Thalamic regulation of sucrose-seeking during unexpected reward omission

SUMMARY

The paraventricular nucleus of the thalamus (PVT) is thought to regulate behavioral responses under emotionally arousing conditions. Reward-associated cues activate PVT neurons, however, the specific PVT efferents regulating reward-seeking remain elusive. Using a cued sucrose-seeking task, we manipulated PVT activity under two emotionally distinct conditions: 1) when reward was available during the cue as expected, or 2) when reward was unexpectedly omitted during the cue. Pharmacological inactivation of the anterior PVT (aPVT), but not the posterior PVT, increased sucrose-seeking only when reward was omitted. Consistent with this, photoactivation of aPVT neurons abolished sucrose-seeking, and the firing of aPVT neurons differentiated reward availability. Photoinhibition of aPVT projections to the nucleus accumbens or to the amygdala increased or decreased, respectively, sucrose-seeking only when reward was omitted. Our findings suggest that PVT bidirectionally modulates sucrose-seeking under the negative (frustrative) conditions of reward omission.

INTRODUCTION

Cues in the environment that are associated with rewarding or aversive outcomes induce changes in emotional states (Flagel et al., 2011; Namburi et al., 2015; Robinson and Berridge, 2013). While the neural encoding of such changes has long been attributed to the amygdala (Esber et al., 2015; Madarasz et al., 2016; Peck and Salzman, 2014; Sears et al., 2014; Stillman et al., 2015; Tye et al., 2008), emerging evidence suggests that the paraventricular nucleus of the thalamus (PVT) contributes to the regulation of emotional responses (Haight and Flagel, 2014; Hsu et al., 2014; Kirouac, 2015). PVT neurons are activated by contexts/cues associated with reward (Choi et al., 2010; Igelstrom et al., 2010; Li et al., 2016; Matzeu et al., 2015; Schiltz et al., 2007) or aversion (Beck and Fibiger, 1995; Do-Monte et al., 2015b; Penzo et al., 2015; Yasoshima et al., 2007; Zhu et al., 2016). This pattern of activation to stimuli with opposing valence suggests that distinct PVT circuits are recruited to modulate different responses. PVT is broadly connected with regions implicated in motivation, including the prefrontal cortex, the nucleus accumbens, and the amygdala; and receives extensive hypothalamic projections related to feeding (Lee et al., 2015; Li and Kirouac, 2008, 2012; Moga et al., 1995; Vertes and Hoover, 2008). These connections place PVT in a unique position to integrate positive and negative emotional states in response to cues (for a review see Do Monte et al., 2016).

Findings from previous studies that investigated the role of PVT in reward-seeking have been inconclusive. Increased food-seeking has been reported following PVT lesions (Haight et al., 2015) or PVT excitation (Barson et al., 2015; Labouebe et al., 2016), and differing effects on food consumption have been described depending on whether the manipulations are made in the anterior PVT (aPVT) or posterior PVT (pPVT; Bhatnagar and Dallman, 1999; Nakahara et al., 2004; Stratford and Wirtshafter, 2013). These discrepancies may reflect antero-posterior differences as well as different functions of distinct PVT efferents, however, the projections of PVT regulating reward-seeking remain to be determined.

Here, we used a cued sucrose-seeking task to assess the role of PVT and its efferents in reward-seeking under conditions of opposing emotional valence: 1) when reward was available during the cue as expected (positive outcome), or 2) when reward was unexpectedly omitted during the cue (negative outcome). Using pharmacological inactivation, unit recording, and optogenetic manipulation of PVT and its outputs, we identified a specific role of aPVT and its projections to the nucleus accumbens and the amygdala in the regulation of reward-seeking specifically during negative outcomes.

RESULTS

Unexpected reward omission increases sucrose-seeking and induces anxiety

Rats previously trained to press a bar for sucrose pellets on a variable reward schedule were given 3 days of cued sucrose-seeking, in which the availability of reward was signaled by a light (30 s) located above the bar. Each press in the presence of the cue delivered one sucrose pellet to a nearby dish (Figure 1A). After 3 days of reward conditioning, rats learned to limit pressing to the cue-on periods (Figure 1B). The following day (day 4), rats were randomly assigned to two groups: 1) those receiving sucrose during the cue as expected, and 2) those for which sucrose would be unexpectedly omitted during the cue. Rats in the reward omitted group increased their press rate, compared to the previous day in the presence of reward or compared to the reward available group (Figure 1C). Rats in this group exhibited a greater number of press bursts (≥ 3 presses/s, 1.2 ± 0.36 bursts/min, n= 24) compared to the reward available group (0.11 ± 0.11 bursts/min, n= 24; unpaired t test, *p= 0.010, t= 2.68). This is consistent with previous studies showing that omission of an expected reward increases reward-seeking responses (Burokas et al., 2012; Dudley and Papini, 1997; Stout et al., 2002), a phenomenon initially described as a reinforcement-omission effect or frustration effect (Amsel and Roussel, 1952; Jensen and Fallon, 1973).

Figure 1. Unexpected omission of sucrose reward increases pressing and induces anxiety-like behavior.

A) Schematic of cued sucrose-seeking model. Rats were trained to press a bar for sucrose in the presence of a 30 s light cue, receiving one sucrose pellet per press. B) Rate of bar-pressing (presses/min) during the conditioning phase (days 1–3). After three days of training, press rates increased during the cue-on period (gray dots), as compared to the cue-off period (white dots, blocks of 2, n= 48). On day 4, rats were exposed to a test session in which reward was either available or omitted during the light cue. C) Cued reward conditioning. Unexpected omission of reward at day 4 test (red group, n= 24) significantly increased rats’ press rate, compared to the previous day in the presence of reward (paired t-test, *p< 0.01, t= 3.73, single trials), or across groups on day 4 (blue group, n= 24, unpaired t-test *p< 0.01, t= 2.95). Inset, reward omitted group pressed significantly more during the first 10 s of the reward omitted session (day 4, red dots), compared to the previous day in which reward was available (day 3, white dots, ANOVA repeated-measures F_(1,46)= 9.04., p= 0.0042. Duncan posthoc test, **p< 0.01. D) A subset of rats were placed in an open field immediately following the test. Rats experiencing reward omission at test (red bar, n= 8) spent less time in the center of the open field (blue bar; n=7, Unpaired t-test *p= 0.018, t= 2.67). E) A subset of rats were tested in an elevated plus maze immediately following the reward available (blue bars, n= 10) or reward omitted (red bars, n= 10) test. Rats experiencing reward omission spent less time in the open arms (solid white), compared to the closed arms (striped lines; unpaired t-test *p= 0.0010, t= 3.88). Data shown as mean ± s.e.m.. *p< 0.05, **p< 0.01.

Omission of expected reward has aversive properties (Amsel, 1958; Huston et al., 2013; Papini, 2003), which increase stress (Dantzer et al., 1980; Zimmerman and Koene, 1998) and anxiety-like behaviors (Komorowski et al., 2012; Manzo et al., 2014) in both experimental animals and humans (Henna et al., 2008; Papini, 2003; Yu et al., 2014). Consistent with this, rats in the reward omitted group spent less time in the center of an open field (Figure 1D) or in the open arms of an elevated plus maze (Figure 1E), when tested immediately following the Day 4 test. This suggests that unexpected omission of reward is anxiogenic in our task.

Pharmacological inactivation of anterior PVT increases sucrose-seeking during reward omission

To assess the role of PVT in cued sucrose-seeking under distinct emotional states, we used the GABA_A (γ-aminobutyric acid type A) receptor agonist muscimol (MUS) to inactivate aPVT or pPVT neurons during the reward available or reward omitted tests (Day 4). Pharmacological inactivation of aPVT had no effect when reward was available (Figures 2A and 2B). When reward was omitted, inactivation of aPVT did not eliminate the increased pressing induced by omission, but augmented it even further (Figure 2C). In contrast, inactivation of pPVT had no effect in either condition (Figure S1). Inactivation of either area did not alter consumption of sucrose pellets available ad libitum (aPVT: SAL: 5.0 ± 0.9 g; MUS: 4.8 ± 0.9 g, unpaired t-test, *p= 0.89, t= 0.14; pPVT: SAL: 4.5 ± 1.0 g; MUS: 4.4 ± 1.0 g, unpaired t-test, *p= 0.97, t= 0.03). Together, these findings suggest that activity in aPVT opposes reward-seeking when rats are experiencing a negative emotion (e.g. unexpected omission of reward).

Figure 2. Pharmacological inactivation of anterior PVT increases sucrose-seeking during reward omission.

A) Left, representative micrograph showing the site of fluorescent muscimol (MUS) injection into the anterior PVT (aPVT). Right, orange areas represent the minimum (dark) and the maximum (light) spread of MUS into aPVT. cc, corpus callosum; IMD, intermediodorsal nucleus of the thalamus; CM, central medial nucleus of the thalamus; MD, mediodorsal thalamus; sm, stria medullaris; CA3, hippocampal CA3 subregion. B) Press rate in rats infused with saline (SAL, black, n= 9) or MUS (olive, n= 6) 30 min before a reward available test performed on day 4 (black arrow). MUS inactivation of aPVT had no effect on sucrose-seeking when reward was available (unpaired t-test, p= 0.79, t= 0.27). C) Press rate in rats infused with saline (n= 9) or MUS (n= 5) 30 min before a reward omitted test performed at day 4. MUS inactivation of aPVT increased sucrose-seeking when reward was unexpectedly omitted during the test (unpaired t-test, *p= 0.015, t= 2.80). Inset, SAL rats pressed significantly more during the first 10 s of the reward omitted session (day 4, red dots), when compared to the previous day in which reward was available (day 3, blue dots, ANOVA repeated-measures F_(1,16)= 6.19., p= 0.024. Duncan posthoc test, block 1–10s, *p= 0.013; block 10–20s, *p=0.014). Data shown as mean ± s.e.m., first trial of each day. *p< 0.05. See also Figure S1.

Photoactivation of aPVT neurons reduces reward-seeking behavior

Because pharmacological inactivation of aPVT increased reward-seeking, we hypothesized that optogenetic activation of aPVT neurons with the light-activated cation channel channelrhodopsin (ChR2) would decrease reward-seeking. Accordingly, aPVT was infused with an adeno-associated viral vector (AAV-5) to express ChR2 combined with enhanced yellow fluorescent protein (eYFP), under the control of a CaMKIIa promoter (AAV5:CaMKIIa::hChR2-eYFP). Laser illumination of aPVT somata increased the expression of the neuronal activity marker cFos in aPVT (Figure 3A–C). Consistent with our prediction, photoactivation of aPVT neurons at cue onset abolished pressing during both reward available and reward omitted conditions (Figure 3D; Movie S1). Pressing was also reduced when aPVT was photoactivated in the middle of the cue, or in rats that were trained to press a bar on a variable interval (60 s) schedule of reinforcement (Figure S2). Such effects were not accompanied by changes in locomotion or anxiety assessed in the open field task (Figure S2). Thus, activation of aPVT neurons is sufficient to interrupt both cued and uncued sucrose-seeking. Interestingly, however, photoactivation of aPVT had no effect on consumption of sucrose in an ad libitium test (Figure S2), suggesting that aPVT regulates the foraging rather than the consumption of sucrose.

Figure 3. Photoactivation of anterior PVT abolishes sucrose-seeking.

A) Diagram showing ChR2-eYFP expression and fiber optic placement in the aPVT. B) Left, representative micrograph showing the expression of eYFP-control or ChR2-eYFP within aPVT and (right) the expression of cFos within the aPVT after photoactivation of aPVT neurons. Scale bar, 100μm. MD, mediodorsal thalamus; sm, stria medullaris; CA3, hippocampal CA3 subregion, 3V, third ventricle. C) Photoactivation of aPVT increased the number of cFos-positive neurons (per 0.1 mm²) in aPVT of ChR2-eYFP group (green, n= 4) compared to eYFP-control group (black, n= 3; unpaired t-test, p= 0.024, t= 3.00). D) Rats expressing eYFP (control, black dots, n= 9) or ChR2-eYFP (green dots, n= 8) in aPVT were trained in cued sucrose-seeking (day 1–3). ChR2-activation of aPVT at cue onset (blue bar, 20 Hz, 30 s) abolished sucrose-seeking when reward was available (day 4, unpaired t-test, p< 0.001, t= 4.20) or when reward was omitted (day 6, unpaired t-test, p< 0.01, t= 4.09). Inset, eYFP control rats pressed significantly more during the first 10 s of the reward omitted session (day 6, red dots), when compared to the previous day in which reward was available (day 5, blue dots, ANOVA repeated-measures F_(1,16)= 4.96., p= 0.040. Duncan posthoc test, *p= 0.042). Data shown as mean ± s.e.m., first trial of each day. * p< 0.05; ** p< 0.01. See also Figure S2 and Movie S1.

aPVT neurons signal reward omission

Rats implanted with unit-recording electrodes in aPVT underwent cued conditioning sessions as described above. A small number of aPVT neurons showed either inhibitory or excitatory responses to the cue (Figure S3), and there were no differences between reward available and reward omitted trials because the cue preceded omission. aPVT neurons also signaled bar presses, with inhibitory responses mainly observed during the reward available trials (Figure S4). However, the greatest changes in aPVT activity occurred when the rat’s head entered the sucrose dish to discover the presence or absence of reward (Figure 4A–C). Two types of responses were observed. Cells showing inhibitory responses when reward was available no longer showed those responses when reward was omitted (Figure 4D and 4E), and cells showing excitatory responses when reward was omitted no longer showed those responses when reward was available (Figure 4F and 4G). Although the percentage of neurons showing excitatory responses during reward omission was relatively low (9%), the magnitude of the observed response was substantial (Z-score average >6, Figure 4G). Despite the observed differences, the normalized baseline firing rate of neurons showing excitatory vs. inhibitory responses across the sessions did not differ significantly (excitatory: 13.9±1.4, inhibitory: 6.36±1.28, unpaired t-test, p= 0.10, t= 1.71). Thus, aPVT activity distinguished reward availability from reward omission in this task.

Figure 4. aPVT neurons signal reward omission.

A) aPVT neurons were recorded from rats undergoing cued sucrose-seeking. B) Diagram of the electrode placements in the aPVT (coordinates from bregma). C) Pie charts summarizing changes in aPVT firing rate at dish entry; 28% inhibited, 6% excited, and 66% did not change when reward was available; whereas 6% inhibited, 9% excited, and 85% did not change when reward was omitted (Fisher exact test, inhibition with reward available vs. excitation with reward available, p= 0.014; inhibition with reward available vs. inhibition with reward omitted, p= 0.014, n= 54 neurons from 13 rats. Bins of 6 s, unpaired t test, all p’s < 0.05). D) Left, raster plot and peristimulus time histogram (PSTH) of a representative aPVT neuron showing inhibitory response at dish entry when reward was available (blue). Right, same neuron showing no response when reward was omitted (red). E) Average PSTH of all aPVT neurons showing inhibitory responses when reward was available. F) Left, raster plot and PSTH of a representative aPVT neuron showing no response at dish entries when reward was available. Right, same neuron showing excitatory response when reward was omitted. G) Average PSTH of all aPVT neurons showing excitatory responses when reward was omitted. See also Figure S3 and S4.

Photoinhibition of aPVT projections to NAc increases sucrose-seeking during reward omission

PVT is the main source of glutamatergic inputs to the nucleus accumbens (NAc) (Li and Kirouac, 2008; Moga et al., 1995; Vertes and Hoover, 2008), a region known to play a crucial role in reward-seeking behavior (for a review see: Baldo and Kelley, 2007; Salamone et al., 2003; Urstadt and Stanley, 2015). We therefore investigated whether projections from aPVT to the NAc are involved in the regulation of cued sucrose-seeking. Rats were infused with AAV-5 expressing the light-sensitive chloride pump halorhodopsin (AAV5:CaMKIIa::eNpHR3.0-eYFP) into aPVT and implanted with optical fibers aiming mainly at the shell portion of the NAc. In anesthetized rats, we observed that photoinhibiton of aPVT terminals within the NAc either reduced the firing rates (6 out of 68 tested, 9%) or increased the firing rates (17 out of 68 tested, 25%) of NAc neurons (Figure 5A–C). Because PVT is largely devoid of GABAergic neurons (Frassoni et al., 1997; Ottersen and Storm-Mathisen, 1984), the excitatory responses observed in the NAc neurons following photoinhibition of aPVT fibers suggests that at least a fraction of aPVT inputs induce feed-forward inhibition of NAc neurons. This could be mediated by activation of local inhibitory circuits in the NAc (Meredith and Wouterlood, 1990; Zhu et al., 2016) or by direct activation of dopaminergic synapses onto NAc neurons, independent of dopamine cell firing (Parsons et al., 2007; Pinto et al., 2003). Considering that medium spiny neurons, which account for 95% of NAc neurons (Graveland and DiFiglia, 1985), can be hyperpolarized under anesthesia (Kirouac and Ciriello, 1997), the possibility exists that our recordings were biased to local interneurons and somewhat overestimated the percentage of neurons with excitatory responses.

Figure 5. Photoinhibition of aPVT to NAc projections increases pressing when reward is omitted.

A) Diagram of recording placement and representative micrograph showing optrode tracks in the nucleus accumbens shell (NAc_sh) following infusion of eNpHR-eYFP into the aPVT. LV, lateral ventricle; ac, anterior commissure. B) Raster plot and PSTH of two representative NAc_sh neurons responding to photoinhibition (yellow bar) of aPVT inputs, showing either inhibition (left) or excitation (right). C) Pie chart summarizing changes in NAc_sh firing rate with photoinhibition of aPVT terminals in the NAc (9% decreased, 25% increased, 66% did not change, unpaired t test, all p’s < 0.05 as compared with laser off period, n= 68 neurons from 3 rats). D) Diagram of optical fiber placement and representative micrograph showing eNpHR-eYFP expression in aPVT and fiber location in the NAc. cc, corpus callosum; MD, mediodorsal thalamus. E) Rats expressing eYFP control (black dots, n= 8) or eNpHR-eYFP (orange dots, n= 8) in aPVT and implanted with optical fibers in the NAc were trained in cued sucrose-seeking (day 1–3). Photoinhibition of aPVT→ NAc projections (yellow vertical bar) had no effect on sucrose-seeking when reward was available during the test (day 4, unpaired t-test, p= 0.61, t= 0.52), but increased sucrose-seeking when reward was unexpectedly omitted (day 6, unpaired t-test, p= 0.016, t= 2.71). Inset, eYFP control rats pressed significantly more during the first 10 s of the reward omitted session (day 6, red dots), compared to the previous day in which reward was available (day 5, blue dots, ANOVA repeated-measures F_(2,28)= 4.31, p= 0.023. Duncan posthoc test, *p= 0.016). Data shown as mean ± s.e.m., first trial of each day. * p< 0.05. See also Figure S5, S6 and S8.

We next assessed the effects of aPVT→ NAc photoinhibition on sucrose-seeking. Similar to pharmacological inactivation of aPVT (see above), photoinhibition of aPVT→ NAc projections had no effect on pressing when reward was available, but increased pressing when reward was omitted (Figure 5D and 5E). This effect was not observed in rats trained under a variable interval schedule of reinforcement (Figure S5), suggesting that aPVT→ NAc projections are recruited specifically during omission of an expected reward. In further support of this, photoinhibition of aPVT→ NAc projections did not affect sucrose consumption during an ad libitium test (Figure S5). Neither did photoinhibition of this pathway affect locomotion or anxiety in an open field (Figure S5), or extinction of the reward-associated cue (Figure S6). Thus, activity in aPVT efferents to the NAc negatively regulates reward-seeking under the frustrative state induced by reward omission.

Photoactivation of aPVT projections to NAc reduces sucrose-seeking and induces place aversion

Using a different set of rats, we next demonstrated that photoactivation of aPVT→ NAc projections with channelrhodopsin (AAV5:CaMKIIa::hChR2-eYFP) reduced cue-induced sucrose-seeking at frequencies of 10 Hz and 20 Hz (all p’s < 0.05), but not at 1 Hz or 5 Hz (all p’s> 0.05; Figure 6A and 6B). In addition, photoactivation of PVT→ NAc projections (at 10 Hz) reduced the time spent on the side of the chamber paired with laser stimulation, in a real-time place preference task (Figure 6C), without affecting locomotion and anxiety in an open field (distance travelled in meters - eYFP control: 12.4± 2.0, ChR2-eYFP: 8.9± 1.0, unpaired t-test, p= 0.16, t= 1.50; percentage of time in center - eYFP control: 11.8± 5.9, ChR2-eYFP: 00.0± 0.0, unpaired t-test, p= 0.07, t= 2.00, n= 6 per group). These results suggest that activity in the aPVT→ NAc pathway is sufficient to induce aversive states and reduce reward-seeking behavior.

Figure 6. Photoactivation of aPVT to NAc projections inhibits sucrose-seeking and induces place aversion.

A) Diagram of optical fiber placement in the nucleus accumbens (NAc) of rats expressing ChR2-eYFP in the aPVT. B) Rats expressing eYFP (control, black dots, n= 7) or ChR2-eYFP (green dots, n= 7) in aPVT and implanted with optical fibers aimed at the NAc were trained in cued sucrose-seeking (day 1–3, data not shown). Photoactivation of aPVT→ NAc projections on day 4 (reward available) reduced cued sucrose-seeking at frequencies of 10 Hz (unpaired t-test, *p= 0.035, t= 2.35) and 20 Hz (unpaired t-test, **p< 0.01, t= 5.51), but not at 1 Hz and 5 Hz (unpaired t-test, all p’s> 0.05). C) Top, representative real-time place preference tracks and heat-maps showing laser-evoked behavioral aversion (at 10Hz) in ChR2-eYFP group (right, n= 6), but not in eYFP-control group (left, n= 6). Bottom, quantification of laser-evoked behavioral aversion. Photoactivation of PVT→ NAc projections reduced the time spent on the side of the chamber paired with laser stimulation (Day 1, unpaired t-test, **p< 0.01, t= 3.19), but had no effect on the following day without photoactivation (Day 2, unpaired t-test, p= 0.29, t= 1.10). Data shown as mean ± s.e.m.. * p< 0.05, **p< 0.01.

Photoinhibition of aPVT projections to the amygdala decreases sucrose-seeking during reward omission

In addition to its projections to the NAc, aPVT also sends dense projections to the amygdala central (CeA) and basolateral (BLA) nuclei (Li and Kirouac, 2008; Moga et al., 1995; Vertes and Hoover, 2008), regions known to regulate reward-seeking (Ambroggi et al., 2008; Knapska et al., 2013; Mahler and Berridge, 2009; Robinson et al., 2014; Tye and Janak, 2007). In anesthetized rats, we first demonstrated that photoinhibiton of aPVT terminals within the amygdala either reduced the firing rates (5 out of 44 tested, 11%) or increased the firing rates (14 out of 44 tested, 32%) of CeA neurons (Fig 7A–C). Similar to NAc, the higher proportion of excitatory responses suggests that aPVT inputs induce feed-forward inhibition of CeA neurons, as previously demonstrated (Penzo et al., 2015). Photoinhibition of aPVT→ amygdala projections (with optical fibers aimed at the CeA portion) did not affect pressing when reward was present, but decreased pressing when reward was omitted (Figure 7D and 7E). These effects were not observed when the optical fibers were aimed at the BLA (Figure S7), however, due to the dense spread of aPVT fibers and the diffuse propagation of light to both amygdalar subregions, we cannot exclude the participation of aPVT→ BLA pathway in such effects. Our results suggest that activity in aPVT efferents to the amygdala has the opposite effect of aPVT efferents to the NAc, increasing sucrose-seeking during frustrative outcomes. This bidirectional regulation of reward-seeking by PVT is supported by our observation that most NAc-projecting neurons do not overlap with CeA-projecting neurons in the aPVT (Figure S8).

Figure 7. Photoinhibition of aPVT to amygdala projections decreases pressing when reward is omitted.

A) Diagram of recording placement and representative micrograph showing optrode tracks in the central nucleus of the amygdala (CeA) following infusion of eNpHR-eYFP into the anterior PVT (aPVT). B) Raster plot and PSTH of representative CeA neurons responding to photoinhibition (yellow bar) of aPVT inputs in the amygdala, showing either inhibition (left) or excitation (right). C) Pie chart summarizing changes in CeA firing rate with photoinhibition of aPVT terminals in the amygdala (11% decreased, 32% increased, 57% did not change, unpaired t test, all p’s < 0.05 compared with laser off period, n= 44 neurons from 1 rat). D) Diagram of optical fiber placement and representative micrograph showing eNpHR-eYFP expression in the anterior PVT (aPVT) and fiber location in the amygdala. E) Rats expressing eYFP (control, black dots, n= 14) or eNpHR-eYFP (purple dots, n= 8) in aPVT and implanted with optical fibers aimed at the CeA were trained in cued sucrose-seeking (day 1–3). Photoinhibition of aPVT→ amygdala projections (yellow vertical bar) had no effect on sucrose-seeking when reward was available (day 4, unpaired t-test, p= 0.75, t= 0.32), but reduced sucrose-seeking when reward was unexpectedly omitted (day 6, unpaired t-test, p= 0.007, t= 2.98). Inset, eYFP control rats pressed significantly more during the first 10 s of the reward omitted session (day 6, red dots), compared to the previous day in which reward was available (day 5, blue dots, ANOVA repeated-measures F_(2,52)= 3.99, p= 0.024. Duncan posthoc test, *p= 0.022). Data shown as mean ± s.e.m., first trial of each day. * p< 0.05. See also Figure S6, S7 and S8.

Photoactivation of aPVT projections to the amygdala reduces sucrose-seeking and induces place aversion

Because photoinactivation of aPVT→ amygdala projections reduces sucrose-seeking during reward omission, we sought to determine if photoactivation of this same pathway would increase reward-seeking. Surprisingly, we found that photoactivation of aPVT→ amygdala projections reduced reward-seeking at frequencies of 10 Hz and 20 Hz (all p’s < 0.05), but not at 1 Hz or 5 Hz (all p’s > 0.05; Figure 8A and 8B). In addition, photoactivation of PVT→ amygdala projections (at 10 Hz) decreased the time spent on the side of the chamber paired with laser stimulation (Figure 8C). This effect persisted the following day when the animals were re-tested in the same chamber without laser illumination, suggesting a role of PVT→ amygdala projections in aversive learning. Photoactivation of PVT→ amygdala projections was also sufficient to impair locomotion and increase anxiety in an open field (distance travelled in meters - eYFP control: 13.5± 1.5, ChR2-eYFP: 7.5± 1.1, unpaired t-test, p= 0.011, t= 3.05; percentage of time in center - eYFP control: 20.2± 6.0, ChR2-eYFP: 3.6± 2.7, unpaired t-test, p= 0.031, t= 2.47, n= 6 per group). These results suggest that activity in the aPVT→ amygdala pathway reduces reward-seeking behavior, induces aversive and anxiogenic states, and promotes aversive learning.

Figure 8. Photoactivation of aPVT to amygdala projections inhibits sucrose-seeking and induces place aversion.

A) Diagram of optical fiber placement in the amygdala of rats expressing ChR2-eYFP in the aPVT. B) Rats expressing eYFP (control, black dots, n= 5) or ChR2-eYFP (green dots, n= 6) in aPVT and implanted with optical fibers aimed at the central nucleus of the amygdala (CeA) were trained in cued sucrose-seeking (day 1–3, data not shown). Photoactivation of aPVT→ amygdala projections on day 4 (reward available) reduced cued sucrose-seeking at frequencies of 10 Hz and 20 Hz (unpaired t-test, **all p’s< 0.01), but not at 1 Hz and 5 Hz (unpaired t-test, all p’s> 0.05). C) Top, representative real-time place preference tracks and heat-maps showing laser-evoked behavioral aversion (at 10Hz) in ChR2-eYFP group (right, n= 6), but not in eYFP-control group (left, n= 5). Bottom, quantification of laser-evoked behavioral aversion. Photoactivation of PVT→ amygdala projections reduced the time spent on the side of the chamber paired with laser stimulation (Day 1, unpaired t-test, **p< 0.01, t= 5.21), an effect that persisted on the following day without photoactivation (Day 2, unpaired t-test, p= 0.011, t= 3.11). Data shown as mean ± s.e.m.. * p< 0.05, **p< 0.01.

DISCUSSION

We examined the role of PVT and its outputs to the NAc or amygdala in the modulation of sucrose-seeking behavior in rats. Remarkably, PVT appears to modulate sucrose-seeking only when reward is unexpectedly omitted. Under this condition, photoinhibition of aPVT→ NAc projections increases reward-seeking, whereas photoinhibition of aPVT→ amygdala projections reduces reward-seeking. Furthermore, aPVT activity distinguishes reward availability from reward omission. These results suggest that different populations of aPVT neurons are recruited to balance foraging during frustrative conditions (e.g. when a cue-reward association is violated).

Our observation that omission of an expected reward increased bar pressing and induced anxiety-like behavior agrees with prior studies suggesting that unexpected reward omission is aversive (Amsel and Roussel, 1952; Burokas et al., 2012; Dudley and Papini, 1997; Jensen and Fallon, 1973; Komorowski et al., 2012; Manzo et al., 2014; Stout et al., 2002). Recruitment of aPVT neurons during aversive outcomes may serve to adjust reward-seeking responses, resembling previously demonstrated PVT modulation of autonomic, neuroendocrine and behavioral responses to stress (for review see Hsu et al., 2014). The lack of effect of aPVT inactivation on sucrose consumption ad libitum reinforces the idea that aPVT neurons are necessary for sucrose-seeking, rather than sucrose consumption, and suggests that aPVT operates as a switch for regulating foraging under aversive conditions.

Reduction of sucrose-seeking by activation of aPVT→ NAc projections is consistent with previous observations that NAc_sh activity and glutamate levels are decreased during feeding (Krause et al., 2010; Rada et al., 1997; Saulskaya and Mikhailova, 2002), and blockade of AMPA receptors in the NAc increases food consumption (Reynolds and Berridge, 2003; Stratford et al., 1998). Considering that PVT releases glutamate in the NAc (Ligorio et al., 2009), activity in aPVT→ NAc glutamatergic projections would therefore be responsible for reducing food-seeking. This idea seems to be at odds with previous studies showing that glutamatergic afferents from the ventral hippocampus and BLA to the NAc increase reward-seeking (Britt et al., 2012; Stuber et al., 2011). A plausible explanation for this divergence is the observation that PVT neurons have postsynaptic targets in the NAc that differ from those of ventral hippocampus and BLA. Whereas PVT efferents preferentially modulate NAc neurons expressing the inhibitory dopaminergic receptor D2 (Zhu et al., 2016), inputs from ventral hippocampus and BLA modulate NAc neurons expressing the excitatory dopaminergic receptor D1 (Floresco et al., 2001; Stuber et al., 2011). Moreover, NAc neurons expressing D1 vs. D2 receptors display different electrophysiological properties (Cepeda et al., 2008), and exhibit opposing roles in reward-seeking behavior (Kravitz et al., 2012; Yawata et al., 2012).

Previous studies have suggested that the core and the shell subregions of the NAc play dissociable roles in guiding reward-seeking behavior. Whereas the core subregion has been involved in learning and action during goal-directed behavior, the shell subregion has been implicated in processing hedonic and motivated behavior (Burton et al., 2015; Castro and Berridge, 2014; Saddoris et al., 2015; West and Carelli, 2016). Such functional differences have been attributed to distinct input sources and output targets, with the core being mainly interconnected with regions involved in motor responses and the shell being mainly interconnected with regions implicated in incentive motivation (Brog et al., 1993; Groenewegen et al., 1999). This distinct pattern of innervation has been also described for PVT efferents to the NAc, which are denser to the shell than to the core (Li and Kirouac, 2008; Moga et al., 1995; Vertes and Hoover, 2008). In our optogenetic experiments, aPVT inputs preferentially innervated the shell portion of the NAc and the optical fibers were aimed specifically at this subregion, however, we cannot exclude the possibility that the light also affected aPVT fibers located in the core portion of the NAc. Similarly, because viral injections into the aPVT may have also involved the adjacent paratenial nucleus, which also projects to the nucleus accumbens (Vertes and Hoover, 2008), we cannot exclude the possibility that part of the observed effects were due to modulation of paratenial nucleus fibers in the NAc.

Our observation that aPVT→ NAc projections modulate sucrose-seeking during reward omission suggests that aPVT neurons are recruited during negative outcomes, as has been previously demonstrated for drug withdrawal (Zhu et al., 2016). Our tracer finding in aPVT showing that NAc-projecting neurons are denser than CeA-projecting neurons is consistent with previous neuroanatomical findings (Li and Kirouac, 2008), and may explain why pharmacological inactivation of aPVT had effects similar to photoinhibition of PVT→ NAc projections. In contrast to NAc, aPVT projections to the amygdala increase sucrose-seeking during reward omission, as evidenced by photoinhibition of the PVT→ amygdala pathway. Prior studies showed that activation of CeA neurons increases cued food-seeking (Holland and Hsu, 2014; Robinson et al., 2014), but most relevant to our findings is the observation that CeA activity increases during unexpected omission of reward (Calu et al., 2010; Lee et al., 2010). Similarly, a population of BLA neurons show increased activity during reward omission, a response that positively correlates with the maintenance of reward-seeking during this frustrative condition (Tye et al., 2010). Our findings suggest that increased amygdalar activity during reward omission may be due to aPVT inputs.

A role of PVT in communicating aversive information to the CeA has been recently demonstrated in Pavlovian fear conditioning (Do-Monte et al., 2015b; Penzo et al., 2015), suggesting that the aversive states observed in conditioned fear and reward omission may recruit similar circuits. However, considering that different populations of CeA neurons are activated during fear conditioning and reward omission (Purgert et al., 2012), it is likely that different subsets of PVT neurons signal these two aversive experiences. Together with our tracer findings, it is possible that activity in dual-projecting neurons in aPVT would both increase fear responses (by activating CeA neurons) and reduce sucrose-seeking (by activating NAc neurons). In contrast, activity in aPVT neurons projecting to the CeA, but not to the NAc, would mediate the increased sucrose-seeking observed during reward omission. This could explain why bulk photoactivation of PVT→ amygdala projections in our experiments increased anxiety/aversion rather than promoting reward-seeking.

Consistent with our optogenetic findings, we observed that aPVT neurons responded differently depending on reward availability. Inhibitory responses were observed more frequently when reward was available, and were no longer observed when reward was omitted. Reward-modulated responses have been previously described for midline thalamic neurons (Li et al., 2016). We also observed a set of aPVT neurons showing excitatory responses exclusively during reward omission. The targets of these two types of PVT neurons is not known, but based on our findings we speculate that neurons with inhibitory responses project to NAc_sh (permitting pressing when reward is available), whereas neurons with excitatory responses project to CeA (increasing pressing when reward is omitted). Further studies using mice and combining cre-recombination system with optrode recordings are needed to identify the specific targets of these two populations of aPVT neurons.

aPVT receives hypothalamic peptidergic inputs implicated in the control of feeding (e.g. neuropeptide Y; Lee et al., 2015), arousal (e.g. orexin; Kirouac et al., 2005) and stress responses (e.g. corticotropin releasing factor; Hsu and Price, 2009). The aPVT also receives GABAergic projections from the anterior portion of the lateral hypothalamus (LHA; Stamatakis et al., 2016), and increasing GABAergic activity in the LHA promotes feeding (Jennings et al., 2015). It is possible, therefore, that GABAergic projections from the LHA inhibit aPVT neurons when reward is available, thereby promoting sucrose-seeking. aPVT is also robustly innervated by efferents from the prefrontal cortex and ventral subiculum (Li and Kirouac, 2012), both implicated in decision-making and goal-directed behavior (Ciocchi et al., 2015; Piantadosi et al., 2016). This unique set of inputs places aPVT in an optimal position to integrate internal physiological states with emotionally salient information (Kirouac, 2015). Omission of expected reward activates the hypothalamic-pituitary adrenal axis, increasing corticosteroid levels (Coover et al., 1971; Mitchell and Flaherty, 1998; Romero et al., 1995). The high density of corticosteroid receptors in PVT (Ahima et al., 1991; Jaferi and Bhatnagar, 2006), together with our findings, suggests that PVT neurons may play a role in mediating the frustrative effects of reward omission (Amsel, 1958; Papini, 2003). Therefore, top-down modulation of aPVT may adjust ascending signals from the hypothalamus during reward omission.

In a natural environment, the availability of food sources is highly dynamic. In order to survive, animals must adjust their foraging behavior when food is no longer available. This adaptive strategy may serve to first invigorate food-seeking in the face of reward loss, and then re-direct such responses to other potential sources (Amsel, 1992; Papini, 2003). Although a great deal of information has been gathered about the behavioral and physiological consequences of reward omission (Burokas et al., 2012; Jensen and Fallon, 1973; Komorowski et al., 2012; Manzo et al., 2015; Stout et al., 2002), far less attention has been paid to the neural circuits involved. In humans, the sudden loss of previously established gains (e.g. loss of employment) has been implicated in the onset and maintenance of psychiatric disorders such as anxiety, depression, and substance abuse (Huston et al., 2013; Papini et al., 2015). Thus, elucidating the neural circuits underlying unexpected reward loss and frustration may help to understand adaptive and motivated behaviors, as well as the pathophysiological mechanisms of psychiatric illnesses.

CONTACT FOR REAGENT AND RESOURCE SHARING

Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Fabricio H. Do Monte (fabricio.h.domonte@uth.tmc.edu). MTAs for viral constructs were provided by Dr. Karl Deisseroth and viral packaging was performed by University of North Carolina (UNC) Vector Core Facility.

EXPERIMENTAL MODEL AND SUBJECT DETAILS

All procedures were approved by the Institutional Animal Care and Use Committee of the University of Puerto Rico School of Medicine, in compliance with National Institutes of Health guidelines for the care and use of laboratory animals. A total of 279 male Sprague Dawley rats (Harlan Laboratories) with 3–5 months of age and weighing 320–420 g at the time of the experiment were single housed and handled as previously described (Quirk et al., 2000). All animals were healthy naïve rats, unless indicated, maintained on a restricted diet of 18 g per day of standard laboratory rat chow, and trained to press a bar for sucrose on a variable interval schedule of reinforcement (VI 60 s). Rats were then assigned to each experimental group after matching for press rate during the conditioning phase. For optogenetic experiments, rats were randomly assigned to each of the experimental groups before the stereotaxic surgery was performed. Group size was estimated based on the literature and power analysis with a level of significance of 0.05 and a power of 0.9.

METHOD DETAILS

Surgeries

Following bar-press training, rats were anaesthetized with isofluorane (5% for induction, 2.5% for maintenance) and positioned in a stereotaxic frame (Kopf Instruments). For pharmacological inactivation experiments, a single guide cannula (26 gauge, 9 mm of length, Plastics One) was aimed at either the anterior paraventricular nucleus of the thalamus (aPVT; coordinates: anteroposterior (AP), −2.1 mm from bregma; mediolateral (ML), −1.83 mm from midline; dorsoventral (DV), −4.7 mm from the skull surface, 20 degree angle); or the posterior paraventricular nucleus of the thalamus (pPVT; AP, −3.0 mm; ML, −1.83 mm; DV, −4.7 mm, 20 degree angle). A stainless-steel obturator (33 gauge) was inserted into the guide cannula to avoid obstruction until infusions were made. The cannula was fixed to the skull using ortho acrylic cement and four anchoring screws.

For optogenetic experiments, a single guide cannula (23 gauge, 9 mm of length, Plastics One) was implanted aiming at aPVT, and an injector extending 1 mm past the tip of the cannula was used to infuse 0.5 μl of virus at a rate of 0.05 μl/min. The injector was kept inside the cannula for an additional 10 min to reduce back-flow. The injector was then removed and an optical fiber (0.22 NA, 200 nm core, constructed with products from Thorlabs, Inc) with 0.5 mm of projection was inserted into the guide cannula for aPVT illumination. The guide cannula and the optical fiber were fixed to the skull using adhesive cement (C&B metabond, Parkell) followed by acrylic cement. For illumination of aPVT terminals, bilateral optical fibers were implanted into the nucleus accumbens shell (NAc_sh; AP, +1.0 mm; ML: −2.3 mm; DV: −7.0, 11 degree angle), the central nucleus of the amygdala (CeA; AP, −2.8 mm; ML, −4.2 mm; DV, −7.0 mm), or the basolateral nucleus of the amygdala (BLA; AP, −2.8 mm, ML, −4.8 mm; DV, −7.1 mm).

For unit recording experiments, an array of 16 microwires (50 μm, 2 × 8, Neuro Biological Laboratories) was implanted aiming at aPVT. For retrograde labeling experiments, a 0.5 μl syringe (Hamilton) was used to infuse 0.1 μl of fast blue (blue fluorescently labeled; Polysciences, Inc) or cholera toxin b (red fluorescently labeled, TermoFisher Scientific), respectively into the NAcsh or CeA. After all surgeries, triple antibiotic was applied to the wound and an analgesic (Ketoprofen, 2 mg/Kg) was injected intramuscularly. Rats were allowed to recover for 1 week before initiating the experiments, except those used for optogenetic experiments, which were allowed 6–8 weeks for viral expression.

Drugs

The GABA_A agonist muscimol (MUS; BODIPY TMR-X conjugated; TermoFisher Scientific) was used to inactivate either aPVT or pPVT. A stainless-steel injector was connected to a 10 μl Hamilton syringe with polyethylene (PE-20) tubing. An infusion machine (Model 11 plus, Harvard Apparatus) allowed the microinjection of MUS (0.11 nmol/0.2μl) over a 1 min time period (0.2 μl/min) 30 min before testing, similar to our previous study (Do-Monte et al., 2015b). After infusion, the injector was kept within the cannula for 1 min to prevent drug backflow into the cannula.

Viruses

The adeno-associated viruses (AAVs; serotype 5) with a CaMKII promoter were obtained from the University of North Carolina Vector Core. Viral titers were 4 × 10¹² particles/ml for channelrhodopsin (AAV5:CaMKIIα::hChR2(H134R)-eYFP), 4 × 10¹² particles/ml for halorhodopsin (AAV5:CaMKIIα::eNpHR3.0-eYFP), and 3 × 10¹² particles/ml for control (AAV5:CaMKIIα::eYFP). Rats expressing only eYFP in aPVT were used to control for any nonspecific effects of viral infection or laser heating. Viruses were housed in a −80°C freezer until the day of infusion.

Laser delivery

Rats expressing channelrhodopsin (ChR2) in aPVT were illuminated using a blue diode-pumped solid state laser (DPSS, 473 nm, 20 Hz, 5 ms pulse width, 5 mW at the optical fiber tip; OptoEngine), connected to a stimulator (S88X, Grass Instruments), similar to our previous study (Do-Monte et al., 2015a). Rats expressing halorhodopsin (eNpHR) in aPVT were bilaterally illuminated into the NAc, CeA or BLA using a DPSS yellow laser (593.5 nm, constant, 10–12 mW at the optical fiber tip; OptoEngine). For both ChR2 and eNpHR experiments, the laser was activated at cue onset and persisted throughout the 30 s cue presentation, unless otherwise indicated. Laser light was passed through a shutter/coupler (200 nm, Oz Optics), patchcord (200 nm core, Doric Lenses), rotary joint (200 nm core, 1 × 2 or 2 × 2, Doric Lenses), single or dual patchcord (0.22 NA, 200 nm core, constructed with products from Thorlabs, Inc), and a single or bilateral optical fiber to reach the brain. For all the optogenetic experiments, rats were familiarized with the patchcord for at least 3 d before starting the experiments.

Single-unit recording

Rats implanted with electrode arrays with 16 fine wires (50 μm, 2 × 8, Neuro Biological Laboratories) aiming at aPVT were reward conditioned as described in the Experimental Procedures section. On the following day, rats received an extra conditioning session in which the light cue was turned off after each bar press, thereby reducing rats’ response to a single bar press and dish entry per cue. This allowed us to correlate specific reward-seeking events with the neuronal activity of aPVT cells (Cineplex, Plexon Inc.). A total of 54 neurons were recorded from 13 rats. Extracellular waveforms exceeding a voltage threshold were amplified (10K gain), digitized at 40 KHz (MAP, Plexon Inc.) and stored onto disk for further off-line analysis. Automated processing was performed using a valley-seeking scan algorithm and evaluated using sort quality metrics (Offline Sorter, Plexon Inc.). Spikes with interspike intervals < 1ms were excluded.

The firing rate of each neuron during the light cue, bar press, and dish entry responses was analyzed with commercial software (Neuroexplorer, NEX Technologies). Cue responses were calculated as Z-scores normalized to 20 pre-cue bins of 500 ms. Bar press responses were calculated as Z-scores normalized to 20 pre-cue bins of 650 ms, which is the approximate duration of the feeder noise. Dish entry responses were calculated as Z-scores normalized to 5 pre-cue bins of 6 s, which is the approximate time a rat spent in the dish area before engaging in a subsequent press. A pre-cue period was used for normalization to avoid firing rate changes induced by the cue. Neurons showing a Z-score > 2.58 (p< 0.01) during the first bin following cue onset, bar press, or dish entry were classified as excitatory responses, whereas neurons showing a Z-score > 1.96 (p <0.05) during the same first bin were defined as inhibitory responses. At the end of the recording sessions, a micro-lesion was made by passing anodal current (0.25 mA for 25 s) through the active wires to deposit iron in the tissue. After perfusion, brains were extracted from the skull and stored in a 30% sucrose/6% ferrocyanide solution to stain the iron deposits.

Optrode recording

Rats expressing eNpHR in aPVT were anaesthetized with urethane (1g/Kg, i.p.; Sigma Aldrich) and mounted in a stereotaxic frame. An optrode consisting of an optical fiber surrounded by 16 single-unit recording wires (NB Labs) was inserted aiming at the NAc_sh (AP, +1.0 mm; ML: −0.9; DV: −7.2) or the CeA (AP, −2.8 mm; ML, −4.2 mm; DV, −7.0 mm). The optrode was ventrally advanced in steps of 0.03 mm. Single-units were monitored in real time (RASPUTIN software, Plexon Inc.). After isolating a single-unit, a 593.5 nm laser was activated for 10 s within a 20 s period, at least 5 times. Single-units were recorded and stored for spike sorting (Offline Sorter, Plexon Inc.) and spike-train analysis (Neuorexplorer, NEX Technologies). In NAc_sh, a total of 68 neurons were recorded from 3 rats. In CeA, a total of 44 neurons were recorded from 1 rat. Excitatory and inhibitory responses were calculated by comparing the average firing rate of each neuron during the 10 s of laser off with the 10 s of laser on (Paired t-test, 1 s bins).

Cued sucrose-seeking

Rats were trained to learn that each bar press in the presence of a light cue resulted in the delivery of a sugar pellet into a nearby dish. After 3 days of cued sucrose-seeking training (24 trials per day, 30 s cue duration), rats learned to discriminate the reward-associated cue as indicated by a significant increase in press rate during the cue-on period compared with the cue-off period (see Fig 1B). Neuronal activity in the PVT or its efferents was then manipulated/recorded under two conditions: 1) when reward was available during the cue (day 4), or 2) when reward was omitted during the cue (day 4 or day 6, according to the experimental group). For all optogenetic experiments, day 5 consisted in a reward available test without laser manipulation.

Real-time place preference test

The place preference apparatus consisted of an acrylic chamber (42cm × 30 cm high × 42 cm) divided into two different compartments connected by an entry. Compartments consisted of black and white checker walls or black and white lined walls. Rats were placed in one side of the chamber (counterbalanced) and the laser was triggered (473 nm, 10 Hz) when the animal crossed to the other side of the chamber. The laser remained on for a maximum of 20 s or until the animal crossed back to the non-stimulated side. In the following day, rats were returned to the chamber in the absence of laser illumination. The percentage of time spent in each side of the chamber was automatically assessed (ANY-Maze) during the 10 min session of each day.

Open field task

Locomotor activity in the open field arena (90 cm diameter) was automatically assessed (ANY-maze, Stoelting) by comparing the total distance travelled between 3 min trials (laser off versus laser on), following a 3 min acclimation period. The percentage of time spent in the center of the open field (30 cm diameter) was used as an anxiety measurement. At the end of the experiments, animals were perfused and their brains were used for histological or immunohistochemical analysis.

Histology and immunohistochemistry

Animals were transcardially perfused and brains were processed for histology as previously described (Do-Monte et al., 2013). Only rats with the spread of fluorescent muscimol, the presence of eYFP or retrograde tracer labeling, and the track of the electrode wires or optical fiber tips located exclusively in the target area were included in the statistical analyses. For cFos immunohistochemistry, ChR2 and eYFP control rats received blue laser illumination (5 mW, 20 Hz, 5 ms pulse width, 2 trials of 30 s, 3 min apart) of aPVT in the home cage. One hour after illumination, animals were perfused and their brains were removed from the skull and stored in a 20% sucrose solution for 48 h. Brains were processed with anti-cFos serum raised in rabbit (1:2,000, EMD Millipore), and placed in a fluorescent secondary-antibody Alexa Fluor 594 (1:200, Life Technologies) for 2 h. Sections were washed with potassium phosphate buffer, mounted in gelatin-coated slides, and cover slipped with anti-fading mounting media (Vector Laboratories).

Immunohistochemistry quantification

Images were generated by using an Olympus microscope (Olympus, model BX51) equipped with a fluorescent lamp (X-Cite, Series 120Q) and a digital camera (Olympus, DP72). Counts of cFos-positive neurons were performed at 20x magnification. Images were generated for aPVT and NAc_sh. Cells were considered positive for cFos-like immunoreactivity if the nucleus was the appropriate size (area ranging from 100 to 500 μm²) and shape (at least 50% of circularity), and presented a red fluorescence different from the background. cFos-positive cells were automatically counted (Metamorph software version 6.1, Molecular Devices) and averaged for both hemispheres at four different rostro-caudal levels of aPVT (from −1.9 mm to −2.6 mm from bregma). The density of cFos-positive cells (cells per 0.1 mm²) was calculated by dividing the number of cFos-positive cells by the total area of each region.

QUANTIFICATION AND STATISTICAL ANALYSIS

Behavior was recorded with digital video cameras (Micro Video Products) and press rate was measured using commercially available software (Graphic State, Coulbourn Instruments). Distance travelled and time spent in the different areas of the open field and place preference chamber were measured using automated video-tracking system (ANY-maze, Stoelting Co). Manual counting was performed by an experimenter blind to the experimental groups, and was used to quantify the percentage of time spent in the different arms of the elevated plus maze task, and the amount of sucrose consumed ad libitum. Presses per minute were calculated by measuring the number of presses during the 30 s cue. Presses during the cue off period were calculated by measuring the number of presses during the 60 s immediately before the cue onset. The number of presses during the first light cue of each day was used as an index of reward memory. A small percentage of rats (2%) were excluded from analysis because they did not meet the criteria for acquisition of reward conditioning (> 10 presses per minute in at least 1 trial of the conditioning phase). Number of replications (n) are equal to either the number of rats used in behavioral and immunohistochemical experiments or the number of neurons recorded from in electrophysiological experiments, as indicated in the figure legends. All graphics and numerical values reported in the figures are presented as mean ± s.e.m.. Parametric analysis was used since the data did not deviate substantially from a normal distribution (Shapiro–Wilk normality test, p< 0.05). Similar variance was observed in all the groups statistically compared (F-test two-sample for variance before t-test, Barttlet’s Chi-square test before ANOVA; p< 0.05). Statistical significance was determined with paired or unpaired Student’s t test or repeated-measures ANOVA followed by Duncan posthoc comparisons (STATISTICA 6, Stat-Soft Inc), as indicated for each experiment. The level of statistical significance adopted was p< 0.05.

KEY RESOURCES TABLE

The table highlights the genetically modified organisms and strains, cell lines, reagents, software, and source data essential to reproduce results presented in the manuscript. Depending on the nature of the study, this may include standard laboratory materials (i.e., food chow for metabolism studies), but the Table is not meant to be comprehensive list of all materials and resources used (e.g., essential chemicals such as SDS, sucrose, or standard culture media don’t need to be listed in the Table). Items in the Table must also be reported in the Method Details section within the context of their use. The number of primers and RNA sequences that may be listed in the Table is restricted to no more than ten each. If there are more than ten primers or RNA sequences to report, please provide this information as a supplementary document and reference this file (e.g., See Table S1 for XX) in the Key Resources Table.

Please note that ALL references cited in the Key Resources Table must be included in the References list. Please report the information as follows:

• REAGENT or RESOURCE: Provide full descriptive name of the item so that it can be identified and linked with its description in the manuscript (e.g., provide version number for software, host source for antibody, strain name). In the Experimental Models section, please include all models used in the paper and describe each line/strain as: model organism: name used for strain/line in paper: genotype. (i.e., Mouse: OXTR^fl/fl: B6.129(SJL)-Oxtr^tm1.1Wsy/J). In the Biological Samples section, please list all samples obtained from commercial sources or biological repositories. Please note that software mentioned in the Methods Details or Data and Software Availability section needs to be also included in the table. See the sample Table at the end of this document for examples of how to report reagents.

• SOURCE: Report the company, manufacturer, or individual that provided the item or where the item can obtained (e.g., stock center or repository). For materials distributed by Addgene, please cite the article describing the plasmid and include “Addgene” as part of the identifier. If an item is from another lab, please include the name of the principal investigator and a citation if it has been previously published. If the material is being reported for the first time in the current paper, please indicate as “this paper.” For software, please provide the company name if it is commercially available or cite the paper in which it has been initially described.

• IDENTIFIER: Include catalog numbers (entered in the column as “Cat#” followed by the number, e.g., Cat#3879S). Where available, please include unique entities such as RRIDs, Model Organism Database numbers, accession numbers, and PDB or CAS IDs. For antibodies, if applicable and available, please also include the lot number or clone identity. For software or data resources, please include the URL where the resource can be downloaded. Please ensure accuracy of the identifiers, as they are essential for generation of hyperlinks to external sources when available. Please see the Elsevier list of Data Repositories with automated bidirectional linking for details. When listing more than one identifier for the same item, use semicolons to separate them (e.g. Cat#3879S; RRID: AB_2255011). If an identifier is not available, please enter “N/A” in the column.

  • A NOTE ABOUT RRIDs: We highly recommend using RRIDs as the identifier (in particular for antibodies and organisms, but also for software tools and databases). For more details on how to obtain or generate an RRID for existing or newly generated resources, please visit the RII or search for RRIDs.

Please see the sample Table at the end of this document for examples of how reagents should be cited. To see how the typeset table will appear in the PDF and online, please refer to any of the research articles published in Cell in the August 25, 2016 issue and beyond.

Please use the empty table that follows to organize the information in the sections defined by the subheading, skipping sections not relevant to your study. Please do not add subheadings. To add a row, place the cursor at the end of the row above where you would like to add the row, just outside the right border of the table. Then press the ENTER key to add the row. You do not need to delete empty rows. Each entry must be on a separate row; do not list multiple items in a single table cell.

KEY RESOURCES TABLE.

REAGENT or RESOURCE	SOURCE	IDENTIFIER
Antibodies
Anti-cFos	EMD Millipore	ABE457
Secondary antibody Alexa Fluor 594	Life Technologies	A20185
Bacterial and Virus Strains
AAV5:CaMKIIα::hChR2(H134R)-eYFP	University of North Carolina (UNC) vector core https://www.med.unc.edu/genetherapy/vectorcore	N/A
AAV5:CaMKIIα::eNpHR3.0-eYFP	UNC vector core	N/A
AAV5:CaMKIIα::eYFP	UNC vector core	N/A
Biological Samples
Chemicals, Peptides, and Recombinant Proteins
Fast Blue	Polysciences, Inc	17740
Cholera Toxin Subunit B (Recombinant), Alexa Fluor 594 Conjugated	ThermoFisher Scientific	C34777
Muscimol BODIPY TMR-X conjugated	ThermoFisher Scientific	M23400
Vectashield anti-fading mounting media	Vector Laboratories	H-1200
Critical Commercial Assays
Blue diode-pumped solid state laser	OptoEngine	DPSS, 473 nm
Yellow diode-pumped solid state laser	OptoEngine	DPSS, 593.5 nm
Electrical Stimulator	Grass Instruments	S88X
Shutter/coupler	OzOptics	HPUC-23-400/700-M-20AC-11-SH
Infusion Machine	Harvard Apparatus	Model 11 plus
Deposited Data
Experimental Models: Cell Lines
Experimental Models: Organisms/Strains
Male Sprague Dawley Rats	Charles River	N/A
Oligonucleotides
Recombinant DNA
Software and Algorithms
Cineplex	Plexon, Inc	N/A
Offline Sorter	Plexon, Inc	N/A
Neuroexplorer	NEX Technologies	N/A
ANY-maze	Stoelting Co	N/A
Graphic State	Coulbourn Instruments	N/A
STATISTICA 6	Stat-Soft, Inc	N/A
Other

Supplementary Material

supplement

MOVIE S1 – Related to Figure 3. Photoactivation of aPVT during sucrose-seeking.

TABLE WITH EXAMPLES FOR AUTHOR REFERENCE

REAGENT or RESOURCE	SOURCE	IDENTIFIER
Antibodies
Rabbit monoclonal anti-Snail	Cell Signaling Technology	Cat#3879S; RRID: AB_2255011
Mouse monoclonal anti-Tubulin (clone DM1A)	Sigma-Aldrich	Cat#T9026; RRID: AB_477593
Rabbit polyclonal anti-BMAL1	This paper	N/A
Bacterial and Virus Strains
pAAV-hSyn-DIO-hM3D(Gq)-mCherry	Krashes et al., 2011	Addgene AAV5; 44361-AAV5
AAV5-EF1a-DIO-hChR2(H134R)-EYFP	Hope Center Viral Vectors Core	N/A
Cowpox virus Brighton Red	BEI Resources	NR-88
Zika-SMGC-1, GENBANK: KX266255	Isolated from patient (Wang et al., 2016)	N/A
Staphylococcus aureus	ATCC	ATCC 29213
Streptococcus pyogenes: M1 serotype strain: strain SF370; M1 GAS	ATCC	ATCC 700294
Biological Samples
Healthy adult BA9 brain tissue	University of Maryland Brain & Tissue Bank; http://medschool.umaryland.edu/btbank/	Cat#UMB1455
Human hippocampal brain blocks	New York Brain Bank	http://nybb.hs.columbia.edu/
Patient-derived xenografts (PDX)	Children’s Oncology Group Cell Culture and Xenograft Repository	http://cogcell.org/
Chemicals, Peptides, and Recombinant Proteins
MK-2206 AKT inhibitor	Selleck Chemicals	S1078; CAS: 1032350-13-2
SB-505124	Sigma-Aldrich	S4696; CAS: 694433-59-5 (free base)
Picrotoxin	Sigma-Aldrich	P1675; CAS: 124-87-8
Human TGF-β	R&D	240-B; GenPept: P01137
Activated S6K1	Millipore	Cat#14-486
GST-BMAL1	Novus	Cat#H00000406-P01
Critical Commercial Assays
EasyTag EXPRESS 35S Protein Labeling Kit	Perkin-Elmer	NEG772014MC
CaspaseGlo 3/7	Promega	G8090
TruSeq ChIP Sample Prep Kit	Illumina	IP-202-1012
Deposited Data
Raw and analyzed data	This paper	GEO: GSE63473
B-RAF RBD (apo) structure	This paper	PDB: 5J17
Human reference genome NCBI build 37, GRCh37	Genome Reference Consortium	http://www.ncbi.nlm.nih.gov/projects/genome/assembly/grc/human/
Nanog STILT inference	This paper; Mendeley Data	http://dx.doi.org/10.17632/wx6s4mj7s8.2
Affinity-based mass spectrometry performed with 57 genes	This paper; and Mendeley Data	Table S8; http://dx.doi.org/10.17632/5hvpvspw82.1
Experimental Models: Cell Lines
Hamster: CHO cells	ATCC	CRL-11268
D. melanogaster: Cell line S2: S2-DRSC	Laboratory of Norbert Perrimon	FlyBase: FBtc0000181
Human: Passage 40 H9 ES cells	MSKCC stem cell core facility	N/A
Human: HUES 8 hESC line (NIH approval number NIHhESC-09-0021)	HSCI iPS Core	hES Cell Line: HUES-8
Experimental Models: Organisms/Strains
C. elegans: Strain BC4011: srl-1(s2500) II; dpy-18(e364) III; unc-46(e177)rol-3(s1040) V.	Caenorhabditis Genetics Center	WB Strain: BC4011; WormBase: WBVar00241916
D. melanogaster: RNAi of Sxl: y[1] sc[*] v[1]; P{TRiP.HMS00609}attP2	Bloomington Drosophila Stock Center	BDSC:34393; FlyBase: FBtp0064874
S. cerevisiae: Strain background: W303	ATCC	ATTC: 208353
Mouse: R6/2: B6CBA-Tg(HDexon1)62Gpb/3J	The Jackson Laboratory	JAX: 006494
Mouse: OXTRfl/fl: B6.129(SJL)-Oxtrtm1.1Wsy/J	The Jackson Laboratory	RRID: IMSR_JAX:008471
Zebrafish: Tg(Shha:GFP)t10: t10Tg	Neumann and Nuesslein-Volhard, 2000	ZFIN: ZDB-GENO-060207-1
Arabidopsis: 35S::PIF4-YFP, BZR1-CFP	Wang et al., 2012	N/A
Arabidopsis: JYB1021.2: pS24(AT5G58010)::cS24:GFP(-G):NOS #1	NASC	NASC ID: N70450
Oligonucleotides
siRNA targeting sequence: PIP5K I alpha #1: ACACAGUACUCAGUUGAUA	This paper	N/A
Primers for XX, see Table SX	This paper	N/A
Primer: GFP/YFP/CFP Forward: GCACGACTTCTTCAAGTCCGCCATGCC	This paper	N/A
Morpholino: MO-pax2a GGTCTGCTTTGCAGTGAATATCCAT	Gene Tools	ZFIN: ZDB-MRPHLNO-061106-5
ACTB (hs01060665_g1)	Life Technologies	Cat#4331182
RNA sequence: hnRNPA1_ligand: UAGGGACUUAGGGUUCUCUCUAGGGACUUAGGGUUCUCUCUAGGGA	This paper	N/A
Recombinant DNA
pLVX-Tight-Puro (TetOn)	Clonetech	Cat#632162
Plasmid: GFP-Nito	This paper	N/A
cDNA GH111110	Drosophila Genomics Resource Center	DGRC:5666; FlyBase:FBcl0130415
AAV2/1-hsyn-GCaMP6-WPRE	Chen et al., 2013	N/A
Mouse raptor: pLKO mouse shRNA 1 raptor	Thoreen et al., 2009	Addgene Plasmid #21339
Software and Algorithms
Bowtie2	Langmead and Salzberg, 2012	http://bowtie-bio.sourceforge.net/bowtie2/index.shtml
Samtools	Li et al., 2009	http://samtools.sourceforge.net/
Weighted Maximal Information Component Analysis v0.9	Rau et al., 2013	https://github.com/ChristophRau/wMICA
ICS algorithm	This paper; Mendeley Data	http://dx.doi.org/10.17632/5hvpvspw82.1
Other
Sequence data, analyses, and resources related to the ultra-deep sequencing of the AML31 tumor, relapse, and matched normal.	This paper	http://aml31.genome.wustl.edu
Resource website for the AML31 publication	This paper	https://github.com/chrisamiller/aml31SuppSite