Dopamine subsystems that track internal states

doi:10.1038/s41586-022-04954-0

. 2022 Aug;608(7922):374-380.

doi: 10.1038/s41586-022-04954-0. Epub 2022 Jul 13.

Dopamine subsystems that track internal states

James C R Grove^{1

2

3}, Lindsay A Gray⁴, Naymalis La Santa Medina⁴, Nilla Sivakumar⁴, Jamie S Ahn⁴, Timothy V Corpuz⁴, Joshua D Berke^{3

5

6}, Anatol C Kreitzer^{1

3

5

6

7}, Zachary A Knight^{8

9

10

11

12}

Affiliations

¹ Department of Physiology, University of California, San Francisco, San Francisco, CA, USA.
² Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, USA.
³ Neuroscience Graduate Program, University of California, San Francisco, San Francisco, CA, USA.
⁴ Howard Hughes Medical Institute, San Francisco, CA, USA.
⁵ Department of Neurology, University of California, San Francisco, San Francisco, CA, USA.
⁶ Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.
⁷ Gladstone Institutes, San Francisco, CA, USA.
⁸ Department of Physiology, University of California, San Francisco, San Francisco, CA, USA. [email protected].
⁹ Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, USA. [email protected].
¹⁰ Neuroscience Graduate Program, University of California, San Francisco, San Francisco, CA, USA. [email protected].
¹¹ Howard Hughes Medical Institute, San Francisco, CA, USA. [email protected].
¹² Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA. [email protected].

PMID: 35831501
PMCID: PMC9365689
DOI: 10.1038/s41586-022-04954-0

Dopamine subsystems that track internal states

James C R Grove et al. Nature. 2022 Aug.

. 2022 Aug;608(7922):374-380.

doi: 10.1038/s41586-022-04954-0. Epub 2022 Jul 13.

Authors

Affiliations

¹ Department of Physiology, University of California, San Francisco, San Francisco, CA, USA.
² Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, USA.
³ Neuroscience Graduate Program, University of California, San Francisco, San Francisco, CA, USA.
⁴ Howard Hughes Medical Institute, San Francisco, CA, USA.
⁵ Department of Neurology, University of California, San Francisco, San Francisco, CA, USA.
⁶ Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.
⁷ Gladstone Institutes, San Francisco, CA, USA.
⁸ Department of Physiology, University of California, San Francisco, San Francisco, CA, USA. [email protected].
⁹ Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, USA. [email protected].
¹⁰ Neuroscience Graduate Program, University of California, San Francisco, San Francisco, CA, USA. [email protected].
¹¹ Howard Hughes Medical Institute, San Francisco, CA, USA. [email protected].
¹² Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA. [email protected].

PMID: 35831501
PMCID: PMC9365689
DOI: 10.1038/s41586-022-04954-0

Abstract

Food and water are rewarding in part because they satisfy our internal needs^1,2. Dopaminergic neurons in the ventral tegmental area (VTA) are activated by gustatory rewards^3-5, but how animals learn to associate these oral cues with the delayed physiological effects of ingestion is unknown. Here we show that individual dopaminergic neurons in the VTA respond to detection of nutrients or water at specific stages of ingestion. A major subset of dopaminergic neurons tracks changes in systemic hydration that occur tens of minutes after thirsty mice drink water, whereas different dopaminergic neurons respond to nutrients in the gastrointestinal tract. We show that information about fluid balance is transmitted to the VTA by a hypothalamic pathway and then re-routed to downstream circuits that track the oral, gastrointestinal and post-absorptive stages of ingestion. To investigate the function of these signals, we used a paradigm in which a fluid's oral and post-absorptive effects can be independently manipulated and temporally separated. We show that mice rapidly learn to prefer one fluid over another based solely on its rehydrating ability and that this post-ingestive learning is prevented if dopaminergic neurons in the VTA are selectively silenced after consumption. These findings reveal that the midbrain dopamine system contains subsystems that track different modalities and stages of ingestion, on timescales from seconds to tens of minutes, and that this information is used to drive learning about the consequences of ingestion.

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Conflict of interest statement

The authors declare no competing interests.

Figures

**Fig. 1. VTA-DA neurons track systemic hydration.**
a, Representative image of GRIN lens placement and VTA-DA neurons expressing GCaMP6. b, Tuning maps of DA neuron responses from the same field of view during and after drinking water. c, Example traces of calcium dynamics in five representative neurons during and after water consumption. d, Individual neuron responses to consumption of water, intragastric (IG) infusion of water (1.2 ml), and intraperitoneal (IP) injection of water (1.2 ml) or hypertonic saline (3 M NaCl, 0.12 ml). e, Population-weighted z-score (calculated as the fraction of neurons activated or inhibited multiplied by their z-scored activity change) for each of the stimuli shown. The percentages of neurons activated (red) and inhibited (blue) are listed above and below each bar graph. ‘Post-ingestion’ is from 0 to 20 min after the end of self-paced consumption of water or 0.3 M NaCl; ‘after IG infusion’ is from 0 to 20 min after the end of intragastric infusion (1.2 ml) of water or 0.3 M NaCl; ‘after IP injection’ is from 0 to 30 min after intraperitoneal injection of water (1.2 ml), NaCl (3 M, 0.12 ml), isoproterenol (100 mg kg⁻¹) or polyethylene glycol (PEG) (40%, 0.4 ml). f, Top, time course of the activation and then return to baseline of individual VTA-DA neurons following intragastric infusion of water (1.2 ml). Bottom, mean trace. Mice are from a separate cohort than those used in d. g, Mean activity traces of neurons (from d) activated by intraperitoneal water injection (red) and inhibited by intraperitoneal NaCl injection (blue), with concurrent blood osmolality changes plotted below. NS, P > 0.05; **P < 0.01, ***P < 0.001. Data are mean ± s.e.m. Statistics are presented in Extended Data Table 2.

**Fig. 2. Distinct dopamine subsystems track food and water ingestion.**
a, Maps of individual VTA-DA neurons tracked across experimental days during imaging. b, Example traces from neurons specifically responding to intragastric infusion (1.2 ml) of either Ensure or water. c, Left, proportion of neurons activated during intragastric infusion of Ensure and water. Right, individual neurons show no correlation in their response during intragastric infusion of water versus Ensure. d, Left, proportion of neurons activated from 0–20 min after the end of intragastric infusion of water or Ensure. Right, individual neurons show no correlation in their response after intragastric infusion of water versus Ensure. e, Left, example traces showing neurons activated after both intragastric infusion and intraperitoneal injection of water (1.2 ml). Middle, proportion of neurons activated by intraperitoneal and intragastric water. Right, the response of individual neurons to intraperitoneal water injection is positively correlated with their response to intragastric water injection. f, Left, example traces showing neurons that display opposite activity patterns after intraperitoneal water injection (1.2 ml) and hypertonic saline injection (3 M NaCl, 0.12 ml). Middle, proportion of neurons activated by intraperitoneal water and inhibited by intraperitoneal saline. Right, the responses of individual neurons to intraperitoneal water and intraperitoneal saline are negatively correlated. Data are mean ± s.e.m. Statistics are shown in Extended Data Table 2.

**Fig. 3. A forebrain–hypothalamic pathway that conveys internal state information to the VTA.**
a, A model of a possible anatomic pathway connecting interoceptive neurons for water and nutrients to the VTA. b, Left, schematic of simultaneous microendoscope imaging of VTA-DA neurons and chemogenetic inhibition (with hM4Di) of LH-GABA neurons. Right, population responses (as defined in Fig. 1) for VTA-DA neurons activated (red) or inhibited (blue) by saline or CNO, and after water infusion following saline or CNO. c, Left, schematic of simultaneous microendoscope imaging of VTA-DA neurons and chemogenetic activation (with hM3Dq) of SFO thirst neurons. Middle, dynamics of individual VTA-DA neurons in response to water infusion after saline or CNO injection in sated mice. Right, population responses of VTA-DA neurons activated (red) or inhibited (blue) after intragastric infusion. d, Population responses of VTA-DA neurons activated (red) or inhibited (blue) after intraperitoneal injection of water. Dehydr., dehydrated. Data are mean ± s.e.m. Statistics are shown in Extended Data Table 2.

**Fig. 4. Dopamine release at different VTA targets tracks different stages of ingestion.**
a, Schematic showing the setup and seven recording sites (red circles) for measuring dopamine release. b, Left, example recording from the mSh showing dopamine release during the oral phase of water ingestion (30 s after the start of licking). Right, mean dopamine release in each recorded region during this oral phase during water (blue) and Ensure (orange) consumption. c, Left, example recording from BLA showing dopamine release during gastrointestinal phase for Ensure (first 12 min after intragastric infusion starts). Right, mean dopamine release in each recorded region during this gastrointestinal phase during water and Ensure infusion. d, Left, example recording from VTA showing dopamine release during systemic phase for water (12 to 50 min after the start of intragastric infusion). Right, mean dopamine release in each recorded region during this systemic phase following water and Ensure infusion. e, Left, schematic of projection-specific imaging. Middle, mean responses of VTA-DA→BLA neurons and VTA-DA→mSh neurons during water intragastric infusion (gastrointestinal phase highlighted). Right, mean responses (population-weighted z-score) of activated neurons projecting to BLA and mSh. *P < 0.05. Data are mean ± s.e.m. Statistics are shown in Extended Data Tables 2 and 3.

**Fig. 5. Post-ingestive changes in fluid balance drive learning about fluids via VTA-DA neurons.**
a, Schematic of closed-loop system for fluid preference training. Mice are hydrated by consumption of one flavoured solution (flavour A) and mildly dehydrated by another (flavour B) via intragastric infusion of water or saline that is triggered by licking. b, Preference for flavour A before and after training. c, Changes in total consumption on the first and last days of training. d, Left, GRAB-DA fluorescence in mSh and BLA during consumption of the dehydrating solution on first and last training days. Right, summary plots of lick-triggered GRAB-DA responses on first and last training days with each solution. e, Inhibiting VTA-DA neurons during training selectively after water access has been removed (minutes 10–60) eliminates preference learning in mice expressing GtACR but not in mCherry controls. Data are mean ± s.e.m. Statistics are shown in Extended Data Table 4.

**Extended Data Fig. 1. VTA-DA neurons respond to post-ingestive changes in fluid balance.**
a, Recording images separated by one hour with cell boundaries generated by CNMFe in mice not subject to manipulation. b, Dynamics of VTA-DA neurons during a bout of licking water and the population weighted z-score of the neurons activated (red) or inhibited (blue) from 0 to 30 s following the onset of the first licking bout. c, Activity traces of individual neurons during and after water consumption (see Fig. 1c for additional examples). d, Mean z-score of neurons activated following drinking water and illustration of how the 50% rise time (T50) is calculated for neurons responding to IG water infusion. Time of water access is shown (“water licks”). e, Mean inferred spike rate of DA neurons activated following water ingestion. **f,g** Inferred spike rate (f) and baseline fluorescence (g; see Methods) changes in DA neurons activated following water ingestion. h, Percentage of neurons activated and inhibited following water ingestion for four mice from Fig. 1d. i, Summary boxplots showing z-scored change of activity following water ingestion for each neuron in each of four mice (intra-class correlation or ICC=varbetween mice/vartotal). j, Cumulative licks for self-paced drinking of water or hypertonic saline (0.3 M NaCl) for thirsty mice (n = 4 and 3). k, (Left) Responses of individual neurons during and following consumption of hypertonic saline (0.3 M NaCl). (Right) Mean z-scored activity of neurons activated (red), inhibited (blue), and unaffected (grey) following saline ingestion. l, Mean z-scored activity during water IG infusion (from Fig. 1c) using different z-score thresholds for defining the activated and inhibited population. m, Summary boxplots showing z-scored change of activity following water IG infusion for each neuron separated by mouse (data comes from all recordings during water IG infusion in dehydrated mice; each replicate is a different mouse; from Fig. 1 and Extended Data Figs. 1, 6). n, Data points are the mean z-scored change in activity (for all neurons) for each mouse shown panel m. Bar graph shows the mean of these mean z-scores. o, Mean activity of neurons activated following IG infusion of water at 0.1 mL/min (slow) and 0.2 mL/min (fast) speeds and a summary plot of the T50. p, Mean head acceleration during and after water IG infusion (n = 3 mice). q, Mean responses of activated and inhibited neurons (population weighted z-score) following IG infusion of different water volumes in sated and water-deprived mice. r, Mean responses of activated and inhibited neurons (population weighted z-score) following IP injections of 0.12 mL of 3 M NaCl, 1 M NaCl, and 2 M mannitol. Note that 1 M NaCl and 2 M mannitol are equiosmotic. s, Mean response of neurons inhibited by tail vein injection of NaCl (zoom in shows a shorter timescale to illustrate the rapid response). t, Mean responses and proportion of neurons activated and inhibited after tail vein injection (asterisks from permutation test applied to all neurons). u, Dynamics of individual neurons activated during IG infusion of water (1.2 mL). u, Dynamics of individual neurons activated during IG infusion of water (1.2 mL). v, Eye wipes elicited within 15s of 0.1% capsaicin ocular delivery. This was performed three days after IP injection of 50 mg/kg capsaicin or control saline in order to functionally validate capsaicin deafferentation. w, Mean responses and proportion of neurons activated and inhibited after IG water infusion (1.2 mL) in dehydrated mice before and after vagal deafferentation with 50 mg/kg capsaicin. ns.P > 0.05, *P < 0.05, **P < 0.01, ***P < 0.001. All error bars show mean±s.e.m. Statistics in Extended Data Table 2.

**Extended Data Fig. 2. Close-up view of the activity of VTA-DA neurons during IG water infusion.**
a, VTA-DA neuron responses to IG water infusion (from Fig. 1d) exhibit instances of apparent coordinated activity when viewed on a timescale of tens of minutes. Points of apparent coordinated activity are marked with arrows. b, Close-up view of first 100 neurons show that not all neurons participate in this coordinated activity. c, Further zoomed in dynamics of the first 100 neurons show that much of this activity is uncoordinated on the seconds timescale.

**Extended Data Fig. 3. VTA-DA neuron responses to food and water occur primarily at different stages of ingestion.**
a, Mean response of VTA-DA neurons during an Ensure lick bout. b, Mean neuron activity during consumption of water and Ensure, depicted as the mean trace and summary plot. “Lick response” is defined as the mean z-scored change of activity from 0 to 30 s after the onset of consumption. “Delayed response” is defined as the mean z-scored change of activity from 0 to 20 min after the end of consumption. c, Responses of individual VTA-DA neurons during and after IG infusion of Ensure and water (1.2 mL). Neurons are separated according to whether they are activated most strongly during or after IG infusion. d, Mean responses of activated and inhibited neurons during and after IG infusion (population weighted z-score, as defined in Fig. 1). e, Rise time of neurons activated (from Extended Data Fig. 2c). ns.P > 0.05, ***P < 0.001, by permutation test. All error bars and shaded lines show mean±s.e.m.

**Extended Data Fig. 4. DA subpopulations respond to ingestion on three distinct timescales.**
a, Tuning maps showing individual DA neuron responses during consumption of water and post-ingestion. b, Proportion of neurons activated during consumption of water and post-ingestion and correlation of activity. c, Proportion of neurons activated during consumption of water and during IG infusion of water and correlation of activity. d, Proportion of neurons activated post-water ingestion and during IG infusion of water and correlation of activity. e, Example traces of neurons activating both after water IG infusion and after self-paced water consumption, alongside proportion of neurons activated by both and the correlation of activity. f, Proportion of neurons activated after Ensure IG infusion and after glucose IP injection and correlation of activity. g, Proportion of neurons inhibited after IG infusion and IP injection of NaCl and correlation of activity. h, Responses of individual neurons during IG infusion of Ensure and glucose, alongside the correlation of activity of the tracked neurons. Statistics in Extended Data Table 2.

**Extended Data Fig. 5. LH-GABA neurons respond to blood osmolality changes and modulate VTA dynamics.**
a, (Left) Representative image of GRIN lens placement for imaging LH neurons. Scale bar, 0.5 mm. (Right) Population-weighted z-scored activity and proportions of LH-GABA neurons activated (red), inhibited (blue), and unaffected (grey) after IG infusion (1.2 mL) of water (388 neurons/3 mice) and Ensure (169 neurons/3 mice). b, Rise time of LH-GABA (from a) and VTA-DA neurons (from Figs. 1e, 2b–c) activated following IG infusion of ensure or water (1.2 mL). c, Dynamics of individual LH-GABA neurons after IP injection of hypertonic saline (3 M NaCl, 0.12 mL; 5 mice). d, (Left) Schematic for microendoscope imaging of LH-GABA→VTA neurons. (Right) Split-plot and proportion of projection neurons activated, inhibited, and unaffected after infusion of water (160 neurons/3 mice) and Ensure (150 neurons/3 mice). e, Schematic for simultaneous microendoscope imaging of VTA-GABA neurons and optogenetic stimulation of LH-GABA neuron terminals, alongside dynamics of individual VTA-GABA neurons during LH-GABA neuron terminal stimulation (3 mice). All shaded lines show mean±s.e.m.

**Extended Data Fig. 6. Hunger and thirst neurons control the gain of VTA-DA neuron responses to nutrients and water.**
a, (Left) Schematic for simultaneous microendoscope imaging of VTA-DA neurons and optogenetic activation of SFO “thirst” neurons. (Middle) Effect of SFO neuron activation on water intake (5 min in sated mice; n = 3 mice). (Right) Summary bar graphs and percentages of VTA-DA neurons activated (red) or inhibited (blue) by IP injection of saline or CNO. b, Mean responses and proportion of neurons activated and inhibited during IG infusion of water (1.2 mL) following SFO neuron activation, water deprivation, or neither. c, (Left) Schematic for simultaneous microendoscope imaging of VTA-DA neurons and optogenetic activation of AgRP “hunger” neurons. (Middle) Effect of AgRP neuron activation on food intake (5 min in sated mice; n = 3 mice). (Right) Mean responses and proportion of neurons activated and inhibited after AgRP neuron activation or control. d, (Left) Individual neuron dynamics. (Right) Mean responses and proportion of neurons activated and inhibited after IG infusion of Ensure (0.6 mL) following AgRP neuron activation, food deprivation, or neither. Note that both food deprivation and AgRP neuron stimulation counterintuitively reduce DA responses to IG nutrients. e, Mean responses and proportion of neurons activated and inhibited after intraperitoneal (IP) injection of 50% glucose (0.3 mL) following AgRP neuron activation, food deprivation, or neither. f, Mean responses and proportion of neurons activated and inhibited during IG infusion of Ensure (0.6 mL) following AgRP neuron activation, food deprivation, or neither. g, (Left) Schematic for simultaneous microendoscope imaging of LH-GABA→VTA neurons and chemogenetic activation (hM3Dq) of SFO “thirst” neurons. (Middle) Summary bar graphs and percentages of LH-GABA→VTA neurons activated (red) or inhibited (blue) by saline or CNO. (Right) Summary bar graphs and percentages of LH-GABA→VTA neurons activated (red) or inhibited (blue) after IG infusion of water (1.2 mL). **h-i**, Responses to food and water in an orthogonal need state. h, Mean responses and proportion of VTA-DA neurons activated and inhibited after IG infusion of water (1.2 mL) while sated or food-deprived. i, Mean responses and proportion of VTA-DA neurons activated and inhibited after Ensure IG infusion (1.2 mL) while sated or dehydrated. j, Mean responses and proportion of VTA-DA neurons activated and inhibited after IG infusion of hypertonic saline (0.3 M NaCl, 1.2 mL) in mice that are sated or sodium depleted. ns.P > 0.05, *P < 0.05, **P < 0.01, ***P < 0.001. All error bars show mean±s.e.m. Statistics in Extended Data Table 2.

**Extended Data Fig. 7. GRAB-DA signal normalization for long recordings.**
a, Mean GRAB-DA fluoresence responses in BLA during and after IG infusion of Ensure or sham infusion using 405 nm and 470 nm excitation wavelengths. Note the timescale of the recording. b, Mean GRAB-DA responses at 470 nm excitation when normalized to the 405 nm “isosbestic” response. c, Mean GRAB-DA responses at 470 nm excitation when normalized using an exponential fit to the fluorescence decay in the baseline period. Statistics in Extended Data Table 3.

**Extended Data Fig. 8. DA release in downstream targets in response to water, salt, and Ensure during different stages of ingestion.**
a, Approximate placements (dots) of photometry fibers for GRAB-DA recordings, alongside representative images. Scale bar, 1 mm. b, GRAB-DA fluorescence responses in VTA and DS to systemic hydration changes following IG infusion (1.2 mL) of water or hypertonic saline (0.3 M NaCl). c, GRAB-DA responses in VTA and DS following IG infusion (1.2 mL) of water and Ensure during sated state and following food or water deprivation. d, Mean GRAB-DA responses in VTA during and after IP injection of water. e, Dynamics of BLA and NAc projection neurons during and after IG infusion of water (see Fig. 4e). f, Mean GRAB-DA responses during self-paced drinking (top and bottom rows) and IG infusion (1.2 mL, middle row) of water (blue), 300 mM NaCl (grey), and Ensure (orange). ns.P > 0.05, *P < 0.05, **P < 0.01, ***P < 0.001. All error bars and shaded lines show mean±s.e.m. Statistics in Extended Data Table 2, 3.

**Extended Data Fig. 9. Timing of fluid preference learning.**
a, Summary plots of consumption of each solution on each fluid preference training day using the protocol in which mice have access to water for 60 min in each training day (see Fig. 5c). b, Illumination of VTA-DA neurons throughout the entire training session (60 min) prevents preference learning in mice expressing GtACR but not in the mCherry-expressing controls. c, (Left) Revised training protocol in which water access is removed after 10 min of consumption in each training session. (Right) Robust preference learning occurs even with only 10 min access (i.e. water is removed before VTA-DA activity has changed due to post-absorptive changes; n = 6). d, Changes in total consumption on the first and last days of training in delayed silencing experiment (Fig. 5e). ns.P > 0.05, *P < 0.05, **P < 0.01. All error bars and shaded lines show mean±s.e.m. Statistics in Extended Data Table 4.

**Extended Data Fig. 10. Dynamics of dopamine release during fluid preference training.**
a, GRAB-DA fluorescence in mSh and BLA during consumption of the hydrating solution on first and last training days (see Fig. 5e). b, Summary plots of lick-triggered GRAB-DA responses on first training days with each solution. ns.P > 0.05. All error bars and shaded lines show mean±s.e.m. Statistics in Extended Data Table 3.

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Tracking ingestion.
Yates D. Yates D. Nat Rev Neurosci. 2022 Sep;23(9):519. doi: 10.1038/s41583-022-00628-y. Nat Rev Neurosci. 2022. PMID: 35915236 No abstract available.

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References

1. Beeler JA, et al. Taste uncoupled from nutrition fails to sustain the reinforcing properties of food. Eur. J. Neurosci. 2012;36:2533–2546. doi: 10.1111/j.1460-9568.2012.08167.x. - DOI - PMC - PubMed
1. Rossi MA, Stuber GD. Overlapping brain circuits for homeostatic and hedonic feeding. Cell Metab. 2018;27:42–56. doi: 10.1016/j.cmet.2017.09.021. - DOI - PMC - PubMed
1. Fernandes AB, et al. Postingestive modulation of food seeking depends on vagus-mediated dopamine neuron activity. Neuron. 2020;106:778–788.e6. doi: 10.1016/j.neuron.2020.03.009. - DOI - PMC - PubMed
1. Augustine V, et al. Temporally and spatially distinct thirst satiation signals. Neuron. 2019;103:242–249.e4. doi: 10.1016/j.neuron.2019.04.039. - DOI - PMC - PubMed
1. Sun F, et al. A genetically encoded fluorescent sensor enables rapid and specific detection of dopamine in flies, fish, and mice. Cell. 2018;174:481–496.e19. doi: 10.1016/j.cell.2018.06.042. - DOI - PMC - PubMed

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[1] Beeler JA, et al. Taste uncoupled from nutrition fails to sustain the reinforcing properties of food. Eur. J. Neurosci. 2012;36:2533–2546. doi: 10.1111/j.1460-9568.2012.08167.x. - DOI - PMC - PubMed

[2] Beeler JA, et al. Taste uncoupled from nutrition fails to sustain the reinforcing properties of food. Eur. J. Neurosci. 2012;36:2533–2546. doi: 10.1111/j.1460-9568.2012.08167.x. - DOI - PMC - PubMed

[3] Rossi MA, Stuber GD. Overlapping brain circuits for homeostatic and hedonic feeding. Cell Metab. 2018;27:42–56. doi: 10.1016/j.cmet.2017.09.021. - DOI - PMC - PubMed

[4] Rossi MA, Stuber GD. Overlapping brain circuits for homeostatic and hedonic feeding. Cell Metab. 2018;27:42–56. doi: 10.1016/j.cmet.2017.09.021. - DOI - PMC - PubMed

[5] Fernandes AB, et al. Postingestive modulation of food seeking depends on vagus-mediated dopamine neuron activity. Neuron. 2020;106:778–788.e6. doi: 10.1016/j.neuron.2020.03.009. - DOI - PMC - PubMed

[6] Fernandes AB, et al. Postingestive modulation of food seeking depends on vagus-mediated dopamine neuron activity. Neuron. 2020;106:778–788.e6. doi: 10.1016/j.neuron.2020.03.009. - DOI - PMC - PubMed

[7] Augustine V, et al. Temporally and spatially distinct thirst satiation signals. Neuron. 2019;103:242–249.e4. doi: 10.1016/j.neuron.2019.04.039. - DOI - PMC - PubMed

[8] Augustine V, et al. Temporally and spatially distinct thirst satiation signals. Neuron. 2019;103:242–249.e4. doi: 10.1016/j.neuron.2019.04.039. - DOI - PMC - PubMed

[9] Sun F, et al. A genetically encoded fluorescent sensor enables rapid and specific detection of dopamine in flies, fish, and mice. Cell. 2018;174:481–496.e19. doi: 10.1016/j.cell.2018.06.042. - DOI - PMC - PubMed

[10] Sun F, et al. A genetically encoded fluorescent sensor enables rapid and specific detection of dopamine in flies, fish, and mice. Cell. 2018;174:481–496.e19. doi: 10.1016/j.cell.2018.06.042. - DOI - PMC - PubMed

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Dopamine subsystems that track internal states

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