group of cells. Furthermore, we have shown that STN responses to nociceptive stimuli were abnormal in a rat model of PD, suggesting that the nociceptive responses recorded in STN depend on the integrity of the nigrostriatal DA system.

When determining the afferent source of nociception-related influence on STN activity, we have revealed a crucial role for two brainstem structures, the PBN and the SC, by demonstrating the effects of their inactivation on nociceptive responses in the STN and also by highlighting the existence of an anatomical direct pathway from the PBN to the STN. This parabrachio-subthalamic projection represents a second example of a subcortical hyperdirect pathway to the STN from a sensori-motor structure, in addition to the tecto-subthalamic pathway described previously (Coizet et al., 2009; Tokuno et al., 1994). Finally, we have shown that these anatomico-electrophysiological findings translate into a functional role for the STN in mediating nociception, in that nociceptive behavioral responses were affected by lesions of the STN. However, a note of caution is required since we used only male rats, and thus care should be taken in extrapolating our results to females.

Using noxious electrical stimulation of the hindpaw allowed us to record precisely the timing of responses in our structures of interest with controlled parameters of stimulation. It is interesting to note that the majority of STN nociceptive responses had short latencies (76/79) and were monophasic (40/79), a pattern of responses that is similar in proportion to the pattern of STN responses following visual stimulation (Coizet et al., 2009) but dissimilar to the pattern of STN responses following stimulation of the frontal (Magill et al., 2004), sensorimotor (Fujimoto and Kita, 1993) or motor cortex (Kolomiets et al., 2001). The latter — in the majority of cases — are multi-phasic, with two excitatory phases (equivalent to the present biphasic +/+) often separated by an inhibition (equivalent to the present triphasic +/–/+). It has been hypothesized previously (Magill et al., 2004; Kitai and Deniau, 1981) that the short latency excitation following cortical stimulation appears to be driven by a hyperdirect pathway to the STN,whereas the later phases of the response arise from polysynaptic interactions, which are manifested more slowly. The inhibition following the first excitation has been hypothesized to involve the reciprocally connected STN–globus pallidus (GP) network (Fujimoto and Kita, 1993). STN excitation may activate GP GABAergic neurons, which in return inhibit the STN. Overall, our data suggest that when the rat is subjected to noxious stimulation, the main pathway to the STN that is activated is a fast hyperdirect pathway, originating in part in the PBN. The fact that we only have a few cells showing an inhibitory second phase (10 biphasic and 5 triphasic, 15/79) indicates that STN nociceptive cells are rarely closely connected to the GP and lack GP-STN feedforward control.

Functionally antagonistic STN neuronal subpopulations have been found in the STN. Specific GO and STOP cells have been described in PD patients performing a stop signal paradigm, during motor execution or response inhibition, respectively (Benis et al., 2016). Sub-populations of STN cells have also been shown to code exclusively for reward magnitude (4% vs 32% sucrose [Lardeux et al., 2009]), error-related activity (‘Oops neurons’ [Lardeux et al., 2009]), reward value (cocaine or sucrose [Lardeux et al., 2013]) and for positive and aversive reinforcers (Breysse et al., 2015).

A major finding of our work is that we were able to differentiate a subpopulation of STN neurons that had a higher spontaneous firing rate on the basis of the effect of noxious stimuli on general tonic activity. This finding is important as glutamatergic tone from the STN is likely to have a strong impact on the tonic level of activity in the basal ganglia network, especially in the output structures (as we hypothesized that nociceptive-responding STN cells may not be densely connected to GP). The results from previous computational studies (Gurney et al., 2001) suggest that tonic control by the STN may adjust the general level of activity of the inhibitory GABAergic neurons of the basal ganglia output structures, which are known to project to the SC and PBN (Schneider, 1986; Deniau and Chevalier, 1992). This tonic STN control is hypothesized to be used by the basal ganglia to optimize selection of the most appropriate action. The identification of separate subpopulations of cells in the STN according to their spontaneous firing rate, and the orientation of the change of their firing rate following the occurrence of noxious stimulation,suggests that the tonic excitatory effects of the STN may not be uniform, although further work is required to elucidate the connectivity of the STN subpopulations. This mechanism is important in the context of PD in which STN activity is pathologically increased (Bergman et al., 1994; Albin et al., 1995), probably disrupting this control. This possibility is further supported by our results showing enhanced phasic nociceptive responses in a PD rat model, with an increase in the latency to make nocifensive responses in the hotplate test following lesions of the STN. As well as interfering with action selection, disrupted STN control in PD would probably have an impact on the SC and PBN and their role in sensory signal processing.

In addition to demonstrating that STN neurons process nociceptive information, we also assessed whether two subcortical sensori-motor structures from the brain stem transmit nociceptive signals to the STN. Despite SC nociceptive responses having shorter latencies than those of STN neurons to the same stimulus, chemical suppression and lesions of SC had relatively minor effects on the responses of STN to noxious footshock. Lesions of the SC with acid ibotenic reduced the number of cells that do not respond to noxious stimulation, suggesting that the SC gates the pool of responding cells in the STN. Our previous work has demonstrated that the SC is a critical relay for short-latency visual input into DA neurons (Dommett et al., 2005) but not for short-latency nociceptive input (Coizet et al., 2006) transmitted by the PBN (Coizet et al., 2010). The current results suggest the same organization when considering visual and nociceptive input into the STN. The SC is a crucial structure to transmit visual information while the PBN strongly contributes to the relay of nociceptive signals. PBN lesions significantly reduced the number of STN cells responding to noxious stimuli, sparing a group of cells with short latency short duration responses (Figure 7C), which are possibly activated by nociceptive information relayed by the thalamus (Dostrovsky, 2000a). This nociceptive network linked to the STN is the probable substrate underlying the successful analgesic effects of STN deep-brain stimulation. Kim et al. (2012) hypothesized that STN-DBS improves secondary pain symptoms in PD because this stimulation decreases the abnormally increased muscle tone in patients and may alleviate the primary nociception processing in the central nervous system. DBS effects are complex and despite the success of DBS in treating a variety of psychiatric and neurological disorders, the mechanisms underpinning its therapeutic efficacy remain unclear (McIntyre et al., 2004; Ashkan et al., 2017). DBS is hypothesized to induce a ‘functional lesion’ of the STN (Follett, 2000), via depolarization blockade and synaptic inhibition (Beurrier et al., 2001; Dostrovsky et al., 2000b), which would lead to a suppression of the activity of STN neurons. We hypothesize that these mechanisms would reduce the pathologically increased firing rate in the STN in PD (and thus the pain symptoms), as well as nociceptive responses.

Our current work using anterograde tract-tracing neuroanatomy coupled with 3D reconstruction indicates that a small ascending bundle leaves the PBN and then splits into three massive projections traveling toward the SC, the thalamus and the SNc/STN. Some fibers from this last ascending pathway continue rostrally to terminate in the amygdala and the cortex. Comparison of the size of the bundle leaving the PBN and the size of the bundles traveling to their targets indicate that the number of labelled fibers clearly increase, suggesting that PBN axons have collaterals. This PBN-STN projection is possibly interconnected with other PBN efferents, such as the PBN–amygdala projection, which partly travels through the STN and has cells of origin that are of a similar type to those of the PBN cells projecting to STN (Sarhan et al., 2005). With a DBS effect on axons and fibers (Chiken and Nambu, 2014), the characterization of this projection and network are important in the context of the effects of STN-DBS on pain symptoms. Overall, STN-DBS would not only impact STN and PBN nociceptive processing but would also modulate PBN-amygdala fibers and possibly other PBN efferents via the collaterals. The effect of STN-DBS would therefore impact many aspects of pain such as, for example, pain-related emotional reactions when activating the PBN-amygdaloid connection or neuroendocrine homeostatic regulation in response to pain by activating the PBN-hypothalamic pathway (Gauriau and Bernard, 2002). Further experiments are now needed to fully characterize the effect of STN-DBS on nociceptive processing in our rat models and how aspects of that network are modulated to achieve a DBS-related analgesic effect.

Pain is a multifaceted experience that can be understood in terms of somatosensory, affective and cognitive dimensions. DBS therapies that are focused on a single facet of pain, originally targeting somatosensory networks or more recently targeting affective regions (Schneider, 1986). The STN is a small structure with functional territories such as the limbic, cognitive and sensory, in close proximity to each other. This would allow the potential modulation of different modalities of pain and, in the future, the best placements of DBS electrodes within those territories would have to be tested to maximize the analgesic effect. Finally, numerous non-motor symptoms can worsen or improve depending on the electrical stimulation parameters, as well as the location of the electrode (Kim et al., 2015). The best parameters of stimulation for nociception would need to take into account the effect of those parameters on other symptoms of PD.

Finally, non-neuropathic pain, recently recognized as a frequent and disabling symptom in PD, is a complaint affecting many patients who have numerous neurodegenerative disease such as Alzheimer’s disease and other dementias, motor neuron disease, Huntington’s disease, spinocerebellar ataxia and spinal muscular atrophy (de Tommaso et al., 2016). Our findings on the involvement of the STN in nociceptive processing and its link to a nociceptive network open a new direction for research to explore a possible role of this structure in other pain syndromes, especially extra-pyramidal ones like Huntington’s disease, which is characterized by a dysfunction of the basal ganglia. It also opens up the possibility of developing therapeutic strategies using DBS. A variety of brain sites have been identified for chronic stimulation procedures to attenuate pain (Davis et al., 1998). These targets include the thalamus, the periventricular gray nucleus, the cingulate cortex and the motor cortex (Gorecki et al., 1989; Davis et al., 1998). With the involvement of the STN in a nociceptive network as demonstrated in our work, the STN-DBS technique can thus be considered in the future as a new target for the treatment of pain not only in pharmaco-resistant patients suffering from previously described neurodegenerative disease, but also, for example, in those with chronic pain disease or pharmaco-resistant patients with certain forms of migraine that have been shown to activate the STN (Schwedt et al., 2014).

All data generated or analysed during this study are included in the manuscript and supporting files. Matlab scripts used to analyse the data are freely available on the ImaGIN platform website (https://f-tract.eu/software/imagin/ ; copy of the source code archived at https://github.com/elifesciences-publications/ImaGIN2_source_code).

1. 1. Albin RL
   2. Young AB
   3. Penney JB

   (1995) The functional anatomy of disorders of the basal ganglia

   Trends in Neurosciences 18:63–64.

   https://doi.org/10.1016/0166-2236(95)80020-3

   • Google Scholar
2. 1. Alexander GE
   2. DeLong MR
   3. Strick PL

   (1986) Parallel organization of functionally segregated circuits linking basal ganglia and cortex

   Annual Review of Neuroscience 9:357–381.

   https://doi.org/10.1146/annurev.ne.09.030186.002041

   • PubMed
   • Google Scholar
3. 1. Almeida TF
   2. Roizenblatt S
   3. Tufik S

   (2004) Afferent pain pathways: a neuroanatomical review

   Brain Research 1000:40–56.

   https://doi.org/10.1016/j.brainres.2003.10.073

   • PubMed
   • Google Scholar
4. 1. Ashkan K
   2. Rogers P
   3. Bergman H
   4. Ughratdar I

   (2017) Insights into the mechanisms of deep brain stimulation

   Nature Reviews Neurology 13:548–554.

   https://doi.org/10.1038/nrneurol.2017.105

   • PubMed
   • Google Scholar
5. 1. Baunez C
   2. Yelnik J
   3. Mallet L

   (2011) Six questions on the subthalamic nucleus: lessons from animal models and from stimulated patients

   Neuroscience 198:193–204.

   https://doi.org/10.1016/j.neuroscience.2011.09.059

   • PubMed
   • Google Scholar
6. 1. Belasen A
   2. Youn Y
   3. Gee L
   4. Prusik J
   5. Lai B
   6. Ramirez-Zamora A
   7. Rizvi K
   8. Yeung P
   9. Shin DS
   10. Argoff C
   11. Pilitsis JG

   (2016) The effects of mechanical and thermal stimuli on local field potentials and single unit activity in Parkinson's Disease Patients

   Neuromodulation: Technology at the Neural Interface 19:698–707.

   https://doi.org/10.1111/ner.12453

   • Google Scholar
7. 1. Benis D
   2. David O
   3. Piallat B
   4. Kibleur A
   5. Goetz L
   6. Bhattacharjee M
   7. Fraix V
   8. Seigneuret E
   9. Krack P
   10. Chabardès S
   11. Bastin J

   (2016) Response inhibition rapidly increases single-neuron responses in the subthalamic nucleus of patients with Parkinson's disease

   Cortex 84:111–123.

   https://doi.org/10.1016/j.cortex.2016.09.006

   • PubMed
   • Google Scholar
8. 1. Berardelli A
   2. Conte A
   3. Fabbrini G
   4. Bologna M
   5. Latorre A
   6. Rocchi L
   7. Suppa A

   (2012) Pathophysiology of pain and fatigue in Parkinson's disease

   Parkinsonism & Related Disorders 18 Suppl 1:S226–S228.

   https://doi.org/10.1016/S1353-8020(11)70069-4

   • PubMed
   • Google Scholar
9. 1. Bergman H
   2. Wichmann B
   3. Karmon B
   4. DeLong R

   (1994) The primate subthalamic nucleus

   II. Neuronal Activity in the MPTP Model of parkinsonism. Journal of Neurophysiologie 72:507–520.

   https://doi.org/10.1152/jn.1994.72.2.507

   • Google Scholar
10. 1. Bernard JF
    2. Peschanski M
    3. Besson JM

    (1989) A possible Spino (trigemino)-ponto-amygdaloid pathway for pain

    Neuroscience Letters 100:83–88.

    https://doi.org/10.1016/0304-3940(89)90664-2

    • PubMed
    • Google Scholar
11. 1. Besson JM
    2. Chaouch A

    (1987) Peripheral and spinal mechanisms of nociception

    Physiological Reviews 67:67–186.

    https://doi.org/10.1152/physrev.1987.67.1.67

    • PubMed
    • Google Scholar
12. 1. Beurrier C
    2. Bioulac B
    3. Audin J
    4. Hammond C

    (2001) High-frequency stimulation produces a transient blockade of voltage-gated currents in subthalamic neurons

    Journal of Neurophysiology 85:1351–1356.

    https://doi.org/10.1152/jn.2001.85.4.1351

    • PubMed
    • Google Scholar
13. 1. Brefel-Courbon C
    2. Ory-Magne F
    3. Thalamas C
    4. Payoux P
    5. Rascol O

    (2013) Nociceptive brain activation in patients with neuropathic pain related to Parkinson's disease

    Parkinsonism & Related Disorders 19:548–552.

    https://doi.org/10.1016/j.parkreldis.2013.02.003

    • PubMed
    • Google Scholar
14. 1. Breysse E
    2. Pelloux Y
    3. Baunez C

    (2015) The good and bad differentially encoded within the subthalamic nucleus in rats

    eNeuro 2:.

    https://doi.org/10.1523/ENEURO.0014-15.2015

    • Google Scholar
15. 1. Canteras NS
    2. Shammah-Lagnado SJ
    3. Silva BA
    4. Ricardo JA

    (1990) Afferent connections of the subthalamic nucleus: a combined retrograde and anterograde horseradish peroxidase study in the rat

    Brain Research 513:43–59.

    https://doi.org/10.1016/0006-8993(90)91087-W

    • PubMed
    • Google Scholar
16. 1. Carpenter KJ
    2. Sen S
    3. Matthews EA
    4. Flatters SL
    5. Wozniak KM
    6. Slusher BS
    7. Dickenson AH

    (2003) Effects of GCP-II inhibition on responses of dorsal horn neurones after inflammation and neuropathy: an electrophysiological study in the rat

    Neuropeptides 37:298–306.

    https://doi.org/10.1016/j.npep.2003.08.001

    • PubMed
    • Google Scholar
17. 1. Chang C
    2. Shyu B-C

    (2001) A fMRI study of brain activations during non-noxious and noxious electrical stimulation of the sciatic nerve of rats

    Brain Research 897:71–81.

    https://doi.org/10.1016/S0006-8993(01)02094-7

    • Google Scholar
18. 1. Chiken S
    2. Nambu A

    (2014) Disrupting neuronal transmission: mechanism of DBS?

    Frontiers in Systems Neuroscience 8:33.

    https://doi.org/10.3389/fnsys.2014.00033

    • PubMed
    • Google Scholar
19. 1. Chudler EH
    2. Dong WK

    (1995) The role of the basal ganglia in nociception and pain

    Pain 60:3–38.

    https://doi.org/10.1016/0304-3959(94)00172-B

    • PubMed
    • Google Scholar
20. 1. Coizet V
    2. Dommett E
    3. Overton PG
    4. Redgrave P

    (2006) Nociceptive responses of dopaminergic neurones modulated by experimental manipulations of the superior colliculus in rat

    Neuroscience 139:1479–1493.

    https://doi.org/10.1016/j.neuroscience.2006.01.030

    • Google Scholar
21. 1. Coizet V
    2. Dommett EJ
    3. Klop EM
    4. Redgrave P
    5. Overton PG

    (2010) The parabrachial nucleus is a critical link in the transmission of short latency nociceptive information to midbrain dopaminergic neurons

    Neuroscience 168:263–272.

    https://doi.org/10.1016/j.neuroscience.2010.03.049

    • PubMed
    • Google Scholar
22. 1. Coizet V
    2. Graham JH
    3. Moss J
    4. Bolam JP
    5. Savasta M
    6. McHaffie JG
    7. Redgrave P
    8. Overton PG

    (2009) Short-latency visual input to the subthalamic nucleus is provided by the midbrain superior colliculus

    Journal of Neuroscience 29:5701–5709.

    https://doi.org/10.1523/JNEUROSCI.0247-09.2009

    • PubMed
    • Google Scholar
23. 1. Coizet V
    2. Heilbronner S
    3. Carcenac C
    4. Mailly P
    5. Lehman J
    6. Savasta M
    7. David O
    8. Deniau JM
    9. Groenewegen HJ
    10. Haber SN

    (2017) The rat prefronto-striatal and prefronto-thalamic bundles analysed in 3D: evidence for a topographical organization

    Journal of Neuroscience 37:2539–2554.

    https://doi.org/10.1523/JNEUROSCI.3304-16.2017

    • Google Scholar
24. 1. Conte A
    2. Khan N
    3. Defazio G
    4. Rothwell JC
    5. Berardelli A

    (2013) Pathophysiology of somatosensory abnormalities in parkinson disease

    Nature Reviews Neurology 9:687–697.

    https://doi.org/10.1038/nrneurol.2013.224

    • PubMed
    • Google Scholar
25. 1. Craig AD

    (1995) Distribution of brainstem projections from spinal Lamina I neurons in the cat and the monkey

    The Journal of Comparative Neurology 361:225–248.

    https://doi.org/10.1002/cne.903610204

    • PubMed
    • Google Scholar
26. 1. Cury RG
    2. Galhardoni R
    3. Fonoff ET
    4. Dos Santos Ghilardi MG
    5. Fonoff F
    6. Arnaut D
    7. Myczkowski ML
    8. Marcolin MA
    9. Bor-Seng-Shu E
    10. Barbosa ER
    11. Teixeira MJ
    12. Ciampi de Andrade D

    (2014) Effects of deep brain stimulation on pain and other nonmotor symptoms in parkinson disease

    Neurology 83:1403–1409.

    https://doi.org/10.1212/WNL.0000000000000887

    • PubMed
    • Google Scholar
27. 1. Davis KD
    2. Lozano AM
    3. Tasker RR
    4. Dostrovsky JO

    (1998) Brain targets for pain control

    Stereotactic and Functional Neurosurgery 71:173–179.

    https://doi.org/10.1159/000029661

    • PubMed
    • Google Scholar
28. 1. de Tommaso M
    2. Arendt-Nielsen L
    3. Defrin R
    4. Kunz M
    5. Pickering G
    6. Valeriani M

    (2016) Pain in Neurodegenerative Disease: Current Knowledge and Future Perspectives

    Behavioural Neurology 2016:1–14.

    https://doi.org/10.1155/2016/7576292

    • PubMed
    • Google Scholar
29. 1. Dellapina E
    2. Gerdelat-Mas A
    3. Ory-Magne F
    4. Pourcel L
    5. Galitzky M
    6. Calvas F
    7. Simonetta-Moreau M
    8. Thalamas C
    9. Payoux P
    10. Brefel-Courbon C

    (2011) Apomorphine effect on pain threshold in Parkinson's disease: a clinical and positron emission tomography study

    Movement Disorders 26:153–157.

    https://doi.org/10.1002/mds.23406

    • PubMed
    • Google Scholar
30. 1. Deniau JM
    2. Chevalier G

    (1992) The lamellar organization of the rat substantia nigra pars reticulata: distribution of projection neurons

    Neuroscience 46:361–377.

    https://doi.org/10.1016/0306-4522(92)90058-A

    • PubMed
    • Google Scholar
31. 1. Djaldetti R
    2. Shifrin A
    3. Rogowski Z
    4. Sprecher E
    5. Melamed E
    6. Yarnitsky D

    (2004) Quantitative measurement of pain sensation in patients with parkinson disease

    Neurology 62:2171–2175.

    https://doi.org/10.1212/01.WNL.0000130455.38550.9D

    • PubMed
    • Google Scholar
32. 1. Dommett E
    2. Coizet V
    3. Blaha CD
    4. Martindale J
    5. Lefebvre V
    6. Walton N
    7. Mayhew JE
    8. Overton PG
    9. Redgrave P

    (2005) How visual stimuli activate dopaminergic neurons at short latency

    Science 307:1476–1479.

    https://doi.org/10.1126/science.1107026

    • PubMed
    • Google Scholar
33. 1. Dostrovsky JO
    2. Levy R
    3. Wu JP
    4. Hutchison WD
    5. Tasker RR
    6. Lozano AM

    (2000) Microstimulation-induced inhibition of neuronal firing in human globus pallidus

    Journal of Neurophysiology 84:570–574.

    https://doi.org/10.1152/jn.2000.84.1.570

    • PubMed
    • Google Scholar
34. 1. Dostrovsky JO

    (2000a) Role of thalamus in pain

    Progress in Brain Research 129:245–257.

    https://doi.org/10.1016/S0079-6123(00)29018-3

    • PubMed
    • Google Scholar
35. 1. Follett KA

    (2000) The surgical treatment of Parkinson's disease

    Annual Review of Medicine 51:135–147.

    https://doi.org/10.1146/annurev.med.51.1.135

    • PubMed
    • Google Scholar
36. 1. Fujimoto K
    2. Kita H

    (1993) Response characteristics of subthalamic neurons to the stimulation of the sensorimotor cortex in the rat

    Brain Research 609:185–192.

    https://doi.org/10.1016/0006-8993(93)90872-K

    • PubMed
    • Google Scholar
37. 1. Gauriau C
    2. Bernard JF

    (2002) Pain pathways and parabrachial circuits in the rat

    Experimental Physiology 87:251–258.

    https://doi.org/10.1113/eph8702357

    • PubMed
    • Google Scholar
38. 1. Gorecki J
    2. Hirayama T
    3. Dostrovsky JO
    4. Tasker RR
    5. Lenz FA

    (1989) Thalamic stimulation and recording in patients with deafferentation and central pain

    Stereotactic and Functional Neurosurgery 52:219–226.

    https://doi.org/10.1159/000099504

    • PubMed
    • Google Scholar
39. 1. Gurney K
    2. Prescott TJ
    3. Redgrave P

    (2001) A computational model of action selection in the basal ganglia. I. A new functional anatomy

    Biological Cybernetics 84:401–410.

    https://doi.org/10.1007/PL00007984

    • PubMed
    • Google Scholar
40. 1. Ha AD
    2. Jankovic J

    (2012) Pain in Parkinson's disease

    Movement Disorders : Official Journal of the Movement Disorder Society 27:485–491.

    https://doi.org/10.1002/mds.23959

    • PubMed
    • Google Scholar
41. 1. Hamani C
    2. Saint-Cyr JA
    3. Fraser J
    4. Kaplitt M
    5. Lozano AM

    (2004) The subthalamic nucleus in the context of movement disorders

    Brain 127:4–20.

    https://doi.org/10.1093/brain/awh029

    • PubMed
    • Google Scholar
42. 1. Hammond C
    2. Deniau JM
    3. Rouzaire-Dubois B
    4. Feger J

    (1978) Pepipheral input to the rat subthalamic nucleus, an electrophysiological study

    Neuroscience Letters 9:171–176.

    https://doi.org/10.1016/0304-3940(78)90067-8

    • PubMed
    • Google Scholar
43. 1. Hanagasi HA
    2. Akat S
    3. Gurvit H
    4. Yazici J
    5. Emre M

    (2011) Pain is common in Parkinson's disease

    Clinical Neurology and Neurosurgery 113:11–13.

    https://doi.org/10.1016/j.clineuro.2010.07.024

    • PubMed
    • Google Scholar
44. 1. Hassani OK
    2. Mouroux M
    3. Féger J

    (1996) Increased subthalamic neuronal activity after nigral dopaminergic lesion independent of disinhibition via the globus pallidus

    Neuroscience 72:105–115.

    https://doi.org/10.1016/0306-4522(95)00535-8

    • PubMed
    • Google Scholar
45. 1. Heise CE
    2. Reyes S
    3. Mitrofanis J

    (2008) Sensory (nociceptive) stimulation evokes Fos expression in the subthalamus of hemiparkinsonian rats

    Neurological Research 30:277–284.

    https://doi.org/10.1179/016164107X235455

    • PubMed
    • Google Scholar
46. 1. Hylden JL
    2. Anton F
    3. Nahin RL

    (1989) Spinal lamina I projection neurons in the rat: collateral innervation of parabrachial area and thalamus

    Neuroscience 28:27–37.

    https://doi.org/10.1016/0306-4522(89)90229-7

    • PubMed
    • Google Scholar
47. 1. Jahanshahi M
    2. Obeso I
    3. Rothwell JC
    4. Obeso JA

    (2015) A fronto-striato-subthalamic-pallidal network for goal-directed and habitual inhibition

    Nature Reviews Neuroscience 16:719–732.

    https://doi.org/10.1038/nrn4038

    • PubMed
    • Google Scholar
48. 1. Kim H-J
    2. Jeon BS
    3. Paek SH

    (2015) Nonmotor symptoms and subthalamic deep brain stimulation in Parkinson’s Disease

    Journal of Movement Disorders 8:83–91.

    https://doi.org/10.14802/jmd.15010

    • Google Scholar
49. 1. Kim HJ
    2. Jeon BS
    3. Lee JY
    4. Paek SH
    5. Kim DG

    (2012) The benefit of subthalamic deep brain stimulation for pain in Parkinson disease: a 2-year follow-up study

    Neurosurgery 70:18–24.

    https://doi.org/10.1227/NEU.0b013e3182266664

    • PubMed
    • Google Scholar
50. 1. Kim HJ
    2. Paek SH
    3. Kim JY
    4. Lee JY
    5. Lim YH
    6. Kim MR
    7. Kim DG
    8. Jeon BS

    (2008) Chronic subthalamic deep brain stimulation improves pain in Parkinson disease

    Journal of Neurology 255:1889–1894.

    https://doi.org/10.1007/s00415-009-0908-0

    • PubMed
    • Google Scholar
51. 1. Kitai ST
    2. Deniau JM

    (1981) Cortical inputs to the subthalamus: intracellular analysis

    Brain Research 214:411–415.

    https://doi.org/10.1016/0006-8993(81)91204-X

    • PubMed
    • Google Scholar
52. 1. Klingelhoefer L
    2. Samuel M
    3. Chaudhuri KR
    4. Ashkan K

    (2014) An update of the impact of deep brain stimulation on non motor symptoms in Parkinson's disease

    Journal of Parkinson's disease 4:289–300.

    https://doi.org/10.3233/JPD-130273

    • PubMed
    • Google Scholar
53. 1. Klop EM
    2. Mouton LJ
    3. Hulsebosch R
    4. Boers J
    5. Holstege G

    (2005) In cat four times as many lamina I neurons project to the parabrachial nuclei and twice as many to the periaqueductal gray as to the thalamus

    Neuroscience 134:189–197.

    https://doi.org/10.1016/j.neuroscience.2005.03.035

    • PubMed
    • Google Scholar
54. 1. Kolomiets BP
    2. Deniau JM
    3. Mailly P
    4. Ménétrey A
    5. Glowinski J
    6. Thierry AM

    (2001) Segregation and convergence of information flow through the cortico-subthalamic pathways

    The Journal of Neuroscience 21:5764–5772.

    https://doi.org/10.1523/JNEUROSCI.21-15-05764.2001

    • PubMed
    • Google Scholar
55. 1. Krack P
    2. Batir A
    3. Van Blercom N
    4. Chabardes S
    5. Fraix V
    6. Ardouin C
    7. Koudsie A
    8. Limousin PD
    9. Benazzouz A
    10. LeBas JF
    11. Benabid AL
    12. Pollak P

    (2003) Five-year follow-up of bilateral stimulation of the subthalamic nucleus in advanced Parkinson's disease

    New England Journal of Medicine 349:1925–1934.

    https://doi.org/10.1056/NEJMoa035275

    • PubMed
    • Google Scholar
56. 1. Kreiss DS
    2. Anderson LA
    3. Walters JR

    (1996) Apomorphine and dopamine D(1) receptor agonists increase the firing rates of subthalamic nucleus neurons

    Neuroscience 72:863–876.

    https://doi.org/10.1016/0306-4522(95)00583-8

    • PubMed
    • Google Scholar
57. 1. Kremer JR
    2. Mastronarde DN
    3. McIntosh JR

    (1996) Computer visualization of three-dimensional image data using IMOD

    Journal of Structural Biology 116:71–76.

    https://doi.org/10.1006/jsbi.1996.0013

    • PubMed
    • Google Scholar
58. 1. Lardeux S
    2. Paleressompoulle D
    3. Pernaud R
    4. Cador M
    5. Baunez C

    (2013) Different populations of subthalamic neurons encode cocaine vs. sucrose reward and predict future error

    Journal of Neurophysiology 110:1497–1510.

    https://doi.org/10.1152/jn.00160.2013

    • PubMed
    • Google Scholar
59. 1. Lardeux S
    2. Pernaud R
    3. Paleressompoulle D
    4. Baunez C

    (2009) Beyond the reward pathway: coding reward magnitude and error in the rat subthalamic nucleus

    Journal of Neurophysiology 102:2526–2537.

    https://doi.org/10.1152/jn.91009.2008

    • PubMed
    • Google Scholar
60. 1. Limousin P
    2. Krack P
    3. Pollak P
    4. Benazzouz A
    5. Ardouin C
    6. Hoffmann D
    7. Benabid AL

    (1998) Electrical stimulation of the subthalamic nucleus in advanced Parkinson's disease

    New England Journal of Medicine 339:1105–1111.

    https://doi.org/10.1056/NEJM199810153391603

    • PubMed
    • Google Scholar
61. 1. Magill PJ
    2. Sharott A
    3. Bevan MD
    4. Brown P
    5. Bolam JP

    (2004) Synchronous unit activity and local field potentials evoked in the subthalamic nucleus by cortical stimulation

    Journal of Neurophysiology 92:700–714.

    https://doi.org/10.1152/jn.00134.2004

    • PubMed
    • Google Scholar
62. 1. Mailly P
    2. Haber SN
    3. Groenewegen HJ
    4. Deniau JM

    (2010) A 3D multi-modal and multi-dimensional digital brain model as a framework for data sharing

    Journal of Neuroscience Methods 194:56–63.

    https://doi.org/10.1016/j.jneumeth.2009.12.014

    • PubMed
    • Google Scholar
63. 1. Matsumura M
    2. Kojima J
    3. Gardiner TW
    4. Hikosaka O

    (1992) Visual and oculomotor functions of monkey subthalamic nucleus

    Journal of Neurophysiology 67:1615–1632.

    https://doi.org/10.1152/jn.1992.67.6.1615

    • PubMed
    • Google Scholar
64. 1. Matthews EA
    2. Dickenson AH

    (2001) Effects of spinally delivered N- and P-type voltage-dependent calcium channel antagonists on dorsal horn neuronal responses in a rat model of neuropathy

    Pain 92:235–246.

    https://doi.org/10.1016/S0304-3959(01)00255-X

    • PubMed
    • Google Scholar
65. 1. McHaffie JG
    2. Kao CQ
    3. Stein BE

    (1989) Nociceptive neurons in rat superior colliculus: response properties, topography, and functional implications

    Journal of Neurophysiology 62:510–525.

    https://doi.org/10.1152/jn.1989.62.2.510

    • PubMed
    • Google Scholar
66. 1. McIntyre CC
    2. Savasta M
    3. Kerkerian-Le Goff L
    4. Vitek JL

    (2004) Uncovering the mechanism(s) of action of deep brain stimulation: activation, inhibition, or both

    Clinical Neurophysiology 115:1239–1248.

    https://doi.org/10.1016/j.clinph.2003.12.024

    • PubMed
    • Google Scholar
67. Book

    1. Paxinos G
    2. Watson C

    (2005)

    The Rat Brain in Stereotaxic Coordinates

    Sydney: Academic Press.

    • Google Scholar
68. 1. Piallat B
    2. Polosan M
    3. Fraix V
    4. Goetz L
    5. David O
    6. Fenoy A
    7. Torres N
    8. Quesada JL
    9. Seigneuret E
    10. Pollak P
    11. Krack P
    12. Bougerol T
    13. Benabid AL
    14. Chabardès S

    (2011) Subthalamic neuronal firing in obsessive-compulsive disorder and Parkinson disease

    Annals of Neurology 69:793–802.

    https://doi.org/10.1002/ana.22222

    • PubMed
    • Google Scholar
69. 1. Reilly S
    2. Trifunovic R

    (2000) Lateral parabrachial nucleus lesions in the rat: aversive and appetitive gustatory conditioning

    Brain Research Bulletin 52:269–278.

    https://doi.org/10.1016/S0361-9230(00)00263-X

    • PubMed
    • Google Scholar
70. 1. Reilly S
    2. Trifunovic R

    (2001) Lateral parabrachial nucleus lesions in the rat: neophobia and conditioned taste aversion

    Brain Research Bulletin 55:359–366.

    https://doi.org/10.1016/S0361-9230(01)00517-2

    • PubMed
    • Google Scholar
71. 1. Saper CB
    2. Loewy AD

    (1980) Efferent connections of the parabrachial nucleus in the rat

    Brain Research 197:291–317.

    https://doi.org/10.1016/0006-8993(80)91117-8

    • PubMed
    • Google Scholar
72. 1. Sarhan M
    2. Freund-Mercier MJ
    3. Veinante P

    (2005) Branching patterns of parabrachial neurons projecting to the central extended amgydala: single axonal reconstructions

    The Journal of Comparative Neurology 491:418–442.

    https://doi.org/10.1002/cne.20697

    • PubMed
    • Google Scholar
73. 1. Schestatsky P
    2. Kumru H
    3. Valls-Solé J
    4. Valldeoriola F
    5. Marti MJ
    6. Tolosa E
    7. Chaves ML

    (2007) Neurophysiologic study of central pain in patients with Parkinson disease

    Neurology 69:2162–2169.

    https://doi.org/10.1212/01.wnl.0000295669.12443.d3

    • PubMed
    • Google Scholar
74. 1. Schneider JS

    (1986) Interactions between the basal ganglia, the pontine parabrachial region, and the trigeminal system in cat

    Neuroscience 19:411–425.

    https://doi.org/10.1016/0306-4522(86)90271-X

    • PubMed
    • Google Scholar
75. 1. Schwedt TJ
    2. Chong CD
    3. Chiang CC
    4. Baxter L
    5. Schlaggar BL
    6. Dodick DW

    (2014) Enhanced pain-induced activity of pain-processing regions in a case-control study of episodic migraine

    Cephalalgia 34:947–958.

    https://doi.org/10.1177/0333102414526069

    • PubMed
    • Google Scholar
76. 1. Swett JE
    2. Woolf CJ

    (1985) The somatotopic organization of primary afferent terminals in the superficial laminae of the dorsal horn of the rat spinal cord

    The Journal of Comparative Neurology 231:66–77.

    https://doi.org/10.1002/cne.902310106

    • Google Scholar
77. 1. Sürücü O
    2. Baumann-Vogel H
    3. Uhl M
    4. Imbach LL
    5. Baumann CR

    (2013) Subthalamic deep brain stimulation versus best medical therapy for L-dopa responsive pain in Parkinson's disease

    Pain 154:1477–1479.

    https://doi.org/10.1016/j.pain.2013.03.008

    • PubMed
    • Google Scholar
78. 1. Tinazzi M
    2. Del Vesco C
    3. Defazio G
    4. Fincati E
    5. Smania N
    6. Moretto G
    7. Fiaschi A
    8. Le Pera D
    9. Valeriani M

    (2008) Abnormal processing of the nociceptive input in Parkinson's disease: a study with CO2 laser evoked potentials

    Pain 136:117–124.

    https://doi.org/10.1016/j.pain.2007.06.022

    • PubMed
    • Google Scholar
79. 1. Tokuno H
    2. Takada M
    3. Ikai Y
    4. Mizuno N

    (1994) Direct projections from the deep layers of the superior colliculus to the subthalamic nucleus in the rat

    Brain Research 639:156–160.

    https://doi.org/10.1016/0006-8993(94)91776-0

    • PubMed
    • Google Scholar
80. 1. Urch CE
    2. Donovan-Rodriguez T
    3. Dickenson AH

    (2003) Alterations in dorsal horn neurones in a rat model of cancer-induced bone pain

    Pain 106:347–356.

    https://doi.org/10.1016/j.pain.2003.08.002

    • PubMed
    • Google Scholar

Author details

1. Arnaud Pautrat

   1. Inserm, Grenoble, France
   2. Grenoble Institute of Neurosciences, Université Grenoble Alpes, Grenoble, France

   Contribution

   Formal analysis, Investigation

   Competing interests

   No competing interests declared

2. Marta Rolland

   1. Inserm, Grenoble, France
   2. Grenoble Institute of Neurosciences, Université Grenoble Alpes, Grenoble, France

   Contribution

   Formal analysis, Investigation

   Competing interests

   No competing interests declared

3. Margaux Barthelemy

   1. Inserm, Grenoble, France
   2. Grenoble Institute of Neurosciences, Université Grenoble Alpes, Grenoble, France

   Contribution

   Formal analysis, Investigation

   Competing interests

   No competing interests declared

4. Christelle Baunez

   Institut de Neurosciences de la Timone, Aix-Marseille Université, Marseille, France

   Contribution

   Investigation, Methodology, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-4368-652X

5. Valérie Sinniger

   1. Grenoble Institute of Neurosciences, Université Grenoble Alpes, Grenoble, France
   2. Service d’Hépato-Gastroentérologie, CHU Grenoble Alpes, Grenoble, France

   Contribution

   Investigation, Methodology

   Competing interests

   No competing interests declared

6. Brigitte Piallat

   1. Inserm, Grenoble, France
   2. Grenoble Institute of Neurosciences, Université Grenoble Alpes, Grenoble, France

   Contribution

   Software, Formal analysis, Methodology

   Competing interests

   No competing interests declared

7. Marc Savasta

   1. Inserm, Grenoble, France
   2. Grenoble Institute of Neurosciences, Université Grenoble Alpes, Grenoble, France

   Contribution

   Funding acquisition, Writing—review and editing

   Competing interests

   No competing interests declared

8. Paul G Overton

   Department of Psychology, University of Sheffield, Sheffield, United Kingdom

   Contribution

   Conceptualization, Project administration, Writing—review and editing

   Competing interests

   No competing interests declared

9. Olivier David

   1. Inserm, Grenoble, France
   2. Grenoble Institute of Neurosciences, Université Grenoble Alpes, Grenoble, France

   Contribution

   Formal analysis, Funding acquisition, Methodology, Writing—review and editing

   Competing interests

   No competing interests declared

10. Veronique Coizet

    1. Inserm, Grenoble, France
    2. Grenoble Institute of Neurosciences, Université Grenoble Alpes, Grenoble, France

    Contribution

    Conceptualization, Formal analysis, Supervision, Funding acquisition, Validation, Methodology, Writing—original draft, Project administration, Writing—review and editing

    For correspondence

    veronique.coizet@univ-grenoble-alpes.fr

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0001-5192-6610

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