The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“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]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
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
Flagged first, then by citations
Cited by
Sorted by citations
Items 601–700 of 795
Prediction error correlates in the striosome-dopamine circuit emerge from information gain
Beck, D. W., & Friedman, A. (2026) · Nature Communications · doi:10.1038/s41467-026-73994-1 · Cited by 2
The effortless custody of automatism
Lerner, T. N. (2018) · Science · doi:10.1126/science.aav1250 · Cited by 2
Two-Photon Microscopy for Studying Reward Circuits of the Brain
Huda, R., Ibrahim, L. A., & Bloem, B. (2020) · Neuromethods · doi:10.1007/978-1-0716-1146-3_17 · Cited by 2
Rawlinson, S., Reichenbach, A., Clarke, R. E., Nunez-Iglesias, J., Dempsey, H., Lockie, S. H., & Andrews, Z. B. (2022) · Endocrinology · doi:10.1210/endocr/bqac095 · Cited by 2
Bimpisidis, Z., Serra, G. P., König, N., & Wallén‐Mackenzie, Å. (2023) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2023.1069834 · Cited by 2
Enhanced Punishment Responses in Patients With Schizophrenia: An Event-Related Potential Study
Akgül, Ö., Fide, E., Özel, F., Alptekın, K., Bora, E., Akdede, B. B., & Yener, G. (2023) · Clinical EEG and Neuroscience · doi:10.1177/15500594231190966 · Cited by 3
Nguyen, V., Harris, A. C., & Eltit, J. M. (2023) · Advances in pharmacology · doi:10.1016/bs.apha.2023.09.001 · Cited by 2
Connectivity and Circuit Architecture Using Transsynaptic Tracing in Vertebrates
Miyamichi, K., & Schwarz, L. A. (2017) · Springer eBooks · doi:10.1007/978-3-319-57363-2_4 · Cited by 2
Protein appetite drives macronutrient-related differences in ventral tegmental area neural activity
(21471335), G. C., (8373876), F. N., Peters, K. Z., (7733501), J. A.-S., (21471338), E. S., & (8373882), J. M. (2025) · Figshare · Cited by 2
Bisht, A., Peringod, G., Gordon, G. R., Bains, J. S., & Murari, K. (2024) · Neural Imaging and Sensing · doi:10.1117/12.3002776 · Cited by 2
Duncan, K. D., & Shohamy, D. (2024) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780190917982.013.24 · Cited by 2
Functional Connectome Analysis of the Striatum with Optogenetics
Chuhma, N. (2021) · Advances in experimental medicine and biology · doi:10.1007/978-981-15-8763-4_27 · Cited by 2
Arousal-State Dependent Alterations in VTA-GABAergic Neural ActivityPreprint
Eban-Rothschild, A., Borniger, J. C., Rothschild, G., Giardino, W. J., Morrow, J. G., & de Lecea, L. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/770313 · Cited by 2
Translational profiling of mouse dopaminoceptive neurons reveals a role of PGE2 in dorsal striatumPreprint
Montalban, E., Giralt, A., Taing, L., Nakamura, Y., Martin, C., de Pins, B., Pelosi, A., Goutebroze, L., Castell, L., Wang, W., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.09.02.279240 · Cited by 2
Internal state dependent control of feeding behaviour via hippocampal ghrelin signallingPreprint
Wee, R. W. S., Mishchanchuk, K., AlSubaie, R., & MacAskill, A. F. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.11.05.467326 · Cited by 2
“Analysis of Ca2+ signals from fibre photometry Measurement of calcium fluorescence signals was carried out as detailed previously (Lerner et al., 2015; Sánchez-Bellot et al., 2022).”
MethodDopaminergic neurons dynamically update sensory values during navigationPreprint
Kato, A., Ohta, K., Okanoya, K., & Kazama, H. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.08.17.504092 · Cited by 2
“Structure of circuits underlying odor value coding by DANs To decipher the circuit mechanisms underlying multifaceted functions of DANs, previous studies in rodents and flies have identified neurons providing direct input to DANs (Beier et al., 2015; Lerner et al., 2015; Menegas et al., 2015; Otto et al., 2020; Watabe…”
BackgroundA Subcortical Feeding Circuit Linking Interoception to Jaw movementPreprint
Kosse, C., Ivanov, J., Knight, Z. A., Pellegrino, K., & Friedman, J. M. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.10.11.561735 · Cited by 2
A septo-hypothalamic-medullary circuit directs stress-induced analgesiaPreprint
Shah, D. P., Sharma, P. R., Agarwal, R., & Barik, A. (2024) · eLife · doi:10.7554/elife.96724.2 · Cited by 2
Innervation density governs crosstalk of GPCR-based norepinephrine and dopamine sensorsPreprint
López, R. C., Noble, N., Özçete, Ö. D., Cai, X., Handy, G. E., Andersen, J. W., Patriarchi, T., Li, Y., & Kaeser, P. S. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.11.23.624963 · Cited by 2
Fritsche, M., Toschi, C., Shevchuk, Y., Didenko, O., Puliyadi, R., Majumdar, A., Bogacz, R., & Lak, A. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.01.01.696999 · Cited by 4
“To measure dopamine or acetylcholine release, we employed chronic fiber photometry 79,80 .”
Neuroscience: Finding the middle ground of behavioral (in)flexibility
Costa, K. M. (2022) · Current Biology · doi:10.1016/j.cub.2022.02.008 · Cited by 1
Hathaway, B. A., Li, A., Brodie, H. G., Silveira, M. M., Tremblay, M., Seo, Y. S., & Winstanley, C. A. (2024) · European Journal of Neuroscience · doi:10.1111/ejn.16287 · Cited by 1
“Dopaminergic neurons in the medial SNc also show characteristics of prediction errors and have distinct intrinsic properties and inputs from neurons located more laterally (Lerner et al., 2015; Zhang et al., 2017).”
BackgroundSeparable dorsal raphe dopamine projections mimic the facets of a loneliness-like state
Lee, C. R., Matthews, G. A., Lemieux, M., Wasserlein, E. M., Borio, M., Miranda, R. L., Keyes, L. R., Schneider, G. P., Jia, C., Tran, A., et al. (2025) · eLife · doi:10.1101/2025.02.03.636224 · Cited by 4
Estrogens produced within the central amygdala inhibit varicella zoster‐induced orofacial pain
Kramer, P. R., Nguyen, L. A., & Kinchington, P. R. (2025) · Journal of Neuroendocrinology · doi:10.1111/jne.70012 · Cited by 1
Breakstone, M., Chen, S. C., Vadapalli, S., Chavez, E., Parsonnet, L. S., Gross, R. E., Tescarollo, F. C., Barker, D. J., & Sun, H. (2025) · ACS Chemical Neuroscience · doi:10.1021/acschemneuro.4c00632 · Cited by 2
Calbindin stratifies midbrain dopaminergic neurons governing distinct aspects of locomotion
Bolduc, C., Oram, C., Donovan, S., Bach, H., Liu, M., Marier, R., Sharpe, M., Liu, S., Campeau, C., Spencer, C. D., et al. (2026) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2613593123 · Cited by 2
“In fact, it has been shown that SNc DA neurons, including ALDH1A1 + DA neurons, receive strong monosynaptic inputs from direct MSNs originating from the DMS and VMS (37, 74, 81), and that direct MSNs (dMSNs) negatively influence DA release in the DLS and firing of ALDH1A1 + DA neurons (82, 83).”
Bertran‐Gonzalez, J., & Balleine, B. W. (2025) · Handbook of behavioral neuroscience · doi:10.1016/b978-0-443-29867-7.00043-8 · Cited by 2
Dopamine neuron connectomes: Inputs and outputs
Watabe-Uchida, M., & Amo, R. (2025) · Handbook of behavioral neuroscience · doi:10.1016/b978-0-443-29867-7.00009-8 · Cited by 3
Lommi, G., Klein, L., Lutz, T. A., & Boyle, C. N. (2025) · Physiology & Behavior · doi:10.1016/j.physbeh.2025.115060 · Cited by 1
Neural responses prior to licking onset in the striatal matrix compartment in mice
Ishimaru, Y., Yoshizawa, T., Kimoto, T., et al. (2025) · Neuroscience · doi:10.1016/j.neuroscience.2025.10.032 · Cited by 1
Wang, Y., Tan, M., Chen, W., & Li, J. (2025) · Molecular Neurobiology · doi:10.1007/s12035-025-05460-w · Cited by 1
“Further studies demonstrated that DA neurons receiving projections from the DLS and DMS encode aversive or value-related signals during lever-pressing behavior in mice [43].”
InfluentialImpact of aging on the central and enteric nervous system in a Parkinson’s disease mouse model
Pradeloux, S., André, M. M., Fréchette, M., Drolet, M., Fontaine-lavallée, C., Côté, M., Coulombe, K., Rieux, M., Calon, F., & Soulet, D. (2025) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2025.1576325 · Cited by 1
“This persistent activity is thought to increase metabolic stress, making them more susceptible to degeneration, especially with aging (Lerner et al., 2015; Chalazonitis et al., 2022).”
Tachykinin 1 neurons in the lateral habenula signal negative reward prediction error
Suzuki, K. E., Seagoe, T. A., Holcomb, B., Kuyat, J. R., & Sylwestrak, E. (2026) · Current Biology · doi:10.1016/j.cub.2026.04.032 · Cited by 2
Filimontseva, A., Fu, Y., & Halliday, G. M. (2026) · Brain Structure and Function · doi:10.1007/s00429-026-03103-x · Cited by 1
“…gray, dorsal raphe, lateral habenula, and basal ganglia)(Omelchenko and Sesack 2010; Beier et al. 2015; Nieh et al. 2015; Hjelmstad et al. 2013; Lerner et al. 2015; Evans et al. 2020; Vounatsos and Gittis 2025b), while others more recently defined are interspersed within the midbrain DA…”
Parabrachial neurons orchestrate cold-induced homeostatic responses
Jung, S., Kondaurova, A., Lee, M., Kwon, J. J., Shin, H., & Kim, S. (2026) · Nature Metabolism · doi:10.1038/s42255-026-01565-1 · Cited by 1
“Real-time fibre photometry recordings were conducted following a previous study 51 .”
Opponent ventrolateral striatal circuits regulate behavioral flexibility and rigidity
Gonzales, B. J., Shalom, I., Lipton, D. M., Turm, H., Noble, J., Festuccia, M., Groysman, M., & Citri, A. (2026) · Current Biology · doi:10.1016/j.cub.2026.08.068 · Cited by 1
Association learning: Dopamine and the formation of backward associations
Kendig, M. D., & Bradfield, L. A. (2022) · Current Biology · doi:10.1016/j.cub.2022.06.007 · Cited by 1
Connectivity Map of Subthalamic Corticotropin-releasing Hormone Neurons in the Mouse Brain
Tseng, Y.-T., Liang, L., Zhao, B., Ye, J., & Wang, L. (2022) · Neuroscience Bulletin · doi:10.1007/s12264-022-00939-1 · Cited by 1
“Furthermore, previous studies have associated the SNc with processing negative emotion [11] and promoting REM sleep [12].”
BackgroundThe Y-Maze Test Combined with Fluorescence Recordings for Assessing Neural Correlates of Cognition
Peleg‐Raibstein, D., Bracey, E. F., Tesmer, A. L., & Burdakov, D. (2024) · Neuromethods · doi:10.1007/978-1-0716-4011-1_1 · Cited by 1
Ritger, A. C., Rasheed, N. M., Padival, M., Ferrara, N. C., & Rosenkranz, J. A. (2024) · eNeuro · doi:10.1523/eneuro.0288-24.2024 · Cited by 1
Huang, J., Crochet, S., Sandi, C., & Petersen, C. C. H. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e37831 · Cited by 1
“Fluorescence was excited by 405 nm and 465 nm sinusoidally modulated light at ~200 Hz and ~500 Hz respectively, and bandpass-filtered 500 – 550 nm emitted light was collected and demodulated [41].”
MethodReflective multi-immersion microscope objectives
Voigt, F. F., Naert, T., Bahl, A., Lienkamp, S. S., & Helmchen, F. (2023) · Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing · doi:10.1117/12.2648095 · Cited by 1
Optoelectronic Systems and Applications for In Vivo Fiber Photometry
Ronayne, K. (2016) · Libraries and Cultural Resources (University of Calgary) · doi:10.11575/prism/27220 · Cited by 1
Circadian clock neurons mediate time-of-day dependent responses to lightPreprint
Jones, J. R., Simon, T., Lones, L., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/291955 · Cited by 1
“To control for motion artifacts, we excited GCaMP6s with its calcium-dependent excitation wavelength of 470 nm and at its calcium-independent isosbestic excitation wavelength of 405 nm (Lerner et al., 2015).”
MethodProtein appetite drives macronutrient-related differences in ventral tegmental area neural activityPreprint
Chiacchierini, G., Naneix, F., Peters, K. Z., Apergis-Schoute, J., Snoeren, E. M. S., & McCutcheon, J. E. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/542340 · Cited by 1
“To assess the activity of VTA neurons during the consumption of differently-flavored macronutrient solutions, the ‘bulk’ fluorescence signal generated by GCaMP6s expressing cells was recorded using fiber photometry (Gunaydin et al., 2014; Lerner et al., 2015).”
MethodGalet, B., Ingallinesi, M., Pegon, J., Thi, A. N. D., Ravassard, P., Biguet, N. F., & Meloni, R. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/617456 · Cited by 1
“21 pathways may provide a system for such lateral transfer of information (71).”
BackgroundMedium spiny neurons activity reveals the discrete segregation of mouse dorsal striatumPreprint
Alegre-Cortés, J., Sáez, M., Montanari, R., & Reig, R. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.02.21.959692 · Cited by 1
“While both regions participate in motor control, DLS is often related with habit, stimulus-response associations and navigation, whereas the DMS mediates action-outcome associations, goal-directed actions and flexible shifting between behavioural strategies, suggesting a role in higher cognitive functions (Faure et al…”
BackgroundNeural Mechanism of Hunger-gated Food-seeking and EvaluatingPreprint
Lee, Y. H., Kim, Y., Kim, K. S., Song, H. Y., Jang, M., Ha, D.-S., Park, J. S., Jung, S.-H., Lee, J., Kim, K. M., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.10.23.352187 · Cited by 1
“F/F0 was calculated as (465nm-405nm)/fitted(405nm) [37].”
The SC-SNc pathway boosts appetitive locomotion in predatory huntingPreprint
Huang, M., Li, D., Pei, Q., Xie, Z., Gu, H., Liu, A., Chen, Z., Wang, Y., Sun, F., Li, Y., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.11.23.395004 · Cited by 1
Cui, L., Tang, S., Zhao, K., Pan, J., Zhang, Z., Si, B., & Xu, N.-L. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.07.30.502110 · Cited by 1
“The 410-nm reference trace was scaled to best fit the 470-nm signals using least-squares regression (Lerner et al., 2015).”
MethodConlisk, D., Ceau, M., Fiancette, J.-F., Winke, N., Darmagnac, E., Herry, C., & Deroche‐Gamonet, V. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.09.02.506312 · Cited by 1
“The current standard in the literature is based on a linear regression model (Bruno et al., 2021; Lerner et al., 2015).”
Adolescent neurostimulation of dopamine circuit reverses genetic deficits in frontal cortex functionPreprint
Mastwal, S. S., Li, X., Stowell, R. D., Manion, M. T. C., Zhang, W., Kim, N., Yoon, K., Song, H., Ming, G., & Wang, K. H. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.02.03.526987 · Cited by 1
IN SITU IMAGING OF RETINAL CALCIUM DYNAMICS IN AWAKE ANIMALSPreprint
Wang, Y., Su, A., Jin, J., Barson, D. G., & Crair, M. C. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.02.11.528145 · Cited by 1
VTA Dopamine Neurons Drive Spatiotemporally Heterogeneous Striatal Dopamine Signals During LearningPreprint
Engel, L., Wolff, A. R., Blake, M. L., Collins, V. L., Sinha, S., & Saunders, B. T. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4530804 · Cited by 1
Adolescent neurostimulation of dopamine circuit reverses genetic deficits in frontal cortex functionPreprint
Mastwal, S. S., Li, X., Stowell, R. D., Manion, M. T. C., Zhang, W., Kim, N., Yoon, K., Song, H., Ming, G., & Wang, K. H. (2023) · eLife · doi:10.7554/elife.87414.2 · Cited by 1
Conde-Berriozabal, S., Sitjà‐Roqueta, L., García-García, E., García-Gilabert, L., Sancho‐Balsells, A., Fernández‐García, S., Rodríguez-Urgellés, E., Giralt, A., López-Gil, J., Muñoz‐Moreno, E., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.06.12.597534 · Cited by 1
“Notably, both pathways project to their specific output nuclei with segregated mediolateral connections 10,11 .”
BackgroundMiller, C. N., Li, Y., Beier, K. T., & Aoto, J. (2024) · bioRxiv · doi:10.1101/2024.08.02.606264 · Cited by 1
Multi-dimensional oscillatory activity of mouse GnRH neurons in vivoPreprint
Han, S. Y., Yeo, S., Kim, J.-C., Zhou, Z., & Herbison, A. E. (2024) · eLife · doi:10.7554/elife.100856.2 · Cited by 1
Breakstone, M., Chen, S. C., Vadapalli, S., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.02.23.639738 · Cited by 1
Schlingloff, D., Szabó, Í., Gulyas, E., Király, B., Kispal, R., Stephenson‐Jones, M., & Hangya, B. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.02.23.639747 · Cited by 1
Orexin and pupillary modulation for hunger control
Kosar, S., Bracey, E. F., Grujic, N., Du, Y., Peleg‐Raibstein, D., & Burdakov, D. (2026) · Proceedings of the National Academy of Sciences · doi:10.1101/2025.03.07.642010 · Cited by 1
Dorsal hippocampus mediates light-tone sensory preconditioning task in micePreprint
Pinho, J., Ramon‐Duaso, C., Manzanares-Sierra, I., & Busquets-García, A. (2025) · eLife · doi:10.7554/elife.105863.1 · Cited by 1
Kim, H., Xu, C., Washington, C., Shi, C., Lowman, M., & Kebschull, J. M. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.06.25.661405 · Cited by 1
Separable Dorsal Raphe Dopamine Projections Mimic the Facets of a Loneliness-like StatePreprint
Lee, C. R., Matthews, G. A., Lemieux, M., Wasserlein, E. M., Borio, M., Miranda, R. L., Keyes, L. R., Schneider, G. P., Jia, C., Tran, A., et al. (2025) · eLife · doi:10.7554/elife.105955.2 · Cited by 1
Cortex-wide circuits for multisensory evidence accumulation and choice formationPreprint
Nabbefeld, G., Rachid, S. A., Lenzi, I., Cravo, E., Musall, S., & Kampa, B. M. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2025.12.23.696238 · Cited by 2
“Here, frames acquired under blue illumination reflect Ca 2+ -dependent fluorescence, while frames acquired under violet illumination represent Ca 2+ -independent fluorescence signal 74,81 .”
Editorial: Dopamine circuitry and heterogeneity in addiction
Lerner, T. N. (2026) · Addiction Neuroscience · doi:10.1016/j.addicn.2026.100250 · Cited by 1
A Multimodal Single-Cell Epigenomic and 3D Genome Atlas of the Human Basal GangliaPreprint
Ding, W., Klein, A., Báez-Becerra, C. T., Rink, J. A., Bartlett, A., Wang, R., Zeng, Q., Castanon, R., Nery, J. R., Osgood, E., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.12.705594 · Cited by 2
Mesoscale molecular architecture of the human striatum across cell types and lifespanPreprint
Kraft, A. W., Lee, M. D., Rayan, N., Gao, H., Milidantri, J., Vanderburg, C. R., Balderrama, K. S., Nadaf, N. M., Kumar, V., Flowers, K., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.03.04.709715 · Cited by 3
Hypothalamic MCH neurons links tau pathology to sleep disruptionPreprint
Pang, K., Guo, S., Yang, R., Kumar, A., Morse, W. D., Xu, L., Liu, Q., Jiang, D., & Zhong, P. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.05.31.729026 · Cited by 1
Dopamine dips during unrewarded actions promote punishment-resistant reward seekingPreprint
Mwenda, N., Nadel, J. A., Shen, T., Seiler, J. L., & Lerner, T. N. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.08.01.742224 · Cited by 1
“0-EYFP (or fluorophore-only control virus AAV5-EF1α -DIO-EYFP) was injected bilaterally into the medial SNc of DAT-IRES-cre mice to preferentially target DMS-projecting dopamine neurons 22 .”
Computational Modeling of the Basal Ganglia : Functional Pathways and Reinforcement Learning
Berthet, P. (2015) · KTH Publication Database DiVA (KTH Royal Institute of Technology)
Gaining on reward prediction errors
Parker, N. F., & Witten, I. B. (2016) · Nature Neuroscience · doi:10.1038/nn.4246
Reward and Decision Encoding in Basal Ganglia
Tian, J., Uchida, N., & Eshel, N. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-805308-9.00005-1
DEVELOPMENT, VALIDATION, AND USE OF A QUANTITATIVE THEORY OF IN VIVO DOPAMINE DYNAMICS
Walters, S. H. (2016) · D-Scholarship@Pitt (University of Pittsburgh)
Hikida, T. (2016) · The Brain & Neural Networks · doi:10.3902/jnns.23.35
Harnessing Pallidal Cell-Type Diversity to Treat Neurological Disorders
Mastro, K. J. (2017) · D-Scholarship@Pitt (University of Pittsburgh)
Neural Circuit Mechanisms Underlying Dopamine Reward Prediction Errors
Tian, J. (2016) · Digital Access to Scholarship at Harvard (DASH) (Harvard University)
Zimmerman, E. I. (2017) · D-Scholarship@Pitt (University of Pittsburgh)
Dopamine : a versatile player in development, regeneration and disease
Pinheiro, T. (2018) · Figshare
Tsien, J. Z. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-804078-2.00020-9
Mapping brain circuits : anatomy, connectivity and function
Xuan, Y. (2018) · Figshare
Research progress and prospect of neural activity-dependent tools
Wang, J., & Hu, H. (2019) · Scientia Sinica Vitae · doi:10.1360/n052018-00292
Avram, M., Brandl, F., Knolle, F., Cabello, J., Leucht, C., Scherr, M., Mustafa, M., Koutsouleris, N., Leucht, S., Ziegler, S. I., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/847178
Tolve, M., Ulusoy, A., Islam, K. U. S., Bodea, G. O., Öztürk, E., Broske, B., Mentani, A., Wagener, A., van Loo, K. M. J., Britsch, S., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.10.06.327940
“…mDA population may signal the valence of the outcome, while mDA neurons projecting to the DLS may signal a salience signal (appetitive or aversive) (Lerner et al., 2015). mDA neurons in the VTA project to the Nucleus accumbens (NAc), the olfactory tubercle (OT), prefrontal cortex (PFC) and…”
BackgroundNadel, J. A., Pawelko, S. S., Scott, J. R., McLaughlin, R., Fox, M., Hollon, N. G., & Howard, C. D. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.10.29.359265
Distinct cortico-striatal compartments drive competition between adaptive and automatized behaviorPreprint
Barnett, W. H., Kuznetsov, A. S., & Lapish, C. C. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.05.21.445068
Faustini, G., Longhena, F., Muscò, A., Bono, F., Parrella, E., Via, L. L., Barbon, A., Pizzi, M., Onofri, F., Benfenati, F., et al. (2021) · Research Square · doi:10.2139/ssrn.3902138
Bloem, B., Huda, R., Amemori, K., Abate, A., Krishna, G., Wilson, A. L., Carter, C. W., Sur, M., & Graybiel, A. M. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.08.17.456542
Kelly, E. A., Contreras, J., Duan, A., Vassell, R., & Fudge, J. L. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4002399
Brandner, D. D., Retzlaff, C. L., Kocharian, A., Stieve, B. J., Mashal, M. A., Mermelstein, P. G., & Rothwell, P. E. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.03.14.484267
Berridge, K. C. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.734515518.793554226
Roth, B. L. (2017) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.731118961.793537352
de Lecea, L. (2018) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.732415229.793550017
Miczek, K. A., & Covington, H. E. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.734556920.793561600
Schultz, W. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.733676004.793565151
Sajikumar, S., & Benoy, A. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.734556920.793555634
Faculty Opinions recommendation of Nucleus accumbens modulation in reward and aversion.
Wolf, M. E. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.734917622.793558354
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review