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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
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ResultUltrasensitive fluorescent proteins for imaging neuronal activity
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BackgroundInfluentialA framework for mesencephalic dopamine systems based on predictive Hebbian learning
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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×
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“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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MethodArchitectures of neuronal circuits
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Self-citationDopamine neurons projecting to the posterior striatum reinforce avoidance of threatening stimuli
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Dopamine neurons create Pavlovian conditioned stimuli with circuit-defined motivational properties
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Dopamine-Evoked Synaptic Regulation in the Nucleus Accumbens Requires Astrocyte Activity
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“We monitored astrocyte Ca2+ levels in the NAc using a fiber-photometry system in freely behaving mice (Lerner et al., 2015; Saunders et al., 2018) and specifically stimulated dopaminergic afferents to the NAc using optogenetics (Figures 1A and 1B).”
MethodThe Basal Ganglia Over 500 Million Years
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Reward and choice encoding in terminals of midbrain dopamine neurons depends on striatal target
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“Light collection, filtering, and demodulation were as previously described (45, 46).”
MethodSelf-citationWiring and Molecular Features of Prefrontal Ensembles Representing Distinct Experiences
Li, Y., Allen, W. E., Thompson, K. R., Tian, Q., Hsueh, B., Ramakrishnan, C., Wang, A.-C., Jennings, J. H., Adhikari, A., Halpern, C. H., et al. (2016) · Cell · doi:10.1016/j.cell.2016.05.010 · Cited by 338
“The COLM system (described earlier in Tomer et al., 2014; Lerner et al., 2015) is optimized for high-resolution imaging and is most useful for studies requiring sub-cellular information, while the approach outlined here is optimized for speed and practicality in cellular resolution work, most…”
Dopamine neurons projecting to the posterior striatum form an anatomically distinct subclass
Menegas, W., Bergan, J. F., Ogawa, S. K., Isogai, Y., Venkataraju, K. U., Osten, P., Uchida, N., & Watabe‐Uchida, M. (2015) · eLife · doi:10.7554/elife.10032 · Cited by 335
“However, there is some disagreement about the extent of collateralization of dopamine axons (Yetnikoff et al., 2014); some dopamine neurons may project to multiple brain areas (Fallon and Loughlin, 1982; Loughlin and Fallon, 1984; Takada and Hattori, 1986).”
BackgroundDopamine neurons share common response function for reward prediction error
Eshel, N., Tian, J., Bukwich, M., & Uchida, N. (2016) · Nature Neuroscience · doi:10.1038/nn.4239 · Cited by 321
The gut–brain axis mediates sugar preference
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A Unified Framework for Dopamine Signals across Timescales
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Dorsal Raphe Dopamine Neurons Modulate Arousal and Promote Wakefulness by Salient Stimuli
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“Our photometry setup utilized a 490 nm beam to activate Ca-dependent GCaMP6 fluorescence, as well as a 405 nm beam to image an isosbestic reference signal, which compensates for photo-bleaching and movement-related artifacts (Lerner et al., 2015).”
Striatal Circuits as a Common Node for Autism Pathophysiology
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“These striatal circuits further serve to regulate the output of the midbrain dopamine system, which extends a widespread neuromodulatory influence throughout the brain (Kupchik et al., 2015; Lerner et al., 2015).”
BackgroundThe Serotonergic Raphe Promote Sleep in Zebrafish and Mice
Oikonomou, G., Altermatt, M., Zhang, R., Coughlin, G. M., Montz, C. J., Gradinaru, V., & Prober, D. A. (2019) · Neuron · doi:10.1016/j.neuron.2019.05.038 · Cited by 309
“Fiber photometry data processing and analysis (mouse): Pre-processing of fiber photometry data was performed as previously described (Cho et al., 2017; Lerner et al., 2015).”
MethodBiased Oxytocinergic Modulation of Midbrain Dopamine Systems
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“Genetically guided tracing experiments have facilitated the identification of input and output wiring of DA neurons in the VTA and SNc (Beier et al., 2015; Lerner et al., 2015; Watabe-Uchida et al., 2012).”
A circuit from hippocampal CA2 to lateral septum disinhibits social aggression
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“Prominent pathways that are implicated but unverified in reward and aversion are also delineated ( gray) (Beier et al. 2015; Britt et al. 2012; Humphries & Prescott 2010; Kirouac et al. 2004; Lammel et al. 2012; Lerner et al. 2015; Liu et al. 2014; Luo et al. 2015; McDevitt et al. 2014; Namburi et al. 2015a,b; Nieh et…”
BackgroundMenegas, W., Babayan, B. M., Uchida, N., & Watabe‐Uchida, M. (2017) · eLife · doi:10.7554/elife.21886 · Cited by 267
“signals were subtracted with and then divided by the average signal in a 1 s period before CS in each trial) in this study, additional methods using activityindependent wavelength of excitation (Kudo et al., 1992; Lerner et al., 2015) or examination of emission spectrum (Cui et al.”
BackgroundMethodPolinski, N. K., Volpicelli-Daley, L. A., Sortwell, C. E., Luk, K. C., Cremades, N., Gottler, L. M., Froula, J., Duffy, M. F., Lee, V. M. Y., Martinez, T. N., et al. (2018) · Journal of Parkinson’s Disease · doi:10.3233/jpd-171248 · Cited by 288
“A–B) Comparison of pS129 aSyn expression in the ipsilateral midbrain after two site striatal injections using (A) original, traditionally-used coordinates [34] or (B) optimized coordinates guided by recent findings revealing distinct SNpc-striatal innervation patterns [54].”
MethodOrganization of long-range inputs and outputs of frontal cortex for top-down control
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The Input-Output Relationship of the Cholinergic Basal Forebrain
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“…tracing of neuromodulatory systems has been used in the noradrenergic, dopaminergic and serotonergic systems (Beier et al., 2015; Faget et al., 2016; Lerner et al., 2015; Ogawa et al., 2014; Pollak Dorocic et al., 2014; Schwarz et al., 2015; Watabe-Uchida et al., 2012; Weissbourd et al., 2014).”
MethodThree-dimensional virtual refocusing of fluorescence microscopy images using deep learning
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SPED Light Sheet Microscopy: Fast Mapping of Biological System Structure and Function
Tomer, R., Lovett-Barron, M., Kauvar, I., Andalman, A. S., Burns, V. M., Sankaran, S., Grosenick, L., Broxton, M. J., Yang, S., & Deisseroth, K. A. (2015) · Cell · doi:10.1016/j.cell.2015.11.061 · Cited by 236
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Classification of midbrain dopamine neurons using single-cell gene expression profiling approaches
Poulin, J.-F., Gaertner, Z., Moreno-Ramos, O. A., & Awatramani, R. (2020) · Trends in Neurosciences · doi:10.1016/j.tins.2020.01.004 · Cited by 238
“Projection specific approaches typically involve injection of viruses that show retrograde capabilities, into a target region of choice, allowing the efficient segregation of DA neuron subtypes based on their projections; indeed, these approaches have been used to segregate functionally distinct subpopulations within…”
MethodActivity patterns of serotonin neurons underlying cognitive flexibility
Matias, S., Lottem, E., Dugué, G. P., & Mainen, Z. F. (2017) · eLife · doi:10.7554/elife.20552 · Cited by 239
“…our fibers to areas where this specificity problem is reduced (Lammel et al., 2015) and that are known to contain the classical DA neurons that show RPE activity and are involved in reward processing (Lammel et al., 2011, 2012; Matsumoto and Hikosaka, 2009; Lerner et al., 2015; Kim et al., 2016).”
BackgroundMethodNucleus accumbens D2R cells signal prior outcomes and control risky decision-making
Zalocusky, K. A., Ramakrishnan, C., Lerner, T. N., Davidson, T. J., Knutson, B. D., & Deisseroth, K. A. (2016) · Nature · doi:10.1038/nature17400 · Cited by 235
Distinct Dopamine Receptor Pathways Underlie the Temporal Sensitivity of Associative Learning
Handler, A., Graham, T. G. W., Cohn, R., Morantte, I. G., Siliciano, A. F., Zeng, J., Li, Y., & Ruta, V. (2019) · Cell · doi:10.1016/j.cell.2019.05.040 · Cited by 231
“Neural circuits involved in associative learning integrate sensory signals with rewarding or punishing reinforcement cues, frequently encoded by neuromodulatory dopaminergic neurons (DANs; Aso et al., 2014a; Bromberg-Martin et al., 2010; Lerner et al., 2015; Schultz et al., 1997; Waddell, 2016).”
BackgroundTask-Dependent Changes in the Large-Scale Dynamics and Necessity of Cortical Regions
Pinto, L., Rajan, K., DePasquale, B., Thiberge, S. Y., Tank, D. W., & Brody, C. D. (2019) · Neuron · doi:10.1016/j.neuron.2019.08.025 · Cited by 244
“, 2009), and can thus be used to estimate Ca2+-independent changes in measured fluorescence (Lerner et al., 2015), which presumably largely come from hemodynamic contamination (Ma et al.”
BackgroundMesolimbic dopamine release conveys causal associations
Jeong, H., Taylor, A., Floeder, J. R., Lohmann, M., Mihalaş, Ş., Wu, B., Zhou, M., Burke, D. A., & Namboodiri, V. M. K. (2022) · Science · doi:10.1126/science.abq6740 · Cited by 232
Wave-like dopamine dynamics as a mechanism for spatiotemporal credit assignment
Hamid, A., Frank, M. J., & Moore, C. I. (2021) · Cell · doi:10.1016/j.cell.2021.03.046 · Cited by 222
“One hypothesis motivated by the excitationrelease coupling principle in neurobiology would suggest that DA waves may be inherited from the sequential firing of topographically projectingmidbrain DA cells (Lerner et al., 2015).”
Distributed and Mixed Information in Monosynaptic Inputs to Dopamine Neurons
Tian, J., Huang, R., Cohen, J. Y., Osakada, F., Kobak, D., Machens, C. K., Callaway, E. M., Uchida, N., & Watabe-Uchida, M. (2016) · Neuron · doi:10.1016/j.neuron.2016.08.018 · Cited by 224
“This is not likely to be due to the potential diversity of dopamine neurons because subpopulations of dopamine neurons projecting to specific targets nonetheless receive inputs from many brain areas (Beier et al., 2015; Lerner et al., 2015; Menegas et al., 2015).”
A Neural Circuit for the Suppression of Pain by a Competing Need State
Alhadeff, A. L., Su, Z., Hernandez, E., Klima, M. L., Phillips, S. Z., Holland, R. A., Guo, C., Hantman, A. W., De Jonghe, B. C., & Betley, J. N. (2018) · Cell · doi:10.1016/j.cell.2018.02.057 · Cited by 218
“Changes in calcium-dependent GcaMP6s fluorescence (490 nm) signal were compared with calcium-independent GCaMP6s fluorescence (405 nm), providing internal control for movement and bleaching artifacts (Lerner et al., 2015; Su et al., 2017).”
Daviu, N., Füzesi, T., Rosenegger, D. G., Rasiah, N. P., Sterley, T.-L., Peringod, G., & Bains, J. S. (2020) · Nature Neuroscience · doi:10.1038/s41593-020-0591-0 · Cited by 217
Nutritive, Post-ingestive Signals Are the Primary Regulators of AgRP Neuron Activity
Su, Z., Alhadeff, A. L., & Betley, J. N. (2017) · Cell Reports · doi:10.1016/j.celrep.2017.11.036 · Cited by 216
“We measured calcium-dependent fluorescence (excited at 490 nm) as a measure of AgRP neuron activity (Cui et al., 2013; Gunaydin et al., 2014) and calcium-independent fluorescence (excited at 405 nm) as a control for movement and bleaching artifacts (Figure 1B) (Lerner et al., 2015).”
Spontaneous behaviour is structured by reinforcement without explicit reward
Markowitz, J. E., Gillis, W. F., Jay, M., Wood, J. J., Harris, R., Cieszkowski, R., Scott, R., Brann, D. H., Koveal, D., Kula, T., et al. (2023) · Nature · doi:10.1038/s41586-022-05611-2 · Cited by 206
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“Furthermore, like the fly DANs, mammalian DANs can be anatomically divided into those that generate aversion and different types of reward (Lammel et al., 2011, 2012; Cohen et al., 2012; Lerner et al., 2015; Beier et al., 2015; Tellez et al., 2016).”
BackgroundStochastic synaptic plasticity underlying compulsion in a model of addiction
Pascoli, V., Hiver, A., Van Zessen, R., Loureiro, M., Achargui, R., Harada, M., Flakowski, J., & Lüscher, C. (2018) · Nature · doi:10.1038/s41586-018-0789-4 · Cited by 185
Cholinergic Mesopontine Signals Govern Locomotion and Reward through Dissociable Midbrain Pathways
Xiao, C., Cho, J. R., Zhou, C., Treweek, J. B., Chan, K. Y., McKinney, S. L., Yang, B., & Gradinaru, V. (2016) · Neuron · doi:10.1016/j.neuron.2016.03.028 · Cited by 212
“…roles of SNc and VTA neurons in exploratory activity, habituation, reinforcement, aversion (Bromberg-Martin et al., 2010; Friedman et al., 2014; Lerner et al., 2015; Roeper, 2013; Walsh et al., 2014), and the involvement of multiple nuclei in locomotion and reward (Benarroch, 2013;…”
InfluentialDodson, P. D., Dreyer, J. K., Jennings, K. A., Syed, E. C. J., Wade‐Martins, R., Cragg, S. J., Bolam, J. P., & Magill, P. J. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1515941113 · Cited by 195
“Around 50% of synapses made with SNc neurons are GABAergic (41), and these originate from numerous sources including the substantia nigra pars reticulata (SNr), the globus pallidus, the superior colliculus, the rostromedial tegmental nucleus, and SPNs located in striosomes (33, 42).”
BackgroundRegeneration of Spinal Cord Connectivity Through Stem Cell Transplantation and Biomaterial Scaffolds
Katoh, H., Yokota, K., & Fehlings, M. G. (2019) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2019.00248 · Cited by 204
A survey on applications of deep learning in microscopy image analysis
Liu, Z., Jin, L., Chen, J., Fang, Q., Ablameyko, S., Yin, Z., & Xu, Y. (2021) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2021.104523 · Cited by 218
“One way to acquire 3D fluorescence information is by mechanical scanning through the sample volume to obtain images at multiple focal planes, such as confocal [124], two-photon [125], light-sheet [126,127] and other various super-resolution microscopy techniques [103, 128 – 132].”
Viral Strategies for Targeting the Central and Peripheral Nervous Systems
Bedbrook, C. N., Deverman, B. E., & Gradinaru, V. (2018) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-080317-062048 · Cited by 168
Distinct hypothalamic control of same- and opposite-sex mounting behaviour in mice
Karigo, T., Kennedy, A., Yang, B., Liu, M., Tai, D., Wahle, I. A., & Anderson, D. J. (2020) · Nature · doi:10.1038/s41586-020-2995-0 · Cited by 189
Hypothalamic detection of macronutrients via multiple gut-brain pathways
Goldstein, N., McKnight, A. D., Carty, J. R. E., Arnold, M., Betley, J. N., & Alhadeff, A. L. (2021) · Cell Metabolism · doi:10.1016/j.cmet.2020.12.018 · Cited by 182
“Dual-wavelength Fiber Photometry (FP): Dual-wavelength FP was performed as we and others have previously described (Lerner et al., 2015; Su et al., 2017; Zalocusky et al., 2016).”
MethodFear balance is maintained by bodily feedback to the insular cortex in mice
Klein, A. S., Dolensek, N., Weiand, C., & Gogolla, N. (2021) · Science · doi:10.1126/science.abj8817 · Cited by 176
Genetic-Based Dissection Unveils the Inputs and Outputs of Striatal Patch and Matrix Compartments
Smith, J. B., Klug, J. R., Ross, D. L., Howard, C. D., Hollon, N. G., Ko, V. I., Hoffman, H., Callaway, E. M., Gerfen, C. R., & Jin, X. (2016) · Neuron · doi:10.1016/j.neuron.2016.07.046 · Cited by 176
Rajasethupathy, P., Ferenczi, E., & Deisseroth, K. A. (2016) · Cell · doi:10.1016/j.cell.2016.03.047 · Cited by 183
Crittenden, J. R., Tillberg, P. W., Riad, M. H., Shima, Y., Gerfen, C. R., Curry, J., Housman, D. E., Nelson, S. B., Boyden, E. S., & Graybiel, A. M. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1613337113 · Cited by 174
Salinas-Hernández, X. I., Vogel, P., Betz, S., Kalisch, R., Sigurdsson, T., & Duvarci, S. (2018) · eLife · doi:10.7554/elife.38818 · Cited by 186
Afferent Inputs to Neurotransmitter-Defined Cell Types in the Ventral Tegmental Area
Faget, L. C., Osakada, F., Duan, J., Ressler, R. L., Johnson, A. B., Proudfoot, J., Yoo, J. H., Callaway, E. M., & Hnasko, T. S. (2016) · Cell Reports · doi:10.1016/j.celrep.2016.05.057 · Cited by 180
“Previous work has used Rb-based approaches to assess celltype-specific afferent inputs to midbrain dopamine neurons (Beier et al., 2015; Lerner et al., 2015; Menegas et al., 2015; Watabe-Uchida et al., 2012).”
BackgroundMethodMotivational neural circuits underlying reinforcement learning
Averbeck, B. B., & Costa, V. D. (2017) · Nature Neuroscience · doi:10.1038/nn.4506 · Cited by 181
Dopamine neurons projecting to medial shell of the nucleus accumbens drive heroin reinforcement
Corre, J., van Zessen, R., Loureiro, M., Patriarchi, T., Tian, L., Pascoli, V., & Lüscher, C. (2018) · eLife · doi:10.7554/elife.39945 · Cited by 178
Hierarchical neural architecture underlying thirst regulation
Augustine, V., Gökçe, S. K., Lee, S., Wang, B., Davidson, T. J., Reimann, F. M., Gribble, F. M., Deisseroth, K. A., Lois, C., & Oka, Y. (2018) · Nature · doi:10.1038/nature25488 · Cited by 169
Dopamine, Updated: Reward Prediction Error and Beyond
Lerner, T. N., Holloway, A. L., & Seiler, J. L. (2020) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2020.10.012 · Cited by 195
A Student’s Guide to Neural Circuit Tracing
Saleeba, C., Dempsey, B., Le, S., Goodchild, A., & McMullan, S. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00897 · Cited by 153
Morel, C., Montgomery, S. E., Li, L., Cuttoli, R. D.-D., Teichman, E. M., Juarez, B., Tzavaras, N., Ku, S. M., Flanigan, M. E., Cai, M., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-29155-1 · Cited by 178
Unique functional responses differentially map onto genetic subtypes of dopamine neurons
Azcorra, M., Gaertner, Z. A., Davidson, C., He, Q., Kim, H., Nagappan, S., Hayes, C. K., Ramakrishnan, C., Fenno, L. E., Kim, Y. S., et al. (2023) · Nature Neuroscience · doi:10.1038/s41593-023-01401-9 · Cited by 172
Communication in Neural Circuits: Tools, Opportunities, and Challenges
Lerner, T. N., Ye, L., & Deisseroth, K. (2016) · Cell · doi:10.1016/j.cell.2016.02.027 · Cited by 159
“It is only when dopamine neurons are viewed from this structural-output-defined perspective that observations of opposite-valence responses to stimuli by different subsets of dopamine neurons become interpretable (Kim et al., 2014a; Lerner et al., 2015; Matsumoto and Hikosaka, 2009).”
InfluentialGut–brain circuits for fat preference
Li, M.-T., Tan, H.-E., Lu, Z., Tsang, K. S., Chung, A. J., & Zuker, C. S. (2022) · Nature · doi:10.1038/s41586-022-05266-z · Cited by 172
Nucleus Accumbens Modulation in Reward and Aversion
Klawonn, A. M., & Malenka, R. C. (2018) · Cold Spring Harbor Symposia on Quantitative Biology · doi:10.1101/sqb.2018.83.037457 · Cited by 163
“Consistent with this heterogeneity, dorsal raphe 5-HT neuron manipulations and recordings suggest complex roles in a range of behaviors related to cognition and motivation (Liu et al. 2014; Cohen et al. 2015; Brodsky et al. 2016; Li et al. 2016; You et al. 2016; Ren et al. 2018).”
BackgroundSchultz, W., Stauffer, W. R., & Lak, A. (2017) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2017.03.013 · Cited by 171
Dopamine neurons encoding long-term memory of object value for habitual behavior
Kim, H. F., Ghazizadeh, A., & Hikosaka, O. (2015) · Cell · doi:10.1016/j.cell.2015.10.063 · Cited by 157
“Recent studies suggest that DA neurons are heterogeneous in terms of their functions (Brischoux et al., 2009; Lerner et al., 2015; Matsumoto and Hikosaka, 2009).”
Learning from Action: Reconsidering Movement Signaling in Midbrain Dopamine Neuron Activity
Coddington, L. T., & Dudman, J. T. (2019) · Neuron · doi:10.1016/j.neuron.2019.08.036 · Cited by 150
SCN VIP Neurons Are Essential for Normal Light-Mediated Resetting of the Circadian System
Jones, J. R., Simon, T., Lones, L., & Herzog, E. D. (2018) · Journal of Neuroscience · doi:10.1523/jneurosci.1322-18.2018 · Cited by 156
“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).”
MethodStimulus-specific hypothalamic encoding of a persistent defensive state
Kennedy, A., Kunwar, P. S., Li, L.-Y., Stagkourakis, S., Wagenaar, D. A., & Anderson, D. J. (2020) · Nature · doi:10.1038/s41586-020-2728-4 · Cited by 144
Duda, J., Pötschke, C., & Liss, B. (2016) · Journal of Neurochemistry · doi:10.1111/jnc.13572 · Cited by 153
GuPPy, a Python toolbox for the analysis of fiber photometry data
Sherathiya, V. N., Schaid, M. D., Seiler, J. L., Lopez, G. C., & Lerner, T. N. (2021) · Scientific Reports · doi:10.1038/s41598-021-03626-9 · Cited by 147
“GuPPy is programmed to use a control isosbestic wavelength recorded by users to remove smaller movement artifacts as well as bleaching artifacts when calculating the ΔF/F (as described in Lerner et al, 2015; Fig.”
MethodLi, C., Navarrete, J. S., Liang-Guallpa, J., Lü, C., Funderburk, S. C., Chang, R. B., Liberles, S. D., Olson, D. P., & Krashes, M. J. (2018) · Cell Metabolism · doi:10.1016/j.cmet.2018.10.016 · Cited by 147
“Critically, a calcium-independent fluorescence in the UV spectra was used in all recordings to control for movement and bleaching artifacts (Figures S5B–S5D) (Lerner et al., 2015).”
Dopaminergic and Prefrontal Basis of Learning from Sensory Confidence and Reward Value
Lak, A., Okun, M., Moss, M. M., Gurnani, H., Farrell, K., Wells, M. J., Reddy, C. B., Kepecs, Á., Harris, K. D., & Carandini, M. (2019) · Neuron · doi:10.1016/j.neuron.2019.11.018 · Cited by 137
Reverse-translational identification of a cerebellar satiation network
Low, A. Y. T., Goldstein, N., Gaunt, J. R., Huang, K.-P., Zainolabidin, N., Yip, A. K. K., Carty, J. R. E., Choi, J. Y., Miller, A. M., Ho, H. S. T., et al. (2021) · Nature · doi:10.1038/s41586-021-04143-5 · Cited by 135
Alhadeff, A. L., Goldstein, N., Park, O., Klima, M. L., Vargas, A. P.-D., & Betley, J. N. (2019) · Neuron · doi:10.1016/j.neuron.2019.05.050 · Cited by 133
“We engineered mice to express the calcium indicator GCaMP6s in AgRP or POMCneurons andmeasured calcium-dependent fluorescence as a proxy for neural activity and calcium-independent fluorescence as a control for bleaching and movement artifacts (Figures 1A and 1B) (Lerner et al., 2015; Su et al., 2017).”
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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