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Intact-Brain Analyses Reveal Distinct Information Carried by SNc Dopamine Subcircuits
Open accessAbstract
Recent progress in understanding the diversity of midbrain dopamine neurons has highlighted the importance--and the challenges--of defining mammalian neuronal cell types. Although neurons may be best categorized using inclusive criteria spanning biophysical properties, wiring of inputs, wiring of outputs, and activity during behavior, linking all of these measurements to cell types within the intact brains of living mammals has been difficult. Here, using an array of intact-brain circuit interrogation tools, including CLARITY, COLM, optogenetics, viral tracing, and fiber photometry, we explore the diversity of dopamine neurons within the substantia nigra pars compacta (SNc). We identify two parallel nigrostriatal dopamine neuron subpopulations differing in biophysical properties, input wiring, output wiring to dorsomedial striatum (DMS) versus dorsolateral striatum (DLS), and natural activity patterns during free behavior. Our results reveal independently operating nigrostriatal information streams, with implications for understanding the logic of dopaminergic feedback circuits and the diversity of mammalian neuronal cell types.
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“Thus, the input-output architecture of the DR serotonin system differs from that of the locus coeruleus norepinephrine system with more homogeneous input and output (Schwarz et al., 2015), and resembles more closely those of the midbrain dopamine systems (Beier et al., 2015; Lerner et al., 2015), with biased input and segregated output.”
From Anatomically defined and functionally distinct dorsal raphe serotonin sub-systems (2018) · cites this paper as Lerner et al., 2015
In the citing paper
“Thus, a strong activation in response to the physical impact of an aversive stimulus in particularly sensitive neurons may supersede a depression reflecting the negative value, and this might appear as a categorical difference in aversive and motivational salience coding15,23,24,134.”
From Dopamine reward prediction-error signalling: A two-component response (2016) · cites this paper as [134]
In the citing paper
“Dopamine neurons in the lateral midbrain display greater burst activity in vivo28 and higher excitability in vitro29,30 than those in the medial midbrain, such as the ventral tegmental area (VTA), where canonical reward-processing dopamine neurons reside.”
From Dopamine dynamics as a regulatory mechanism for shifting between defensive and reward-seeking behaviors (2026) · cites this paper as [30]
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Cites
A neural substrate of prediction and reward
Schultz, W., Dayan, P., & Montague, P. R. (1997) · Science · doi:10.1126/science.275.5306.1593 · Cited by 9,388 · cited 2×
“Seminal early studies into the information encoded by midbrain DA neurons suggested that a key function of DA is to transmit reward prediction error signals (Mirenowicz and Schultz, 1996; Schultz et al., 1997; Waelti et al., 2001), a hypothesis concordant with temporal difference learning models (Montague et al.”
ResultUltrasensitive fluorescent proteins for imaging neuronal activity
Chen, T.-W., Wardill, T. J., Sun, Y., Pulver, S. R., Renninger, S. L., Baohan, A., Schreiter, E. R., Kerr, R. A., Orger, M. B., Jayaraman, V., et al. (2013) · Nature · doi:10.1038/nature12354 · Cited by 6,474 · cited 1×
“We expressed GCaMP6f (Chen et al., 2013) in DMS- or DLS-projecting SNc DA neurons by injecting CAV-cre into the DMS or the DLS, followed by injection of a cre-dependent GCaMP6f construct into the SNc.”
MethodLearning to predict by the methods of temporal differences
Sutton, R. S. (1988) · Machine Learning · doi:10.1007/bf00115009 · Cited by 5,148 · cited 2×
“…neurons suggested that a key function of DA is to transmit reward prediction error signals (Mirenowicz and Schultz, 1996; Schultz et al., 1997; Waelti et al., 2001), a hypothesis concordant with temporal difference learning models (Montague et al., 1996, 2004; Steinberg et al., 2013; Sutton, 1988).”
BackgroundDopamine in motivational control: rewarding, aversive, and alerting
Bromberg-Martin, E. S., Matsumoto, M., & Hikosaka, O. (2010) · Neuron · doi:10.1016/j.neuron.2010.11.022 · Cited by 2,396 · cited 4×
“…that the DA neurons, which increase their firing in response to these stimuli, may signal salience rather than value (Brischoux et al., 2009; Bromberg-Martin et al., 2010; Matsumoto and Hikosaka, 2009), though controversy on this point remains (Cohen et al., 2012; Fiorillo et al., 2013,…”
BackgroundInfluentialA framework for mesencephalic dopamine systems based on predictive Hebbian learning
Montague, P., Dayan, P., & Sejnowski, T. (1996) · The Journal of Neuroscience · doi:10.1523/jneurosci.16-05-01936.1996 · Cited by 2,066 · cited 1×
“…neurons suggested that a key function of DA is to transmit reward prediction error signals (Mirenowicz and Schultz, 1996; Schultz et al., 1997; Waelti et al., 2001), a hypothesis concordant with temporal difference learning models (Montague et al., 1996, 2004; Steinberg et al., 2013; Sutton, 1988).”
Structural and molecular interrogation of intact biological systems
Chung, K., Wallace, J., Kim, S.-Y., Kalyanasundaram, S., Andalman, A. S., Davidson, T. J., Mirzabekov, J. J., Zalocusky, K. A., Mattis, J., Denisin, A. K., et al. (2013) · Nature · doi:10.1038/nature12107 · Cited by 2,008 · cited 6×
“We began by demonstrating that novel circuit-tracing and -recording methodologies can be effectively combined with whole-brain CLARITY/COLM imaging (Chung et al., 2013; Tomer et al., 2014) to provide a uniquely informative overview of richly defined cell types and their global connectivity motifs…”
BackgroundMethodInfluentialSelf-citationHaber, S. N., Fudge, J. L., & McFarland, N. R. (2000) · The Journal of Neuroscience · doi:10.1523/jneurosci.20-06-02369.2000 · Cited by 1,610 · cited 1×
“This information notably enriches the ascending spiral model proposed by Haber et al. (2000), which could not make definitive statements about striatal inputs onto DAergic versus non-DAergic midbrain cells.”
BackgroundNatural neural projection dynamics underlying social behavior
Gunaydin, L. A., Grosenick, L., Finkelstein, J. C., Kauvar, I. V., Fenno, L. E., Adhikari, A., Lammel, S., Mirzabekov, J. J., Airan, R. D., Zalocusky, K. A., et al. (2014) · Cell · doi:10.1016/j.cell.2014.05.017 · Cited by 1,389 · cited 1×
“…monitored activity from projection-defined SNc DA neurons during behavior using fiber photometry, a method for collecting population intracellular [Ca2+] fluorescent signals from a genetically encoded Ca2+ indicator such as GCaMP through a single chronic fiber optic implant (Gunaydin et al., 2014).”
MethodTwo types of dopamine neuron distinctly convey positive and negative motivational signals
Matsumoto, M., & Hikosaka, O. (2009) · Nature · doi:10.1038/nature08028 · Cited by 1,378 · cited 5×
“Another study used recordings in awake monkeys to demonstrate a correlation between the depth at which a DA neuron was recorded along the electrode (indicating a more ventromedial location in the midbrain) and the likelihood that it would decrease rather than increase its firing in response to an aversive cue (Matsumo…”
BackgroundResultInfluentialNeuron-type-specific signals for reward and punishment in the ventral tegmental area
Cohen, J. Y., Haesler, S., Vong, L., Lowell, B. B., & Uchida, N. (2012) · Nature · doi:10.1038/nature10754 · Cited by 1,318
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Vanderschuren, L. J. M. J. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.735805842.793563122
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Optogenetics and Related Technologies for Psychiatric Disease Research
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“This diversity is thought to underline the broad range of DA functions and may contribute to the selective vulnerability observed in neurodegenerative diseases (Brichta & Greengard, 2014; Giguere et al., 2018; Lerner et al., 2015; Poulin et al., 2018; Surmeier et al., 2017).”
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“Consistent with previously described projection patterns 23 , activation of SNc dopamine neurons evoked DA responses in the NAc, DLS, and mPFC, with the largest amplitudes observed in the NAc (2-s stimulation: mean peak amplitude A = 0.18, 0.57, and 0.43; 10-s stimulation: A = 0.24, 0.86, and 0.44;…”
InfluentialCholinergic–dopaminergic synergy and antagonism shape prediction-error broadcastingPreprint
Király, B., Pillár, V., Szabó, Í., Schlingloff, D., Hegedüs, P., Szigeti, K., Li, Y., & Hangya, B. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.19.706866
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“signature in Kcnj15 ⁻/⁻ mice Finally, to interrogate the downstream molecular consequences of the nigral dysfunction described above in Kcnj15 ⁻/⁻ mice ( Figs 1-6 ), we performed bulk RNAseq on the striatum, the primary projection target of SNpc neurons [37], using 18-month-old female mice.”
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“Many diverse populations of neurons in the mammalian brain have been discovered that are functionally incorporated into different circuits with different roles, even in very small nuclei such as dopaminergic neurons in the substantia nigra pars compacta (SNc) ( Lerner et al., 2015 ).”
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Muhsinov, J. M., Iliakis, E. A., Tu, W., Ramirez, A. N., Muniak, M. A., Wasilczuk, A. Z., Davatolhagh, M. F., Proekt, A., Mao, T., & Fuccillo, M. V. (2026) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2026.1795921
“…thalamic inputs, dopaminergic afferents from the ventral midbrain exhibit pronounced topographic organization across the caudoputa-men, with regional differences in connectivity, synaptic architecture, and behavioral function (e.g., Lerner et al., 2015; Menegas et al., 2015; Poulin et al., 2018).”
Motor-to-Limbic Design of Direct Synaptic Communication between Dopamine Neurons in the Midbrain
Hammer, N., Tian, G., Fischer, B., Stojanovic, S., Beier, K. T., & Roeper, J. (2026) · Journal of Neuroscience · doi:10.1523/jneurosci.2126-25.2026
“Furthermore, these di ff erent subpopulations possess molecular di ff erences (Poulin et al., 2018) and receive di ff erent synaptic inputs from cortico-striatal, hypothalamic, and brainstem sources (Watabe-Uchida et al., 2012; Beier et al., 2015; Lerner et al., 2015).”
Individual differences in prosocial learning are represented in the hippocampal dorsal CA1
Greca, F. L., Zianni, E., Cerchiaro, I., Gusmini, M., Coccia, G., Carrea, A., Pelucchi, S., Castoldi, C., Maggioni, D., Marcello, E. E., et al. (2026) · Nature Neuroscience · doi:10.1038/s41593-026-02292-2 · Cited by 1
“First, we applied the Δ F / F (signal − control)/con-trol × 100) 46 .”
Brainwide dopamine dynamics across sleep-wake transitionsPreprint
Chen, C., Tu, X., Lu, L., Pham, C., Zhang, X., Su, R., Li, E., Jin, Z., Cao, W., Yang, Y., et al. (2026) · eLife · doi:10.7554/elife.110675
Brainwide dopamine dynamics across sleep-wake transitionsPreprint
Chen, C., Tu, X., Lu, L., Pham, C., Zhang, X., Su, R., Li, E., Jin, Z., Cao, W., Yang, Y., et al. (2026) · eLife · doi:10.7554/elife.110675.1
Kim, C. S., Banks, J., Miswakumari, L. A. D., & Kang, S. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.05.15.725448
“Application of PLS-based baseline correction together with isosbestic motion correction(Lerner et al., 2015) substantially attenuated these lux-356 dependent step shifts; however, residual lux-related drift, including a downward trend toward the end of the recording, was still detectable…”
Schuch, H. D. C., Woo, J., Kugler, H., Jiang, K., & Ostroumov, A. (2026) · Neuropharmacology · doi:10.1016/j.neuropharm.2026.111124
Dendrite-specific Synaptic Inputs onto Dopaminergic SNc NeuronsPreprint
Evans, R. C., Zhang, R., & Khaliq, Z. M. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.7261325
Status-dependent competition engagement via mesocortical pathway
Jin, S., Liu, Y., Wang, T., Shan, X., Liu, J., Zhu, S., Shen, T., Liang, Y., Wei, G., Cao, Y., et al. (2026) · Neuron · doi:10.1016/j.neuron.2026.07.020
Region-specific weighting of sensory intensity and reward prediction error by dopamine signals
Bouchard, S.-J., Boutin, J., Lévesque, M., & Breton‐Provencher, V. (2026) · iScience · doi:10.1016/j.isci.2026.117130 · Cited by 1
“Tracing studies indeed suggest that both long-range and local inputs converge onto SNc and VTA dopamine neurons, 18,59,60 potentially accounting for the high correlations observed between projection-specific dopaminergic neurons originating from different midbrain nuclei.”
Mesolimbic and mesocortical pathways differentially support fentanyl-context associations
Montemarano, A., Sohail, H., Murdaugh, L. B., Derr, K., Alkhaleel, F. A., Fox, L. D., Pandey, S., & Fox, M. E. (2026) · Psychopharmacology · doi:10.1007/s00213-026-07151-3 · Cited by 1
Wang, Y., Burgeno, L. M., Cerpa, J.-C., Manohar, S., Bogacz, R., & Walton, M. E. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.08.19.745693
“Nonetheless, given the heterogeneity within the nigrostriatal pathway and their widely spread arborisations 53,54,55,56,57,58,59 , it is possible that RPE and APE signals are separately encoded by dif-305 ferent populations of dopaminergic neurons originating in the substantia nigra with different…”
Niido, M., Yoshida, T., Isoo, N., Mimaki, M., Nakajima, K., & Hayashi, T. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.09.01.748702
“Fluorescence traces were processed separately by region using dual-wavelength reference correction and biexponential detrending [24–27].”
Miah, M. H., Li, G. G., Bose, S., & Cataldo, G. (2026) · Pain · doi:10.1097/j.pain.0000000000004113
EthoTrace: from behaviour to neural dynamics in a unified analysis systemPreprint
Oo, H., Tao, C., & Zhang, G. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.10.04.756578
Young, P. A., & Nashmi, R. (2026) · Neuroscience · doi:10.1016/j.neuroscience.2026.10.027
tVTA controls two distinct dopaminergic inputs to the external Globus PallidusPreprint
Lebouc, M., Fois, G. R., Bilella, A., Baufreton, J., Barrot, M., & Georges, F. E. (2026) · Research Square · doi:10.21203/rs.3.rs-11143061/v1
Striosomes: Small Circuits With a Large Role in Locomotion
Okunomiya, T., Watanabe, D., Takahashi, R., & Inoue, H. (2026) · The Neuroscientist · doi:10.1177/10738584261479729
Metadata
- Authors
- Lerner, T. N., Shilyansky, C., Davidson, T. J., Evans, K. E., Beier, K. T., Zalocusky, K. A., Crow, A. K., Malenka, R. C., Luo, L., Tomer, R., & Deisseroth, K.
- Affiliations
- Stanford University (US)
- Stanford Medicine (US)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Deisseroth, Karl
- ORCID
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2015-07
- Volume
- 162
- Issue
- 3
- Pages
- 635-647
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC4790813
- OpenAlex
- W1875506666
- Cited by
- 794
- References
- 55
- Citations by year
- 2026: 52 · 2025: 90 · 2024: 87 · 2023: 77 · 2022: 85 · 2021: 77 · 2020: 70 · 2019: 71 · 2018: 70 · 2017: 51 · 2016: 51 · 2015: 13
- FWCI
- 28.63
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Howard Hughes Medical Institute
- H. L. Snyder Medical Foundation
- National Institutes of Health (5f31mh105151-02, 1f32mh105053-01)
- Defense Advanced Research Projects Agency
- National Institute of Mental Health (1F31MH105151-01, F32 MH105053, 1F32MH105053-01, P50MH086403, F31 MH105151)
- National Institute on Drug Abuse (F32DA038913, R37DA035377)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Health Sciences › Medicine › Clinical Neurology › Deep Brain Stimulation and Movement Disorders
- Keywords
- substantia nigra pars compacta, dopaminergic neurons, neuronal cell types, nigrostriatal pathway, dorsomedial striatum, dorsolateral striatum, striatal output, neuronal heterogeneity, clarity, optogenetics, viral tracing, fiber photometry
- MeSH terms
- Animals, Brain Mapping, Dopamine, Mice, Inbred C57BL, Neural Pathways, Neurons, Reward, Shock, Substantia Nigra, Mice
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